United States        Office of Water              EPA-822-B-00-002
Environmental Protection   Office of Science and Technology     July2000
Agency            Washington, DC 20460          www.epa.gov
Nutrient Criteria
Technical Guidance Manual

Rivers and Streams


This manual provides technical guidance to States, Tribes, and other authorized jurisdictions to establish
water quality criteria and standards under the Clean Water Act (CWA), in order to protect aquatic life
from acute and chronic effects of nutrient overenrichment.  Under the CWA, States and Tribes are
required to establish water quality criteria to protect designated uses. State and Tribal decisionmakers
retain the discretion to adopt approaches on a case-by-case basis that differ from this guidance when
appropriate and scientifically defensible. While this manual constitutes EPA's scientific
recommendations regarding ambient concentrations of nutrients that protect resource quality and aquatic
life, it does not substitute for the CWA or EPA's regulations; nor is it a regulation itself. Thus, it cannot
impose legally binding requirements on EPA, States, Tribes, or the regulated community, and might not
apply to a particular situation or circumstance.  EPA may change this guidance in the future.



Contributors	ix

Acknowledgments  	xi

Executive Summary	xiii

1. Introduction	  1
    1.1 Purpose of the Document	  1
    1.2 Nutrient Enrichment Problems in Rivers and Streams	  3
    1.3 Water Quality Standards and Criteria  	  9
    1.4 Overview of the Criteria Development Process	  10
    1.5 The Criteria Development Process	  11
    1.6 Identify Needs and Goals	  15
    1.7 Document Structure 	  15

2. Stream System Classification  	  17
   2.1 Introduction  	  17
   2.2 Classification Schemes Based on Physical Factors	  20
       Ecoregional Classification  	  20
       Fluvial Geomorphology  	  22
       Rosgen	  22
       Stream Order	  23
       Physical Factors Used to Classify Streams and Analyze Trophic State	  23
   2.3 Classification Schemes Based on Nutrient Gradients  	  25
       Classification by Nutrient Ecoregions  	  26
       Classification by Trophic State	  26

3. Select Variables  	  29
   3.1 Introduction  	  29
   3.2 Primary Variables	  30
       Nutrients	  30
       Algal Biomass as Chlorophyll a	  31
       Total Suspended Solids, Transparency, and Turbidity	  32
       Flow and Velocity	  33
   3.3 Secondary Response Variables  	  35
       Sensitive Response Variables	  35
       Other Secondary Response Variables	  38

4. Sampling Design for New Monitoring Programs 	  47
   4.1 Introduction  	  47
   4.2 Sampling Protocol  	  48
       Considerations for Sampling Design  	  48
       Where to Sample	  49
       When to Sample  	  49
       Approaches to Sampling Design	  51

       Identifying and Characterizing Reference Stream Reaches	  54
       Other Considerations for Monitoring Nutrients	  55
       Involvement of Citizen Monitoring Programs 	  59

5.  Building a Database of Nutrients and Algae-Related Water Quality Information 	  61
    5.1 Introduction  	  61
    5.2 Databases and Database Management	  61
       National Nutrients Database	  62
    5.3 Collecting Existing Data  	  62
       Potential Data Sources  	  63
       Quality of Historical Data	  69
       Quality Assurance/Quality Control  	  71

6.  Analyze Data	  73
    6.1 Introduction  	  73
    6.2 Linking Nutrient Availability to Algal Response	  74
       Defining the Limiting Nutrient	  74
       Establishing Predictive Nutrient-algal Relationships	  76
       Analysis Methods for Establishing Nutrient-algal Relationships	  80
       Analysis of Algal Species Composition to Classify Stream Response to Nutrients 	  81
       Characterizing Nutrient Status with Algal Species Composition	  83
       Developing Multimetric Indices to Complement Nutrient Criteria 	  85
       Assessing Nutrient-algal Relationships Using Experimental Procedures  	  88
       Other Issues to Keep  in Mind	  89
    6.3 Statistical Analyses  	  89
       Frequency Distribution	  90
       Correlation and Regression Analyses	  90
       Tests of Significance	  91
    6.4 Using Models as Management Tools	  91

7.  Nutrient and Algal Criteria Development  	  93
    7.1 Introduction  	  93
    7.2 Methods for Establishing Nutrient and Algal Criteria	  94
       Using Reference  Reaches to Establish Criteria  	  94
       Using Predictive  Relationships to Establish Criteria	  97
       Using Published Nutrient Thresholds or Recommended Algal Limits  	  100
       Considerations for Downstream Receiving Waters 	  103
    7.3 Evaluation of Proposed Criteria	  103
       Guidance for Interpreting and Applying Criteria	  103
       Sampling for Comparison to Criteria	  104
       Criteria Modifications	  105
       Implementation of Nutrient Criteria into Water Quality Standards	  106

8.   Management Programs	  107
    8.1 Introduction  	  107
    8.2 Managing Streamflow Conditions	  108
       Low Flows  	  108
       High Flows  	  109


    8.3 Managing Point Source Pollution  	  110
       Water Quality Standards	  110
       NPDES Permits	  112
       Combined Sewer Overflows (CSOs) 	  113
       Stormwater Planning	  114
       Total Maximum Daily Load	  114
       Look to the Future ... Pollutant Trading	  115
    8.4 Managing Nonpoint Source Pollution 	  116
       Nonpoint Sources of Nutrients	  117
       Efforts to Control Nonpoint Source Pollution  	  118

9. Monitoring and Reassessment  of Nutrient Criteria Ranges	  125
    9.1 Introduction 	  125
    9.2 Assessment of Process Through Monitoring and Periodic Review	  125
    9.3 Completion and Evaluation 	  126
    9.4 Continued Monitoring of the System	  126

References 	  127

Appendix A: Nutrient Criteria Case Studies 	  A-l

Appendix B: Methods of Analysis for Water Quality Variables  	 A-65

Appendix C: Statistical Tests and Modeling Tools 	 A-75

Appendix D: Acronym List and Glossary  	 A-81



Sharon Buck (U.S. Environmental Protection Agency)*
Gregory Denton (Tennessee Department of Environment and Conservation)
Walter Dodds (Kansas State University)*
Jen Fisher (U.S. Environmental Protection Agency)*
David Flemer (U.S. Environmental Protection Agency)
Debra Hart (U.S. Environmental Protection Agency)*
Amanda Parker (U.S. Environmental Protection Agency)*
Stephen Porter (U.S. Geological Survey)
Sam Rector (Arizona Department of Environmental Quality)
Alan Steinman (South Florida Water Management Districts)
Jan Stevenson (Michigan State University)*
Jeff Stoner (U.S. Geological Survey)
Danielle Tillman (U.S. Environmental Protection Agency)
Sherry Wang (Tennessee Department of Environment and Conservation)
Vicki Watson (University of Montana)*
Eugene Welch (University of Washington)*
*Denotes primary authors


The authors wish to gratefully acknowledge the efforts and input of several individuals. These include
several additional members of our rivers and streams workgroup:  Susan Davies (Maine Department of
Environmental Protection), Susan Holdsworth (USEPA), Susan Jackson (USEPA), and Latisha Parker
(USEPA). We also wish to thank Thomas Gardner (USEPA) and James Keating (USEPA) for their
reviews and comments on draft versions of the guidance; Jessica Barrera (Hispanic Association of
Colleges and Universities/University of Miami) for her assistance in compiling references; and Joanna
Taylor (CDM Group, Inc.) for her careful, editorial review.

This document was peer reviewed by a panel of expert scientists.  The peer review charge focused on
evaluating the scientific validity of the process for developing nutrient and algal criteria described in the
guidance.  The peer review panel comprised Drs. Elizabeth Boyer (State University of New York), Nina
Caraco (Institute of Ecosystem Studies), Gary Lamberti (University of Notre Dame), Judy Meyer
(University of Georgia), and Val Smith (University of Kansas).  Edits and suggestions made by the peer
review panel were incorporated into the final version of the guidance.

Cover Photograph:  South Umpqua River, Oregon.  Photograph courtesy of Dr. E. B. Welch, University
of Washington.


                                  EXECUTIVE SUMMARY

The purpose of this document is to provide scientifically defensible technical guidance to assist States
and Tribes in developing regionally-based numeric nutrient and algal criteria for river and stream
systems. The Clean Water Action Plan, a presidential initiative released in February 1998, includes an
initiative to address the nutrient enrichment problem. Building on this initiative, the EPA developed a
report entitled National Strategy for the Development of Regional Nutrient Criteria (USEPA 1998). The
report outlines a framework for development of waterbody-specific technical guidance that can be used
to assess nutrient status and develop regional-specific numeric nutrient criteria. This technical guidance
manual builds on the strategy and provides specific guidance for rivers and streams.  Similar documents
are being prepared for lakes and reservoirs, estuaries and coastal marine waters, and wetlands.

A directly prescriptive approach to nutrient criteria development is not appropriate due to regional
differences that exist and the lack of a clear technical understanding of the relationship between
nutrients, algal growth, and other factors (e.g., flow,  light, substrata).  The approach chosen for criteria
development must be tailored to meet the specific needs of each State or Tribe. The criteria development
process described in this guidance can be divided into the following iterative steps.

1.    Identify water quality needs and goals with regard to managing nutrient enrichment problems.
2.    Classify rivers and streams first by type, and then by trophic status.
3.    Select variables for monitoring nutrients, algae, macrophytes, and their impacts.
4.    Design sampling program for monitoring nutrients and algal biomass in rivers and streams.
5.    Collect data and build database.
6.    Analyze data.
7.    Develop criteria based on reference condition and data analyses.
8.    Implement nutrient control strategies.
9.    Monitor effectiveness of nutrient control strategies and reassess the validity of nutrient criteria.

The components of each step is explained in detail in succeeding chapters of the document.

Chapter 1 addresses the necessity of defining water quality needs and goals for rivers and streams, and
gives a general overview of nutrient criteria development.  Well-defined needs and goals help to assess
the applicability of the criteria development process and identify attainable water quality goals. This step
will be revisited throughout the criteria development process to assure defined needs and goals are met.

Chapter 2 discusses classification of streams for water quality assessment and nutrient criteria
development. The intent of classification is to identify groups of rivers or streams that have comparable
characteristics (i.e., similar biological, ecological, physical, and/or chemical features).  Classifying rivers
and streams reduces the variability of river-related measures (e.g., physical, biological, or water quality
attributes) within classes, maximizes variability among classes, and allows criteria to be identified on a
broader rather than site-specific scale.  Hence, classification of stream systems will assist in setting
appropriate criteria for specific regions and stream system types and provide information used in
developing management and restoration strategies.

Chapter 3 describes the candidate variables that can be used to evaluate or predict the condition or degree
of eutrophication in a water body. Variables that are required for nutrient criteria development are water
column nutrient concentrations (total nitrogen [TN] and total phosphorus [TP]), algal biomass (measured

as chlorophyll a [chl a]), and a measure of turbidity. Measurement of these variables provides a means to
evaluate nutrient enrichment and can form the basis for establishing regional and waterbody-specific
nutrient criteria. This chapter provides an overview of the required variables and additional variables
that can be considered when setting criteria.

Chapter 4 provides technical guidance on designing effective sampling programs. Appropriate data
describing stream nutrient and algal conditions are lacking in many areas. Where available data are not
sufficient to derive criteria, it will be necessary to collect new data through existing or new monitoring
programs. New monitoring programs should be designed to assess nutrient and algal conditions with
statistical rigor while maximizing available management resources.

Chapter 5 describes how to build a database of nutrient and algal information. A database of relevant
water quality information can be an invaluable tool to States and Tribes as they develop nutrient criteria.
Databases can be used to organize existing information, store newly gathered monitoring data, and
manipulate data as criteria are being developed.  This chapter discusses the role of databases in nutrient
criteria development and provides a brief review of existing data sources for nutrient-related water
quality information.

Data analysis, described in Chapter 6, is critical to nutrient criteria development. Proper analysis and
interpretation of data determines the scientific defensibility and effectiveness of the criteria. The
purpose of this chapter is to explore methods for analyzing data that can be used to derive nutrient
criteria. Included in this chapter are techniques that link cause and effect relationships between nutrient
loading and algal growth, statistical analyses to evaluate compiled data, and use of computer models.
Methods of statistical  analyses and a review of relevant computer simulation models are provided in

Chapter 7 presents several approaches that water quality managers can use to select numeric criteria for
the rivers and streams in their State/Tribal ecoregions. The approaches that are presented include:  the
use of reference streams, applying predictive relationships to select nutrient concentrations that will
result in desirable levels of aquatic growth, and deriving criteria from thresholds established in the
literature. Considerations are also presented for those situations in which development of applicable
river and stream nutrient criteria might be driven by conditions that are deemed acceptable for
downstream receiving waters (i.e., the lake, reservoir, or estuary to which the river drains).

Chapter 8 provides information on regulatory and non-regulatory programs that may be affected by or
utilize nutrient criteria. This chapter is intended to serve as an informational resource for water quality
managers and foster potential  links among regulatory and non-regulatory watershed programs.
Information on other agency programs that may assist in implementing criteria and maintaining water
quality is included.

Chapter 9 discusses the continued monitoring of river and stream systems to reassess goals and
established nutrient criteria. This step should (1) evaluate the appropriateness of the nutrient criteria, (2)
ensure that river and stream systems are responding to management action, and (3) assess whether water
quality goals established by the resource manager are being met.

Appended to the guidance document are case studies; technical discussions of analytical methods,
statistical analyses, and computer modeling; a list of acronyms; and a glossary.

Chapter  1.

The purpose of this document is to provide scientifically defensible technical guidance to assist States
and Tribes in developing regionally-based numeric nutrient, algal, and macrophyte criteria for river and
stream systems. Criteria are "elements of State water quality standards, expressed as constituent
concentrations, levels, or narrative statements, representing a quality of water that supports a particular
use. When criteria are met, water quality will generally protect the designated use" (USEPA 1994).
Water quality criteria are based on scientifically-derived relationships among water constituents and
biological condition.  "Water quality standards (WQS) are provisions of State or Federal law which
consist of a designated use or uses for the waters of the United States, water quality criteria for such
waters based upon such uses.  Water quality standards are to protect public health or welfare, enhance the
quality of the water, and serve the purposes of the Act (40 CFR 131.3)" (USEPA 1994). Water quality
standards are comprised of three main components: criteria, which are scientifically based; designated
uses, which involve economic, social and political considerations including effects on downstream
receiving waters; and an anti-degradation policy, which protects the level of water quality necessary to
maintain existing uses (Figure  1).

Water quality can be affected when watersheds are modified by alterations in vegetation, sediment
balance, or fertilizer use from industrialization, urbanization, or conversion of forests and grasslands to
agriculture and silviculture (Turner and Rabalais 1991; Vitousek et al. 1997; Carpenter et al. 1998).
Cultural eutrophication (human-caused inputs of excess nutrients in waterbodies) is one of the primary
factors resulting in impairment of U.S. surface waters (USEPA 1996). Both point and nonpoint sources
of nutrients contribute to impairment of water quality. Point source discharges of nutrients are fairly
constant and are controlled by USEPA National Pollutant Discharge Elimination System (NPDES)
permitting (see Section 8.3) [Source: http://www.epa.gov/owm/gen2.htm]. Nonpoint pollutant inputs
have increased in recent decades and have degraded water quality in many aquatic systems (Carpenter et
al. 1998). Nonpoint sources of nutrients are most commonly intermittent and are usually linked to
seasonal agricultural activity or other irregularly-occurring  events such as construction or storm events.

JuK 2010


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mi pji'i




Figure 1, Developing water quulily standards for nutrients,

July 2000	Chapter 1. Introduction

Control of nonpoint source pollutants focuses on land management activities and regulation of pollutants
released to the atmosphere (Carpenter et al. 1998).

Control of nutrients is further complicated by the cycling of nitrogen (N) and phosphorus (P) in aquatic
systems. Nutrients can be re-introduced into a waterbody from the sediment, or by microbial
transformation, potentially resulting in a long recovery period even after pollutant sources have been
reduced. In flowing systems, nutrients may be rapidly transported downstream and the effects of nutrient
inputs may be uncoupled from the nutrient source, further complicating nutrient source control (Turner
andRabalais  1991;Wetzel 1992; Vitousek et al. 1997; Carpenter etal. 1998). Recognizing cause-and-
effect relationships between nutrient input and general waterbody response is the first step in mitigating
the effects of cultural eutrophication.  Once relationships are established, nutrient criteria can be
developed to protect waterbodies. This document describes the process of developing numeric nutrient
criteria, a new initiative by the USEPA to address the problem of cultural eutrophication (USEPA

The Clean Water Action Plan, a presidential initiative released in February 1998, provides a blueprint for
Federal agencies to work with States, Tribes and other stakeholders to protect and restore the Nation's
water resources.  The Clean Water Action Plan includes an initiative to address the nutrient enrichment
problem. Building on this initiative, the USEPA developed a report entitled National Strategy for the
Development of Regional Nutrient Criteria (USEPA 1998a). The report outlines a framework for
development of waterbody-specific technical guidance that can be used to assess nutrient status and
develop regional-specific  numeric nutrient criteria.  This technical guidance manual builds on the
strategy and provides specific guidance for rivers and streams. Similar documents are being prepared for
lakes and reservoirs, estuaries and coastal marine waters, and wetlands.

For the purposes of this document, river and stream systems are identified collectively as streams or
stream systems, unless otherwise noted.  Information presented here will provide water quality managers
with an overview of the current state of the science, guidance on establishing and compiling a database,
and suggested methods for data analyses.  The process for setting stream nutrient and algal criteria
ranges and a summary of appropriate regulatory and technical considerations are discussed. Diverse
geomorphic and climatologic conditions throughout the nation require nutrient and algal criteria
development to occur at the ecoregional, State, Tribal, or individual waterbody level to be scientifically
valid. The framework for nutrient and algal criteria development follows a logical iterative process that
begins with defining goals and needs for State and Tribal water quality. The steps of the process are
described in this chapter and detailed in succeeding chapters.


Nutrient enrichment frequently ranks as one of the top causes of water resource impairment. Systems are
impaired when water quality fails to meet designated use criteria.  The USEPA reported to Congress
that of the systems surveyed and reported impaired, 40 percent of rivers, 51 percent of lakes, and 57
percent of estuaries listed and nutrients as  a primary cause of impairment (USEPA 1996). The nutrient
enrichment issue is not new; however, traditional efforts at nutrient control have been only moderately
successful. Specifically, efforts to control nutrients in waterbodies that have multiple nutrient sources
(point and nonpoint sources) have been less effective in providing satisfactory, timely remedies for

                                            PAGE 3

July 2000	Chapter 1. Introduction

enrichment-related problems. The development of numeric criteria should aid control efforts by
providing clear numeric goals for nutrient and algal/macrophyte levels. Furthermore, numeric nutrient
criteria provide specific water quality goals that will assist researchers in designing improved best
management practices.

Nutrient impaired waters can cause problems that range from annoyances to serious health concerns
(Dodds and Welch 2000). Nuisance levels of algae and other aquatic vegetation (macrophytes) can
develop rapidly in response to nutrient enrichment when other factors (i.e., light, temperature, substrate,
etc.) are not limiting. High macrophyte growth can interfere with aesthetic and recreational uses of
stream systems (Welch 1992). Algae in particular can grow rapidly when the nutrients N and P (primary
nutrients that most frequently limit algal growth, see Section 6.2 Defining the Limiting Nutrient)  are
abundant, often developing into single or multiple species blooms. Algal bloom development involves
complex relationships that are not always well understood.  However, the relationship between nuisance
algal growth and nutrient enrichment in stream systems has been well-documented in the literature
(Welch 1992; Van Nieuwenhuyse and Jones 1996; Dodds et al. 1997; Chetelat et al. 1999).  Taste and
odor problems in drinking water supplies are usually caused by algal blooms and actinomycete (nitrogen-
fixing filamentous bacteria) occurrence and other bacterial blooms that frequently  follow (Silvey and
Watt 1971; Dorin 1981; Taylor et al. 1981).  Algal blooms of certain cyanobacterial species produce
toxins that can affect animal and human health. Reports of livestock, waterfowl, and occasionally human
poisonings after drinking from waterbodies with blue-green algal blooms are not uncommon (Darley
1982; Carmichael 1986, 1994).

Human health problems can be attributed to nutrient enrichment.  One serious human health problem
associated with nutrient enrichment is the formation of trihalomethanes (THMs).  Trihalomethanes are
carcinogenic compounds that are produced when certain organic compounds are chlorinated and
bromated as part of the disinfection process in a drinking water treatment facility.  Trihalomethanes and
associated compounds can be formed from a variety of organic compounds including humic substances,
algal metabolites, and algal decomposition products.  The density of algae and the  level of eutrophication
in the raw water supply has been correlated with the production of THMs (Oliver and Schindler 1980;
Hoehnetal. 1982).

Effects directly related to nutrients can also result in human health problems. A study of nitrate in
groundwater (the primary source of drinking water in the US) indicated that nitrate contamination
generally increased with high nitrogen input, greater proportions of well-drained soils, and low woodland
to cropland ratios (Nolan et al. 1997). The USEPA has an established maximum contaminant level of 10
mg/L because nitrates in drinking water can cause potentially fatal low oxygen levels in the blood when
ingested by infants (USEPA 1995).  Nitrate concentrations as low as 4 mg/L in drinking water supplies
from rural areas have also been linked to an increased risk of non-Hodgkin lymphoma (Ward et al.
1996). A more detailed discussion of human health concerns related to eutrophication can be found in

Nutrient impairment can cause problems other than those related to human health.  One of the most
expensive problems caused by nutrient enrichment is the increased treatment required for drinking water.
Nutrient enriched waters commonly cause drinking water treatment plant filters to clog with algae or
macrophytes (Welch 1992) and can contribute to the corrosion of intake pipes (Nordin  1985).  High algal

                                            PAGE 4

July 2000	Chapter 1.  Introduction

biomass in drinking water sources require greater volumes of water treatment chemicals, increased back-
flushing of filters, and additional settling times to attain acceptable drinking water quality (Nordin 1985).

Adverse ecological effects associated with nutrient enrichment include reductions in dissolved oxygen
(DO) and the occurrence of HABs (harmful algal blooms). High algal and macrophyte biomass may be
associated with severe diurnal swings in DO and pH in some waterbodies (Wong et al. 1979; Welch
1992; Edmonson 1994; Correll 1998).  Low DO can release toxic metals from sediments (Brick and
Moore 1996) contaminating habitats of local aquatic organisms.  In addition, low DO can cause
increased availability of toxic substances like ammonia and hydrogen sulfide, reducing acceptable
habitat for most aquatic organisms, including valuable game fish. Decreased water clarity (increased
turbidity) can cause loss of macrophytes and creation of dense algal mats.  Loss of macrophytes and
increased algal biomass may also reduce habitat availability for aquatic organisms.  Thus, nutrient
enrichment may alter the native composition and species diversity of aquatic communities (Nordin 1985;
Welch 1992; Smith  1998; Carpenter et al. 1998; Smith et al. 1999).

A large area (6,000 to 7,000 square miles) of hypoxia-water which contains less than 2 parts per million
of DO-located off the Gulf of Mexico Texas-Louisiana Shelf is believed to be caused by a complicated
interaction of excessive nutrients transported to the Gulf of Mexico from the Mississippi River drainage;
physical changes to the river (e.g., channelization and loss of natural wetlands and vegetation along
riverbanks); and the interaction of riverine freshwater with Gulf marine waters (Turner and Rabalais
1994; Rabalais et al. 1996; Brezonik et al. 1999). Hypoxia can cause stress or death in bottom dwelling
organisms that cannot move out of the hypoxic zone. Abundant nutrients trigger excessive algal growth
which results in reduced sunlight, loss of aquatic habitat, and a decrease in DO. Depletion of DO for the
water column has resulted in virtually no biological activity in the hypoxic zone. Reductions in DO have
also been implicated in fish kills leading to significant economic impacts on local recreational and
commercial  fisheries.

Harmful algal blooms (e.g., brown tides, toxic Pfiesteriapiscicida outbreaks,  and some types of red
tides) are also associated with excess nutrients.  Evidence suggests that nutrients may directly stimulate
the  growth of the toxic form of Pfiesteria, although more research is required  to prove this conclusively
(Burkholder et al. 1992; Glasgow et al. 1995). Pfiesteria has been implicated as a cause of major fish
kills at many sites along the North Carolina coast and in several Eastern Shore tributaries of the
Chesapeake  Bay.

The primary limiting nutrients in freshwaters are phosphorus and nitrogen. Phosphorus is a mineral
nutrient, i.e., it is introduced into the biological components of the environment by the breakdown of
rock and soil minerals. The breakdown of mineral phosphorus produces inorganic phosphate ions (PO43~)
that can be absorbed by plants from the soil or water. Phosphorus moves through the food web primarily
as organic phosphorus (after it has been incorporated into plant or algal tissue), where it may be released
as phosphate in urine or other waste (by heterotrophic consumers) and reabsorbed by plants or algae to
start another cycle (Figure 2a) (Nebel and Wright 2000).

The primary reservoir of nitrogen is the air. Plants and animals cannot utilize nitrogen directly from the
air, but require nitrogen in mineral form such as ammonium ions (NH4+) or nitrate ions (NO3~) for uptake.
However, a number of bacteria and cyanobacteria (blue-green algae) can convert nitrogen gas to the


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July 2000	Chapter 1. Introduction

ammonium form through a process called biological nitrogen fixation. Mineral forms of nitrogen can be
taken up by plants and algae, and incorporated into plant or algal tissue. Nitrogen follows the same
pattern of food web incorporation as phosphorus, and is released in waste primarily as ammonium
compounds. The ammonium compounds are usually converted to nitrates by nitrifying bacteria, making
it available again for uptake, starting the cycle anew (Figure 2b) (Nebel and Wright 2000).

Nitrogen and P are transported to receiving waterbodies from rain, overland runoff, groundwater,
drainage networks, and industrial and residential waste effluents.  Once nutrients have been received in a
waterbody they can be taken up by algae, macrophytes and micro-organisms (either in the water column
or in the benthos); sorbed to organic or inorganic particles in the water and sediment; accumulated or
recycled in the sediment; or transformed and released as a gas from the waterbody (denitrification).

Nitrogen and P have different chemical properties and therefore are involved in different chemical
processes. Nitrogen gas  dissolved in the water column may be converted to ammonia (a usable form of
N) by nitrogen-fixing bacteria and algae when nitrate or ammonia are not readily available. However,
receiving waters  can lose N through denitrification-anaerobic transformation of nitrate or nitrite into
gaseous N oxides (which are released into the air)-mediated by denitrifying bacteria (Atlas and Bartha
1993). Phosphorus is found primarily in two forms, organic and inorganic, in freshwater. The
biologically available form of inorganic P in water is orthophosphate (PO4~3). Most P in surface water is
bound organically, and much of the organic P fraction is in the particulate phase of living cells, primarily
algae (Wetzel and Likens 1991). The remainder of the organic fraction is present as dissolved and
colloidal organic P. Phosphorus readily sorbs to clay particles in the water column reducing availability
for uptake by algae, bacteria and macrophytes. The exchange of P between the sediments and overlying
water involves net movement of P into the sediments. Exchanges across the sediment interface are
regulated by mechanisms associated with mineral-water equilibria, sorption processes, redox
interactions, and  the activities of bacteria, fungi, algae, and invertebrates.  Therefore, P in the sediment is
slow to recycle into the water column.  Detailed discussions of N and P cycling in freshwater can be
found in Wetzel (1983);  Goldman and Home (1983); Atlas and Bartha (1993); and other limnology texts.

Many lakes have been successfully treated for nutrient enrichment problems by an assortment of
techniques (Cooke et al.  1993). Lake Washington is a well-recognized example of nutrient diversion.
Nutrients were diverted from Lake Washington  by eliminating direct discharge from wastewater
treatment plants and other dischargers, effectively reducing nuisance algal blooms and improving water
clarity (Edmonson 1994). Although many cases have been documented for controlling organic waste
inputs to rivers (e.g., the  Thames River, England [Goldman and Home 1983]), nutrient control efforts to
correct algal and/or macrophyte problems in streams and rivers have been either minimal or
undocumented in the peer-reviewed, published literature.  Two well-documented cases are described in
detail in Appendix A:  the Clark Fork River, MT, and the Bow River, Alberta. Despite these and other
efforts, a greater  percentage of stream systems surveyed are  reported as being nutrient impaired (USEPA
1994; USEPA 1996).

Many States, Tribes, and Territories have adopted some form of nutrient criteria related to maintaining
natural conditions and avoiding nutrient enrichment.  Most States and Tribes have narrative criteria with
no specific numeric criteria. Established criteria most commonly pertain to P concentrations in lakes.
Nitrogen criteria, where they have been established, are usually in response to the toxic effects of


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S-mincc: Knvironmenial Science:  "l"he Way the World Worfcs 7/K by Ncbcl & Wright, f 2CHKJ.  Reprinted
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                                             P.«> 8

July 2000	Chapter 1.  Introduction

ammonia and nitrates. In general, levels of nitrates (10 ppm for drinking water) and ammonia high
enough to be toxic (1.24 mg N/L at pH = 8 and 25°C) will also cause problems of enhanced algal growth
(USEPA 1986).


States and authorized Tribes are responsible for setting water quality standards to protect the physical,
biological, and chemical integrity of their waters (Figure 1). "Water quality standards (WQS) are
provisions of State or Federal law which consist of a designated use or uses for the waters of the United
States, water quality criteria for such waters based upon such uses. Water quality standards are to protect
public health or welfare, enhance the quality of the water, and serve the purposes of the Act (40 CFR
131.3)" (USEPA 1994).  A water quality standard defines the goals for a waterbody by designating its
specific uses, setting criteria to protect those uses, and establishing an antidegradation policy to protect
existing water quality. The three main components of water quality standards are based on different
concerns: criteria are scientifically based; specific uses involve economic, social and political
considerations including the protection of downstream receiving waters; and the anti-degradation policy
protects the level of water quality necessary to maintain designated uses (Figure 1). A waterbody can be
defined by an existing use (a use actually attained in the waterbody on or after November 28, 1975—the
date of the promulgation by USEPA of the first water quality standards regulations) or designated use (a
use specified in a water quality standard for each waterbody or segment, regardless of whether it is being
attained).  An established use cannot be removed unless it is being replaced by one requiring more
stringent (protective) criteria.  At a minimum, the uses must include recreation in and on the water, and
propagation offish and wildlife (Clean Water Act, Section  101[a] and 303[c]). Other uses, such as
boating, cold water fisheries, or drinking water supply, may also be adopted.

Once designated uses of a waterbody have been established, the State or Tribe must adopt numeric or
narrative criteria to protect and support the specified uses. Narrative criteria are verbal expressions of
desired water quality conditions that are meant to describe the unimpaired condition of a waterbody.  A
narrative criterion from Vermont is shown below:

    There shall be no increase, in any waters, of total phosphorus above background conditions that
    may contribute to the acceleration of eutrophication or the stimulation of the growth of aquatic
    biota in a manner that has  an undue adverse effect on any beneficial values or uses of any
    adjacent or downstream waters.
    (Source: http://www.state.vt.us/wtrboard/mles/vwqs.htnrfC 1S1)

Numeric criteria, on the other hand, attempt to quantify this ideal by building on and refining narrative
criteria. Numeric criteria are values assigned to measurable components of water quality, such as the
concentration of a specific constituent that is present in the water column (e.g., average total phosphorus
[TP] concentration in a recreational stream shall not exceed 20 |-lg/L during the growing season).  In
addition to narrative and numeric criteria, some States and Tribes use numeric goals or assessment
levels,  an intermediate step between numeric criteria and water quality standards, that are not written into
State or Tribal laws but are used internally by the State or Tribal agency for assessment and management
                                            PAGE 9

July 2000	Chapter 1.  Introduction

Numeric criteria can be more useful than narrative criteria in a number of ways. Numeric criteria
provide distinct interpretations of acceptable and unacceptable conditions, form the foundation for
responsible measurement of environmental quality, and reduce ambiguity for management and
enforcement decisions.  Despite these advantages, however, most of the Nation's waterbodies do not
have numeric nutrient criteria. The lack of numeric criteria makes it difficult to assess the condition of
rivers and streams and develop protective water quality standards, hampering the water quality
manager's ability to implement management strategies.

Setting numeric nutrient criteria can provide a variety of benefits. For example, information obtained
from compiling existing data  and conducting new surveys can provide water quality managers and the
public a better perspective on the condition of State and Tribal waters. The compiled waterbody
information can be used to most effectively budget personnel and financial resources for the protection
and restoration of river and stream systems. In a similar manner, data collected in the criteria
development and implementation process can be compared before, during, and after specific
management actions.  Analyses of these data can determine the response of the waterbody and the
effectiveness of management endeavors.

Nutrient criteria also support watershed-protection activities. Nutrient criteria can be used in conjunction
with State/Tribal and  Federal biocriteria surveys, National Estuary Program and Clean Lakes projects,
and in development of TMDLs (Total Maximum Daily Loads) to improve resource management at local,
State, Tribal, and national levels.


This section describes the five general elements of nutrient criteria development outlined in the National
Strategy (USEPA  1998a) and is followed by a detailed overview of the steps taken to derive nutrient
criteria for river and stream systems. A prescriptive approach is not appropriate due to regional
differences that exist and the scientific community's limited technical understanding of the relationship
between nutrients, algal growth, and other factors (e.g., flow, light, substrata).  The approach chosen for
criteria development must be  tailored to meet the specific needs of each State or Tribe.

The USEPA has adopted the following principal elements as part of its National Strategy for the
Development of Regional Nutrient Criteria (USEPA 1998a). This document can be downloaded in PDF
format at the following website: www.epa.gov/OST/standards/nutrient.html.

1.       Ecoregional nutrient criteria will be developed to account for the  natural variation existing
        within various parts of the country. Different waterbody processes and responses dictate that
        nutrient criteria be specific to the waterbody type. No single criterion will be sufficient for each
        waterbody, therefore  we anticipate system classification within waterbody type for appropriate
        criteria derivation (see Section 1.5, item 2).

2.       Guidance documents for nutrient criteria will provide methodologies for developing nutrient
        criteria for four primary variables (total nitrogen [TN], TP, chlorophyll a [chl a], and a measure
        of turbidity) by ecoregion and  waterbody type.
                                           PAGE 10

July 2000	Chapter 1. Introduction

3.     Regional Nutrient Coordinators will lead State/Tribal technical and financial support operations
       used to compile data and conduct environmental investigations. A team of agency specialists
       from USEPA Headquarters will provide technical and financial support to the Regions, and will
       establish and maintain communications between the Regions and Headquarters.

4.     Nutrient criteria numeric ranges, developed at the national level from existing databases and
       additional environmental investigations, will be used to derive specific criterion values. Criteria
       values will be implemented into water quality standards by States and Tribes within three years
       of criteria publication.  Ecoregional nutrient criteria will be used by States and Tribes either as a
       point of departure for the development of more refined criteria, or as numeric criteria.  The
       USEPA will promulgate nutrient criteria in the absence of State or Tribal criteria development

5.     Nutrient and algal criteria will serve as benchmarks for evaluating the relative success of any
       nutrient management effort, whether protection or remediation.  Criteria will be re-evaluated
       periodically to assess whether refinements or other improvements are needed.

Nutrient criteria will form the basis for regulatory values such as standards, NPDES permit limits, and
TMDL values. Nutrient criteria will also be valuable as decision making benchmarks for management
planning and assessment.  The development of TMDLs may serve as an intermediate step between
criteria development and watershed-based management planning.

The USEPA Strategy envisions a process by which State/Tribal waters are initially measured, reference
conditions are established, individual waterbodies are compared to reference waterbodies, and
appropriate management measures are implemented.  This process is outlined in detail below.


Figure 3 presents a flow chart of the nine key steps involved in the criteria development process.  A brief
discussion of each of the steps involved, and what ideally is accomplished at each stage, is given below:

1. Identify water quality needs and goals with regard to managing nutrient enrichment problems. State
and Tribal water quality managers should define the water quality needs and goals for their rivers and
streams. Well-defined needs and goals will help in assessing the success of the criteria development
process, and will identify  attainable water quality goals.  This step should be revisited throughout the
criteria development process to assure defined needs and goals are addressed.

2. Classify rivers and streams first by type, and then by trophic status.  The intent of classification is to
identify groups of stream  systems that have comparable characteristics (i.e., biological, ecological,
physical, chemical features). Classifying rivers and streams reduces the variability of stream-related
measures (e.g., physical, biological, or water quality attributes) within classes and maximizes variability
among classes.  Classification will allow criteria to be identified on a broader rather than site-specific
                                            PAGE 11

                              Nutrient Criteria
                                Monitor and
I ijjui e 3. CriLLTia development flow chait.
                                     :, 1

July 2000	Chapter 1.  Introduction

3.  Select variables for monitoring nutrients. Variables, in the context of this document, are  measurable
attributes that can be used to evaluate or predict the condition or degree of eutrophication in  a water
body. Four primary water quality variables that must be addressed are TN, TP, chl a as an estimate of
algal biomass, and turbidity (see Section 3.2). Measurement of these variables provides a means to
evaluate nutrient enrichment and can form the basis for establishing regional and waterbody-specific
nutrient criteria.  Additional secondary variables may also be monitored.

4.  Design a sampling program for monitoring nutrients and algal biomass in rivers and streams. New
monitoring programs should be designed to identify statistically  significant differences in nutrient and
algal conditions while maximizing available management resources (see Section 4.2). Initial monitoring
efforts should focus on targeting reference stream reaches that can be used to assess impairment by
nutrients and algae.

5.  Collect data and build database. Potential sources of additional data for nutrient criteria  development
include current and historical water quality monitoring data from Federal, State, and local water quality
agencies; university studies; and volunteer monitoring information.  Databases can be used to organize
existing data, store newly gathered monitoring data, and manipulate data as criteria are being developed.
The USEPA is developing a national relational database for State/Tribal users to store, screen, and
manipulate nutrient-related data.

6.  Analyze data.  Statistical analyses are used to interpret monitoring data for criteria development.
Nutrient criteria development should relate nutrient concentrations in streams, algal biomass, and
changes in ecological condition (e.g., nuisance algal accrual rate and deoxygenation). In addition, the
relative magnitude of an enrichment problem can be determined by examining total nutrient
concentration and chl a frequency distributions for stream classes. These analyses provide water quality
managers with a tool for measuring the potential extent of overenrichment.

7.  Develop criteria based on reference conditions and data analyses.  Criteria selected must first meet
the optimal nutrient condition for that stream class and second be reviewed to ensure that the level
proposed does not result in adverse nutrient loadings to downstream waterbodies.

Three general approaches for criteria setting are discussed in this manual: (1) identification of
reference reaches for each stream class based on best professional judgement (BPJ) or  percentile
selections of data plotted as frequency distributions, (2) use of predictive relationships (e.g., trophic
state classifications, models, biocriteria), and (3) application  and/or modification of established
nutrient/algal thresholds (e.g., nutrient concentration thresholds or algal limits from published

Initial criteria should be verified and calibrated by comparing criteria in the system of study  to nutrients,
chl a, and turbidity values in waterbodies of known condition to  ensure that the system of interest
operates as expected. A weight of evidence approach that combines any or all of the three
approaches above will produce criteria of greater scientific validity. Selected criteria and the data
analyzed to identify these criteria will be comprehensively reviewed by a panel of specialists in each
USEPA Region.  Calibration and review of criteria may lead to refinements of either derivation
                                            PAGE 13

July 2000	Chapter 1. Introduction

techniques or the criteria themselves.  In  some instances empirical and simulation modeling, or data sets
from adjacent States/Tribes with similar systems may assist in criteria derivation and calibration.

8.  Implement nutrient control strategies.  Much of the management work done by USEPA and the States
and Tribes is regulatory. Nutrient criteria can be incorporated into State/Tribal standards as enforceable
tools to preserve water quality. As an example, nutrient criteria values can be included as limits in
NPDES permits for point source discharges. The permit limits for N, P and other trace nutrients emitted
from wastewater treatment plants, factories, food processors and other dischargers can be appropriately
adjusted and enforced in accordance with the criteria.

In addition, watershed source reduction responsibilities, especially with respect to nonpoint sources, can
be established on the basis of nutrient criteria.  Resource managers can use nutrient criteria to help define
source load allocations for a watershed.  Once sources have been identified, resource  managers can
begin land use improvements and other activities necessary to maintain or improve the system. System
improvements from a watershed perspective must proceed on a reasonable scale so that protection and
restoration can be achieved.

9.  Monitor effectiveness of nutrient control strategies and reassess the validity of nutrient criteria.
Nutrient criteria can be applied to evaluate the relative success of management activities. Measurements
of nutrient enrichment variables in the receiving waters preceding, during, and following specific
management activities, when compared to criteria, provide  an objective and direct assessment of the
success of the management project.

Throughout the continuing process of problem identification, response and remediation, and evaluation
to protect and enhance our water resources, States, Tribes, and the USEPA are called upon by the U.S.
Congress to periodically report on the status of the Nation's waters (Section 305 [b] of the Clean Water
Act as amended).  Establishment of nutrient criteria will add two causal and two response parameters
(see Sections 3.2 - 3.3) to the measurement process required for the biannual Report to Congress. These
measurements can be used to document change and monitor the progress of nutrient reduction activities.

The chapters that follow present detailed information that elaborates upon this outline of nutrient criteria
development. For some water quality managers, components of certain criteria development steps may
already be completed for existing stream monitoring programs (e.g., sampling design  for specific stream
systems).  Thus, some steps can be excluded as the manager advances further through the process.
However,  should new or revised monitoring programs be envisioned, review by the water quality
manager of each of the steps outlined  in this guidance is recommended.

Although this document is meant to provide the best available scientific procedures and approaches for
collecting  and analyzing nutrient-related data, including examination of nutrient and algal relationships,
a comprehensive understanding of nutrient and algal dynamics within all types of stream systems is
beyond the current state of scientific knowledge. The National Nutrient Program represents a new effort
and approach to criteria development that, in conjunction with efforts made by State and Tribal water
quality managers, will ultimately result in a heightened understanding of nutrient/algal relationships.  As
the proposed process is put into use  to set criteria, program success will be gauged over time through
evaluation of management and monitoring efforts. A more comprehensive knowledge base pertaining to

                                            PAGE  14

July 2000	Chapter 1. Introduction

nutrient and algal relationships will be expanded as new information is gained and obstacles overcome,
justifying potential refinements to the criteria development process described here.


The overarching goal of developing nutrient criteria is to ensure the quality of our national  waters.
Ensuring water quality may include restoration of impaired systems, conservation of high quality waters,
and protection of systems at high risk for future impairment.  The goals of a State or Tribal water quality
program will be defined differently based on the needs of each State or Tribe, but should, at a minimum,
protect established designated uses for the waterbodies within State or Tribal lands.  Once goals and
objectives are defined, they should be revisited regularly to evaluate progress and assess the need for
refinements or revisions.

The first task of a water quality manager is to set a water quality goal, such as "no nuisance algal blooms
such that swimming is restricted during  summer months." After such a goal is established, managers
must develop a timeline, budget, and plan of action for accomplishing this goal. Needs of the program,
such as funding, acquiring relevant data, and assigning employee responsibilities must be addressed.
Well-defined needs and goals will help in assessing the success of the criteria development process and
will identify attainable water quality goals.


This manual comprises nine chapters that formulate the steps recommended for nutrient criteria
development.  The first step of the process, identifying goals and objectives, is unique to each water
quality manager and should be revisited regularly to evaluate progress and assess the need for goal
and/or objective refinements or revisions.  The next step entails stream classification based on physical
and nutrient gradient factors (Chapter 2). Sampling variables, including primary and appropriate
secondary variables (Chapter 3), should be selected for monitoring efforts.  Once these variables are
determined, sampling designs for new monitoring programs can be developed (Chapter 4).  Chapter 5
discusses potential data sources that can be used by water quality managers to develop criteria and
addresses the usefulness of databases  in compiling, storing, and analyzing data. A variety of data
analysis methods and techniques used to derive  criteria are presented in Chapters 6 and 7, respectively.
These two chapters are meant to provide water quality managers with a range of options that may be
useful for deriving criteria. Nutrient management programs (including nutrient control strategies for
point and nonpoint sources) and points of contact or references that may be useful to water quality
managers are provided in Chapter 8. Chapter 9  concludes the criteria development process with a brief
discussion of continued monitoring and  reassessment of goals and the established criteria.

It should be noted that completion of each previously described step may not be required by all water
quality managers.  Many State  or Tribal water quality agencies already have established stream classes,
monitoring programs, and/or databases for their programs and therefore can bypass those steps. This
manual is meant to be comprehensive in the  sense that all of the criteria development steps are described;
however, the process can be adapted to suit existing water quality programs.
                                            PAGE 15

July 2000	Chapter 1.  Introduction

Appendix A of the manual contains five case studies: (1) Tennessee ecoregion streams (southeastern
U.S.), (2) Clark Fork River (western forested mountains), (3) upper Midwest river basins (prairie-
agricultural river systems), (4) Bow River (northern Rockies), and (5) desert streams (arid western U.S.).
These case studies are meant to characterize some of the variability observed within North American
stream systems and region-specific issues that should be considered when developing nutrient criteria.
Appendices B and C provide water quality managers with information and additional references for
laboratory/field methods and statistical tests/modeling tools, respectively.  Appendix D defines
frequently used acronyms and technical terms found throughout the document.
                                            PAGE 16

Chapter  2.
Stream System
                                                                              Stream System

This chapter discusses classification of streams for water quality assessment and nutrient criteria
development. The purpose of classification is to identify groups of rivers or streams that have
comparable characteristics (i.e., similar biological, ecological, physical, and/or chemical features) so that
data may be compared or extrapolated within stream types.  This chapter focuses on providing water
quality managers with a menu of tools that can be used to classify the stream system of interest, resulting
in different aggregations of physical parameters that correlate with water quality variables.

Classifying rivers and streams reduces the variability of stream-related measures (e.g., physical,
biological, or water quality variables) within identified classes and maximizes inter-class variability.
Classification schemes based on non-anthropogenic factors  such as parent geology, hydrology, and other
physical and chemical attributes help identify variables that affect nutrient/algal interactions.
Classification can also include factors that are useful when creating nutrient control strategies such as
land use characteristics, bedrock geology, and identification of specific point and nonpoint nutrient
sources. Grouping streams with similar properties will aid in setting criteria for specific regions and
stream system types, and can provide information used in developing management and restoration

A two-phased approach to system classification is prescribed here. Initially, stream classification is
based primarily (though not exclusively) on physical parameters associated with regional and site-
specific characteristics, including climate, geology, substrate features, slope, canopy cover, retention time
of water, discharge and flow continuity, system  size, and channel morphology. The second phase
involves further classifying stream systems by nutrient gradient  (based upon measured nutrient
concentrations and algal biomass).  Trophic state classification,  in contrast, focuses primarily on
chemical and biological parameters including concentrations of  nutrients, algal biomass as chlorophyll a,
and turbidity, and may also include land use and other human disturbance parameters. The additional
                                           PAGE 17

July 2000	Chapter 2. Stream System Classification

sub-classification of streams by nutrient condition, in conjunction with an understanding of dose-
response relationships between algae and nutrients, helps define the goals for establishing nutrient

The physical and nutrient characterization discussed above can often be complemented by designated use
classifications. These are socially-based classifications developed in accordance with EPA policy and
based on the predominant human uses that a State or Tribe has concluded are appropriate for a particular
stream or river. Water quality standards, predicated on criteria, are applied to these designated use
classifications and are enforceable to protect specified uses. Uses are designated in accordance with
relative water quality condition and trophic state.  For more information on designated use classifications
and their relationship to water quality criteria and standards, see the USEPA Water Quality Standards
Handbook (USEPA 1994).

Stream classification requires consideration of stream types at different spatial scales. Drainage basins
can be delineated and classified at multiple spatial scales ranging from the size of the Mississippi River
basin to the  few square meters draining into a headwater stream.  The general approach is to establish
divisions at the largest spatial scale (river basins of the continent), and then to continue stratification at
smaller scales to the point at which variability of algal-nutrient relationships is limited within specific
stream classes.

The highest level of classification at the national level is based on geographic considerations. The
Nation has been divided into 14 nutrient ecoregions (Omernik 2000) based on landscape-level geographic
features including climate, topography, regional geology and soils, biogeography, and broad land use
patterns (Figure 4). The process of identifying geographic divisions (i.e., regionalization) is part of a
hierarchical classification procedure that aggregates similar stream systems together to prevent grouping
of unlike streams.  The process of subdividing the 14 national ecoregions should be undertaken by the
State(s) or Tribe(s) within each of those ecoregions. Classification of State/Tribal lands invariably
involves the professional judgement of regional experts. Experts familiar with the range of conditions in
a region can help define a workable system that clearly separates different ecosystem types, yet does not
consider each system a special case.

The usefulness of classification is determined by its practicality within the region,  State, or Tribal lands
in which it will be applied; local conditions determine the appropriate classes. In this Chapter, a
regionalization system derived at the national level is presented.  This system provides the framework
from which  State and Tribal water resource management agencies can work to establish appropriate
subdivisions. In addition, different classification schemes are presented to provide resource  managers
with information to use  in choosing a stream classification system. It is the intent of this document to
provide adequate flexibility to States and Tribes in identifying State and Tribal-specific subregions.

The following sections describe specific examples of first-phase physical classification based on
variation in natural characteristics and secondly, nutrient gradient classification schemes for identifying
similarities within stream system types.  Each classification method is presented and the rationale for its
use is provided.
                                             PAGE 18

                            Draft Aggregations of Level III  Ecoregions
                                   for the National Nutrient  Strategy

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July 2000	Chapter 2. Stream System Classification


The classification systems described in the following sections (including ecoregional, fluvial
geomorphological, and stream order classification schemes) are based on physical stream and watershed
characteristics.  Stream systems are characterized by the continual downstream movement of water,
dissolved substances, and suspended particles. These components are derived primarily from the land
area draining into a given channel or the drainage basin (watershed).  The climate, geology, and
vegetational cover of the watershed are reflected in the hydrological, biological, and chemical
characteristics of the stream. Therefore, factors such as general land use, climate, geology and general
hydrological properties must be considered regardless of the method of classification used.  As described
above, the initial classification should be based on physical characteristics of parent geology, elevation,
slope, hydrology and channel morphology. Hydrologic disturbance frequency and magnitude are also
important when classifying stream systems.

In addition to classification of stream systems, factors contributing to trophic state and macrophyte and
algal growth should be considered.  Table 1 presents several factors that  affect periphyton and plankton
biomass levels in stream systems. Macrophyte-dominated systems could occur under conditions similar
to those favorable for high periphyton biomass (Table 1), if the velocity is low and the substrate includes
organic sediment. Macrophytes are generally unlikely to develop in systems where the stream bottom is
composed primarily of gravel or other large substrata (Wong and Clark 1979). The following section
specifically addresses the potential effects of hydrology and channel morphology, flow, and parent
geology on algal and macrophyte growth within stream systems.

River and stream types (and reaches within these waterbodies) are too diverse to set one criterion for all
stream/river types. However, it is not necessarily feasible or recommended to develop site-specific
criteria for every stream reach within the U.S.  Morphological and fluvial characteristics of a stream
influence many facets of its behavior.  Streams with similar morphologies may have similar nutrient
capacities or similar responses to nutrient loadings.  Rivers and streams are very diverse within
ecoregions.  Reaches within one stream can have a distinct morphology.  The geomorphology of a river
or stream - its shape, depth, channel materials - affects the way that waterbody receives, processes, and
distributes nutrients.  Nutrient cycling processes that occur upstream affect communities and processes
downstream by altering the form and concentration of nutrients and organic  matter in transport (nutrient
spiraling); these effects can be further intensified by patch dynamics (Mulholland et al. 1995).  The
spatial scales which most influence upstream-downstream linkages are the geomorphology-controlled
patterns observed at the landscape scale and the nutrient-cycling-controlled patterns observed at the
stream reach scale (Mulholland et al. 1995). Therefore, to set appropriate criteria for rivers and streams
in an ecoregion, streams must be classified by their morphological characteristics at both the landscape
and stream reach scale, with an emphasis on those characteristics most likely to affect nutrient cycling.


Ecoregions are based on geology, soils,  geomorphology, dominant land uses, and natural vegetation
(Omernik 1987; Hughes and Larsen 1988) and have been shown to account for variability of water
quality and aquatic biota in several areas of the United States (e.g., Heiskary et al. 1987; Barbour et al.
1996). On a national basis, individual streams and rivers are affected by  varying degrees of development,
and user perceptions of acceptable water quality can differ even over  small distances.


July 2000
           Chapter 2. Stream System Classification
Table 1. Geological, physical, and biological habitat factors that affect periphyton and phytoplankton
biomass levels in rivers and streams given adequate to high nutrient supply and non-toxic conditions.
Note that only one factor is sufficient to limit either phytoplankton or periphyton biomass.
 Phytoplankton-Dominated Systems
Periphyton-Dominated Systems
 High Phytoplankton Biomass
 • low current velocity(< 10 cm/s)/long
   detention time (>10 days) and
 • low turbidity/color and
 • open canopy and
 • greater stream depth and
 • greater depth to width ratio
High Periphyton Biomass
•  high current velocity (>10 cm/s) and
•  low turbidity/color and
•  open canopy and
•  shallow stream depth and
•  minimal scouring and
•  limited macroinvertebrate grazing and
• gravel or larger substrata and
• smaller depth to width ratio	
 Low Phytoplankton Biomass
 • high current velocity (>10 cm/s)/short
    detention time (<10 days) and/or
 • high turbidity/color and/or
 • closed canopy and/or
 • shallow stream depth
Low Periphyton Biomass
•  low current velocity (< 10 cm/s) and/or
•  high turbidity/color and/or
•  closed canopy and/or
•  greater stream depth and/or
•  high scouring and/or
•  high macroinvertebrate grazing and/or
•  sand or smaller substrata
Ecoregions are generally defined as relatively homogeneous areas with respect to ecological systems and
the interrelationships among organisms and their environment (Omernik 1995).  Ecoregions can occur at
various scales; broad-scale ecoregions may include the glaciated corn belt of the central and upper
Midwest or the arid to semi-arid basin and desert regions of the southwest. At more refined scales,
regions within the broader regions can be identified.

Ecoregions serve as a framework for evaluating and managing natural resources.  The ecoregional
classification system developed by Omernik (1987) is based on multiple geographic characteristics (e.g.,
soils, climate, vegetation, geology, land use) that are believed to cause or reflect the differences in the
mosaic of ecosystems.  Omernik's original compilation of national ecoregions was based on a fairly
coarse (1:7,500,000) scale that has subsequently been refined for portions of the southeast, mid-Atlantic,
and northwest regions,  among others (Omernik 1995).  The process of defining subregions within an
ecoregion requires collaboration with State/Tribal  scientists and resource managers. Once appropriate
subregions are delineated, reference sites can be identified (see  Section 4.2).  Similar to the process
described for ecoregion refinement, reference site selection involves interactions with scientists and
water quality managers that understand local conditions.  Field verification techniques, methods for
selecting reference sites for small and/or disjunct subregions can be found in Omernik (1995).

July 2000	Chapter 2. Stream System Classification


Fluvial geomorphology mechanistically describes river and slope processes on specific types of
landforms, i.e., the explanation of river and slope processes through the application of physical and
chemical principles. The morphology of the present-day channel is governed by the laws of physics
through observable stream channel features and related fluvial processes. Stream pattern morphology is
directly influenced by eight major variables including channel width, depth, velocity,  discharge, channel
slope, roughness of channel materials, sediment load and sediment size (Leopold et al. 1964).  A change
in one variable causes a series of channel adjustments which lead to changes in the other variables,
resulting in channel pattern alterations. Many stream classification systems, have a fluvial
geomorphologic component.


The stream classification method devised by David Rosgen is a comprehensive guide  to river and stream
classification (see Rosgen  1994 or 1996).  The Rosgen classification system is currently utilized by
several States. This system integrates fluvial geomorphology with other stream characteristics.
Specifically, Rosgen combines several methods of stream classification into one complete, multi-tiered
approach.  Rosgen's method has four levels of detail: broad morphological (geomorphic)
characterization, morphological description (stream types), stream "state" or condition, and verification.
Level I classification, geomorphic characterization, takes into account channel slope (longitudinal
profile), shape (plan view morphology, cross-sectional geometry), and patterns.  Level I streams are
divided into seven major categories and labeled A-G. The Level II morphological delineative criteria
include landform/soils,  entrenchment ratio, width/depth ratio, sinuosity, channel slope, and channel
materials.  The 42 subcategories of Level II streams are labeled with a letter and a number, A1-G6 (see
Rosgen 1994, 1996). Level III designations are primarily used in specific studies or in restoration
projects to assess the quality and/or progress of a specific reach. Level IV classifications may  be used to
verify results of specific analyses used to develop empirical relationships (such as a roughness
coefficient) (Rosgen 1996).

Rivers  and streams are complicated systems.  A classification scheme is an extreme simplification of the
geomorphic and fluvial processes. However, the Rosgen system of classification is a  useful frame of
reference to:

1.    Predict a river's behavior from its appearance;
2.    Develop specific  hydraulic and sediment relations for a given morphological channel type and
3.    Provide a mechanism to extrapolate site-specific data collected on a given stream reach to those of
     similar character; and
4.    Provide a consistent and reproducible frame of reference of communication for  those working with
     river systems in a variety of professional disciplines (Rosgen 1994).

Classification of streams and rivers allows comparisons and extrapolation of data from different streams
or rivers in an ecoregion. Comparing similar streams may help to predict the behavior of one stream
based data and observations from another. Applied River Morphology (Rosgen 1996) contains in-depth
descriptions of each Level II stream type (A1-G6) and includes photographs and illustrations.  Rosgen


July 2000	Chapter 2. Stream System Classification

discusses theoretical characterizations and variables and provides field methods for delineating stream
types. The Rosgen classification system may be more detailed than needed for many States and Tribes.
For more information on the Rosgen classification system, see Rosgen (1996).


Identifying stream orders in a given delineated watershed can provide a classification system for
monitoring streams. A variety of methods have been proposed for ordering drainage networks for stream
classification and monitoring.  The Horton-Strahler method (Horton 1945; Strahler 1952) is most widely
used in the US.  Each headwater stream is designated as a first order stream. Two first order streams
combine to produce a second order stream, two second order streams combine to produce a third order
stream and so on (Figure 5). Only when two streams of the same order are combined does the stream
order increase. Numerous lower order streams may enter a main stream without changing the stream
order. As a result, utilizing this method for classification may lead to problems of disparity in
hydrological and ecological conditions among same order streams even within the same region.
Resource managers using stream order as a classification system should ensure that topographic maps
used to identify watershed boundaries all utilize the same scale.  The inclusion or exclusion of perennial
headwater streams should be decided before ordering drainage networks of interest.

Stream order (Strahler 1952) is used to classify streams in the EPA Environmental Monitoring and
Assessment Program (EMAP).  Sample sites were selected using a randomized sampling design with a
systematic spatial component.  The survey in the mid-Atlantic region was restricted to wadeable streams
defined  as 1st, 2nd, or 3rd order as delineated using USGS 1:100,000 scale USGS hydrologic maps that
were incorporated into EPA's River Reach File (Version 3).  Sample probabilities were set so that
approximately equal numbers of 1st, 2nd, and 3rd order stream sites would appear in the sample population.
Data were collected at 368 different sites representing 182,000 km of wadeable streams in the mid-
Atlantic region (Herlihy et al. 1998).


The following sections focus on physical characteristics of streams that can be used to sub-classify
stream systems. Physical characteristics that can be used for stream classification include system
hydrology and morphology, flow conditions, and underlying geology.

Hydrology and Morphology
Hydrologic and channel morphological characteristics are often  important determinants of algal biomass.
Unidirectional flow of water sets up longitudinal  patterns in physical and chemical factors that may also
affect macrophyte growth when light and substrate conditions are adequate. Channel morphology or
shape of a river or stream channel at any given location is a result of the flow, the quantity and character
of the sediment moving through the channel, and the composition of the streambed and banks of the
channel including riparian vegetation characteristics (Leopold et al. 1964).  Frequent disturbance from
floods (monthly or more frequently) and associated movement of bed materials can scour algae from the
surface rapidly and often enough to prevent attainment of high biomass (Peterson 1996). In areas with
less stable substrata, such as sandy bottomed streams, only slight increases in flow may lead to bed
movement and scouring. Scouring by movement of rocks has been directly linked to reduction in algal
biomass and subsequent recovery from floods (Power and Stewart 1987).  Larger, more stable rocks can
have higher periphyton biomass (Dodds  1991; Cattaneo et al.  1997). Thus, in cases where


July 2000
Chapter 2. Stream System Classification
         \     -%,
           \      i\       >

            I        Y
           i          t
        ;        *

    /i          \   A
   I    ***-^,      ?  A   '
   *         "**•«    •*• Jv.  ?
  Figure 5. Stream ordering of a watershed basin network using the Strahler method. (Adapted from

  Strahler [1964]).

July 2000	Chapter 2.  Stream System Classification

there is frequent movement of substrata, high nutrients may not necessarily translate into excessive algal
biomass (Biggs et al. 1998a,b).

Consideration of both geology and hydrologic disturbance can provide important insights into factors
influencing algal biomass. Research done in New Zealand identified geology, land use patterns, and
stream conductivity (as a surrogate for total nutrients) as important determinants of algal biomass
because these factors affected nutrient inputs and flood disturbance (Biggs  1995).  The effects of
disturbance by floods can be complex and complicated by biological factors; very stable stream beds may
be associated with an active grazing community and have less biomass than more unstable systems. This
notwithstanding, flow regime, channel morphology and bed composition (such as sand versus large
boulders) appear to be major controlling factors and should be considered when managing eutrophication
in a particular watershed.

Flow Conditions
Low and stable flow conditions should be considered in addition to frequency and timing of floods when
physically classifying stream systems. Flood frequency and scouring may be greater in steep-gradient
(steep slope) and/or channelized streams and in watersheds subject to intense precipitation events or
rapid snow melt. Periods of drying can also reduce algal biomass to low levels (Dodds et al. 1996). A
stream may flood frequently during certain seasons, but also remain stable for several months  at a time.
The effects of eutrophication may be evident during stable low flows.  Also, stable flow periods are
generally associated with low flow conditions, resulting in the highest nutrient concentration from point
source loading. Hence, low-flow periods often present ideal conditions for achieving maximum algal
biomass. For these reasons, nutrient control plans may require strategies that vary seasonally (e.g.,
criteria for a specific system may differ with season or index period).

Underlying Geology
Streams draining watersheds with phosphorus-rich rocks (such as from sedimentary or volcanic origin)
may be naturally enriched and the control of algal biomass by nutrient reduction in such systems may be
difficult. Bedrock composition has been related to algal biomass in some systems (e.g., Biggs 1995).  In
addition, nutrient content, and hence algal biomass, often naturally increases as elevation decreases,
especially in mountainous areas (Welch et al. 1998).  Some naturally phosphorus-rich areas include
watersheds draining some volcanic soils, and other areas have high weathering of nitrate from bedrock
(Halloway et al. 1998). Review of geologic  maps and consultation with a local Natural Resources
Conservation Service (NRCS) agent or soil scientist may reveal such problems.


Nutrient loading is the factor most likely to be controlled by humans, but the ability to control algal
biomass within the stream itself may be influenced by additional factors. Factors that may control algal
biomass in streams include bedrock type and elevation (because they determine the natural or
background nutrient supply), physical disturbance (flooding and drying), light, sediment load, and
grazing. Many of these factors will be accounted for in the physical classification of stream systems.
However,  characterization of nutrient gradients in stream systems will be influenced by land use
practices as well as point source discharges (Carpenter et al. 1998). The nutrient ecoregions defined by
Omernik (2000) separate the country into large ecoregions with common land use characteristics.  These
ecoregions should be further subdivided for use at the State, Tribal, or local scale.


July 2000	Chapter 2. Stream System Classification

Changes in the natural processes that control algal production and biomass in a stream or river as one
moves downstream through a watershed are obviously an important consideration. The River Continuum
Concept (RCC) (Vannote et al. 1980) provides one general model for predictions of stream size effects
on algal-nutrient relations. The RCC predicts, among other things, that benthic algal biomass will
increase with stream size to a maximum for intermediate stream orders (i.e., third and fourth order stream
reaches) as stream width increases and canopy cover consequently decreases. The RCC also suggests
that (1)  sestonic (suspended) chlorophyll will become more important in larger, slow-moving rivers and
(2)  turbidity in deep, high order streams causes light attenuation, which tends to prohibit high benthic
algal biomass. The RCC may not hold for unforested watersheds (e.g., Dodds et al. 1996)  or those with
excessive human impacts such as impoundments or severe sediment input from logging. For example,
Rosenfield and Roff (1991) observed that stream primary productivity in Ontario streams was largely
independent of stream size. However, the RCC is valuable for identifying variables that change with
stream size and affect algal-nutrient relations.


The draft nutrient aggregations map of level III ecoregions for the conterminous United States (Figure 4;
Omernik 2000) defines broad areas that have general similarities in the quantity and types  of ecosystems
as well as natural and anthropogenic characteristics of nutrients.  As such, ecoregions are intended to
provide  a spatial framework for the National Nutrient Criteria Program. In general, the variability in
nutrient concentrations in streams, lakes, and soils should be less in those ecoregions having higher
hierarchical levels, i.e., nutrient concentrations found in level III ecoregions (84 ecoregions delineated for
the  mainland U.S.) (Omernik 1987), than those of waterbodies located in draft aggregations of Level III


The primary response variable of interest for stream trophic state characterization is algal biomass.  Algal
biomass is usually concentrated in the benthos of fast-flowing, gravel/cobble bed streams (i.e.,
periphyton dominated)  and measured as benthic chl a per unit area of stream substrate.  In  slow-moving,
sediment-depositing rivers (i.e., plankton dominated), algal biomass is suspended in the water column
and measured as sestonic chl a per unit water volume. Trophic classifications for lakes and reservoirs
may be  appropriately applied to seston in slow-moving rivers as these classifications are based primarily
on chl a per unit volume (e.g., OECD 1982). However, lake classification schemes have limited value
for  fast-flowing streams dominated by benthic periphyton because the limited areal planktonic
chlorophyll data available for lakes reveal little differentiation between oligotrophic and eutrophic
systems (Dodds et al. 1998).

Nitrogen and phosphorus are important variables for classification of trophic state because they are the
nutrients most likely to limit aquatic primary producers and are expressed per  unit volume in both fast-
flowing  streams and slow-flowing rivers. Concentrations of total nutrients and suspended algal biomass are
well-correlated in lakes  and reservoirs (Dillon and Rigler 1974; Jones and Bachmann 1976; Carlson 1977).
Developing predictive relationships between nutrient and algal levels in fast-flowing streams may be
difficult considering that most available nutrients are in the water column and most chl a is in the benthos.
Therefore, trophic state  classification for periphyton-dominated stream systems is more appropriately based
on benthic or areal algal biomass (e.g., mg/m2 chl a) than on concentrations of N and P.


July 2000
Chapter 2. Stream System Classification
As stated above, classification of trophic state in stream systems is most appropriately based on algal
biomass and secondarily on nutrients. When trophic state classification is based upon nutrients, total
water column concentrations (TP and TN) are more appropriate than dissolved inorganic nitrogen (DIN)
or soluble reactive phosphorus (SRP).  Inorganic nutrient pools are depleted and recycled rapidly. Most
monitoring programs will not be able to closely track soluble nutrients in a stream system and should
therefore focus on total water column concentration rather than soluble nutrient species.

Additional factors also confound the interpretation of dissolved nutrient data.  Algae are able to directly
utilize inorganic nutrient pools (DIN and SRP) and deplete these pools if algal biomass is high enough
relative to stream size and nutrient load.  Thus, moderately low levels of DIN and SRP do not necessarily
result in low algal biomass. This seeming contradiction is because the supply rate of inorganic nutrients
may still be high even if a large biomass of algae has removed  a significant portion of the DIN or SRP
from the water column. Algal growth rate (including diatoms and filamentous greens) can be saturated at
low dissolved inorganic nutrient concentrations (Bothwell 1985, 1989; Watson et al. 1990; Walton et al.
1995). Total phosphorus and TN may better reflect stream trophic status compared to inorganic P and N
because algal drift increases with benthic algal biomass. Thus, as soluble nutrient depletion increases
with benthic algal biomass, that depletion can be partially compensated for by increases in particulate
fractions of TP and TN resulting from benthic algal drift and suspension in the water column.

A trophic classification scheme for streams and rivers, based on chlorophyll a and nutrients, was recently
developed by Dodds et al. (1998). The approach used by Dodds et al. was  based upon establishing
statistical distributions of trophic state-related variables. The data were viewed in two ways: 1) three
trophic state categories were constructed based on the lower, middle, and upper thirds of the distributions
and were assigned to oligotrophic, mesotrophic and eutrophic categories respectively; and 2) the actual
distributions (Table 2) were used to determine the proportion of streams in each trophic category. It
should be stressed that this approach proposes

Table 2. Suggested boundaries for trophic classification of streams  from cumulative frequency
distributions. The boundary between oligotrophic and mesotrophic systems represents the lowest third of
the distribution and the boundary between mesotrophic and eutrophic marks the top third of the
Variable (units)
mean benthic chlorophyll (mg rrT2)+
maximum benthic chlorophyll (mg rrf 2)+
sestonic chlorophyll
(M-g L-T
TN (|ig L-')+'+++
TP (|J.g L-1)^'^
Sample size
+Data from Dodds et al. (1998); ++data from Van Nieuwenhuyse and Jones (1996); +++data from Omernik

July 2000	Chapter 2. Stream System Classification

trophic state categories based on the current distribution of algal biomass and nutrient concentrations
which may be greatly changed from pre-human settlement levels. These distributions were determined
using data for benthic and sestonic chlorophyll and water column TN and TP from a wide variety of
previously published studies. The data were gathered from temperate stream sites located in North
America and New Zealand. The data for TN and TP used in this analysis were not taken from the same
sources as the data for benthic and sestonic chlorophyll a.  Hence, the distributions should only be used
to link nutrient concentrations and algal biomass in a very general sense.

Management Applications
Classifying streams by trophic state can assist water quality managers in setting criteria and identifying
those systems most at risk for impairment by nutrient enrichment. For example, an understanding of
stream trophic state and ambient nutrient concentrations allows the manager to determine if the system of
interest is eutrophic due to nutrient inputs that are natural or cultural. Comparisons with streams in the
same local area that have similar physical characteristics will help clarify this issue prior to making
management decisions. Management options may be limited if the condition of the stream is caused by
high background levels of nutrient enrichment.  However, if nutrient sources are largely cultural,
establishing nutrient control strategies may realistically result in improvements in stream trophic state
and therefore be useful in managing the stream system.

Chapter 3.
Select Variables
                                                                            Select Variables

Candidate variables, in the context of this document, are measurable water quality variables that can be
used to evaluate or predict the condition or degree of eutrophication in a water body. Data that are most
useful in determining river and stream trophic status are water column nutrient concentrations and algal
biomass.  Benthic and/or planktonic biomass can reach nuisance levels in many stream systems.
Measurement of these variables provides a means to evaluate the current degree of nutrient enrichment,
and can form the basis for establishing regional and waterbody-specific nutrient criteria. Numerous
variables can potentially be used as part of nutrient surveys or eutrophication assessments including
measures of water column nutrient concentrations (e.g., TP, SRP, orthophosphate, TN, total Kjeldahl
nitrogen [TKN], NO3", ammonia [NH3]); dissolved organic carbon (DOC); water column and
algal/macrophyte tissue N:P nutrient ratios; and algal biomass surrogates (e.g., chl a, ash-free dry mass
[AFDM], turbidity, percent of benthic algal coverage, species composition).

Criteria development at the EPA Regional and National level will begin with nutrient data gleaned
from EPA's STORET (STOrage and RETrieval) database. Primary nutrient parameters to be
considered include water column concentrations of TN, TP, algal biomass as chl a, and turbidity or
transparency.  These four variables are considered a starting point for criteria development and their
efficacy in controlling nutrient enrichment will be re-evaluated over time.  Inorganic nutrient species
(PO4 and NO3) are usually more biologically available, and may need to  be considered in instances where
small scale effects from specific sources are an important issue (e.g., point source impacts from outfall
pipes, and non-point source impacts during rain events immediately following inorganic fertilizer
application). STORET data on the primary parameters are the foundation of the dataset used at National
and Regional levels for developing nutrient criteria. Supplemental data from other Federal agencies,
State/Tribal agencies, and university studies will  also be included as available. Sources of available data,
the parameters included in the primary datasets, and the minimum data requirements for criteria
development are discussed in Chapter 5.

Interpretation of parameter values and their cause-and-effect relationships depends on whether the data
are from stream segments that are slow-moving with a depository substratum and plankton-dominated, or
                                          PAGE 29

July 2000	Chapter 3. Select Variables

that are fast-moving with an eroding (gravel/cobble) substratum and periphyton-dominated. Criteria for
streams with intermediate characteristics, i.e., in which the bottom is not generally visible in slow-
moving segments and is not likely to have algal biomass problems, may need to be developed primarily
for fast moving stream segments.  Hence, significance of each individual or group of variables is
discussed for each extreme stream/river type; the reader, of course, realizes that flowing waters can be
found along all points on the trophic continuum and parameter values can vary even within a stream
reach.  This chapter lists and describes (1) primary response variables that will be used by EPA to set
default criteria and (2) secondary response variables (including sensitive variables, i.e., those likely to be
most sensitive to enrichment as influenced by increased primary producer biomass and metabolic
activity) that can be used to predict the enrichment status of stream systems.


The primary variables considered for nutrient criteria development are water column concentrations of
TN, TP, benthic and planktonic algal biomass as chl a, and turbidity or transparency. These variables
will be used to set criteria ranges for each EPA ecoregion at the National level (see section 1.5). The
primary causal variables, TN and TP, are closely related to the response variables, algal biomass as chl a
and turbidity or transparency, although the relationships between these variables are not as tightly
coupled in rivers and streams as they are in lakes. Concentrations of nutrients and algal biomass and
measures of turbidity/transparency are more highly variable in rivers and streams because of fluctuating
flow conditions.  Therefore, knowledge of the flow  conditions  in the waterbody of concern will be used
to help define the nutrient condition of that waterbody, and will be used in criteria development. Criteria
will not be established for flow as a variable.  Stream sampling should be conducted during periods of
peak algal biomass or periods when problems related to algae may be greatest  (e.g., low-flow or
following rain  events with high nonpoint source nutrient inputs). Subsequent sections of the chapter
discuss other potential variables that may be useful in developing nutrient criteria.  Methods for
measuring and analyzing many of the variables discussed in this Chapter can be found in Appendix B.


Nitrogen and phosphorus are the primary macro-nutrients that enrich streams and rivers and cause
nuisance levels of algae. Conditions that allow periphyton/plankton biomass to accumulate (i.e.,
adequate light, optimum current velocity  [periphyton], sufficient water detention time  [plankton], as well
as low loss  to grazing) will not result in high biomass without sufficient nutrient supply. Nutrients,
especially P, are frequently the key stimulus to increased and high algal biomass.

Phosphorus is the key nutrient controlling productivity and causing excess algal biomass in many
freshwaters worldwide. However, nitrogen can become important in waters receiving  agricultural runoff
and/or wastewater with a low N/P ratio and in waters with naturally phosphorus-rich bedrock (Welch
1992). Nitrogen may have more importance as a limiting element of biomass in streams than in lakes
(Grimm and Fisher 1986; Hill and Knight 1988; Lohman et al. 1991; Chessman et al. 1992; Biggs 1995;
Smith et al. 1999).  Lohman et al. (1991)  reported low NO3-N causing N limitation at sixteen sites in ten
Ozark Mountain  streams and cited sources for N limitation in northern California and the Pacific
Northwest.  Nitrogen was clearly the limiting nutrient in the upper Spokane River, Washington (Welch et
al. 1989). Chessman et al. (1992) observed that N was more often limiting than P in Australian streams.
                                            PAGE 30

July 2000	Chapter 3. Select Variables

Analyses of data from 200 rivers suggests that TN is more closely correlated to mean benthic algal
biomass than TP, and DIN is more closely correlated to biomass than SRP (Dodds et al. unpublished).

The directly available forms of N and P are mainly inorganic (NO3~, NH4+ and PO43"), although many
algae are able to use organic forms (Barley 1982). Total N and TP include these soluble fractions, as
well as the particulate and dissolved organic fractions.  Particulate and dissolved organic fractions are not
immediately available and portions may be relatively refractory.  Because soluble inorganic fractions are
directly available, soluble inorganic N, P, or both may be low during active growth periods when demand
is high and, therefore, may not be good predictors of biomass (Welch et al. 1988). Total N and TP are
often good predictors of algal biomass in lakes and reservoirs, to a large extent because much of the
particulate fraction is live algal biomass. That is not the case in fast-flowing, gravel/cobble bed streams
where the total nutrient concentration includes detritus but not the living periphytic algae where biomass
measurements are taken. In fast-flowing systems, water column nutrients flow past the living periphyton
biomass before they can be completely assimilated.  Therefore, the relationship between benthic
chlorophyll and water column nutrients is weaker in fast-flowing versus standing water systems (Dodds
etal. 1998).


Algae are either the direct or indirect cause of most problems related to excessive nutrient enrichment;
e.g., algae are directly responsible for excessive, unsightly periphyton mats or surface plankton scums,
and may cause high turbidity, and algae are indirectly responsible for diurnal changes in DO and pH. Chi
a is a photosynthetic pigment and sensitive indicator of algal biomass.  It can be considered the most
important biological response variable for nutrient-related problems. The following discussion of chl a
as a primary variable includes information for both benthic and planktonic chl a. Benthic chl a can be
difficult to measure reliably due to its patchy distribution and occurrence on non-uniform stream
bottoms.  Periphyton is  often analyzed for AFDM, which includes non-algal organisms. Additional
factors that can be used to determine  which type of chlorophyll (benthic or planktonic) is most important
in the system of interest can be found in Table 1,  Section 2.2.

Unenriched, light-limited, or scour-dominated stream systems typically have benthic chl a values much
less than 50 mg/m2. Biggs (1995) reported the following range of chl a values from monthly
observations over a one year period in 16 New Zealand streams:  1) unenriched streams in forested
catchment (0.5-3 mg/m2), 2) moderately enriched streams in catchments with moderate agricultural use
(3-60 mg/m2), and 3) enriched streams in catchments highly developed for agriculture and/or underlain
with nutrient-rich bedrock (25-260 mg/m2).  Lohman et al. (1992) reported a range of 42 to 678 mg/m2
chl a from over two years of spring to fall biweekly observations at 22  sites on 12 Missouri Ozark
Mountain streams, with higher levels occurring at more enriched sites.  Unenriched sites exhibited mean
biomass values that did not exceed 75 mg/m2. However, highly and moderately enriched sites exceeded a
nuisance level mean biomass (150 mg/m2) within 3 or 4 weeks, respectively, following flood-scour
events. The  highest maximum value  observed at ten sites in late summer 1987 in the Clark Fork River,
Montana, was approximately 600 mg/m2 (Watson and Gestring 1996).  Furthermore, values for benthic
chl a as high as  1200 mg/m2 have been observed in gravel/cobble bottom bed streams (Welch et al.
                                            PAGE 31

July 2000	Chapter 3. Select Variables

Planktonic chl a in deep, slow-moving rivers will have an upper limit determined by light attenuation,
which increases with the suspended chl a concentration.  Maximum chl a can be low (<10 |-lg/L) even if
slow-moving systems are nutrient enriched because most flowing systems disperse phytoplankton before
high algal biomass develops. However, under low flow conditions (accompanied by low mixing and
shallow depth),  large planktonic algal blooms often develop in slow-moving, nutrient enriched rivers.
The theoretical maximum attainable before light limits photosynthesis in lakes (assuming light is
attenuated by algae only) is about 250 mg/m2. This theoretical maximum is equivalent to 25 mg/m3
(|-lg/L) in a 10-m depth water column or 125  |J,g/L in a 2 m deep lake. Van Nieuwenhuyse and Jones
(1996) compiled summer mean suspended chl a values for rivers, and found no values greater than 180
|_lg/L. Mixing and light attenuation from non-algal particulate matter, which are typical in deep, slow-
moving rivers, may further limit light availability for photosynthesis.

A conceptual distribution of algal biomass in the euphotic zone over a range of water detention times was
suggested by Rickert et al. (1977) (see Welch 1992). For example, the lower Duwamish River,
Washington estuary typically contained around 2 |_lg/L chl a during summer, even though it was heavily
enriched with secondary treated sewage effluent.  However, when the water detention time increased and
mixing decreased as a combined result of minimum range tidal conditions and low river flow in August,
chl a reached a maximum of 70 |_lg/L (Welch 1992).

Algal biomass data in fast-flowing, gravel/cobble bed streams and deep, slow-moving, turbid rivers must
be interpreted in light of the physical constraints that determine the potential for nutrient utilization (see
Chapter 2).  Relatively low biomass can be observed in highly enriched waters, if physical (light,
temperature, current) or grazing constraints are severe. Relatively high algal biomass can occur with low
enrichment if physical constraints approach the optima for algal growth. However, chl a concentrations
near the maximum values cited above will not occur without nutrient enrichment.


Total suspended solids (particulate matter suspended in the water column) attenuate light and reduce
transparency, whether the source is algae, algal detritus or inorganic sediment. Streams may also have
high concentrations of light-absorbing dissolved compounds (e.g., blackwater streams). The
concentration of total suspended solids can be determined directly or as an  effect on light transmission or
scattering.  Quantitative relationships have been developed for individual and/or groups of waters to
predict transparency from particulate matter and/or chl a  (Reckhow and Chapra 1983; Welch 1992).
However, relationships of chl a and transparency (as an effect of nutrients) are not prevalent in fast-
moving streams systems; most likely because of interference from time- and flow-variable inorganics and
large diameter suspended solids. Total suspended solids  may increase due to algae and detritus sloughed
from large algal mats, but caution should be exercised in  interpreting these  data.  During high flow, the
concentration of suspended solids (and water clarity) will likely be more strongly influenced by inputs of
inorganic sediment or channel erosion in streams, especially in urbanized and agricultural watersheds.

Turbidity, as NTUs (Nephelometric Turbidity Units), measures suspended matter in the water column
whether of organic (i.e., chl  a) or inorganic origin. Turbidity correlated with rain-event sampling may
help identify non-point source loadings.  Although turbidity is not commonly used as an  index of
eutrophication in either lakes or streams, it nonetheless should increase  in streams with increasing algal
biomass due to nutrient enrichment.

                                            PAGE 32

July 2000	Chapter 3. Select Variables

Periphyton are directly affected by suspended solids (as turbidity) due to light attenuation. Quinn et al.
(1992) found that waters with turbidity measurements that range between 7-23 NTUs have reduced
abundance and diversity of benthic invertebrates. They attributed the reduction in benthic invertebrates
to turbidity, largely because of its adverse effect on periphyton production as an invertebrate food source
(Quinn et al. 1992).  In Illinois, the turbidity of agricultural streams (NTU 10-19) had more effect on
periphyton accrual than did nutrient enrichment (Munn et al. 1989). Total suspended solids ranging from
about 22 to 30 mg/L increased the loss rate of periphyton (mixture of filamentous blue-green and
diatoms) tenfold, although increased velocity with and without solids caused more loss (Horner et al.

The vertical water column in relatively clear-water, gravel/cobble bed streams/rivers is usually
insufficient to determine Secchi disk depth. However, the white Secchi disk routinely used in lakes and
reservoirs  to determine transparency is appropriate for slow-moving streams and rivers (Welch 1992).
Transparency, as influenced by low concentrations of particulate matter in shallow,  fast-flowing streams
systems, can also be determined with a black disk (Davies-Colley 1988). The path length for
transparency is measured horizontally in such shallow streams, as opposed to vertically in lakes,
reservoirs  and deep rivers/estuaries. As periphyton biomass increases, particulate matter sloughed and/or
eroded from the substratum also increases, reducing transparency.


The rate of discharge or flow in a stream system can be separated into two primary components, baseflow
and storm  or direct runoff. Baseflow comprises the regular groundwater inputs to a stream. This water
typically reaches the stream through longer flow paths than direct runoff and sustains streamflow during
rainless periods.  Direct runoff is hillslope or overland flow runoff that reaches a stream channel during
or shortly after a precipitation event. Both components of flow are reflected in a hydrograph (a graph of
the  rate of discharge plotted against time) of the stream segment. Runoff processes  (including stream
discharge and groundwater recharge),  seasonal variation of flow, and methods to calculate average
stream velocity, the annual probability hydrograph and flow duration curves are discussed at length in
Dunne and Leopold (1978).

The flow of a river or stream affects the concentration and distribution of nutrients.  Generally, point
source concentrations are higher during low flow conditions due to reduced water volumes; in contrast,
nutrients from non-point sources may be more highly concentrated during high flow conditions due to
increased flow paths through the upper soil horizons and overland flow.  There is also a rough correlation
of total dissolved solids concentration with climate and hydrology. Streams in arid regions tend to have
high concentrations of total dissolved solids (though the total annual solute transport is low because of
low runoff), whereas in humid regions, concentrations tend to be lower with higher total annual solute
transport (Dunne and Leopold 1978).  However, the complexity of the interactions of nutrient
concentration and flow make it important to examine both point sources and non-point sources of
nutrients and wet weather (high flow)  and dry weather (low flow) stream conditions to verify nutrient
sources and concentrations in multiple flow conditions (Dunne and Leopold 1978).

Brandywine Creek, Pennsylvania, provides an example of how stream flow can affect nutrient
concentrations in a stream system (Dunne and Leopold 1978).  The Brandywine Creek watershed drains
portions of the Piedmont plateau and Atlantic coastal plain into the Delaware River. The watershed land

                                            PAGE 33

July 2000	Chapter 3.  Select Variables

use is a mix of urban, agricultural and suburban uses, and includes both point and non-point pollution
sources. Brandywine Creek was sampled during periods of storm runoff and dry-weather flow for P and
stream discharge. Point discharges of P were diluted as stream discharge increased following storm
events. As storm runoff occurred, concentrations of P increased dramatically at sampling sites not
dominated by point discharges. At sites not dominated by point discharges, runoff from forested and
cultivated hillslopes washed large amounts of P into the Brandywine Creek in both solid organic form
and sorbed to soil particles.

Hydrologic variability is an important consideration in the development of nutrient and algal criteria for
all streams; nonetheless, there is often a higher degree of variability for specific types of regional stream
systems.  In particular, the spatial and temporal heterogeneity found in arid regions, the stark contrast
between wet and dry, can be dramatic (see Desert Streams Case Study, Appendix A). When viewing
desert catchments from above, the observer is often presented with a dry landscape of high relief bisected
by the string of glistening beads that is the spatially intermittent stream. The dry arroyos or quiet,
disconnected pools and short reaches of wetted stream that characterize desert streams during dry periods
are in complete contrast to the raging torrents that they can become at flood stage. This hydrologic
variability and the unique chemical and biological characteristics of arid lands aquatic ecosystems make
the use of broad generalizations to explain nutrient regimes difficult.

In arid landscapes,  stream ecosystems are dynamically linked with the surrounding upland ecosystem. In
addition, surface discharge regimes may vary from completely dry, to flows as much as three to five
orders of magnitude greater than mean annual flow, all within a period of hours or days.  In comparison
to streams in more mesic regions, the coefficient of variation of annual flow is 467% greater in arid lands
streams (Davies et al. 1994). The aquatic ecosystems structured by these chaotic flow regimes (Thorns
and Sheldon 1996) may require different techniques for nutrient criteria development than those used in
more homogeneous environments.

Drying disturbance, or more specifically the contraction and fragmentation of a stream ecosystem, is a
critical component of the hydrologic regime of desert streams. Drying occurs as a spatially or temporally
intermittent stream recedes after a wet period. In streams where the dry period and extent may be
greater than the wet, drying is likely to be an important determinant of biological pattern and process
(Stanley et al. 1997; Stanley and Boulton 1995).

In order to properly characterize the nutrient regime of a stream ecosystem, the flow of water, surface
and subsurface, flood or base flow, wet or dry must be considered at ecologically significant temporal
and spatial scales.  It is also important that the manager address this hydrologic regime at the scale of the
question to be answered.  If a stream is dry for 75% of the average year, or for 75% of its length, is it
correct to  characterize it from surface water data alone?  If 50% of the entire annual load of a limiting
nutrient passes through a stream ecosystem in three discrete storm events, what is the effect of that
nutrient on the stream ecosystem itself?  What is the effect to downstream ecosystems? Due to the
spatial and temporal variability of flow patterns, the characterization of desert stream nutrient dynamics
is an intricate undertaking. However, stream  complexities will only be understood through appropriate
assessment and evaluation.
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July 2000	Chapter 3. Select Variables


The following sections describe additional variables that may be useful in criteria development. These
variables comprise chemical, physical, and biological parameters, some of which exhibit heightened
response to nutrient enrichment.


The variables discussed below that are apt to be most sensitive to nutrient enrichment, via increased algal
productivity and biomass are:  1) DO and pH, 2) benthic community metabolism, and 3) autotrophic
index.  These variables should vary directly with algal productivity and detect relatively small changes in
nutrient condition. While other variables such as total suspended solids, macroinvertebrate indices,
dissolved organic  matter, and secondary production may be directly affected by algal productivity and
biomass, they may also be strongly dependent on other natural factors and/or sources/types of pollutants.

Dissolved Oxygen and pH
Periphyton algal biomass above nuisance levels often produces large diurnal fluctuations in DO and pH.
Photosynthesis/respiration by dense periphyton mats commonly causes water quality violations
(Anderson et al. 1994; Watson et al. 1990; Wong and Clark 1976). These water quality impairments
occur in stream  systems as a result of nutrient-produced excessive algal biomass in fast-flowing,
gravel/cobble bed streams as well as sluggish stream systems. Excessive macrophyte biomass can
produce similar swings in DO and pH (Wong and Clark 1979; Wong et al. 1979).

The extent of diurnal swings in DO and pH will depend on several factors, such as turbulence (which
affects reaeration), light, temperature, buffering capacity, and the amount and health of algal and/or
macrophyte biomass. Sluggish streams and  rivers may show a greater range in DO and pH per unit
biomass compared to faster streams due to less turbulence and associated atmospheric exchange of CO2
and O2 (Odum 1956; Welch 1992). Light limitation may also be a common feature of algae in enriched
streams, and therefore, light is likely an important control on diurnal DO and pH swings (Jasper and
Bothwell 1986;  Boston and Hill 1991; Hill 1996).  Higher temperatures tend to enhance algal growth in
many streams and may increase photosynthesis and respiration in many systems resulting in greater
variation in diurnal DO  and pH values.  Streams with low buffering capacity will show greater diurnal
swings in pH. Furthermore, biomass-specific metabolic rate  (especially respiration-see
photosynthesis/respiration discussion) tends to be greater in fast-flowing waters because periphytic
growth is stimulated by velocity.  The influence of the above factors on DO concentration and pH value
reduce the specificity and potentially reduce the reliability of these variables to indicate response from
nutrient enrichment. Therefore, direct measures  of algal biomass, such as chl a, are preferred response

Aquatic animals are affected most by maximum pH and minimum DO, rather than by the daily means for
these variables (Welch 1992).  Hence, monitoring for water quality should include pre-dawn hours to
observe the diurnal minimum DO and afternoon hours for maximum pH.  Routine grab samples in
monitoring programs usually do not include such strict protocols. It may be possible to estimate
minimum DO from equilibrated average and maximum DO (Slack 1971) which occurs during mid-day to
afternoon, along with maximum pH.
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July 2000	Chapter 3. Select Variables

Photosynthetic rate, or primary productivity, is often considered a more sensitive variable of response to
nutrients than algal biomass. Biomass is a net result of gains (productivity) minus losses (algae lost due
to death, scour, etc.) (see discussion in Stevenson 1996).  Productivity is essentially growth, and
therefore is a more direct measure of nutrient effects. Productivity can be determined for whole stream
reaches by monitoring diurnal DO concentrations (see methods section, Appendix B) or alternatively,
productivity and respiration may be measured using light/dark  chambers. Whole-stream metabolism
measurements are integrative over all components of the stream system and eliminate artifacts of
enclosure that commonly confound results in chamber experiments.  Marzolf et al. (1994, 1998) detail
the methods for measuring whole-stream metabolism. Productivity and respiration in light/dark
chambers may vary on an hourly and daily basis with temperature, light, and nutrients; short-term
measurements must be corrected for those factors (Welch et al. 1992). The necessity of normalizing
measurements and the greater analytical difficulty of productivity, has made algal biomass the preferred
variable to indicate nutrient effects on periphyton and phytoplankton as evidenced by the generally
established trophic state criteria for lakes and reservoirs (Welch 1992), and proposed for streams/rivers
(Dodds et al. 1998). The rate at which maximum biomass is attained is dependent mostly on nutrient
availability, minus losses to grazing and scouring, or washout in the  case of phytoplankton. While
integrated daily productivity is usually directly related to biomass as chl a (Boston and Hill 1991), there
can be considerable variability in the relationship due to the variables discussed above, as shown by the
ratio of productivity to biomass as chl a (Figure 6).  The ratio  of productivity to biomass as chl a  is an
index of growth rate. If there is no variability in productivity:biomass, the relationship will be constant
and will not vary on a day-to-day basis.

Gross photosynthesis/respiration ratios (P/R ratios) can be useful indicators of trophic characteristics.
P/R ratios have long been recognized to indicate the relative autotrophic (P/R >1) or heterotrophic (P/R
<1) character of streams and rivers. Measurement of P/R and interpretation of results is dependent on the
scale at which the measurements are made, and the point in the annual cycle when the measurements are
taken.  For example, low-order streams that flow through forested watersheds tend to be heterotrophic
with photosynthesis limited by light due to shading; mid-order streams and rivers flowing through areas
with minimal riparian vegetation, or largely unshaded due to width,  are usually autotrophic (unless
organic waste inputs are significant); high order rivers tend to return to a heterotrophic character due to
light limitation brought on by increased depth and turbidity (Vannote et al. 1980; Bott et al. 1985).
Furthermore, the P/R ratio for a short-term measurement (24-72 hours) in the spring may indicate  an
autotrophic stream, while on an annual basis the stream is heterotrophic (Hall and Moll 1975; Wetzel
1975; Wetzel and Ward 1992).

There are problems with interpreting P/R ratios, however. Photosynthesis/respiration ratios can vary
seasonally and could actually reflect a temporary heterotrophic condition during a period of low
periphyton biomass, due to scouring or low light, while otherwise it  would be autotrophic.  Decreased
velocity can also decrease  stream/river P/R, because  mat thickness of periphytic diatoms can increase
while the depth of active photosynthesis remains relatively constant  (Biggs and Hickey 1994). Thus,
photosynthesis is limited by light attenuation in the mat, but respiration is stimulated by movement of
organic materials to heterotrophic organisms in the mat.
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July 2000
             Chapter 3. Select Variables
                     Gross Primary Productivity

                                     0     °o

                      0      0°       0
                         Assimilation Number





o o
0° ° ® 0° °
o000^^-^^ o (9 o o o -
1 1 1
                           10            10
                                 Chi a (mg m" )
Figure 6. Integrated daily productivity related to biomass as chlorophyll a (data compiled by Dodds

from published literature; many of the data from Bott et al. 1985).
                                 PAGE 37

July 2000	Chapter 3. Select Variables

Autotrophic Index
The ratio of AFDM to chl a is termed the autotrophic index for periphyton and is used to distinguish the
relative response of inorganic (N and P) and organic (BOD) enrichment. Periphyton growing in surface
water that is relatively free of organic matter contain approximately one to two percent chl a by weight.
Surface water that is high in particulate organic matter may support large populations of bacteria, fungi
and other non-chlorophyll bearing microorganisms, and have a larger ratio of AFDM to chl a.  Increased
ratios indicate that heterotrophs utlizing organic substances comprise a larger percentage of AFDM than
autotrophic periphyton that rely largely on inorganic nutrients to increase biomass (Weber 1973).  Ratios
of AFDM/chl a can vary over three orders of magnitude, with values >400 indicating organically
polluted conditions (Collins and Weber  1978). Ratios of AFDM/chl a around 250 are more typical for
streams enriched with inorganic nutrients that are likely to have existing or potential eutrophication
problems (Watson and Gestring  1996; Biggs 1996).  The autotrophic index should be used with caution,
because non-living organic detrital material may  artificially inflate the ratio.

Interpretation of Sensitive Response Variables
High algal productivity can cause supersaturated  DO and high pH during the day, P/R ratios >1, and
unusually low autotrophic indices.  Unfortunately, broad predictive relationships do not exist between
nutrient concentration and algal/macrophyte biomass, DO, or pH. However, relationships could be
developed for individual streams and rivers.  Nevertheless, without inclusion of other factors that affect
DO and pH (such as exchange with the atmosphere for specific stream systems), a biomass limit to
prevent low DO (e.g., <5 mg/L) cannot be determined from any existing relationship, such as the chl a -
TP  relationships discussed earlier (Lohman et al.  1992; Dodds et al. 1997).  As concentrations of
nutrients and algae increase, diel fluctuations in DO and pH also increase (see Dissolved Oxygen and pH
discussion above).  However, established relationships observed in lakes and reservoirs, such as TP
loading and hypolimnetic DO deficit (Welch 1992), do not exist for streams and rivers.


Additional chemical, physical, and biological attributes may be useful when evaluating nutrient and algal
relationships. Descriptions for several potential useful variables are provided below.

Chemical Waterbody Characteristics

Specific conductance (typically measured as conductivity) has also been used as an indicator of nutrient
enrichment (Biggs and Price 1987; Biggs 1996).  Conductance reflects the concentrations of macro-ions,
so nutrients dissolved from bedrock are assumed  to increase proportionately with increases in total ions.
Conductance at low flow was found to increase proportionately with urbanization in 23 western
Washington streams and was hypothesized to be  a loose surrogate for soluble nutrient supply during
summer when residual soluble nutrient concentration was low due to algal demand (May et al. 1997).
However, conductance may be a poor indicator of nutrient availability in calcareous regions or those with
high concentrations of dissolved salts that are not typically limiting nutrients.

Dissolved Organic Carbon
DOC  is an important energy source that drives the heterotrophic community and can alter a river's
response to algal growth problems.  DOC can originate as allochthonous inputs naturally from the

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July 2000	Chapter 3. Select Variables

watershed through decomposition of terrestrial primary production, or from cultural waste production.
The heterotrophic community will dominate the periphyton in gravel/cobble bed streams and rivers that
have high inputs of labile DOC.

Inflow and in-stream DOC should be related to the autotrophic index, as discussed previously.  Streams
and rivers enriched with DOC will have high autotrophic indices, and may be more prone to low oxygen
events that can be exacerbated by excessive periphyton biomass. High rates of autochthonous DOC
production' is usually a result of inorganic nutrient enrichment. Such eutrophication-caused DOC
production can be an important source of decomposition by-products (e.g., tri-halomethane precursors
and other sources of taste and odor problems) which is a concern for drinking water supplies.

Physical Waterbody Characteristics

Algal metabolic rate, at a given biomass and growth phase (relative cell health), is controlled by
temperature (DeNicola 1996), water movement, nutrients  and light. In general, the response to
enrichment will be faster at higher than lower temperature; e.g., twice as fast at 20°C as at 10°C (Mclntire
and Phinney 1965; Welch 1992).  However, the maximum biomass will depend on nutrient availability;
temperature will determine only the rate at which the maximum is reached (Welch 1992).

Temperature, as it interacts with  light and nutrients, will determine which taxa dominate the algal
biomass. The various algal taxa have individual thermal optima. In general blue-greens have higher
optima than greens which have higher optima than diatoms (Rodhe 1948; Cairns 1956; Hutchinson
1967). For example, the nuisance filamentous green, Cladophora, apparently has an optimum around
18°C and its growth stops at 25°C (Storr and Sweeney 1971). As a result of differing thermal optima,
seasonal succession of taxa is often observed, with diatom dominance during spring low temperature and
greens and blue-greens dominating in summer. However, nutrients often override temperature effects,
with diatoms dominating the periphyton throughout the spring-summer period at low nutrient
concentrations and greens (and/or blue-greens) dominating for the whole period at high nutrient
concentrations (Welch 1992).

Biological Attributes

Algal Biomass as Ash-Free Dry Mass
Algal biomass or standing crop is often expressed as AFDM. However, the weight of particulate detritus
in fresh water frequently exceeds that of the algae. No reasonable method currently exists to separate
algae from detrital material in the water.  Therefore, chl a is usually the primary biomass indicator
because it is specific to algae, while AFDM can include other living or non-living organic matter (Darley
1982; Wetzel 1975).

Algal Biomass - % Cover of Bottom by Nuisance Algae
Extent of periphyton coverage of a stream bed can be an important indicator of algal biomass problems.
As  enrichment increases, the fraction of periphyton biomass composed of filamentous greens increases,
as does the percent of stream bed covered with algae (Welch et al.  1988; Lohman et al. 1992; Biggs
1996). However, there may be an uncoupling between percent cover and total biomass depending on the
thickness of the algal mat, e.g., a system might have 100% algal cover, but if the  algal growth was very

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July 2000	Chapter 3. Select Variables

thin (e.g., "sheets" of Oscillatoria filaments), the total biomass could be far less than a system with 50%
cover ofCladophora.  Nevertheless, estimates of percent cover are often a useful indicator of the
intensity of algal proliferation in gravel/cobble-bed streams, and as an index of aesthetic appeal.  The
occurrence of floating blue-green algae scums in slow-moving rivers, lakes, and reservoirs is likewise an
aesthetic nuisance, but there has been no attempt to quantify scum intensity/surface-cover similarly to
periphyton in fast-flowing streams, largely due to the variable, diurnal nature of floating blue-green

Pigment Ratios
Two pigment ratios are commonly used in periphyton assessments.  One is the chl a:AFDM ratio, which
is a modified version of the autotrophic index (Weber 1973; Stevenson 1996; Stevenson and Bahls 1999)
and indicates the relative importance of autotrophy versus heterotrophy in streams. Values of the
autotrophic index increase when algae (chl a) become a greater proportion of benthic biomass. The
second is the chl a:phaeophytin ratio, which is an indicator of periphyton health. Phaeophytin is a
degradation product of chlorophyll. Relatively low values of phaeophytin, thus relatively high values of
the chl a:phaeophytin index, indicate periphyton is actively growing.

Chemical Composition of Algae (N:P Stoichiometry)
Phosphorus and N concentrations in periphyton increase with nutrient concentrations and trophic status
of streams (Humphrey and Stevenson 1992; Biggs 1995).  Periphyton can be analyzed for P and N
content, as well as chl a or AFDM.  Then P and N concentrations in periphyton can be expressed as a
fraction of algal biomass as indicated by chl a or AFDM (|ig P/|lg chl a or |ig P/mg AFDM).  This metric
can be another valuable complement to assessments of P and N availability, especially when P and N
concentrations are variable in the stream.

Nutrient ratios in periphyton may provide a line of evidence to indicate whether N or P is limiting algal
growth. The range of ambient or cellular N:P ratios has been used as to define the transition between N
and P limitation for benthic algae (Schanz and Juon 1983). If ambient N:P ratios are greater than 20:1,
then P can be assumed to be in limiting supply.  If the ambient N:P ratio is less  than 10:1, then N can be
assumed to be in limiting  supply. The distinction of the limiting nutrient when ambient N:P ratios are
between 10 and 20 to 1 is not precise. Nutrient enrichment studies have supported these transition ratios
in broad terms (e.g., Grimm and Fisher 1986a; Peterson et al. 1993). However, the accuracy of ambient
nutrient ratio analysis decreases when greater amounts of detritus occur in periphyton samples.  In
streams, N:P ratios of periphyton can be different than N:P ratios  in the water column (Humphrey and
Stevenson 1992). Periphyton N:P ratios may better indicate relative nutrient availability to the
periphyton than ratios based on water column nutrient concentrations. In addition, ambient ratios may
not reflect the cellular ratio relevant to physiological growth processes when nutrients are abundant.
Cellular nutrient ratios are a more direct measurement of nutrient limitation (Borchardt 1996). Even so,
nutrient ratios only suggest limitation-bioassays are required to establish cause and effect relationships.

Phosphatase Activity
Alkaline phosphatase is an enzyme excreted by algae in response  to P limitation. Alkaline phosphatase
hydrolyzes phosphate ester bonds, releasing PO4 from organic P compounds (Steinman and Mulholland
1996). Concentration of alkaline phosphatase in the water column can be used to evaluate P limitation.
Alkaline phosphatase activity (APA), monitored over time in a waterbody, can be used to assess the
influence of P loads  on the growth limitation of algae (Smith and  Kalff 1981).  Artificial stream channel

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July 2000	Chapter 3. Select Variables

experiments by Klotz (1992) support the hypothesis that stream N:P ratio is the important factor in
determining periphyton APA. In this study, APA varied seasonally, and shading of the stream channel
resulted in lower APA. Results from studies of cultured algae appear to indicate that phosphatase levels
above 0.003 mmol (micromoles) mg chl a1 h"1 indicate moderate P deficiency, and phosphatase levels
above 0.005 mmol mg chl a1 h"1 indicate severe P deficiency (Steinman and Mulholland 1996).

Algal Species Composition
Assessment of algal species composition can indicate that nutrient related problems exist or that
conditions are right for such problems to develop (Kelly and Whitton 1995; Pan et al.  1996).  Since algae
are often the problem associated with nutrient contamination, assessments of algal species composition
can show whether nuisance algae are present or whether biotic integrity of this target community has
changed. Assessment of algal species composition is more time consuming than simpler measurements
of water chemistry or chl a measurement, however algal species composition may provide more reliable
indicators of trophic status in streams and rivers than one-time sampling and assessment of water
chemistry and benthic algal biomass (Stevenson, unpublished data). Assessment of algal species
composition is an element of periphyton programs in all States that monitor periphyton. One of the
reasons for relying on species composition is periphyton biomass is so variable spatially and temporally,
and challenging to measure accurately. In addition, species composition is highly informative, especially
when linked to the ecology of a species in relation to the environment, i.e., the autecological information
about the species (Stevenson and Bahls 1999).

Many attributes of algal species composition can be used as metrics or indicators  of nutrient conditions,
trophic status, and biotic integrity (Stevenson and Bahls 1999).  Indicators of nutrient  status based on
algal taxa fall in three categories: diversity, deviations in species composition from reference conditions,
and weighted-average autecological indices.  Diversity is comprised of two components:  1) the variety of
species (species richness), and 2) the relative abundance of species (eveness).  Shannon diversity (a
measure of diversity which combines the components of diversity [Pielou 1975]) usually decreases with
increasing trophic status because evenness decreases. Weighted-average autecological indices based on
pollution tolerance, or more specifically, nutrient requirements can be used to infer nutrient status or
trophic conditions in a habitat (Steinberg and Scheifele  1988; Schiefele and Schreiner 1991; Van Dam et
al. 1994; Kelly and Whitton 1995; Pan et al. 1996). Dissimilarity in species composition between test
and reference sites can be used to determine whether water quality is similar in test and reference sites.
A more complete review of metrics  and how algae can be used in environmental assessment of rivers and
streams can be found in McCormick and Cairns (1994), Stevenson and Pan (1999) or Stevenson and
Bahls (1999).

Grazers and Secondary Production
Dense populations of algae-consuming grazers may lead to negligible algal biomass in spite of high
levels of nutrients (Steinman 1996). The existence of a "trophic cascade" (control of algal biomass by
community composition of grazers and their predators) has been demonstrated for some streams (e.g.,
Power 1990). Grazer biomass was related more strongly with P concentration in 12 Quebec streams than
was periphytic algal biomass, which was considered controlled  by grazing in spite of TP concentrations
ranging from 5 to 60 |J,g/L (Bourassa and Cattaneo 1998). The  potential for manipulations of foodwebs
to control eutrophication certainly warrants more investigation, but there is not currently enough
information on trophic cascades in streams to allow for use of foodweb dynamics as a management
option.  Managers still should realize the potential control of algal biomass by grazers, but also be aware

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July 2000	Chapter 3. Select Variables

that populations of grazers may fluctuate seasonally or unpredictably, and fail to control biomass at
times.  Consideration of grazer populations may at least explain why some stream systems with high
nutrients have low algal biomass.

Phytoplankton losses in slow-moving rivers due to filter-feeding grazers can also be significant.  Bivalve
communities can filter large volumes of water on a daily basis (as much as 10-100% of the water column,
depending on population density) (Strayer et al. 1999).  The amount of particulate matter grazed from
this filtration may exceed losses to pelagic filter-feeders or downstream advection. Significant losses of
pelagic phytoplankton have been observed in large rivers.  Strayer et al. (1999) describe a zebra mussel
invasion of the Hudson River ecosystem that drastically reduced phytoplankton (and zooplankton)
biomass by 80-90%, as well as a 50% reduction in phytoplankton biomass in a reach of the Potomac
River following colonization by the bivalve Corbicula fluminea. Ecosystem response to severe biomass
reduction by filter-feeding grazers is often characterized by an increase in dissolved nutrients like SRP,
reduced turbidity, and proliferation of macrophytes.  Inherent qualities of the waterbody (e.g., mixing,
sediment stability, and light attenuation) are a factor in determining whether phytoplankton biomass is
permanently reduced, regardless of increases in nutrient concentration, or temporarily reduced and then
replenished with a shift in dominant phytoplankton species (Caraco et al. 1997).

Production and biomass of consumers is expected to be greater in streams/rivers enriched with N and P.
At some point, however, productivity and biomass will cease to increase at all or the rate of increase per
unit nutrient will be greatly reduced. One feature of highly enriched lakes and reservoirs is the switch to
grazer-resistant filamentous/colonial blue-green algae, which reduces the efficiency of nutrient utilization
and energy conversion to higher trophic levels (Welch 1992).  Although not well documented, the same
phenomenon may be expected in enriched streams and rivers resulting in increased biomass and percent
coverage of filamentous green algae. On the other hand, low-level enrichment of oligotrophic streams
and rivers may result in pronounced increases in benthic invertebrates and fishes in addition to increased
algal biomass. For example, continuous enrichment of the P-limited Keogh River and Grilse Creek on
Vancouver Island, British Columbia, led to substantial increases in secondary producers, but did not
produce nuisance biomass levels of periphyton (Perrin et al. 1987; Slaney and Ward 1993).  Enrichment
of the Keogh River and Grilse Creek with 5-10 and 5 |ig/L SRP, respectively, produced maximum
periphyton biomass (chl a) levels of 100-150 and 50-100 mg/m2. Consequently, benthic invertebrate
biomass increased from 2-7 fold and fish size 1.4-2 fold. Phosphorus fertilization (10 |lg/L) of a tundra
river led to increased fish and algae production, but negligible increases in invertebrate production
(Peterson et al. 1993). In some cases, enrichment of oligotrophic waters may result in increased grazer
biomass with little or no change in periphyton biomass (Biggs and Lowe 1994).

Even if nuisance levels of periphyton are produced, secondary production will probably be higher than in
unenriched waters in spite of reduced efficiency of conversion.  Enrichment of Berry Creek, Oregon,
with sucrose (1-4 mg/L) produced large, nuisance mats of filamentous bacteria, but benthic invertebrate
biomass increased 4.5 fold and fish (cutthroat trout) increased 6.3 fold with enrichment (Warren et al.
1964). Although adverse effects of periphytic mats and water quality were apparently not evaluated, fish
growth obviously prospered from the large biomass of chironomids that consumed the filamentous

Secondary production can clearly respond to enrichment and the response may be more efficient and
beneficial in oligotrophic than eutrophic streams systems.  A transition region in enrichment from

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July 2000	Chapter 3. Select Variables

beneficial to detrimental effects has not been defined to the extent that it has for lakes and reservoirs
(Welch 1992), but probably exists for different physical types of streams and rivers. Two recent studies
have provided independent estimates of target streamwater nutrient concentrations that should be
maintained in order to assure acceptable water quality needed for fish growth (Smith et al. 1999).
McGarrigle (1993) concluded that maintaining a mean annual SRP concentration <47 mg m"3 was
necessary to prevent the nuisance growth of attached algae and to preserve water quality suitable for
salmonid fishes in Irish rivers. Similarly, Miltner and Rankin (1998) observed deleterious effects of
eutrophication on fish communities in low order Ohio streams when total inorganic nitrogen (TIN) and
SRP concentrations exceeded 610 mg m"3 and 60 mg m"3, respectively.

Invertebrate and fish biomass are considered very useful variables, albeit more demanding to measure
than other indices discussed above.  Measuring such variables could prove useful because:  1) both may
respond to enrichment, 2) fish are of direct economic and recreational importance, and 3) case studies are
needed to develop guidelines for regions of enrichment that represent a transition between beneficial and
detrimental effects  of enrichment.

Macrophyte is a general term of no taxonomic significance that is applied  to many species of aquatic
vegetation. Aquatic plants (macrophytes) can be classified into four groups: emergent, floating-leaved,
submersed, and freely floating and are large enough to be observed by the naked eye.  Aquatic
macrophytes represent a taxonomically diverse group of aquatic plants and include flowering vascular
plants, mosses, ferns, and macroalgae (USEPA 1973; Wetzel 1975).  Macrophytes are found in most
waterbodies and play an important role in the aquatic community providing food for other aquatic
organisms, processing nutrients or toxic elements in the water column, and aiding in the stabilization of
river/stream sediments (Davis 1985).

The four categories of macrophytes are defined by their connection or anchor to the waterbody substrate:
free-floating, emergent (rooted but breaking the water surface), floating leaf anchored, and immersed
floating mat anchored (USEPA 1973).  The type of growth form plays an important role in the effects of
eutrophication on macroscopic plant communties in rivers and streams. For example, the large surface
area provided by the thin narrow leaves of Potamogeton pectinatus (sago pondweed) allow this species to
persist in flowing water with high turbidity (Hynes 1969; Goldman and Home 1983).  Emergent
macrophytes grow on the banks of rivers and streams in depths of water less than a meter and are
typically rooted in the sediment, have their basal portions submersed in water and have their upper
structural biomass growing in the air.  Most emergent macrophytes are perennials (living for more than
one year). Common emergent macrophytes include plants such as reeds (Phragmites spp.),  bulrushes
(Scirpus spp.), cattails (Typha spp.), and wild rice  (Zizania spp.). Floating-leaved macrophytes are
rooted to the river bottom with leaves that  float on the surface of the water such as waterlilies (Nymphaea
spp.) and spatterdock (Nuphar spp).  Submersed macrophytes are a diverse group that grow  completely
under the water and include mosses (Fontinalis spp.), muskgrasses (Chara spp.), stoneworts (Nitella
spp.) and numerous native vascular plants  such as various pondweeds (Potamogeton spp.), tape-grass
(Vallisneria spp.), and exotic species including hydrilla and Eurasian watermilfoil. Free-floating
macrophytes typically float on or just under the water surface with their roots suspended in the water
column.  These unattached macrophytes range in size from small duckweeds (Lemna spp.) and water fern
(Salvinia spp.) to larger surface floating plants such as water hyacinth (Eichhornia crassipes). Free-
floating species are entirely dependent on the water for their nutrient supply.  The distribution and

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July 2000	Chapter 3.  Select Variables

abundance of free-floating macrophytes in streams is affected by current velocity and wind. Thus, they
are most frequently found in backwaters and embayments (Goldman and Home 1983).

The most important environmental factors affecting the abundance and distribution of aquatic
macrophytes in rivers are light availability (Spence  1975; Chambers and Kalff 1985; Canfield et al.
1985), nutrients and water chemistry (Hutchinson 1975; Beal 1977; Kadono 1982; Hoyer et al.  1996),
substratum characteristics (sediment texture, nutrient content) (Pearsall  1920; Barko et al. 1986; Nichols
1992), and current velocity.  Aquatic plants require  light for growth, thus light availability is often
considered the single most crucial environmental factor regulating the maximum depth of plant growth
(Pearsall 1920; Spence 1975; Chambers and Kalff 1985). Light availability is directly linked to water
clarity; as water depth increases or water clarity decreases, both the amount and spectral quality of light
for photosynthesis decreases (Canfield et  al. 1985; Chambers and Kalff 1985). Light availability in
rivers is controlled by riparian canopy cover and water clarity, which can be due to both organic and
inorganic suspended particles (Vannote et al. 1980). Thus,  shaded, turbid, and deep rivers will  have
fewer aquatic macrophytes.

There are few reports of nutrient-related growth limitation for aquatic plants; nutrients supplied from
sediments combined with those in solution are usually adequate to meet nutritional demands of rooted
aquatic plants,  even in oligotrophic systems (Barko  et al. 1986). There are exceptions, however. Barko
et al. (1991) showed that interstitial ammonia limited the growth of hydrilla in the Potomac estuary.
Nutrient enrichment of nutrient poor waters will increase plant production if no other factors constrain
growth. However, the effects of enrichment for macrophytes are confounded by competition with
planktonic and epiphytic algae that may reduce underwater  light penetration of submerged macrophytes
and negate any direct effects of nutrient enrichment (Chambers et al. 1999). Bottom sediments  act as the
primary nutrient source for macrophytes, and for the most part, water column nutrients must be
incorporated into the sediments before they become available for uptake by macrophytes (Chambers et al.

The physical aspects of sediment texture and as an anchoring point for aquatic plants are also important
to the success of macrophytes in stream systems.  Some bottom types (e.g., rocks or cobble) are so hard
that plant roots cannot penetrate them and fast flowing gravel/cobble bottom stream systems rarely
contain enough sediment to support rooted macrophytes. Other sediments are too soft or unstable to
anchor rooted macrophytes well enough to endure changes in velocity. In addition, extremely coarse-
textured sediment (sand) can be nutritionally poor and therefore require accumulation of organic matter
from plant growth or erosion to provide suitable substrate for macrophyte growth (Goldman and Home

Macrophytes affect the water quality and human uses of water, other resident organisms, and nutrient
cycling. In turn, the above factors  influence the growth and abundance of the macrophyte community.
To obtain the desired biological integrity of an  aquatic community, macrophytes should be present and
healthy. However, excess natural or cultural enrichment may yield an overabundance or nuisance growth
of macrophytes (USEPA 1973). Macrophytes can inhibit phytoplankton growth by competing for
nutrients and sunlight, and by limiting light penetration and therefore photosynthetic processes below the
surface (Wetzel 1975). Macrophytes affect the DO and carbon dioxide (CO2) concentrations, alkalinity,
pH, and nutrient supply of a water body through primary production and respiration.  Overgrowth of
macrophytes in rivers and streams may decrease sediment transport by lowering the flow velocity.

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July 2000	Chapter 3. Select Variables

Current velocity, sediment type, and light availability to a large extent determine the plant types that
occur in rivers (Hynes 1969; Goldman and Home 1983; Chambers et al. 1999).

Macrophytes can be an important index of biological health in a waterbody. Their abundance or shortage
may be an indicator of excess or deficient nutrient supply. By monitoring macrophytes over a long
period of time  (along with other parameters), relationships may be developed between macrophyte
productivity and nutrients, nutrient cycling, eutrophication, sediment, and other biota (USEPA 1973).
Depending on  natural nutrient conditions or waterbody trophic state, N or P may be the limiting nutrient
in algal/macrophyte biomass accumulation (USEPA 1973; Smart 1990).  Phosphorus in particular, but
also N and other nutrients, may be taken up by submerged macrophytes from  sediment, uncoupling
macrophyte growth from water column nutrient concentrations (Welch 1992). Hence, water column
measurements  of total N and P (or soluble N and P) are usually not indicative of macrophyte growth
potential.  However, macrophyte growth has been shown to be responsive to sediment pore-water
ammonia content. As noted in the Bow River case study (see Appendix A), macrophytes declined in the
Bow River following N removal from point source wastewater plants. This decline was hypothesized to
have resulted from reductions in sediment N.

Macroinvertebrate Multi-Metric Indices
Indices employing macroinvertebrates as indicators of nutrient pollution have great potential because
they are the most reliable  and frequently used organisms to indicate the quality of water.
Macroinvertebrates are 1) highly sensitive to changes in water quality and disturbance, 2) relatively
immobile, long-lived and  easy to sample, and  3) an important food supply for fish and therefore
economically important. While the productivity and biomass of macroinvertebrates, as secondary
producers, readily respond to enrichment as noted above, the individual taxa also respond. Some
macroinvertebrates are particularly sensitive to nutrient enrichment, but local metrics of
macroinvertebrates must be developed to reliably use macroinvertebrates as indicators of nutrient
enrichment.  The peer-reviewed stream ecology literature describing nutrient and macroinvertebrate
interactions is  extensive.  Wallace and Webster (1996) provide a review of the literature.  Specific
methods for sampling macroinvertebrates and developing metrics for different stressors are described in
Barbour et al. (1999). Further discussion of macroinvertebrate multi-metric index development can be
found in Resh  and Rosenberg (1984) and Resh et al. (1996).  This type of metric development could be
used to derive  macroinvertebrate indices of nutrient enrichment in wadeable streams and rivers. In
addition, Norton et al. (2000) describes procedures to use biological  assessments, including multi-metric
indices, for identifying nutrient stress on both macroinvertebrates and fish.
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July 2000	Chapter 3. Select Variables
                                            PAGE 46

Chapter 4.
Sampling  Design  for
New Monitoring
  Sampling Design
    for New
Monitoring Programs

The purpose of this chapter is to provide technical guidance on designing effective sampling programs
for reconnaissance. Appropriate data describing stream nutrient and algal conditions are lacking in many
places. Where available data are not sufficient to derive criteria, it will be necessary to collect new data
through existing or new monitoring programs.  New monitoring programs should be designed to assess
nutrient and algal conditions with statistical rigor while maximizing available management resources.

Nutrient monitoring programs are used to better define nutrient and algal relationships within stream
systems. At the broadest level, monitoring data should detect:

1.    Seasonal patterns in nutrient levels and their relationship to algal biomass levels;

2.    The assimilation capacity of the system for nutrients: i.e., how much nutrient loading can be
     assimilated without causing unacceptable changes in water quality or the algal community
     (biomass and composition);

3.    Whether nutrient concentrations are increasing, decreasing, or staying the same over time.

This Chapter provides discussion on issues to consider with regard to monitoring nutrients and their
effects in stream systems. The various forms of nutrients to consider for sampling are discussed in
Chapter 3.  Field sampling and laboratory methods for nutrient assessment are described in Appendix B.

Monitoring programs are often poorly and inconsistently funded or are improperly designed and carried
out, making it difficult to collect a sufficient number of samples over time and space to identify changes
in water quality or estimate average conditions with statistical rigor. This Chapter provides a procedural
approach for assessing water quality condition and identifying impairment by nutrients and algae in
stream reaches. The approaches described below present sampling designs that allow one to obtain a
significant amount of information with relatively minimal effort.  Probabilistic and stratified random
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July 2000	Chapter 4. Sampling Design for New Monitoring Programs

sampling begin with large-scale random monitoring designs that are reduced as nutrient and algal
conditions are characterized. The tiered approach to monitoring begins with coarse screening and
proceeds to more detailed monitoring protocols as impaired and high-risk systems are identified and
targeted for further investigation.

Water quality variables other than the primary variables discussed in Chapter 3, e.g., DO, pH, TSS, etc.,
should be critically selected in a monitoring design to obtain the most cost-effective information required
to assess river system nutrient and algal conditions. Sampling should be designed to answer questions
such as: how, when, where and at what levels do nutrient concentration and algal biomass contribute to
unacceptable water quality conditions (e.g., offensive odors, aesthetic impairment, degraded habitat for
aquatic life, diurnal decreases in DO and pH increases)? These questions are interrelated, and a well-
designed program that monitors the primary variables (TN, TP, chl a, turbidity)  with other water quality
variables can contribute to answering them.



Developing nutrient criteria and monitoring the success of nutrient management programs involve
important considerations for sampling design.  Initially, the  relationships between critical response
variables and nutrient concentrations need to be established. Next, reference reaches  should be sampled
and assessed for specific classes of streams.  Nutrient concentrations and algal biomass levels in
reference reaches should define the ecological state that  could be attained if impaired reaches were
restored. In some streams and rivers, nutrient levels may be naturally high if bedrock, soils, or wetlands
are nutrient-rich sources in the region.  However, human actions can exacerbate nutrient enrichment
regardless of the natural nutrient condition.

Reach/stream selection for establishing causal relationships between nutrients and algal biomass is based
on the need to sample a relatively large number of streams with nutrient concentrations distributed along
the entire nutrient gradient for each class of streams in a specific regional setting.  Cause-response
relationships can also be identified using large sample sizes and streams with low as well as medium and
high nutrient concentrations. All ranges of responses should be observed along the gradient from
reference condition to high levels of human disturbance. Therefore, streams should be selected based on
land-use in the region so that watersheds range from minimally impaired with expected low nutrient
runoff to high levels of development (e.g., agriculture, forestry, or urban) with expected high runoff.

Assessing watershed characteristics through aerial photography and the use of geographical information
systems (GIS) linked to natural resource and land-use databases, can aid in identifying reference and
impaired streams. Some examples of watershed characteristics which can be evaluated using GIS and
aerial photography include land-use, land-cover (including riparian vegetation),  soils, bedrock,
hydrography, infrastructure (e.g., roads, public sewerage systems, private septic systems), and climate.
Watersheds with little or no development that receive minimal anthropogenic inputs could potentially
contain streams that would serve as reference sites (see section below). Watersheds with a high
percentage of their area occupied by nutrient-rich soils, heavily fertilized agricultural  land, and extensive
unsewered development in coarse soils are likely to contain streams receiving high nutrient loads that
could potentially be considered 'at risk' for developing nutrient and algal problems. The USDA

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July 2000	Chapter 4. Sampling Design for New Monitoring Programs

agricultural census provides information on agricultural land use (crops, livestock, irrigation, chemicals
used) at the national, state, and county levels.  Data are available on their website at:

Once the watershed level has been considered, a more stream-specific investigation can be initiated to
better evaluate nutrient and algal conditions. Rivers and streams need adequate light and nutrients to
develop and maintain high levels of algal biomass.  In addition, attached algae (periphyton) require
coarse substrata (cobbles, boulders) and a flow regime that provides sufficient periods between scouring
floods (at least one month) to accumulate high levels of biomass. The condition of the riparian zone
needs to be considered. Riparian buffer zones may mediate the effects of nonpoint sources of nutrients
and turbidity and, depending on the slope of the system, may reduce the velocity of overland runoff to a
stream.  Riparian wetlands may serve as both sources and sinks for nutrients varying with wetland type,
seasonal flows, and degree of disturbance.  The presence or absence of streamside trees can affect light
limitation in a stream.  Light is unlikely to  limit algal growth where streamside trees have been removed
or the stream is wide, shallow and clear enough to permit sufficient light to reach much of the bottom.
Shaded  streams may have high nutrient concentrations with no correlative response in algal growth,
though the nutrient load may stimulate algal growth further downstream.  The relative risk to develop
nutrient and algal problems could be assessed by noting how many of the above factors that permit higher
algal levels and/or nutrient concentrations are common to a stream or reach.


Nutrient inputs can occur at a myriad of points along a river system resulting in highly variable
concentrations of nutrients throughout the system. System variability and multiple nutrient input points
require numerous sampling sites for assessing the nutrient condition of a river system. Monitoring
stations  for nutrients in streams and rivers should be located upstream and downstream from major
sources  of nutrients or diluting waters (e.g., discharges, development, tributaries, areas of major
groundwater inputs) to quantify sources and loads.


Nutrient and algal problems are frequently seasonal in streams and rivers, so sampling periods can be
targeted to the seasonal periods associated  with nuisance problems. Nonpoint sources may cause
increased nutrient concentrations and turbidity or nuisance algal blooms following periods of high runoff
during spring and fall, while point sources  of nutrient pollutants may cause low-flow plankton blooms
and/or increased nutrient concentrations in pools of streams and in rivers during summer. In most state
monitoring programs, sampling is only conducted once during the season when greatest impacts are
expected.  If only a one-time sampling  is possible, then sampling between two to four (2-4) weeks after a
storm or high flow event has disturbed algal assemblages (Stevenson and Bahls 1999) is recommended.
Two to four weeks will allow sufficient time for algal biomass recovery in streams where algal biomass
predominantly consists of diatoms or micro-algae. Alternatively, sampling should be conducted during
the growing season at the  mean time after flooding for the system of interest. In streams where macro-
algae or macrophytes comprise the dominate photosynthetic biomass, recovery of photosynthetic biomass
may take one  or more growing seasons following a major high-flow event. However, if a high-flow event
does not move anchoring substrata, the flow event will only have a nominal effect on photosynthetic
biomass. High flow events late in the growing season when algal and macrophyte filaments and fronds

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July 2000	Chapter 4.  Sampling Design for New Monitoring Programs

are more prone to slough, may cause a reduction in the photosynthetic biomass. A one-time sampling
approach may be adequate for indicators of nutrient status,  designated use, and biotic integrity.
However, criteria and biological or ecological indicator development (see Assessing Algal Biomass
below) may require more frequent sampling to observe nutrient conditions that relate to peak algal
biomass (Biggs 1996; Stevenson 1996; Stevenson 1997b).

Nutrient concentrations vary with climate-driven changes in flow. Algal blooms, both benthic and
planktonic, can develop rapidly and then may dissipate as nutrient supplies are depleted or flow
increases. Thus sampling through the season of potential blooms may be necessary to observe peak algal
biomass and to characterize the nutrient conditions that caused the bloom.  Sampling through the season
of potential problems is important for developing cause-response relationships (with which biological
and ecological indicators can be developed) and for characterizing reference conditions. Keep in mind
that there is a time-lag between nutrient enrichment and algal response. Therefore to characterize algal
response to a specific enrichment event, nutrient sampling should be conducted prior to algal sampling.
Samples for nutrients should also be collected during the season  of lowest algal levels (at least 3
samplings spread over the period) to determine current background levels of algal biomass; avoid the
problem of algal uptake attenuating nutrient concentrations, and help provide an estimate of maximum
nutrient concentration.  Many nutrient monitoring programs are based on quarterly sampling.  However,
quarterly samples are usually inadequate to detect long-term trends due to year-to-year variation in the
window of high flows, the period of high nutrient uptake and algal growth, and the period of algal
sloughing at the end of the growing season.

If few nutrient and algal data exist, then multi-year surveys on a twice monthly or monthly basis may be
necessary to determine if nuisance algal problems occur.  Frequent sampling is necessary because algal
blooms may develop and dissipate rapidly with residual adverse effects, such as fish kills and  impaired
aquatic habitat.  Multi-year sampling is necessary because unusually large annual variability can occur
annually in the intensity of nutrient/algal problems, due to timing of weather (primarily scouring storm
events or persistent low flow events with long residence time) and seasonality of algal blooms.

Ideally, water quality monitoring programs produce long-term datasets compiled over multiple years, to
capture the natural, seasonal and year-to-year variations in waterbody constituent concentrations (e.g.,
Dodds et al. 1997; Tate 1990).  Multiple-year datasets can be analyzed with statistical rigor to identify
the effects of seasonality and unusual flow years (Miltner and Rankin 1998).  Once the pattern of natural
variation has been described, the data can be analyzed to determine the water quality conditions that
degrade the ecological state of the waterbody or effect downstream receiving waters. Long-term data
sets have also been extremely important in determining the  cost-effectiveness of management techniques
for lakes and  reservoirs (Cooke et al. 1993).  The same should be true for streams and rivers, if not more
so (due to greater constituent variability), although management of nutrients to improve quality in
streams and rivers has not been as well documented.

In spite of the documented value of long-term data sets, there is a tendency even in lake/reservoir
management to intensively study a waterbody for one year before and one year after treatment. A more
cost-effective approach would be to measure only the most essential indices, but to double or triple the
monitoring period. Two or more years of data are needed to identify the effects of years with  extreme
climatic or flow conditions. Low periphyton biomass has often been observed during high-flow summers
as well as the reverse, i.e., high biomass-low flow. The cause for that is not entirely clear; high flows

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July 2000	Chapter 4.  Sampling Design for New Monitoring Programs

may reduce biomass through scouring and/or dilute inputs of ground water nutrients. Whatever the
cause, the effect will be "averaged out" enough to discern the overall effect of treatment (e.g., nutrient
reduction or diversion) if several years of data are available to minimize the effect of the unusual flow
year(s). At the very minimum, two years of data before and two after implementing nutrient
management, but preferably three or more each, are recommended to evaluate treatment cost-
effectiveness with some degree of certainty. If funds are limited, restricting sampling frequency and/or
numbers of constituents analyzed should be considered to preserve a longer-term data set.  This will
allow for effectiveness of management approaches to be assessed  against the  high annual variability that
is common in most streams. High hydrological variation in a stream from year to year, requires more
years of sampling before and after mitigation procedures.

Characterizing Precision of Estimates
Estimates of dose-response relationships, nutrient and biological conditions in reference reaches, and
stream conditions of a region are based on sampling. Therefore, precision and accuracy must be
assessed. Determining precision of measurements for one-time assessments from single samples in a
reach is often necessary. The variation associated with one-time assessments from single samples in a
reach can often be determined by re-sampling a specific number of reaches during the survey.
Measurement variation among replicate samples can then be used to establish the expected variation for
one-time assessment of single samples. Re-sampling does not establish the precision of the assessment
process, but rather identifies the precision of an individual measurement.  Re-sampling frequency is often
conducted for one stream reach in every block often reaches. However, investigators should adhere to
the objectives of re-sampling (often considered an essential element of QA/QC) to establish an
assessment of the variation in a one-time/sample assessment.  The larger the sample size the better
(smaller) will be the estimate of that variation. Often, more than one in ten samples need to be replicated
in monitoring programs to  provide a reliable estimate of measurement precision.


The following sections discuss two different approaches to sampling design, probabilistic and goal-
oriented. Both approaches have advantages and disadvantages that under different circumstances warrant
the choice of one approach over the other (Table 3). The decision as to the best approach for sample
design in a new monitoring program must be made by the water quality resource manager or management
team after carefully considering different approaches.

Probabilistic Sampling
Probability sampling, where randomness is  required, can be used to determine the variability of nutrient
and algae levels in streams and rivers across a state or a region. Random sampling is a generic type of
probability sampling where randomness can enter at any stage of the sampling process. Probabilistic
sampling - a sampling process wherein randomness is a requisite (Hayek  1994) - can be used to
characterize the status of nutrient conditions and biotic integrity in a region's streams and rivers.
Probabilistic designs are often modified by  stratification (such as classification  [Chapter 2]), by deleting
"redundant" reaches, or by adding important sites. Stratification or stratified  random sampling is a type
of probability sampling where a target population is divided into relatively homogenous groups or classes
(strata) prior to  sampling based on factors that influence variability in that population (Hayek 1994).
Analysis of variance can be used to identify statistically different parameter means among the sampling
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July 2000
Chapter 4.  Sampling Design for New Monitoring Programs
Table 3. Comparison of probabilistic and goal-oriented sampling designs.
               Probabilistic Sampling
                   Goal-oriented Sampling
 • random selection of streams from entire population
 within a region
 • requires no prior knowledge of streams within the
 sample population
 • may require more resources (time and money) to
 randomly sample stream classes because more streams
 may be sampled
 • nutrient condition characterization for a class of
 streams is more statistically robust
 • potentially best for regional characterization of
 stream classes, especially if water quality conditions
 are not known
      • targeted selection of streams based on problematic
      (reaches known to have nutrient/algal problems) and
      reference reaches
      •  requires prior knowledge of streams within the
      sample population
      •  utilizes fewer resources because only targeted
      streams are sampled
      •  nutrient condition characterization for a class of
      streams is less statistically robust, though
      characterization of a targeted stream or reach may be
      statistically robust
      •  potentially best for site-specific and watershed-
      specific criteria development when water quality
      conditions for the reach of interest are known
      • selection of sites that represent a range of nutrient
      conditions will facilitate establishment of nutrient-algal
      relationships for the systems of interest
strata or classes.  The strata are then used as the analysis of variance treatments (Poole 1972).  Goal-
oriented sampling as described in the tiered approach in this  Chapter, is not as easily analyzed by
rigorous statistical analyses. Goal-oriented monitoring may be better suited to statistical analyses using
basic descriptive statistics and correlational analyses.

Streams are selected for probabilistic sampling by random selection of a sample of streams from the
entire population of streams within a region. Thus, all stream reaches within a region must be identified
to establish the statistical population of streams; then a sample of all possible streams is selected from
that population. The results of collecting and assessing water quality and biotic responses with a
probabilistic sample is, presumably, an unbiased estimate of the descriptive statistics (e.g., means,
variances, modes, and quartiles) of all streams in a region. Probabilistic sampling designs are commonly
modified by stratifying by stream size and stream classes.  Otherwise, sample statistics would be most
characteristic of the numerous small streams of the dominant stream types in a region.

Many state 305b and watershed monitoring programs utilize  modified probabilistic sampling designs.
Stratification in many of these programs is based on identifying all stream reaches in a region (or
watershed) and then selecting an "appropriate" sample of reaches from the defined population.  The
sample  population is often modified by deleting stream reaches that are too close to other reaches to be
different, thereby reducing redundant collection efforts. The selected sample of streams may also be
modified by adding sites that are near known sources of impact.  Estimates of ecological conditions from
these kinds of modified probabilistic sampling designs can be used to characterize the nutrient status, and
over time, to distinguish trends in stream nutrient condition within a region.  Estimates of regional
conditions are best when sites near known sources of impact are removed from the analysis and later
compared to the distribution of regional nutrient conditions.
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July 2000	Chapter 4.  Sampling Design for New Monitoring Programs

Goal-Oriented Sampling
A goal-oriented approach to sampling design may be more appropriate when resources are limited. The
tiered approach described here focuses the greatest efforts on identifying and characterizing rivers and
streams likely to have nutrient problems, and on relatively undisturbed streams, often called reference
streams or reaches, that can serve as regional or sub-regional examples of natural biological integrity.
Choosing sampling stations that best allow comparison of nutrient concentrations at reference stream or
river sites of known condition can conserve financial resources.  Goal-oriented sampling also includes
some elements of randomness. However, the identification of systems with nutrient problems and
reference conditions eliminates the need for selecting a random sample of the population for monitoring.

Goal-oriented sampling assumes some knowledge of the systems sampled. Systems with evidence of
impairment are compared to reference systems that are similar in their physical structure. Sites chosen to
represent a range of nutrient conditions will facilitate development of nutrient concentration-algal
biomass relationships. Goal-oriented sampling requires that the reaches  be characterized according to
assessed nutrient and algal levels. Comparison of the monitoring data to data collected from reference
stream reaches will allow characterization of the sampled streams. Reaches identified as 'at risk' should
be evaluated through a sampling program to characterize the degree of impairment. An impaired reach is
simply a reach of any length where nutrient concentrations exceed acceptable levels, or algae interfere
with beneficial uses.  Once characterized, the reaches should be placed in one of the following

1.    Impaired reaches - reaches in which nutrients or algal biomass levels interfere with designated

2.    High-risk reaches - reaches where nutrient concentrations are high but do not significantly impair
      designated uses. In high-risk streams impairment is prevented by one or a few factors that could be
      changed by human actions, though water quality characteristics (e.g., DO, turbidity) are already

3.    Low-risk reaches - reaches where many  factors contain nutrient concentrations and algal biomass
      levels  are below problem levels and/or no development is contemplated that would change these

4.    Reference reaches - reaches where nutrient concentrations and algal biomass levels most closely
      represent the pristine or minimally impaired condition.

Once stream reaches have been classified based on their physical structure (see Chapter 2) and placed
into the above categories, specific reaches need to be selected for monitoring. At this point, randomness
is introduced; stream reaches should be randomly selected within each class and risk category for

Monitoring efforts are often prioritized to best  utilize limited resources.  Impaired and high-risk streams
should be monitored more intensively than low-risk streams.  Impaired streams should be monitored to
evaluate, implement, and assess management activities to reduce algal biomass and improve water
quality. High-risk streams should be monitored to assure that no further degradation takes place. Low-
risk streams  can be monitored less frequently, but should be monitored frequently enough to identify any

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July 2000	Chapter 4. Sampling Design for New Monitoring Programs

increase in nutrients or algae, and/or change of water quality.  Reference reaches should be monitored
frequently enough to make robust comparisons with impaired and high-risk stream reaches.  In addition,
monitoring of changes in the watershed can help identify areas where changes are likely to result in
degradation of nutrient condition. Human activities within a watershed that can increase the risk of
nutrient and/or algal problems include 1) stabilization of flows (reduces scour); 2) reduction of flows
(increases light, reduces dilution of nutrients); 3) removal of streamside vegetation (increases light, may
decrease depth of stream; and increases the flux of nutrients from the stream hillslope due to reduced
uptake from plant roots); 4) discharge of nutrient rich waste water; 5) construction of unsewered
residential development (especially in thin coarse soils); 6) over fertilization of agricultural  land; 7)
development that increases the percent of impervious surface in the watershed; and hence nutrient runoff;
and 8) discharge of toxins or release  of exotic species that reduce grazer populations.


Potential reference streams should be characterized to allow for the identification of appropriate
reference streams and reference  stream reaches.  Classification of streams, as discussed in Chapter 2,
will allow appropriate reference reaches to be identified for specific regions and stream types. Stream
classification should be supplemented with information on return frequency of flows. Reference streams
or reaches may not be available for all stream classes. In this case, data from systems that are as close as
possible to the assumed unimpaired state of rivers and streams in that class should be sought from  States
or Tribes within the same nutrient ecoregion.

The identification of reference reaches as opposed to reference streams is an important distinction (see
Chapter 7, Section  7.2).  Identification of impaired and reference streams would be relatively simple if an
entire stream had all the same physical characteristics and risk factors. However, only one specific
portion of a stream length, a reach, may have all the characteristics necessary to produce algal problems.
It may not be possible to find an entire stream that has little or no impacts anywhere in its watershed.
Therefore, stream reaches should be targeted, but their watersheds should also be kept in mind. The
stream bed, banks,  and riparian zone of a reference reach should be in a fairly natural state, and its
watershed as undeveloped as possible. States/Tribes should endeavor to protect such reference reaches
from future development.

Streams for reference-reach sampling should be selected based on low levels  of human alteration in their
watersheds and aquatic habitat.  Selecting reference reaches usually involves  assessment of land-use
within watersheds,  and visits to streams to ground-truth expected land-use and check for unsuspected
impacts. Sometimes ecological impairment that was not apparent from land-use and local habitat
conditions may be identified. Again, sufficient sample size is important to characterize the range of
conditions that can be expected in the least impacted systems of the region (see TN case study in
Appendix A).

Reference reaches should be identified for each nutrient ecoregion in the State or Tribal lands and then
characterized with respect to nutrient concentrations, algal biomass levels, algal community composition
and associated environmental conditions including turbidity, light, and substrata as well as factors  that
are affected by algae, such as DO and pH. For each ecoregion in a state, a minimum of three low impact
reference systems should be identified for each stream class. Highest priority should be given to
identifying reference streams for those stream types considered to be at the greatest risk from nutrients

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July 2000	Chapter 4. Sampling Design for New Monitoring Programs

and algae. Reference stream reaches are often less accessible than reaches adversely affected by nutrient
and algal impairments.  However, sampling need not be as frequent in reference reaches, except to
validate models of algal response to nutrient loads for such reaches.

Continuation of Less Intensive Monitoring of High-Risk Reaches
The continuation of monitoring of high-risk reaches  should focus on factors likely to increase nutrient
concentrations or limit algal growth and on any actions that might alter those factors.  For example, if
light is limiting, it may be most appropriate to evaluate the potential impact of the removal of streamside
trees or of the manipulation of water levels which may kill streamside trees.  Stabilization of flows
results in the  decline of flood-dependent vegetation.  Increased grazing levels can reduce streamside trees
degrade banks, altering the depth and width of the stream. State/Tribal water quality agencies should
encourage adoption of local riparian protection plans where light is limiting to minimize nutrient-caused
water quality problems.

If scouring flows limit algal accrual and significantly dilute nutrient loading, a closer evaluation of plans
that could manipulate flows (by diversion, damming or altering management at existing structures) is
warranted.  State/Tribal water quality agencies should inform agencies that regulate water development
of the potential impacts of flow manipulation.

Development plans in the watershed should be evaluated where nutrients are limiting (see Defining the
Limiting Nutrient, Section 6.2).  Changes in point sources can be monitored through the NPDES permit
program. Changes in nonpoint sources can be evaluated through the identification and tracking of
wetland loss and/or degradation, increased residential development, increased tree harvesting, and shifts
to more intensive agriculture with greater fertilizer use or increases in livestock numbers. Local planning
agencies should be informed of the risk of increased nutrient loading and encouraged to guide
development  accordingly. Nutrient levels often gradually increase due to many growing nonpoint
sources. Hence, in-stream nutrient monitoring is warranted in nutrient-limited, high-risk reaches if
sufficient resources remain after meeting the needs of impaired reaches.  Seasonal nutrient levels should
be more stable in streams with low algal biomass than in streams with high algal biomass because
nutrient concentrations would not be depleted in such streams.  Sampling during growing season
baseflow and nongrowing season baseflow should provide a limited, yet useful, assessment of trends in
nutrient levels from year-to-year.

Whenever development plans appear likely to alter factors that were limiting algae growth in a high-risk
reach, instream monitoring should be initiated at a level similar to that described for impaired reaches in
order to enhance the understanding of baseline conditions.


Assimilative Capacity
The assimilative capacity of a stream for nutrients depends on its physical and biological nature.
Assimilative capacity is the load of nutrients entering a river system at which nutrient and algal biomass
levels remain low enough such that excessive diurnal fluctuations of DO concentrations and pH levels
will not occur, recreation and aesthetics will not be negatively impacted, irrigation ditches will not be
clogged with  algae, and biotic criteria will be consistently met. Such nutrient loads are difficult to
predict because nutrients are stored in many forms and released under a variety of conditions, and

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July 2000 _ Chapter 4. Sampling Design for New Monitoring Programs

because the levels of nutrients and algae causing impaired conditions may vary from system to system.

The simplest model applied has been to apply an exponential decline in instream nutrient concentrations
below point sources  and tributaries, with the rate of decline derived from monitored data.  This approach
does not quantify mechanisms (such as sedimentation, uptake, dilution by groundwater and
denitrification), that  can lead to nutrient losses. Such an approach was applied on the Clark Fork River
(Dodds et al. 1997) to model the influence of lowered inputs from point sources on instream nutrient

Nutrient Load Attenuation
A given nutrient load may produce a few kilometers (km) containing unacceptable algal biomass
followed by a section of river containing acceptable levels because a river's load is attenuated by
retention in algae and sediment. The total length of river containing unacceptable algae biomass levels
may change from year-to-year due to changing nutrient loads or changes in other factors (e.g., flow,
dilution) that may limit algae growth (see Section 6.2).  This phenomenon was illustrated following
nutrient control in the Bow River, Alberta, where TDP  remained high (25 (ig/L) for several km
downstream from the treated wastewater source. High  TDP in the portions of the stream closest to the
point source release  resulted in no change in algal biomass, while algae decreased farther downstream as
TDP decreased (see  Bow River case study, Appendix A). The length of river containing unacceptable
algal biomass levels  may be hypothetically estimated by the following equation described  in Welch et al.
                    Dc = Q^SRP, - SRPc)/[(P/chl a day)*Bn*T*W* 103 m/km])

where SRP is in (ig/L (mg/m3) producing the threshold nuisance biomass (150 mg chl/m2) in the growth
period (nominally ~ 1-4 mg/m3 in channel experiments  [Walton et al. 1995]); Q is the daily flow in
mVday; r accounts for the recycle (~ 1.5, after Newbold et al. 1981); SRPj is the influent concentration
(ambient river and groundwater in mg/m3) to the segment; SRPC is the critical concentration, above which
nuisance algal growth occurs; P/chl a-day is the average uptake by periphyton with nominal value of 0.2;
Bn is the nuisance threshold biomass of 150 mg chl a/m2;  T is the factor for trophic (consumer) retention
(~ 1.2 representing a 20% conversion); and W is average  stream width in meters.

This equation is simply the ratio of SRP mass available for uptake in excess of the critical level and the
expected demand for SRP by periphyton in an enriched stream  reach in which the threshold nuisance
biomass is attained. The basis of the formulation is that periphytic biomass will not be reduced unless
SRP is less than the critical concentration (SRPC) during low-flow, maximum growth conditions, which
has been shown to be quite low in channel experiments (Walton et al.  1995). Low values for the critical
P concentration were supported by the Bow River case  study (see Appendix A). The length of river with
unacceptable algal biomass levels increases as the criterion decreases. The important recycle rate in the
equation is a nominal value taken from uptake studies in a natural stream and could be highly variable.
More definite predictions of limiting nutrient content and algal biomass changes downstream from a
point source requires a dynamic model for algal biomass, such as:

                                  dB/dt = (u * L * Bi) - (S + G)
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July 2000	Chapter 4. Sampling Design for New Monitoring Programs

where u = nutrient uptake rate in I/day, L = dimensionless light factor, Bi = periphyton biomass from
previous time step in mg chl/m2, S = sloughing loss in mg chl/m2-day and G = grazing loss in mg chl/m2-
day (after Elswick 1998).

Estimating nutrient loads to a stream is at least as complex as a detailed nutrient source study for a lake
and requires the tracking of nutrient sources upstream and upgradient.  In some cases, loading estimates
of stream and river systems may be back calculated from the loading estimate for the receiving
waterbody. That is, the partition of the nutrient load to a receiving waterbody (lake or estuary)  identified
as belonging to a particular stream may be used as an estimate of the total load for that stream or reach.
Loading is often estimated using a calibrated model that predicts nutrient loads from hydrologic inputs or
other parameters if nutrient data are inadequate to calculate  load.

The USGS has developed a set of spatially referenced regression models for evaluating nutrient loading
in a watershed. The modeling approach is referred to as SPARROW (SPAtially Referenced Regressions
On Watershed attributes), a statistical modeling approach that retains spatial referencing for illustrating
predictions, and for relating upstream nutrient sources to downstream nutrient loads (Preston and
Brakebill 1999) (See Appendix C). Stream-load estimates at gaged monitoring sites are generated from
stream-discharge and water quality data by utilizing a log-linear regression model called ESTIMATOR.
The ESTIMATOR model estimates daily concentration values based on flow, season, and temporal trend
terms (Preston and Brakebill 1999) (see Appendix C).

Better Assessment Science Integrating Point and Nonpoint Sources, or BASINS, is a tool developed by
EPA to facilitate water quality  analysis on a watershed level for specific waterbodies or stream  segments.
BASINS was designed to integrate national water quality  data, modeling capabilities, and (GIS) so that
regional, State, local and Tribal agencies can easily address  the effects  of both point and nonpoint source
pollution and perform sophisticated environmental assessments (http://www.epa.gov/ost/BASINS/).

Models  should be used with caution.  Models can be used incorrectly and, therefore, can be less accurate
than loads calculated from data. Regardless of the method used for calculating loads, subsequent
changes in the watershed may alter the relationship between hydrologic and nutrient inputs requiring
loads to be re-calculated to reflect those changes.

Assessing Algal Biomass
This section focuses on assessing attached algal biomass and how to  obtain a meaningful, representative
algal biomass sample.  Sampling strategies will vary with  objectives of programs.  Algal sample
collection techniques for streams and laboratory methods  for the analysis of chlorophyll, AFDM,  and
other measures of biomass are discussed in Appendix B.

If the goal of sampling is to develop a relationship between nutrients and algal problems for the rivers of
a region or to assess status and  trends in nutrient-related problem areas of a region (i.e. probabilistic
sampling), then one representative estimate of algal assemblage characteristics is all that can be used in
an analysis.  In most cases, the  desired estimate is a mean algal biomass measure for a reach that can be
obtained with composite sampling (explained below).  However, spatial extent and temporal duration of
blooms or nuisance growths may also be important parameters to characterize. More than one sample (or
estimate) from a site would result in pseudoreplication (Hurlburt 1984) and would be unacceptable for
data analyses which require independent observations of conditions (biotic and nutrient) at each site.

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July 2000	Chapter 4. Sampling Design for New Monitoring Programs

Variability in attached algal biomass estimates due to spatial variability can be reduced by collecting
composite samples and by sampling in targeted habitats where algal biomass is relatively uniform (e.g.,
riffles).  Composite sampling calls for combining subsamples from many substrata into a single sample,
thus incorporating spatial variability into the one sample.  The targeted habitat is usually defined as the
habitat in which nuisance problems are greatest, typically the riffles during higher flow seasons and pools
during low-flow seasons. Variability in algal biomass assessments should decrease with increasing
numbers of riffles and area of stream assessed.  Therefore, composite samples should be collected over
the entire study reach.

Large scale assessments are particularly important for patchy filamentous algae, which may be best
assessed using rapid periphyton surveys (in-stream, visual assessments of periphyton biomass; see
Stevenson and Bahls 1999). Streams and rivers shallow enough to be wadeable during the period when
nuisance problems are greatest may be sampled randomly across the entire width of the stream. If
variability is still too great, the focus of assessments could be reduced to an indicator zone (an area
having a high potential for nuisance algal growth) with a narrow range of water velocity, depth, and
substratum size.  For rivers with unwadeable depths, sampling attached algae is commonly confined to
the wadeable portions because deeper portions may not have enough light for dense benthic algal growth.
However,  SCUBA has been used to sample benthic algae in large rivers (Lowe 1974).

In streams and rivers where nuisance algal problems arise from planktonic algal blooms during low-flow
conditions, sources of variability in algal biomass (and related factors like low DO) tend to be due to
temporal as opposed to spatial variability. Repeated plankton sampling during the low-flow period is
strongly recommended to relate nutrients to peak plankton biomass and potential problems of low DO or
noxious (toxic, taste, and odor causing) algal blooms.  If the goal of estimating algal biomass at a
problem site is to compare estimates of biomass to  a criterion, then replicate sampling of at least four
samples at that site is recommended to characterize the mean and variance in observations.  If the goal  of
sampling is to develop a relationship between nutrients and algal problems for the rivers of a region, or to
assess status and trends for nutrient-related problems, then replicate sampling is not as important as
accounting for temporal variability and sampling more sites.

Relating nuisance algal problems to nutrient concentrations during stream low-flow conditions can be
complicated by a number of factors. Algal problems may be due to a combination of planktonic algae
blooming throughout pools and benthic algae along margins of pools. Planktonic algae may settle into
sediments  of pools and may generate oxygen demand from those sediments.  Thus, thorough sampling
designs should be employed that consider both spatial and temporal variability in algal biomass and
associated nutrients to ensure development of accurate and precise relationships between nuisance algal
problems and nutrients.

Attached algal biomass can vary greatly in time as well as space within the same stream.  Temporal
variability in algal biomass can be addressed by repeated sampling during periods when high algal
biomass is most likely a problem.  Alternatively, algal biomass can be sampled during periods of peak
biomass following flood disturbances. This period of peak biomass may endure from one week to two
months, depending upon nutrient concentrations in streams and the severity of flood events. Repeated
assessment of algal biomass in streams can be facilitated by using rapid periphyton surveys to reduce
sampling and laboratory assay costs (see Stevenson and Bahls 1999). Even though many measurements
are being made through time, only one measurement per site can be used to develop biomass-nutrient

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July 2000	Chapter 4.  Sampling Design for New Monitoring Programs

relationships because of site-specific dependence and problems of repeated measures from the same site
(Green 1979; Sokal and Rohlf 1998).

In some cases, the goal of assessment might be to estimate algal biomass at a problem site to compare
estimates of biomass to a criterion.  In this case, replicate sampling of at least four or many more samples
at a site is recommended to characterize the mean and variance in the mean with replicate samples from a
site. If the variability in algal biomass is similar to that in the Clark Fork River (see Appendix A case
study), as many as 20 replicate samples may be required to  detect small changes, which may be important
to monitor restoration efforts.


Citizen input can be used to assist in identifying and prioritizing potential problem streams. For
example, citizens can be asked (through the use of surveys) to identify streams in which they have
observed algal biomass levels that interfere with human uses or impair aesthetic enjoyment.  They can
also be asked to provide their evaluation of which streams have been affected most and which uses have
been impaired to the greatest degree.

While state water quality agencies will likely take the lead in monitoring impaired reaches, citizen
monitors may provide much of the monitoring on high-risk  reaches. If properly trained and directed,
citizen volunteers can be valuable in algal and nutrient monitoring.  Citizens, with training, can visually
assess algal levels,  collect algal samples and freeze them for analysis by an approved laboratory, and may
also help in the initial characterization of streams. Citizen monitors can frequently provide more
complete flow records by visiting gauges more often than state personnel. Once advised that a stream is
high-risk and that the limiting factors have been identified,  citizens can help monitor development plans
that might affect those factors. Involvement in monitoring programs may lead  citizens to effective
participation in local planning.

Many excellent resources  are available for training citizen monitors. EPA has a volunteer monitoring
coordinator (Alice Mayio—E-mail:  alice.mayio@epamail.epa.gov) and a web site that lists many
resources http://www.epa.gov/OWOW/monitoring/volunteer/spring94/ppresf04.html). Numerous non-
governmental organizations, such as the Izaak Walton League, have developed citizen monitoring
manuals. One of the best is the Streamkeeper's Guide by the Adopt-a-Stream Foundation (600-128th St.
SE, Everett, WA 98208, phone 206-316-8592; web site: http://www.streamkeeper.org/).
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July 2000	Chapter 4. Sampling Design for New Monitoring Programs
                                          PAGE 60

Chapter 5.
Building  a Database
of Nutrient- and
Algae-Related Water
Quality  Information
 Building a Database\
of Nutrient- and Algae-
   Related Water
 Quality Information J

A database of relevant water quality information can be an invaluable tool to States and Tribes as they
develop nutrient criteria. Existing data may provide considerable information that is specific to the
region where criteria are to be set. First the data must be located, then the suitability of the data (type
and quality) ascertained before they are to be used for historical reconstruction of water quality
parameters. It is also important to determine how the data were collected to make future monitoring
efforts compatible with earlier approaches.

Databases operate much like spreadsheet applications, but have greater capabilities. While spreadsheets
analyze and graphically display small quantities of data,  databases store and manage large quantities of
data and allow viewing and exporting of data sorted in a variety of ways. Databases can be used to
organize existing information, store newly gathered monitoring data, and manipulate data  as criteria are
being developed. Databases can sort data for export into statistical analyses programs, spreadsheets, and
graphics programs. This chapter will discuss the role of databases in nutrient criteria development, and
provide a brief review of existing sources of nutrient-related water quality information for streams and


This section describes general database structure and provides detailed information on relational and GIS
databases.  A database is a collection of information related to a particular subject or purpose. Databases
are arranged so that they divide data into separate electronic repositories called tables.  Data in tables can
be viewed and edited, and new data can be added. A single datum is stored in only one table, but can be
viewed from multiple locations. Updating one view of a datum will update it in all the various viewable
forms.  Each table should contain a specific type of information. Data from different tables can be
viewed simultaneously according to the user-defined table relationships. That is,  the relationship among
data in different tables can be defined so that more than one table can be queried or reported, and
accessed in a single view.  Data stored in tables can be located and retrieved using queries. A query
allows the user to find and retrieve only the data that meets user-specified conditions.  Queries can also
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July 2000	Chapter 5. Building a Database of Nutrient- and Algae-Related Water Quality Information

be used to update or delete multiple records simultaneously and to perform built-in or custom
calculations of data. Data in tables can be analyzed and printed in specific layouts using reports. Data
can be analyzed or presented in a specific way in print by creating a report.

To facilitate data manipulation and calculations, it is highly recommended that historical and present-day
data be transferred to a relational database. A relational database is a collection of data items organized
as a set of formally-described tables from which data can be accessed or reassembled in many different
ways without having to reorganize the database tables.  Each table (which is sometimes called a relation)
contains one or more data categories in columns.  Each row contains a unique instance of data for the
categories defined by the columns. The organization of data into relational tables is known as the logical
view of the database. In other words, the logical view is the form in which a relational database presents
data to the user and the programmer (www.whatis.com/relation.htm). Relational databases are powerful
tools for data manipulation and initial data reduction. They allow selection of data by specific, multiple
criteria, and definition and redefinition of linkages among data components.

GISs are geo-referenced relational databases that have a geographical component (i.e., spatial platform)
in the user interface.  Spatial platforms associated with a database allow geographical display of sets of
sorted data. Databases with spatial platforms are becoming more common.  The system is based on
premises that "pictures are worth thousands of words" and most data can be related to a map or other
easily understood graphic. GIS platforms such as Arc View™, Arclnfo™, and Maplnfo™ are frequently
used to integrate spatial data with monitoring data for watershed analysis.


The Nutrient Criteria Program has initiated development of a national relational database application that
will be used to store and analyze nutrient data. The ultimate use of these data will be to derive
ecoregion- and waterbody-specific numeric nutrient criteria ranges. Initially, EPA is developing a
Microsoft Access™ application which will ultimately be populated with STORET Legacy Data, USGS
NAWQA, NASQAN and Benchmark data, and other relevant nutrient data from universities,
States/Tribes, and additional data rich entities. EPA is also developing a compatible, interactive system
in an Oracle™ environment which allows for easy web-accessibility, geo-referencing/GIS compatibility,
and data analysis on both a State/Tribal, regional, and national basis. The total amount of existing
nutrient data nationally is large (>20 gigabytes), and it is anticipated that more data will be entered into
the system. The Oracle™ application can easily manage large quantities of data and will provide ample
room for expansion as more data are collected.  Both the Access™ and the Oracle™ database
applications are being designed for compatibility with EPA's latest edition of STORET to avoid
duplication of effort for users of STORET and the Nutrients database application. Considerable efforts
are also being made to assure compatibility with other database systems (e.g., WQS and RAD) currently
being developed in EPA's Office of Water. The Microsoft Access™ application will be available in
January 2000; the Oracle™ application will be online in the spring of 2000.


In some States/Tribes, historical data on streams and rivers are already available.  These data can be used
to identify reference streams and begin development of potential nutrient criteria. Data should be

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July 2000	Chapter 5. Building a Database of Nutrient- and Algae-Related Water Quality Information

compiled in a format that is easily imported into database and spreadsheets.  Ideally, data will be
compiled in the Nutrients Database described above. Potential data sources for river and stream nutrient
data that will be useful for developing criteria are discussed below. These data sources contain extensive
water quality data, however, data collection should not be limited to these sources.  Collection of
scientifically sound water quality data from any reliable source is encouraged.


Potential sources of data include water quality monitoring data from Federal, State, Tribal and local
water quality agencies; university studies; and volunteer monitoring information. The data sources
described in this section do not encompass the full extent of available data sources. Many State/Tribal,
and Federal programs that are regional or site-specific are excellent data sources, but are not included in
this discussion.

EPA Water Quality Data
EPA has many programs of national scope that focus on collection and analysis of water quality data.
The following presents information on several of the databases and national programs that may be useful
to water quality managers as they compile data for criteria development.

STOrage and RETrieval system (STORET) is EPA's national database for water quality and biological
data.  EPA's original STORET System, operated continuously since the 1960s, was historically the
largest repository of water quality data in the nation. This legacy mainframe-based system will cease to
exist in the year 2000.  In its place, EPA will support two independent, web-accessible databases.  The
older database, called the STORET Legacy Data Center (LDC) is the repository of all data held in EPA's
original STORET System as of the end of 1998.  The newer, modernized database, simply called
STORET, is designed as a replacement for the original STORET System. It is the repository for more
current data, and offers major improvements in database content and quality control documentation.

Interested parties may view both databases on the World-Wide-Web, where the capability will exist to
produce printed reports and download data files. Queries for data via the web will be designed for use by
the general public and will require no special training or software.  The web site will be announced in the
first quarter of FY2000.

STORET (the new STORET  system) is a compendium of data supplied by Federal, State, and local
organizations  which evaluates environmental conditions in the field.  The data in STORET is organized
by both geographic location and data ownership. Every field study site is identified by at least one
latitude/longitude and, where appropriate, also by State/Province, County, drainage basin, and stream
reach.  Monitoring activities recorded include field measurements, habitat assessments, water and
sediment samples, and biological population surveys.  Records cover the complete spectrum of physical
properties, concentrations of substances, and abundance and distribution of species observed during
biological monitoring. STORET is designed for maximum  compatibility with commercial  software,
including Geographic Information Systems such as the ESRI Arc View package, and statistical packages
such as PC SAS. STORET download files import easily into all standard spread sheet packages.
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July 2000	Chapter 5.  Building a Database of Nutrient- and Algae-Related Water Quality Information

Further information about STORET may be obtained by e-mailing STORET@epa.gov, or telephoning
toll-free at 1-800-424-9067.

National Surface Water Survey (NSWS)
EPA's National Surface Water Survey consists of two parts: the National Lake Survey and the National
Stream Survey. The purpose of the National Lake Survey is to quantify, with known statistical
confidence, the current status, extent, and chemical and biological characteristics of lakes in regions of
the United States that are potentially sensitive to acidic deposition. The purpose of the National Stream
Survey (NSS) is to determine the percentage, extent, and location of streams in the United States that are
presently acidic or have low-acid neutralizing capacity and may, therefore, be susceptible to future
acidification, as well as to identify streams that represent important classes in each region for possible
use in more intensive studies or long-term monitoring. The NSS provides an overview of stream water
quality chemical characterisitics in regions of the United States that are expected, on the basis of
previous alkalinity data, to contain predominantly low-acid neutralizing capacity waters (EPA website

Environmental Monitoring and Assessment Program (EMAP)
The Environmental Monitoring and Assessment Program is an EPA research program designed to
develop the tools necessary to monitor and assess the status and trends of national ecological resources
(see EMAP Research Strategy on the EMAP website: www.epa.gov/emap). EMAP's goal is to develop
the scientific understanding  for translating environmental monitoring data from multiple spatial and
temporal scales into assessments of ecological condition and forecasts of future risks to the
sustainability of the Nation's natural resources. EMAP's research supports the National Environmental
Monitoring Initiative of the Committee on Environment and Natural Resources (CENR)
(www.epa.gov/emap/). Data from the EMAP program can be downloaded directly from the EMAP
website (www.epa.gov/emap/). The EMAP Data Directory contains information on available data sets
including data and metadata (language that describes the nature and content of data). Current status of
the data directory as well as composite data and metadata files are available on this website.

Clean Lakes Program (CLP)
The EPA Clean Lakes Program was initiated to assess water quality in impaired public lakes and
reservoirs and to restore these systems where appropriate. CLP included a monitoring and assessment
component to identify the efforts needed to restore water quality.  Lakes in this program were selected
because they were perceived to have water quality impairment.  Major tributaries into lakes and
reservoirs included in this program were sampled on a regular basis.  EPA encouraged States in its May
1996 section 319 nonpoint source guidance to use section 319 funds to fund eligible activities that might
have been funded in previous years in the CLP under Section 314. Data from this program may be useful
for positioning river and stream systems on a nutrient gradient continuum, but are unlikely to provide
data for reference stream reaches. Information about EPA's CLP can be found at the website:

Ecological Data Application System (EDAS)
ED AS is EPA's program-specific counterpart to STORET. EDAS was developed by EPA's Office of
Water to manipulate data obtained from biological monitoring and assessment and to assist States/Tribes
in developing biocriteria.  It contains built-in data reduction and recalculation queries that are used in

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July 2000	Chapter 5. Building a Database of Nutrient- and Algae-Related Water Quality Information

biological assessment. The ED AS database is designed to enable the user to easily manage, aggregate,
integrate, and analyze data to make informed decisions regarding the condition of a water resource.
Biological assessment and monitoring programs require aggregation of raw biological data (lists and
enumeration of taxa in a sample) into informative indicators.  ED AS is designed to facilitate data
analysis, particularly the calculation of biological metrics and indexes. Pre-designed queries that
calculate a wide selection of biological metrics are included with ED AS. Future versions of ED AS will
include the capability to upload data to, and download data from, the distributed version of modernized
STORET. EDAS is not a final data warehouse, but is a program or project-specific customized data
application for manipulating and processing data to meet user requirements. The EDAS application is
currently under development; more information will be available at a later date through the EPA website.

USGS (U.S. Geological Survey) Water Data
The USGS has national and distributed databases on water quantity and quality for waterbodies across
the nation. Much of the data for rivers and streams are available through the National Water Information
System (NWIS). These data are organized by state, Hydrologic Unit Codes (HUCs), latitude and
longitude, and other descriptive attributes. Most water quality chemical analyses are associated with an
instantaneous streamflow at the time of sampling and can be linked to  continuous streamflow to compute
constituent loads or yields. The most convenient method of accessing  the local data bases is through the
USGS State representative. Every State office  can be reached through the USGS home page on the
Internet at URL http://www.usgs.gov/wrd002.html.

USGS data from several national water quality programs covering large regions offer highly controlled
and consistently collected data that may be particularly useful for nutrient criteria analysis.  Two
programs, the Hydrologic Benchmark Network (HBN) and the National Stream Quality Accounting
Network (NASQAN) include routine monitoring of rivers and streams during the past 30 years. The
HBN consisted of 63 relatively small,  minimally disturbed watersheds. HBN data were collected to
investigate naturally-induced changes  in streamflow and water quality and the effects of airborne
substances on water quality. The NASQAN program consists of 618 larger, more culturally influenced
watersheds.  NASQAN data provides information for tracking water-quality conditions in major U.S.
rivers and streams. The watersheds in both networks include a diverse set of climatic, physiographic,
and cultural characteristics. Data from the networks have been used to describe geographic variations in
water-quality concentrations, quantify water-quality trends, estimate rates of chemical flux from
watersheds, and investigate relations of water quality to the natural environment and anthropogenic
contaminant sources.  Since 1995, the NASQAN Program has focused on monitoring the water  quality of
four of the Nation's largest river systems—the Mississippi (including the Missouri and Ohio), the
Columbia, the Colorado, and the Rio Grande.  NASQAN currently operates a network of 40 stations in
which the concentration of a broad range  of chemicals—including pesticides and trace elements—and
stream discharge are measured.

Alexander and others (1996) assembled much of the historical water-quality and streamflow data
collected by the NASQAN and HBN on two CD-ROMs, including supporting documentation and quality
assurance information (see Internet URL http://wwwrvares.er.usgs.gov/wqn96/). These data are
collectively referred to as Water-Quality Networks (WQN).  The CD-ROMs are designed to allow users
to efficiently browse text files and retrieve data for subsequent use in user-supplied software including

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July 2000	Chapter 5.  Building a Database of Nutrient- and Algae-Related Water Quality Information

spreadsheet, statistical analysis, or geographic information systems. The data may be extracted from one
of the CD-ROMs (the "DOS disc") using the supplied DOS-based software, and output in a variety of
formats. This software allows the user to search, retrieve, and output data according to user-specified
requirements. Alternatively, the ASCII form of the WQN data may be accessed on a second CD-ROM
(the "ASCII disc") from user-supplied software including a Web browser, spreadsheet, or word

A comprehensive review of sources, concentrations, and loads of nutrients in the Mississippi River Basin
was completed by USGS under the Committee of Environmental Natural Resources. The review focused
on analyzing issues related to the Gulf of Mexico hypoxia.  Much of Topic 3, Flux and sources of
nutrients in the Mississippi-Atchafalaya River Basin, includes data and analysis that could be useful for
the  development of nutrient criteria in large river systems, such as the Mississippi River. Results of this
effort, which was led by the National Oceanic and Atmospheric Administration, have been published and
can also be found at the Internet site http://www.nos.noaa.gov/products/pubs_hypox.html.

The USGS National Water-Quality Assessment (NAWQA) Program is building a third national database
of stream quality information from data collected and analyzed for more than 50 river basins and aquifer
systems, called Study Units, across the Nation. NAWQA studies are based on a complex sampling
design that targets specific land uses and hydrologic conditions in addition to assessing the most
important  aquifers and large streams and rivers in each area studied. Gilliom and others (1995) describe
the  NAWQA sampling design in detail. A comprehensive data screening, computer retrieval, and review
of existing data on nutrients in streams was completed for each of the first 20 Study Units (Mueller et al.
1995). A major component of the sampling design for streams is to target specific watersheds influenced
primarily by a single dominant land use (agricultural or urban) that is important in a particular area of the
United States.  Some of the watersheds were selected as undeveloped areas relative to the rest of the
Study Unit to use in comparative analysis of land-use effects on water quality.  Water-quality data
collection  during 1992-1996 include analyses of eight nutrient species from about 8,500 samples of
streams and rivers in the first 20 Study Units.  A data set used for national synthesis of water quality has
been compiled and can be viewed and downloaded via the Internet URL
http://wwwrvares.er.usgs.gov/nawqa/nutrient.html. Mueller and others (1997) describe quality control of
the  NAWQA stream data and Mueller (1998) provides a rigorous assessment of the quality of these data.

The Water, Energy,  and Biogeochemical Budgets (WEBB) program was developed by USGS to study
water, energy, and biogeochemical processes in a variety of climatic/regional scenarios.  Five
ecologically diverse watersheds, each with an established data history, were chosen. This program may
prove to be a rich data source for ecoregions in which the five watersheds are located. Many
publications on the WEBB project are available.  See the USGS website for more details

Agricultural Research Service (ARS)
ARS houses Natural Resources and Sustainable Agricultural Systems, which has seven national
programs to examine the effect of agriculture on the environment.  The program on Water Quality and

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July 2000	Chapter 5. Building a Database of Nutrient- and Algae-Related Water Quality Information

Management addresses the role of agriculture in nonpoint source pollution through research on
Agricultural Watershed Management and Landscape Features, Irrigation and Drainage Management
Systems, and Water Quality Protection and Management Systems. Research is conducted across the
country and several models and databases have been developed. Information on research and program
contacts is listed on the website (http://www.nps.ars.usda.gov/programs/nrsas.htm).

Forest Service
The Forest Service has designated research sites across the country, many of which are Long Term
Ecological Research (LTER) sites. Many of the data from these experiments  are available in the USFS
databases located on the website (http://www.fs.fed.us/research/).  Most of the data are forest-related, but
may be of use for determining land uses and questions on silviculture runoff.

National Science Foundation (NSF)
The National Science Foundation funds projects for the LTER Network.  The Network is a collaboration
of over 1,100 researchers investigating a wide range of ecological topics at 24 different sites nationwide.
The LTER research programs are not only an extremely rich data source, but also a source of data
available to anyone through the Network Information System  (NIS), the NSF data source for LTER sites.
Data sets from sites are highly comparable due to standardization of methods  and equipment. Data can
be accessed from the website http://www.lternet.edu/research/data/nis/.

U.S. Army Corps of Engineers (COE)
The U.S. Army Corps of Engineers is responsible for more than 750 reservoirs.  Many have  extensive
monitoring data that could contribute to the  development of nutrient criteria for tributaries to those
reservoirs.  The COE focuses more on water quantity issues than on water quality issues. As a result,
much of the river and stream system data collected by the COE does not include nutrient or algal
constituents. Nonetheless, the COE does have a large water sampling network and supports  USGS and
EPA monitoring efforts in many programs.  A list of the water quality programs that the COE actively
participates in was compiled in 1997.  This information can be found at the website:

U.S. Department of the Interior, Bureau of Reclamation (BuRec)
The Bureau of Reclamation manages many irrigation and water supply reservoirs in the West, some of
which may have operational data available.  These data focus  on water supply information and limited
water quality data.  However, real time flow data are collected for rivers supplying water to BuRec,
which may be useful for the flow component of criteria development. These data can be gathered on a
site-specific basis from the BuRec website:  www.usbr.gov. Extensive remote sensing data are available
from the website:  http://wais.rsgis.do.usbr.gov/html/rsgig_wq.html.

State/Tribal Monitoring Programs
Most  states monitor some subset of stream and river systems within their borders for algal and nutrient
variables. Data collected by State/Tribal water quality monitoring programs can be used for nutrient
criteria development.  These data should be  available from the agencies  responsible for monitoring.
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July 2000	Chapter 5.  Building a Database of Nutrient- and Algae-Related Water Quality Information

Volunteer Monitoring Programs
Many States have volunteer water quality monitoring programs. Some programs are state-sponsored,
while others are independent organizations such as Adopt-A-Stream. Citizens in many areas donate their
time, money, or experience to aid State, Tribal, and local governments in collecting water quality data.
Volunteers analyze water samples for DO (dissolved oxygen), nutrients, pH, temperature, and a host of
other water constituents; evaluate the health of stream habitats and aquatic biological communities; note
stream-side conditions and land uses that may affect water quality; catalogue and collect beach debris;
and restore degraded habitats.

State and local agencies may use volunteer data to screen for water quality problems, establish
trends in waters that would otherwise be unmonitored, and make planning decisions. Volunteers
benefit from learning more about their local water resources and identifying what conditions or
activities might contribute to pollution problems. As a result, volunteers frequently work with clubs,
environmental groups, and State/Tribal  or local governments to address problem areas.

The EPA supports volunteer monitoring and local involvement in protecting our water resources.  EPA
support takes many forms including: sponsoring national and regional conferences to encourage
information exchange among volunteer groups, government agencies, businesses, and educators;
publishing sampling methods manuals for volunteers; producing a nationwide directory of volunteer
programs; and providing technical assistance  (primarily on quality control and lab methods) and
Regional coordination through the ten EPA Regional offices. In addition, grants to States/Tribes that can
be used to support volunteer monitoring in lakes and for nonpoint source pollution control are managed
by the EPA Regions (http://www.epa.gov/OWOW/monitoring/volunteer/epavm.html).

The Adopt-A-Stream Foundation (AASF) is a non-profit organization that works to increase public
awareness and involvement in water quality issues, stream enhancement, and environmental education.
Their two main areas of focus are Environmental Education and Habitat Restoration. AASF seeks to
protect streams through volunteer work, encouraging school and community groups, sports clubs, civic
organization, and individuals to become "Streamkeepers." "Adoption" of a  stream requires that
volunteers provide long-term care of the stream and establish stream monitoring, restoration, and
community-wide environmental education activities. AASF provides education materials, classes, and
tools for monitoring. Data collected through the volunteer monitoring associated with Adopt-A-Stream
is usually  site-specific, focusing on a single stream. However, if volunteers have been properly trained,
the data collected may be useful in helping identify streams at risk for nutrient problems.  The AASF
website contains additional information on this organization and data they may be able to provide

American Heritage Rivers
The American Heritage Rivers Initiative is a program launched by President Clinton to help communities
restore their local waters and waterfront areas. Participation is voluntary and must be initiated by the
community.  To date, fourteen rivers have been designated on the basis of historical, economic, and
environmental considerations. One goal of the program is to develop additional information that can be
used by communities to improve any river system.  Through the American Heritage Rivers website
(http://www.epa.gov/OWOW/heritage/rivers.html), valuable information about our nation's rivers is

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July 2000	Chapter 5.  Building a Database of Nutrient- and Algae-Related Water Quality Information

easily available to everyone. Information organized geographically on flood events, population change,
road networks, condition of water resources, and partnerships already at work in the area is available.
Additionally, customized maps and environmental and educational assessment models will be made
available through this initiative.

Electric Utilities
Many electric utilities own reservoirs for hydroelectric power generation, and are required to monitor the
reservoirs' water quality.  The largest of these, the Tennessee Valley Authority (TVA), has extensive
chemical and biological monitoring data from most of its reservoirs from the early  1980s to the present.
Data collected in conjunction with hydroelectric reservoirs must be gathered from the facility owners or

Drinking Water Facilities
Many local drinking water facilities are supplied from river systems.  These facilities continuously
monitor some water quality parameters at the intake pipe. Nutrients  are infrequently monitored by most
of these facilities, but supplemental data, i.e., turbidity, pH, and flow are usually measured. These data
may not provide the necessary parameters for deriving criteria, but may be very useful in combination
with State/Tribal water quality monitoring data to develop criteria. Data from these facilities should be
accessed locally for the waterbody of concern.

Academic and  Literature Sources
Many research studies are conducted by academic institutions that may provide data useful for
developing nutrient criteria.  Much of the research conducted by the  academic community concentrates
on unimpaired or minimally impaired systems.  While data collected from these sources may not be
directly representative of the population of stream systems within an ecoregion, they could be  useful for
identifying reference conditions.  Academic research also tends to be site-specific and  span a limited
number of years, although data for some systems may span 20 years  or more. Academic research data
should be available from researchers and the scientific literature.


The value of older  historical data sets is a recurrent problem because data quality is often unknown.
Knowledge of data quality is also problematic for long-term data repositories such  as STORET and long-
term State databases, where objectives, methods, and investigators may have changed many times over
the years.  The most reliable data tend to be those collected by a single agency, using the same protocol,
for a limited number of years. Supporting documentation should be examined to determine the
consistency of sampling and analysis protocols. Investigators must determine the acceptability of data
contained in large,  heterogeneous data repositories.  Considerations and requirements for acceptance of
these data are described below.

STORET and USGS data are geo-referenced with latitude, longitude, and Reach File 3 (RF3) codes.
Geo-reference data can be used to select specific locations, or specific USGS  Hydrologic Units. In
addition, STORET often contains a site description.  Knowledge of the rationale and methods  of site
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selection from the original investigators may supply valuable information. Metadata of this type, when
known, is frequently stored within large long-term databases.

Variables and Analytical Methods
Thousands of variables are recorded in database records. Each separate analytical method yields a
unique variable.  For example, five ways of measuring TP results in five unique variables. We do not
recommend mixing analytical methods in data analyses because methods differ in accuracy, precision,
and detection limits. Data analyses should concentrate on a single analytical method for each parameter
of interest.  Selection of a particular "best" method may result in too few observations, in which case it
may be more fruitful to select the most frequently used analytical method in the database.  Data may
have been recorded using analytical methods under separate synonymous names, or analytical methods
incorrectly entered when data were first added to the database. Review of recorded data and analytical
methods recorded by knowledgeable personnel is necessary to correct these problems.

Laboratory Quality Control (QC)
Laboratory QC data (blanks, spikes, replicates, known standards, etc.) are infrequently reported in larger
data repositories. Records of general laboratory quality control protocols and specific quality control
procedures associated with specific datasets are valuable in evaluating data quality. However, premature
elimination of lower quality data can be counterproductive, because the increase in variance caused by
analytical laboratory error may be negligible compared to natural variability or sampling error, especially
for nutrients and related water quality parameters.  However,  data of uncertain and undocumented
quality should not be accepted.

Data Collecting Agencies
Selecting data from particular agencies with known, consistent sampling and analytical methods and
known quality will reduce variability due to unknown quality problems. Requesting data review for
quality assurance from the collecting agency will reduce uncertainty about data quality.

Time Period
Long-term records are critically important for establishing trends. Determining if trends exist in the time
series database is also important for characterizing reference conditions for nutrient criteria. Length of
time series data needed for analyzing nutrient data trends is discussed in Chapter 4.

Index Period
An index period for estimating average concentrations can be established if nutrient and water quality
variables were measured through seasonal cycles. The index  period may be the entire year or the
summer growing season. The best index period is determined by considering stream characteristics for
the region,  the quality and quantity of data available, and estimates of temporal variability (if available).
Additional  information and considerations for establishing an index period are discussed in Chapter 4.

Data may have been collected for specific purposes. Data collected for toxicity analyses, effluent limit
determinations, or other pollution problems may not be useful for developing nutrient criteria. Further,
data collected for specific purposes may not be representative of the region or stream classes of interest.
The investigator must determine if stream systems or a subset of the stream systems in the database are

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July 2000	Chapter 5. Building a Database of Nutrient- and Algae-Related Water Quality Information

representative of the population of stream systems to be characterized. If a sufficient sample of
representative systems cannot be found, then a new survey will be necessary (see Chapter 4).

Gather New Data
New data should be gathered following the sampling design protocols discussed in Chapter 4. New data
collection activities for developing nutrient criteria  should focus on filling in gaps the database and
collecting regional monitoring data. Data gathered  under new monitoring programs should be imported
into databases or spreadsheets and merged with existing data for criteria development.

Data Reduction
Data reduction requires a clear idea of the analysis that will be performed and a clear definition of the
sample unit for the analysis.  For example, a sample unit might be defined as "a watershed during July-
August". For each variable measured, a mean value would then be estimated for each watershed in each
July-August index period on record. Analyses are then done with the observations (estimated means) for
each sample unit, not with the raw data.  Steps in reducing the data include:

•    Selecting the long-term time period for analysis;
•    Selecting an index period;
•    Selecting relevant chemical species;
•    Identifying the quality of analytical methods;
•    Identifying the quality of the data recorded; and
•    Estimating values for analysis (mean, median, minimum, maximum) based on the reduction


The validity and usefulness of data depend on the care with which they were collected,  analyzed and
documented. The EPA provides guidance on data quality assurance  (QA) and quality control (USEPA
1998b) to assure the quality of data. Factors that should be addressed in a QA/QC plan are elaborated
below. The  QA/QC plan should state specific goals for each factor and should describe the methods and
protocols used to achieve the goals. The five factors discussed below are: representativeness,
completeness, comparability, accuracy and precision.

Sampling program design (when,  where, how you sample) should produce samples that are
representative or typical  of the environment being described.  Sampling designs for developing nutrient
criteria are addressed in Chapter 4.

Data sets are often incomplete because of spilled samples, faulty equipment, and/or lost field notebooks.
A QA/QC plan should describe how complete the data set must be in order to answer the questions posed
(with a statistical test of given power and confidence) and the precautions being taken to ensure that
completeness. Data collection procedures should document the extent to which these conditions have
been met.  Incomplete data sets may not invalidate the collected data, but may reduce the rigor of
statistical analyses. Therefore, precautions should be taken to ensure data completeness. Precautions to

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July 2000	Chapter 5.  Building a Database of Nutrient- and Algae-Related Water Quality Information

ensure completeness may include collecting extra samples, having back-up equipment in the field,
installing alarms on freezers, copying field notebooks after each trip, and/or maintaining duplicate sets of
data in two locations.

In order to compare data collected under different sampling programs or by different agencies, sampling
protocols and analytical methods must demonstrate comparable data.  The most efficient way to produce
comparable data is to use sampling designs and analytical methods that are widely used and accepted.

To assess the accuracy of field instruments and analytical equipment, a standard (a sample with a known
value) must be analyzed and the measurement error or bias determined. Internal standards should
periodically be checked with external standards provided by acknowledged sources. At Federal, State,
Tribal, and local government levels, the National Institute of Standards and Technology (NIST) provides
advisory and research services to all agencies by developing, producing, and distributing standard
reference materials. For calibration sevices and standards see:

Standards and methods of calibration are typically included with turbidity meters, pH meters DO  meters,
and DO testing kits. The USGS, the EPA  and some private companies provide reference standards or
QC samples for nutrients. Reference  standards for chlorophyll are also available from the EPA and some
private companies, although chlorophyll standards are time  and temperature sensitive because they
degrade over time.

Natural variability rather than imprecision in the method used, is usually the greatest source of error in
the constituent measured. The variability in field measurements and analytical methods should be
demonstrated and documented to identify the source of variability when possible.  EPA QA/QC guidance
provides an explanation and protocols for  measuring sampling variability (USEPA 1998b).  Methods for
creating a chlorophyll standard to determine if the spectrophotometer is measuring chlorophyll
consistently from  one year to the next or from the beginning to the end of an analytical run are described
in Wetzel and Likens (1991).  In addition, a large number of replicates for each sample time and site
must be collected  because the largest  source of variation is likely to be natural (i.e., in the samples).
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 Chapter  6.
 Analyze  Data
Analyze Data

Data analysis is critical to nutrient criteria development. Proper analysis and interpretation of data
determines the scientific defensibility and effectiveness of the criteria.  Therefore, it is important to re-
evaluate short and long-term goals for stream systems within the ecoregion of concern. These goals
should be addressed when analyzing and interpreting nutrient and algal data. Specific objectives to be
accomplished through use of nutrient criteria should be identified and revisited regularly to ensure that
goals are being met. The purpose of this chapter is to explore methods for analyzing data that can be used
to develop nutrient criteria.  Included are techniques that link relationships between nutrient loading and
algal biomass, statistical analyses to evaluate compiled data, and a discussion of computer simulation

The difficulty associated with understanding predictive relationships between nutrient loading and algal
biomass is perhaps the biggest challenge to establishing meaningful nutrient criteria. Several relatively
simple methods of making this link for a variety of stream systems are discussed in this chapter. This
chapter also presents more in-depth methods to use when simpler techniques prove inadequate.

Macrophytes depend primarily on sediments for nutrient uptake, and are relatively unaffected by nutrient
water column concentrations. However, attempts to relate macrophyte growth or biomass with sediment
nutrient content have been largely unsuccessful (Chambers et al. 1999). Links between macrophytes and
nutrient enrichment are more indirect than with algae, and are therefore not considered here.  A review of
macrophytes and the current state of the science can be found in Chambers et al. (1999).

Statistical analyses are used to interpret monitoring data for criteria development.  Statistical methods are
data-driven, and range from very simple descriptive statistics to more complex statistical analyses. The
type of statistical analysis required for criteria development will be determined by the source, quality, and
quantity of data being analyzed. Concerns to be aware of during statistical analyses are discussed in this
chapter. Specific statistical tests that may be useful in criteria development are described in Appendix C.
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July 2000	Chapter 6. Analyze Data

Models are abstractions designed to represent something real. In this sense, models can be anything from
a representation of the human form in plaster, or a statistical equation expressing assumed relationships
between parameters of interest. This chapter discusses modeling as mathematical abstractions for the
purposes of analyzing data to derive nutrient criteria.  Mathematical models can be categorized as
process-based or empirical, and are used for different purposes.  This guidance focuses on empirical
models that serve to illuminate the relationship between the behavior of the system and measurements of
one or many attributes of the system. Empirical models identify patterns but do not explain them. In
contrast, process-based models are explanatory, and are built of equations that contain directly definable,
observable parameters. The rules used for process-based models invoke levels of organization other than
the components being modeled (Wiegert 1993).

Empirical  models can be simple, statistical models or more complex simulation models. A linear
regression of chlorophyll and P (phosphorus) data from a population of streams is a simple empirical
model, in that it elucidates the relationship between chlorophyll and P in a single equation represented by
a line.  A more complex empirical model is the computer simulation model CE-QUAL-RIV1, which is
comprised of a set of equations that predicts a constituent concentration over time. Prediction by both
linear regression and  computer simulation are based on empirical observations of a stream or population
of streams. The linear regression described above is an example of a static model; static models do not
represent changes overtime.  Dynamic models, such as CE-QUAL-RIV1, represent changes in system
constituents overtime (Wiegert 1993).


When evaluating the relationships among nutrients and algal response within stream systems, it is
important to first understand which nutrient is limiting. Once the limiting nutrient is defined, critical
nutrient concentrations can be specified and nutrient and algal biomass relationships can be  examined to
identify potential criteria to avoid nuisance algal levels. This section will discuss defining the limiting
nutrient, establishing  predictive nutrient-algal relationships, analysis methods for establishing nutrient-
algal relationships, analysis of algal species composition for system response to nutrients, characterizing
biotic integrity and response to nutrients, developing a multimetric index of trophic status, assessing
nutrient-algal relationships using experimental procedures, and a few other issues to keep in mind while
analyzing data.


Defining the limiting nutrient is the first step in identifying nutrient-algal relationships. Nuisance levels
of algal biomass are common in areas with strong nutrient enrichment, ample light, and stable flow
regime. Experimental data have demonstrated that given optimum light, non-scouring flow, and modest
to low grazing, enrichment of an oligotrophic stream will usually increase algal biomass and even
secondary production (Perrin et al. 1987; Slaney and Ward 1993; Smith et al. 1999). Identification of the
limiting nutrient is the first step in controlling nutrient enrichment and algal growth (Smith  1998; Smith et
al. 1999).  Criteria will be set for both TN and TP, but it is often more cost-effective to reduce the loading
of one nutrient (N or P) to achieve reduction of nuisance algal growths.
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Nitrogen frequently limits algal growth in streams and some have argued that this might be more common
in streams than it is in lakes (Grimm and Fisher 1986; Hill and Knight 1988; Lohman et al. 1991;
Chessman et al. 1992; Biggs 1995; Smith et al. 1999). However, there is evidence that P still often limits
stream algae (Dodds et al. 1998; Welch et al. 1998; Smith et al. 1999). If nonpoint sources of nutrients
predominate (assuming relatively high background levels of N), then N control may be a more important
issue than control of P. However, if N limits growth in a stream due to point source discharges such as
wastewater with low N:P, then the logical, cost-effective measure to control nuisance biomass is to reduce
P input, because N:P should then increase and cause P limitation (see Section 3.3 Secondary Response
Variables). If N and P are co-limiting, increasing the concentration of one nutrient will result in the other
nutrient becoming limiting (e.g., an increase in N concentrations will result in P becoming limiting). The
most prudent approach to controlling nutrient enrichment, regardless of the limiting nutrient, is to set
criteria for maxima of N  and P, and try to limit inputs of both.

Nitrogen usually becomes more limiting as enrichment increases because (1) wastewater N:P ratios are
low, (2) N is increasingly lost through denitrification; (3) P is more easily sorbed to sediment particles
than N and, thus, tends to be deposited in the sediment (in a waterbody with enough residence time to
allow sedimentation) more effectively than does N (Welch  1992); and (4) P is released from high P-
yielding bedrock. However, N lost through anaerobic denitrification may be limited by streamflow
aeration, although denitrification rates may still be relatively high if the subsurface (hyporheic and
parafluvial) components  of the stream ecosystem are considered (see Holmes et al. 1996). Furthermore, P
dissolved from bedrock or soil, whether complexed or not, is apt to remain in the water until it reaches a
waterbody with enough residence time to allow sedimentation, therefore loss of nutrients via
sedimentation is not usually important in most  streams.

Although N may be a relatively more important controlling factor for growth in streams than lakes, there
is evidence that P can limit stream algae.  For instance, ratios of soluble N:P averaged 90:1 (by weight) in
seven western Washington streams draining both forested and urbanized watersheds (Welch et al. 1998).
Soluble N:TP ratios averaged 13:1 in three other western Washington streams (Welch et al.  in press).
Even more convincing evidence for a greater prevalence for P limitation in streams comes from the large
data set discussed later in this chapter (Dodds et al. 1998).  These data show that: 1) TN:TP ratios are
nearly all >10:1, and 2) TN:TP ratios declined as enrichment increased from 24:1 (10% of data; TN = 316
and TP = 13 |ig/L) to 20:1 (50% of data; TN =  1000 and TP = 50 |ig/L) to 12.6:1 (90% of data; TN =
2512 and TP = 100 |lg/L).  The second point indicates that TN:TP in streams behaves similarly to that in
lakes as enrichment increases, i.e., as enrichment increases, the ratio of water column TN:TP declines.
An important cause for this may be the high concentration of P in wastewater (N:P = 3:1; Welch 1992)
and in the runoff from applied animal  manure (N:P < 3:1; Daniel et al. 1997). As an in-stream example,
DIN to SRP ratios in seven New Zealand streams receiving wastewater averaged 57:1 upstream and  13:1
downstream from effluent inputs (Welch et al.  1992).

Many experimental procedures are used to determine which nutrient (N, P, or carbon) limits algal growth.
Algal growth potential (AGP)  bioassays are very useful  for determining the limiting nutrient and
revealing the presence of chemical inhibitors (USEPA 1971). Yet, results from such assays usually agree
with what would have been predicted from N:P ratios in the water or, especially N:P in biomass. While
limiting nutrient-potential biomass relationships from AGP bottle tests are useful in projecting maximum
potential biomass in standing or slow-moving water bodies, they are not as useful in fast-flowing, and/or

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July 2000	Chapter 6. Analyze Data

gravel or cobble bed environments. Also, the AGP bioassay utilizes a single species which may not be
representative of the natural species assemblage response.

Limitation may be detected by other means, such as alkaline-phosphatase activity, to determine if N is
actually limiting in spite of a high N:P ratio.  Alkaline phosphatase is an enzyme excreted by some algal
species in response to P limitation. This enzyme hydrolyzes phosphate ester bonds, releasing
orthophosphate (PO4) from organic phophorus compounds (Steinman and Mulholland 1996). Therefore,
the concentration of alkaline phosphatase in the water column can be used to assess the degree of P
limitation. Alkaline phosphatase activity, monitored over time in a waterbody, can be used to assess the
influence of P loads on the growth limitation of algae (Smith and Kalff 1981).

Periphyton biomass accrual experiments using nutrient-diffusing substrata (Pringle and Triska 1996) are
useful for determining the limiting nutrient for a mixed species assemblage in running water and include
the important factors of velocity-enhanced, nutrient uptake as well as constraints imposed by mat
thickness that are nonexistent with bottle tests (Grimm and Fisher 1986b; Lohman et al. 1991; Pringle and
Triska 1996). However, the existing ambient nutrient concentrations produced from the nutrient diffusing
substrata and available for algal uptake are largely unknown with such tests.

Another experimental technique to determine ambient nutrient-maximum periphyton biomass potential in
running water is with constructed channels, either with controlled light and temperature in the laboratory
(Horner et al. 1983) or with natural light and temperature outdoors, along side natural streams (Stockner
and Shortreed 1976; Bothwell 1985,  1989; Pringle and Triska 1996). Pringle and Triska (1996) describe
methodologies for both nutrient diffusing substrata and in-stream channels.

Correlations between algal biomass and TN and TP (Dodds et al. 1997) indicate that N explains more of
the variance than does P, although P may frequently be the limiting nutrient in stream systems. However,
these  results may be biased by the stream data used in correlation analyses.  That is, the systems where
nuisance algal biomass has been measured may be primarily N limited, although this may not be a
reflection of a tendency for N limitation in all stream  systems generally. In addition, sediment-bound
particulate P may  remain suspended in streams, confounding the relationship between P and algal
biomass. Finally, the nutrient that limits growth in the short term may not always be the most cost-
effective nutrient to control.  Therefore, careful evaluation of nutrient limitation should be undertaken
prior to criteria development and restoration efforts.


Once  the limiting  nutrient has been identified, the data need to be analyzed to characterize nutrient-algal
relationships and patterns that clarify those relationships.  Data analyses can provide mathematical
approximations of the relationships that will allow prediction of algal biomass as a function of nutrient
concentration. Predictive relationships between nutrients and periphyton (or phytoplankton) biomass are
required to identify the critical or threshold concentrations that produce a nuisance algal biomass.

Relationships between TP and/or TN and periphytic biomass in streams have relatively low r2 values on
the order of 0.4-0.6 (Lohman et al. 1992;  Dodds et al. 1997).  Therefore, the following considerations
need  to be taken into account when establishing predictive nutrient-algal relationships. Critical and
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highly variable factors other than nutrients - shading, type of attachment surfaces, scour, water level
fluctuations that result in dessication, grazing intensity - have major effects on algal biomass levels and
may provide an explanation for the weakness of the predictive relationships in streams.  In addition, TP in
the stream water column contains more sediment-and detrital-bound P than observed in lakes, and
sediment-bound P is not necessarily available for algal uptake. The high detritus level in streams is
indicated by TP versus chl a per volume (i.e., seston) relationships in streams where chl a/TP ratios
ranged from 0.08 to 0.22 (Van Nieuwenhuyse and Jones 1996).  These ratios suggest that the high detritus
levels in streams are indicative of high proportions of water-column P bound to sediment or heterotrophic
components of detrital material. Finally, inorganic nutrient species (PO4 and NO3) are frequently more
available for uptake, and may need to be considered  in instances where small scale effects  from specific
point and nonpoint sources are an important issue.

There are few existing relationships that predict algal biomass as a function of TN and TP.  Dodds et al.
(1997) compiled and analyzed the largest and broadest dataset (approximately 200 sites) in the literature
that predicts relationships for benthic algal biomass.  The best general approach for predicting mean
suspended chlorophyll was developed using data from 292 temperate streams (Van Nieuwenhuyse and
Jones 1996). The equations derived from these analyses are presented for use with periphyton-dominated
and plankton-dominated systems, respectively.

The equations suggested by Dodds et al. (1997) are recommended to predict benthic algal biomass if more
local, ecoregion-specific relationships are unavailable:

              log (mean chl a) = 1.091 + log (TP) * 0.2786 (r2 = 0.089)

              log (mean chl a) = 0.01173 + log  (TN) * 0.5949 (r2 =0.35)

              log (maximum chl a) = 1.4995 + log(TP) * 0.28651 (r2 = 0.071)

              log (maximum chl a) = 0.47022 + log (TN) * 0.60252  (r2  = 0.28)

where seasonal mean and maximum benthic chlorophyll are in mg/m2 and TN and TP are in |lg/L. The
above equations are fairly simple and, although they have low r2 values, are best suited for use with data
having high TN and TP concentrations. Note that the graphical illustration of the relationships from
which these equations were derived, shows a broad distribution of the data (Figure 7). This distribution
suggests that periphytic algae tend to respond in a similar fashion to nutrients, regardless of location.

A second set of equations, also derived by Dodds et al. (1997), combines TN and TP measures resulting in
higher r2 values, but may be inaccurate in some high nutrient situations.

      log (mean chl) = -3.233 + 2.826(log TN) - 0.431(log TN)2 + 0.255(log TP)  (r2 = 0.43)

      log (max chl) = -2.702 + 2.786(log TN) - 0.433(log TN)2 + 0.306(log TP) (r2 = 0.35).
                                             PAGE 77

July 2000
Chanter 6. Analyze Data
*! io2
•5 1
5 10°
| 102
f 101
5 10°

°R WA!^O^^^^S^MO c
AK l^^^fyM °U
WA MM$^° ^°
102 103
Total N (\ig
• wAMOjWoy™^
^o EU NZ ^c
D° 101 102
Total P
Q.UV" Wt&^ii mi
w&lro m^WA ou :

r2 = 0.35 ':
L )

r2 = 0.089

103 104

(M L"1)
Figure 7. Relationships of log-transformed mean chlorophyll a as a function of TN and TP.
Data points are represented by abbreviations identifying the State or country of origin: AK- Alaska, ID-
Idaho, Ml- Michigan, MO-Montana, NH-New Hampshire, NC-North Carolina, OR-Oregon, PA-
Pennsylvania, WA-Washington, QU-Quebec, EU-Europe, NZ-New Zealand.
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July 2000	Chapter 6. Analyze Data

It should be kept in mind that there is considerable variance in these relationships, and if extensive data
for a single system are available, tighter predictive relationships may be constructed. More local,
ecoregion-specific data sets should produce tighter relationships.

The equation suggested by Van Nieuwenhuyse and Jones (1996) is recommended to predict mean
suspended chlorophyll if more local, ecoregion-specific relationships are unavailable:

               log Chi = -1.65 + 1.99(log TP) - 0.28(log TP)2 (?= 0.67)

Where chl = summer mean chlorophyll and TP are expressed in mg/m3.

Yields of algal biomass from given nutrient concentrations derived from regression models differ from
the yield observed in controlled channel experiments. This discrepancy creates a problem when
attempting to predict nutrient-periphyton chl a relationships in streams. For example, to produce a mean
chl a of 100 mg/m2 would require approximately 100-200 |lg/L TP according to regression models of
Lohman et al. (1992) and Dodds et al. (1997). Brezonik et al.  1999 used the equation from Van
Nieuwenhuyse and Jones (1996) that includes the catchment size (basin area) to predict likely
improvements in concentrations of growing season mean chl a that would occur with corresponding
reductions in growing season mean TP.

       log Chl = -1.92 + 1.96(log TP) - 0.30(log TP)2 + 0.12(log Ac)  (r2 = 0.73, n = 292)

Where Ac = stream catchment area.

They predicted that a reduction of stream water TP from 125 to 100 (ig/L would result in a chl a reduction
of 18%, and a TP reduction from 50 to 25 (ig/L would result in a chlorophyll a reduction of 52%.
However, in-channel experiments have produced 600 to 1000 mg/m2 chl a in a mixed algal assemblage
using in-channel SRJ3 and TP concentrations of 10-15 and 20-50 |ig/L , respectively, a yield of-10-50 chl
a/TP (Horner et al. 1983, 1990; Walton et al. 1995; unpublished data). This seeming discrepancy may
result from the nutrient demand by heterotrophic organisms in the detritus of natural streams. Residence
time was short (16 minutes or less) in the above cited channel experiments, nutrient input was controlled
to low  levels, and velocity  was usually constant with little sloughing during the growth period (Horner et
al. 1990).  Such characteristics would generate little detritus and low ambient TP and, hence, higher in-
channel chl a/TP ratios than in natural streams sampled throughout the year.

The discrepancy in algal biomass yield between regression models and channel experiments may partly
justify  the use of regression models generated from large field data sets in recommending nutrient criteria.
Channel data are not significantly confounded by the  sloughed biomass that produces detrital material in
natural streams and is unavailable for uptake and algal biomass increase.  Although the correlation
between chl a and nutrients in natural streams may be weakened (from the cause-effect standpoint) due to
interference with detritus, the relations may nonetheless be useful for extrapolation and management
because nutrient criteria must be applied where high detritus levels do exist.

Soluble nutrient concentrations determine periphytic growth rate and biomass; uptake is clearly saturated
at very low (<10 |ig/L SRP) concentrations (Bothwell 1985, 1989; Walton et al. 1995) and is independent

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July 2000	Chapter 6. Analyze Data

of TP concentrations. However, soluble nutrients are usually lowest when biomass is highest, due to
depletion by algal uptake, similar to the situation in lakes. Therefore, estimates of inflow nutrient
concentrations, in-stream concentrations during non-growth periods or at least annual mean
concentrations are required to use soluble nutrients to set critical levels and relate soluble nutrients to
algal biomass. These data/relationships are not currently available, but should be pursued in order to
develop more direct, stronger nutrient-biomass relationships for streams.


The following analysis methods are suggested to develop predictive nutrient-biomass relationships in
stream systems. These methods were primarily developed for gravel/cobble bed streams, but should
function for other stream types with modifications. Intermittent and effluent-dominated streams will
benefit from supplemental analysis methods specific to those stream types as the seasonal sampling
discussed here may not be possible (see Appendix A). Samples for soluble and/or total N and P should be
collected for at least one, preferably two or more years at sites with high as well as low summer biomass.
Ideally, samples for periphyton biomass should be collected weekly or biweekly during summer low flow,
beginning immediately after spring runoff or any subsequent high water, scouring event.  Monthly data
collection may be sufficient to define algal-nutrient relationships if supporting long-term trend data is
available.  Data can be analyzed using one or all of the following methods to establish predictive nutrient-
biomass relationships in stream systems.

1.     Relate the total concentration of a limiting nutrient (e.g., TN, TP) with the mean and maximum
      algal biomass as chl a; both data sets should be collected at the same time during summer (or
      season of maximum algal biomass). Such data were used by Dodds et al. (1997) to develop the
      relationship between nutrients and algal biomass discussed in the previous section. Relate the
      low/non-growing period mean concentration of limiting nutrient to summer maximum biomass as
      chl a.

2.     It may also be possible to relate the pre-maximum growth period (usually spring, immediately
      following runoff) mean soluble limiting nutrient concentration to maximum algal biomass.
      Inorganic soluble N (ammonium and nitrate) should be used as the limiting nutrient if the N:P
      (soluble) is <10 (by weight) and SRP should be used if N:P >10. The threshold of 10 is chosen to
      simplify the assessment protocol, although N and P are known to be co-limiting over a rather wide
      range in N:P ratio (7-15) (Smith 1982; Welch 1992).  Data should be stratified into discrete ranges
      of N:P ratios, if this approach does not produce sound relationships, in a manner similar to the
      methods used by Prairie et al. (1989).

      This analysis selects data that would most closely represent an "inflow concentration" of dissolved
      inorganic limiting nutrient because it utilizes the  available form of the designated limiting nutrient
      during a period when algal nutrient uptake is minimal. The pre-growth period nutrient
      concentration should be  analogous to the inflow limiting nutrient concentration (including
      groundwater) entering a continuous algal culture system, whether planktonic or periphytic, that
      yields a maximum steady-state biomass.  Analysis of N and P loading could be used for this
      assessment in stream systems, though it has not been tested.  However, because rivers,  streams,
      lakes, and estuaries form a linked system in the context of a watershed, load analysis becomes
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July 2000	Chapter 6. Analyze Data

       crucial at watershed scales. Relationships can be sought for TP and TN using this method and in
       method 3 below, which may be more appropriate for criteria throughout an ecoregion, although
       less specific for given streams.

3.     Relate annual mean soluble nutrient concentration to the 75th percentile mean algal biomass. This
       approach does not provide sound continuous culture rationale like inflow concentration-maximum
       biomass relationships, but annual mean values for nutrients were used in the cellular N and flood
       frequency versus chl a relationship discovered by Biggs (1995), as well as soluble N and P
       concentrations versus maximum chl a for different accrual times (Biggs 2000).  In instances where
       nutrient data are inadequate to provide distinct and reliable values used in method 2 above, an
       annual mean approach may offer a reasonable approximation of nutrient availability.

4.     Another possibility for developing strong predictive relationships is the use of cellular
       concentrations of limiting nutrient (same ratio criterion used in 2 above) determined during the
       summer growth period, related to maximum algal biomass.  This approach estimates the available
       nutrient directly from physiologically relevant data, as opposed to using the pre-growth soluble
       fractions in water to infer what is available for uptake.  The validity of this approach is supported
       by a multiple relationship among cellular N, chl a,  and flood frequency, in which cellular N
       content varied over a range of four-fold (Biggs 1995). A sound relationship between cellular
       nutrient content and periphytic algal biomass would, however, still require a link to the respective
       limiting  nutrient concentration in water for management purposes. That could be accomplished by
       developing a relationship between cellular nutrient and ambient nutrient concentrations (either
       soluble or total) using constant flow laboratory channel experiments.

As further evidence for the potential of this approach, Wong and Clark (1976) described a direct
relationship (^=0.80) between cellular P and ambient TP in six rubble-bed streams in Ontario,  such that;

                                       TPW = 0.05 Pt - 0.02

where Pt is tissue content, and TPW is ambient water column TP.  They determined further that
photosynthetic rate ofCladophora at optimum light availability, decreased below 1.6 mg P/g dry weight,
which was equivalent to 60 mg/L TP in the water. Nevertheless, this had no predictive value for
maximum biomass.  Development of a relation between cellular limiting nutrient and biomass, instead of
productivity, would be necessary to back- calculate to ambient nutrient content, either soluble nutrient as
in methods two or three above, or total nutrient as from method one and Wong and Clark (1976).


Differences in algal species composition among streams can identify important regional environmental
gradients that may affect algal-nutrient relationships. Algal species composition should be used in data
analysis to validate stream classification and enable development of indicators of nutrient conditions and
the likelihood of nuisance algal blooms. Different classes  of streams may require different nutrient
criteria, depending upon algal responses to nutrients in different stream classes.  For example, algal-
nutrient problems may be related to proliferation of filamentous green algae Cladophora or Spirogyra,
benthic or planktonic diatoms, dinoflagellates, or blue-green algae. Each of these problems may occur at
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July 2000	Chapter 6. Analyze Data

different nutrient concentrations, but will probably only occur in certain classes of streams during specific
seasonally-optimum conditions (Biggs et al. 1998b).

Cluster analysis is used to identify groups of streams with similar algal assemblages. TWINSPAN (Two
Way INdicator SPecies Analysis; Hill 1979) and UPGMA (Unweighted Pair Group  Method using
Arithmetic averages; Sneath and Sokal 1973) represent two examples of cluster analysis that are
commonly used and differ in how results are generated.  TWINSPAN employs a divisive approach in
which all algal assemblages are initially grouped in one cluster and then that cluster is divided into two
groups based on the greatest dissimilarities between the groups. Subsequently, each cluster is divided into
two more clusters so that one cluster becomes two, two becomes four, four becomes eight, and eight
becomes 16, etc. In contrast, UPGMA is an aggregational technique that begins with all algal
assemblages separated into single assemblage clusters and builds clusters by aggregation of the most
similar clusters.  So N clusters becomes N-l clusters, and N-l clusters becomes N-2 clusters, and so on.
At each step, one algal assemblage is grouped with another assemblage or group of assemblages. Results
of both techniques can be used together by identifying groups of assemblages (and associated streams)
that cluster the same in both analyses.  These groups can be designated as core clusters.  Assemblages that
are not grouped in the same clusters in both analyses can be associated with core clusters based on some
simple evaluation, such as percent similarity to assemblages in the core cluster.

Cluster analysis of algal assemblages can be used as one step in classifying streams  based on their
response to nutrients (e.g., Pan et al.  in press). Habitat classification is based on assemblages in reference
conditions, because human impacts may constrain species membership in assemblages and mask diversity
among stream classes and impacts that nutrients have on that diversity. In addition, algal assemblages in
different classes of streams may respond differently to nutrient addition (Biggs et al. 1998b). The number
of stream classes that should be used depends on many factors, but the number should be limited based on
practicality, utility in explaining algal responses to nutrient enrichment, and utility in explaining algal
responses to remediation. In addition,  statistical significance of clusters, based on discriminate analysis
for example, can also form the basis for determining the number of stream classes. Algal assemblage
clusters can be related to the physical classification (described in Chapter 2), to predict responses of
similar stream classes to further enrichment or remediation (Biggs et al. 1998b).

The form of species composition data used in classification  of stream algal assemblage, and other
analyses as well, has a substantial effect on resolution of patterns that are related to the phenomena with
which we are concerned. Algal species composition data based on species densities (cells/cm2), relative
abundance (% of assemblage), and presence/absence differ successively in sensitivity to diurnal and daily
changes in environmental conditions. Both theoretically and in practice, species composition data based
on species densities are more sensitive to small-scale spatial and temporal variability than are data based
on species relative abundances and presence/absence data (Stevenson unpublished data).  Most stream
classification analyses should be done with relative abundances because they integrate over space and
time and most results in the literature are presented in this form.

Ordination helps to visualize differences in species assemblages among classes of streams. When species
composition is combined with environmental data or algal autecological characteristics, the important
environmental factors affecting species composition in a region can be deduced.  These environmental
factors may be important for constraining algal response to nutrient concentration and may therefore be
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July 2000	Chapter 6. Analyze Data

important for identifying confounding factors in the relationship between algal assemblages and nutrient
conditions. Caution should be exercised in using ordination to develop attributes of algal assemblages for
use in establishing nutrient criteria.  Ordination scores for taxa and classifications will change as new data
are added and ordinations are recalculated. Therefore, ordinations should not be recalculated after a
standard classification system or assessment system has been established. Species scores based on the
original ordination should be used in subsequent classifications and assessments (Barbour et al. 1999).


Theory and empirical evidence indicate that algal species composition may be a more precise indicator of
nutrient status and the potential for nuisance algal problems than one-time sampling and assessment of
nutrient concentrations and algal biomass. Shifts in algal species composition may be more sensitive to
changes in nutrient concentrations and may therefore help define nutrient criteria.  Many monitoring
programs utilize multiple lines of evidence to increase the certainty of assessments. Algal species
composition,  as well as growth form and mat chemistry, can provide evidence of nutrient condition and a
greater certainty of assessing nutrient conditions. This topic has been the subject of many recent reviews
(McCormick  and Cairns 1994; Kelly et al. 1995; Whitton and Kelly 1995; Lowe and Pan 1996; Stevenson
1998; McCormick and Stevenson 1998; Wehr and Descy 1998; Kelly et al. 1998; Ibelings et al. 1998;
Stevenson and Pan 1999; Stevenson and Bahls 1999; Stoermer and Smol 1999; Stevenson in press).

Species composition and autecological characteristics of algae are commonly used to evaluate
environmental conditions, ranging from organic (sewage) contamination to pH and nutrient conditions
(Kolkwitz and Marsson 1908; Zelinka and Marvan 1961; Renberg and Hellberg 1982; Charles  and Smol
1988; Whitmore 1989; Kelly and Whitton 1995; Pan et al. 1996).  With diurnal and weekly variability in
environmental concentrations within streams due to metabolic and weather-related factors or periodic
releases of pollution from point sources, it is assumed that the biological assemblages that develop over
longer periods of time are adapted to the average conditions in those habitats and tolerant to the
environmental maxima and minima.  Thus, if environmental tolerances and sensitivities of organisms are
known, the physical, chemical, and potentially biological conditions for a habitat can be inferred if
environmental effects  differed among species.

Autecological characteristics, the environmental preferences for specific taxa, are frequently documented
in the literature, particularly for diatoms (see van Dam et al. [1994] or Stevenson and Bahls [1999] for a
literature list). Autecological characteristics have been compiled and summarized in several publications
(Lowe 1974;  Beaver 1981; Van Dam et al. 1994).  Accuracy of the autecological characterizations in
these compilations is limited to multi-category classification systems.  For example, a categorical
characterization of nutrient sensitivity might vary with the integers from 1-5, where 1 would be assigned
to species least sensitive to low nutrients and 5 would indicate taxa most sensitive to low nutrients (van
Dam et al. 1994).  Thus, high abundance in a habitat of taxa classified as 5 would indicate highly
eutrophic conditions.  In contrast, more accurate characterizations of algal taxa have been achieved
recently by using weighted averages of species relative abundances and a quantitative assessment of the
environmental conditions in which they are observed (e.g., ter Braak and van Dam 1989; Birks 1988).
The result is an accurate assessment of the specific environmental conditions in which a species will have
its highest relative abundance (environmental optima). The weighted average approach assumes that
species have optima along environmental gradients if each gradient (nutrients, pH, salinity, organic
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July 2000 _ Chapter 6. Analyze Data

contamination) includes a broad range of conditions that includes most of a species range. These
weighted average descriptions of species autecologies have been developed for optimal total phosphorus
concentrations in streams (Pan et al. 1996).

 A trophic status indicator (TSI) can be calculated by summing the products of species relative
(proportional) abundances (pi; ranging from 0-1) and their autecological characterization for trophic status
(0j) for all / species:
If all / species do not have autecological characteristics, normalize the index by adjusting description of
the community to only those taxa that have autecological characteristics:
Weighted average indices can be calculated easily with a spreadsheet.  The weighted average formula can
be used with categorical or weighted average autecological characterizations; see Kelly and Whitton
(1995) and Pan et al. (1996) respectively. When indices are used with the highly accurate environmental
optima determined by weighted average regression, they actually infer the phosphorus concentration or
nitrogen concentration in the stream (Pan et al.  1996). Comparisons of precision of inferring TP
concentrations with weighted average indicators and one-time measurement of TP concentration in a
stream show that diatom indices are more precise (Stevenson and Smol in press).

Kelly and Whitton (1995) make several adjustments to sample processing and index calculation that make
processing  easier while maintaining index performance and distinguishing between organic and inorganic
nutrients. They make sample processing easier by only counting 200 diatoms and a single set of diatom
taxa that are easy to identify and that are good indicators of nutrient condition (Kelly 1996).  Weights of
species can be added to this formula to decrease the importance of taxa that have a broad tolerance to
trophic status (see formula in Kelly and Whitton 1995), but they may not improve precision of the indices
(Pan et al. 1996).  Finally, autecological information is also available for assessing organic (sewage)
contamination in waters. This information can be used with a TSI to distinguish enrichment effects due to
inorganic and organic pollution Kelly and Whitton (1995).

Most autecological characteristics of diatom taxa have been described  from European populations.
Further testing will be important to determine how well autecological characterizations of taxa found in
Europe compare to those in North America. However, these autecological indices should be useful for
general classification of relative trophic status in streams when reference conditions and relations between
changes in  species composition and nutrient concentrations have not been established.  The relative
benefits of more accurately defining autecological characteristics with weighted averages versus coarse
scale categories have not been thoroughly evaluated. Investigations have shown that inferences of
environmental conditions based on indices using weighted average autecologies are more precise than
those using categorical autecologies (ter Braak and van Dam 1989; Agbeti 1992).  Tradeoffs may exist
between greater precision for indices that are calculated with weighted average autecologies when they
are used in  conditions similar to those where the autecologies were developed versus less error associated
with categorical autecologies when indices are used across broad diverse regions.  Details and references

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July 2000	Chapter 6. Analyze Data

to development of algal indices of environmental conditions can be found in recent reviews (Birks 1998;
Stoermer and Smol 1999, Stevenson and Pan 1999; Stevenson and Smol in press).


Multimetric indices are valuable for summarizing and communicating results of environmental
assessments and may be  developed  as an alternative to numeric criteria. Furthermore, preservation of the
biotic integrity of algal assemblages, as well as fish and macroinvertebrate assemblages, may be an
objective for establishing nutrient criteria. Multimetric indices for macroinvertebrates and fish are
common (e.g., Kerans and Karr 1994; Barbour et al. 1999), and multimetric indices with benthic algae
have recently been developed and tested on a relatively limited basis (Kentucky Division of Water 1993;
Hill et al. 2000). However, fish and macroinvertebrates do not directly respond to nutrients, and therefore
may not be as sensitive to changes in nutrient concentrations as algal assemblages.  It is recommended
that relations between biotic integrity of algal assemblages and nutrients be defined and then related to
biotic integrity of macroinvertebrate and fish assemblages in a stepwise, mechanistic fashion.  This
section provides an overview for developing a multimetric index that will indicate algal problems that are
associated with trophic status in streams.

The first step in developing a multimetric index of trophic status is to select a set of ecological attributes
that respond to human changes in nutrient concentrations  or loading in streams. Attributes that respond to
an increase in human disturbance are referred to as metrics.  Six to ten metrics  should be selected for the
index based on their sensitivity to human activities that increase  nutrient availability (loading and
concentrations), their precision, and their transferability among regions and habitat types.  Selected
metrics should also respond to the breadth of biological responses to nutrient conditions (see discussion of
metric properties in McCormick and Cairns 1994; Stevenson and Smol in press).

Many structural and functional attributes of algal assemblages can be used to characterize the biotic
integrity of algae (McCormick and Cairns 1994; Stevenson 1996; Kelly et al. 1998; Stevenson and Pan
1999). Biomass, species composition, species diversity, chemical composition, productivity, respiration,
and nutrient turnover rates (spiraling distance) are examples of these attributes. All of these attributes are
important and respond with different lag times to spatial and temporal variability in environmental
conditions. Most monitoring programs measure structural attributes because structural characteristics
vary less than functional characteristics on diurnal and daily time scales. For example, state monitoring
programs (e.g.,  KY, MT) rely on changes in species composition, rather than biomass and chemical
composition, to assess ecological conditions in streams because species composition is hypothesized to
vary less.  However, the  relationship between all algal attributes, if characterized for an appropriate time
and space, can be related to nutrient concentrations to determine the effect of nutrients on algal
assemblages in  streams.

Many algal metrics can be used to characterize the valued ecological attributes that we want to protect in a
habitat or the nuisance problems that may develop as a result of nutrient enrichment.  These are
"response" or "condition" metrics (Paulsen et al. 1991; Barbour et al. 1999) and they should be
distinguished from "stressor" or "causal" indicators, such  as nutrient concentrations (water chemistry or
periphyton chemistry) and biological indicators of nutrient concentrations. While both "response" and
"stressor" metrics could be used in a single multimetric index, we recommend that separate multimetric
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July 2000	Chapter 6. Analyze Data

indices be used for "response" and "stressor" assessment.  Distinguishing between "response" and
"stressor"  indices can be accomplished utilizing a risk assessment approach with separate hazard and
exposure assessments that are linked with response-stressor relationships (USEPA 1996; Stevenson 1998;
Barbour et al. 1999; Stevenson and Smol in press). A multimetric index that specifically characterizes
"responses" can be used to clarify goals of management (maintainance or restoration of valued ecosystem
attributes) and to measure whether goals have been attained with nutrient management strategies.
Measurements of nutrient concentrations and algal indicators of nutrients could be combined to develop a
multimetric "stressor" index specifically for nutrient conditions. Metrics of nutrient concentrations such as
water and mat chemistry (|ig P/mg AFDM, |ig N/mg AFDM) are described in Appendix C and are
relatively straight forward. Biological indicators of nutrient concentrations are described in the above
section, Characterizing Nutrient Status with Algal Species Composition.  The following paragraphs
discuss algal metrics that characterize valued ecological attributes and nuisances.

Algal metrics can be distinguished with respect to types of designated use that is being impaired.  Algal
biomass can be measured as percent cover by filamentous algae, turbidity, mg chl aim2, g AFDM/m2.
Determining when biomass becomes a nuisance will require relating biomass to designated uses, such as
support of aquatic life (biotic integrity), or potability. Effects of nutrients on algal biomass and effects of
algae on the biotic integrity of macro invertebrates and fish should be characterized to aid in developing
nutrient criteria that will protect designated uses related to aquatic life (e.g., Miltner and Rankin 1998).
Potability can be impaired by algae that cause taste and odor problems and whose growth may be
stimulated by nutrients.  Thus, relationships should be developed between nutrients and taste and odor
producing algae or nutrients and the frequency of taste and odor complaints to develop management plans
and criteria to support potability as a designated use.  Relative abundance or biomass of taste and odor
algae (Palmer 1962) may be good indicators of the potential for potability problems. Percent toxic algae
could provide indicators of potential for toxic algal blooms in streams at low flow in which wildlife and
livestock could be endangered, although little is known about the effects of toxic  algae in streams.

Biotic integrity of algal assemblages may be indicated by many quantitative attributes of algal
assemblages (Stevenson 1996; Stevenson and Pan 1999). Attributes of species composition  can be
characterized at different levels of resolution, e.g., actual biomass (biovolume/cm2), relative  biovolume
relative abundances, cell density, or presence/absence at each taxonomic level. Relative biovolume is
usually used to characterize changes in functional groups (as defined by physiognomy and taxonomic
division) of algae in assemblages because cell sizes vary so much among functional groups (e.g.,
filamentous cyanobacteria, colonial cyanobacteria, diatoms,  and large cells of filamentous green algae).
Relative abundances are usually used to characterize changes in species composition of specific groups of
taxa, such as diatoms. Many environmental programs only evaluate diatom assemblages for species level
indicators (e.g., Kentucky Division of Water 1993; Pan et al. 1996; Kelly et al. 1998).

Even though many taxonomic attributes of algal assemblages would be expected to change in response to
increasing nutrient concentrations, analyses should be focused to some extent on variables that have
intrinsic value. Thus, changes in relative biovolume from non-nuisance algae (e.g., diatoms) to
filamentous green algae with nutrient addition may be an indicator of loss in biotic integrity, because
habitat structure and food availability  for invertebrates (e.g., Holomuzki et al. 2000).  Loss of species may

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July 2000	Chapter 6. Analyze Data

be an issue:  such as some macroalgae that are relatively sensitive to nutrient enrichment and overgrowth
by diatoms (e.g., filamentous red algae or some nitrogen-fixing, blue-green algae such as Nostoc).

Another approach for characterizing biotic integrity of algal assemblages as a function of trophic status in
streams is to calculate the deviation in species composition or algal growth forms at assessed sites from
composition in the reference condition. Multivariate similarity or dissimilarity indices need to be
calculated for multivariate attributes such as taxonomic  composition (Stevenson 1984; Raschke  1993) as
defined by relative abundance of different algal growth forms or species, or species presence/absence.
One standard form of these indices is percent community similarity (PSC, Whittaker 1952):

                                       psc =EW

Here a1 is the percentage of the i* species in sample a, and b1 is the percentage of same i* species in
sample b. A  second common community similarity measurement is based on a distance measurement
(which is actually a dissimilarity measurement, rather than similarity measurement, because the  index
increases with greater dissimilarity, Stevenson 1984; Pielou 1984). Euclidean distance (ED) is a standard
distance dissimilarity index, where:


log-transformation of species relative abundances in these calculations can increase precision of metrics
by reducing variability in the most abundant taxa. Theoretically and empirically, we expect to find that
multivariate  attributes based on taxonomic composition more precisely and sensitively respond to nutrient
conditions than do univariate attributes of algal assemblages (see discussions in Stevenson and Smol
accepted). High precision and sensitivity argues for including  assessments of algal species composition
and its response to nutrient conditions in the process of developing nutrient criteria. The response of algal
species composition to increases in nutrient concentrations can be used as another line of evidence to
develop a rationale for specific nutrient criteria in specific classes of streams.

To develop the multimetric index, metrics must be selected and their values normalized to a standard
range such that they all increase with trophic status. Criteria for selecting metrics can be found in
McCormick  and Cairns (1994) or many other references. Basically, sensitive and precise metrics should
be selected for the multimetric index and selected metrics should represent a broad range of impacts and
perhaps, designated uses. Values can be normalized to a standard range using many techniques. For
example, if 10 metrics are used and the maximum value of the multimetric index is defined as 100, all ten
metrics should be normalized to the range of 10 so that the  sum of all metrics would range between 0 and
100. The multimetric index is calculated as the sum of all metrics measured in a stream. A high value of
this multimetric index of trophic status would indicate high impacts of nutrients in a stream and  should be
a robust (certain and transferable) and moderately sensitive indicator of nutrient impacts in a stream.  A 1-
3-5 scaling technique is commonly used with aquatic invertebrates (Barbour et al. 1999; Karr and Chu
1999) and could be used with a multimetric index of trophic status as well.

Arguments have been made for limiting membership of metrics in a mulitmetric index to only biological
metrics and only biological metrics from one assemblage of organisms (Karr and Chu 1999). We
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July 2000	Chapter 6. Analyze Data

generally concur with that recommendation. More detailed descriptions of this multimetric index
development can be found in Karr and Chu (1999), Barbour et al. (1999), and Hill et al. (2000)


Management of nutrients to ensure high stream quality is greatly strengthened by examining relationships
between the limiting nutrient and maximum algal biomass (i.e., potential) that will occur if/when other
factors are optimum. Relationships between ambient nutrient content and existing biomass may not
adequately predict maximum biomass potential for any single stream because other factors, such as light,
high-flow scouring, and grazing often limit biomass accrual in natural streams. Experimental procedures
are valuable for determining the maximum biomass potential of a system.  However, physical constraints
imposed in experimental setups are often unrealistic. Thus, the value of extrapolating results from
laboratory experiments to natural conditions is often uncertain. There are many more  experimental results
reported to determine which nutrient (N, P, or carbon) limits algal growth,  than to determine nutrient-
biomass relationships.  Experimental  procedures to determine the limiting nutrient/s for algal growth are
discussed earlier in this section (see Defining the Limiting Nutrient).

As indicated previously, biomass levels up to 1000 mg/m2 chl a were accrued on stones of in-stream
channels receiving as little as 10 mg/L SRP (Walton et al. 1995).  Although Cladophora has not been
grown in channels,  other filamentous  green algae (FGA) (Mougeotia, Stigeoclonium, Ulothrix) have
dominated in such experiments. In contrast, bottle tests with unattached Cladophora have shown that
growth/biomass is not saturated at such low SRP concentrations (Pitcairn and Hawkes 1973), indicating
results from flowing-water channel experiments more closely represent natural systems.  Nevertheless,
Bothwell (1989) did show added accrual of diatom films from about 250 mg/m2 chl a at an SRP of 5
|lg/L, increasing to  350 mg/m2 at about 50 |lg/L.

There may be problems with achieving a species assemblage in channel experiments that is representative
of the natural stream(s) in question. In fact, accurate prediction or even chatacterization of ambient
assemblages in dynamic systems may be challenging. Cladophora has  been difficult,  if not impossible, to
establish in such systems, and other FGA have not established on Styrofoam substrata (used by Bothwell
1985), even when abundant in the source stream. Diatoms are usually first to establish, with more time
required for FGA to colonize due to their more complex reproduction requirements. Natural stones seem
to be the most effective substratum for colonizing either diatoms or FGA in these systems, but resulting
dominant taxa in channels may not replicate exactly as in natural streams, even though channels are
inoculated from stream rocks. Moreover, diatoms may, in fact, dominate the biomass  in channels even
though FGA establishes and appears most abundant to the eye.  Correctly predicting community
composition in future stages of succession is very difficult, even in simple  systems. Given the complexity
inherent in dynamic ecosystems, only excessively broad predictions may be possible.  Data gathered from
channel experiments may be little better at characterizing process than a grab sample is at characterizing
water chemistry.  Only simple extrapolations can be made employing data  gathered from simple systems.

Caution is recommended in applying  nutrient-biomass relationships developed in channel experiments to
natural streams, primarily for two reasons: (1) TP and TN content required to produce a maximum
biomass will probably be higher in natural streams than in channels, as previously discussed, because
more detrital TP and TN will accumulate in enriched natural streams than in short-detention time
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July 2000	Chapter 6.  Analyze Data

channels.  Hence, the yield (i.e., slope of regression line) of chl a/TP or TN in channels will be greater.
(2) The more or less continual input of soluble nutrients from groundwater to the natural stream is usually
unknown, so inflow soluble nutrient-maximum biomass relations from short-detention time channels may
not be applicable to natural streams where in-stream soluble nutrients are low as a result of algal uptake
during long travel times, yet may have a relatively high inflow concentration of soluble nutrients.


Changes in certain physical factors including:  (1) riparian vegetation; (2) total suspended solids (TSS);
(3) reduced flow following scouring-flood conditions; (4) greatly reduced summer flow due to prolonged
drought (somewhat common); or (5) reduced grazing may cause nuisance algal growths in  stream
systems.  Identifying the controlling physical constraint(s), should be rather straightforward.  If the stream
is shaded, available light at the streambed should be measured to determine the extent to which
photosynthesis is inhibited (Jasper and Bothwell 1986; Boston and Hill 1991).  Shading can substantially
reduce production (Welch et al. 1992), even though photosynthesis of periphyton is usually saturated at
relatively low intensities (<25% full sunlight; Boston and Hill 1991). Turbidity can inhibit periphyton at
relatively low levels (>10 NTU) (Quinn et al. 1992).

Biggs (1996) argued that flood disturbance is "perhaps the fundamental factor" determining the physical
suitability for algal accrual in unshaded streams. Floods act as a "reset" mechanism, initiating a new
cycle of accrual, succession, and loss due to grazing.  Post-flood (scour) accrual rates are related to
enrichment level (Lohman et al. 1992). The role of scouring high flow should be readily discernible from
flow records and the seasonal pattern of periphyton accrual (Biggs 1996).

Flow can also regulate biomass. For example, Cladophora was observed to reach high biomass followed
by senescence and detachment from substrata in enriched, unregulated northern California  rivers, which
experienced winter flooding and scour (Power 1992). In regulated rivers, where the flood,  scour, and re-
growth phenomenon did not occur, low biomass levels of Cladophora were maintained through grazing.


Statistical analyses are used to identify variability in data and to elucidate relationships among sampling
parameters.  Several statistical approaches for analyzing data are mentioned here.  We advocate simple
descriptive statistics for initial data analyses, i.e., calculating the mean, median, mode, ranges and
standard deviation for each parameter in the system of interest.  The National Nutrients Database
discussed in Chapter 5 will calculate simple descriptive statistics for queried data. Creating a histogram
or frequency distribution of the data for the class of streams of concern can identify the nutrient condition
continuum for that class  of streams.  Specific recommendations for setting criteria using  frequency
distributions are discussed in Chapter 7, although the basis for the analysis is discussed here.  Methods of
statistical analyses are included in Appendix C to provide relevant references for the investigator if
additional analyses are needed to understand and interpret data for criteria derivation.
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July 2000	Chapter 6. Analyze Data


Frequency distributions can be used to aid in the setting of criteria. Frequency distributions do not require
prior knowledge of individual stream condition prior to setting criteria. Criteria are based on and, in a
sense, developed relative to the population of stream systems in the Region, State, or Tribe.

Data plotted on a scale of mean nutrient concentration versus frequency of occurrence in a specific stream
class produces a frequency distribution of mean nutrient concentration. Plots of frequency distributions of
mean TP,  mean TN, mean chl a, and turbidity for the index period (discussed in Chapter 4) should be
examined to determine the normalcy of the data in the distribution and to locate patterns for the class of
streams being investigated.  A  sample size of thirty streams within a stream class is recommended for
developing nutrient criteria.  Smaller sample sizes  will require more reference streams, more complete
knowledge of the stream systems being investigated, more in-depth statistical analyses,  and/or modeling
to complete criteria derivation. Sample sizes smaller than thirty may be highly affected by extreme values
in the dataset.  Data that are not normally distributed are often transformed into a distribution more
approximating the normal distribution by taking the logarithm of each value. Analysis of outliers may
assist in explaining variability in small data  sets. Additional analysis can be conducted to identify the
statistical  significance of population differences.


The relationship between two variables may be of use in analyzing data for criteria derivation.
Correlation and regression analyses allow the relationship to be defined in statistical terms. A correlation
coefficient, usually identified as r, can be calculated to quantitatively express the relationship between
two variables.  The appropriate correlation coefficient is dependent on the scale of measurement in which
each variable is expressed (whether the distribution of data is continuous or discrete) and, whether there is
a linear or non-linear relationship.  Results of correlation analyses may be represented by indicating the
correlation coefficient, and represented graphically as a scatter diagram which plots all of the collected
data, not just a measure of central tendency. The statistical significance of a calculated  correlation
coefficient can be determined with the t test. The t test is used to determine if there is a true relationship
between two variables. Therefore, the null hypothesis states that there is no correlation  between the data
variables measured within the population. A critical a value is chosen as a criterion for determining
whether to reject the null hypothesis.  If the  null hypothesis is rejected, the alternate hypothesis states that
the  correlation at the calculated r value between the two variables is significant.

Regression analyses provides a means of defining a mathematical relationship between two variables that
permits prediction of one variable if the value of the other variable is known. In contrast to correlation
analyses, there should be a true independent variable (a variable under the control of the experimenter) in
regression analyses. Regression analyses establishes a relationship between two variables that allows
prediction of the dependent variable (predicted variable) for a given value of an independent variable
(predictor variable). However, scientists (other than statisticians) apply regression analyses to field data
when a relationship is known to exist, even when there is no true independent variable (e.g., cell counts of
algae and  chlorophyll concentration; nutrient concentrations and chlorophyll concentration) (Ott 1988,
1995; Campbell 1989; Atlas and Bartha 1993).
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July 2000	Chapter 6. Analyze Data


Various statistical tests are used to assess the hypotheses being tested. Statistical tests of significance
differ in their applicability to the dataset of interest, and the power of the test (the ability of the test to
detect a false null hypothesis).  A parametric test of significance assumes a normal distibution of the
population. Non-parametric analyses are valid for any type of distribution (normal, log-normal, etc.) and
can be used if the data distribution is not normal or unknown.  A parametric test has more power than a
non-parametric test when its assumptions are satisfied. Two types of errors can be made when testing
hypotheses:  Type I-where a correct null hypothesis is mistakenly rejected, and Type II-when there is a
failure to reject a false null hypothesis. The parametric test is  less likely to make a Type II error,  when
the assumptions are met, than a non-parametric test.  Therefore, if given a choice, the parametric test
should be used rather than the non-parametric test when the assumptions of the parametric test are
fulfilled. Less powerful, non-parametric tests of significance must be used in cases where the data do not
fit the assumption of a normal distribution (Ott 1988; Campbell 1989; Atlas and Bartha 1993). Parametric
tests include: the student ^test, analysis of variance, multivariate analysis of variance, and multiple range
tests.  Non-parametric tests include:  chi square, Mann Whitney U test; and the Kruskal - Wallis test (Ott
1988; Campbell  1989; Atlas and Bartha 1993) Detailed descriptions of these and other relevant statistical
tests can be found in Appendix C.


Computer simulation modeling and probability testing can be used to predict responses to candidate
criteria (i.e., numeric nutrient concentrations).  Models that have been calibrated and verified can  be used
to extrapolate to  a projected nutrient condition where existing  data are either insufficient or unavailable.
Data from the same system that is far removed from the present can be used if parameters can be adjusted
to the present conditions.  The model output can be compared  to data from a similar stream system of the
same class and in the same ecoregion for validation. Data from a similar system may also be used to
extrapolate the nutrient condition when data for the system of  interest are unavailable. In both cases, data
are complemented by a set of clearly stated assumptions developed from data representing one point in
time to estimate conditions in the future.  In some instances, surrogate information such as turbidity and
chl a concentration can be used to estimate nutrient concentrations.

Site-specific simulation models can also be developed for a system of interest, although this is frequently
a time-consuming,  expensive process. Site-specific computer  simulation models should be solicited from
the regional academic community, because they are more accurate for predicting specific waterbody
concentrations and loadings. This section will not discuss site-specific model development, although
several ecological and water quality modeling texts and articles can assist the investigator in developing
such a model (see Fry [1993] and Mclntire et al.  [1996]).  Appendix C provides information on several
relevant stream water quality models.
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July 2000	Chapter 6. Analyze Data
                                           PAGE 92

Chapter 7.
Nutrient  and  Algal
 Nutrient and Algal
Criteria Development

This chapter addresses the details of developing scientifically defensible criteria for nutrients and algae.
Three approaches are presented that water quality managers can use to derive numeric criteria for
streams in their State/Tribal ecoregions.  The approaches that are presented include: (1) the use of
reference streams, (2) applying predictive relationships to select nutrient concentrations that will result in
appropriate levels of algal biomass, and (3) developing criteria from thresholds established in the
literature. Considerations are also presented for deriving criteria based on the potential for effects to
downstream receiving waters (i.e., the lake, reservoir, or estuary to which the stream drains). The
chapter concludes with the process for evaluating proposed criteria including the role of the Regional
Technical Assistance Group (RTAG) in reviewing criteria, guidance for interpreting and applying
criteria, considerations for sampling for comparison to criteria, potential revision of criteria, and final
implementation of criteria into water quality standards.

The most rational approach for deriving criteria is to determine nutrient values in the absence of non-
nutrient related factors that influence growth of algal biomass (e.g., light availability, flow). Then,
refinements and exceptions to the criteria can be made based on the extent to which non-nutrient related
factors are present for specific streams in an ecoregion or subecoregion. Thus, for both periphyton- and
plankton-dominated systems, criteria should be set with the goal of reaching an acceptable algal biomass
in streams with little or no light limitation, during periods of stable, post-flood/runoff, and moderate
numbers of grazing invertebrates. For periphyton-dominated streams, substrata for attachment is
assumed to be adequate and stable.

Expert evaluations are important throughout the criteria development process. The data upon which
criteria are based and the analyses performed to arrive at criteria must be assessed for veracity and
applicability. The EPA RTAGs are responsible for these assessments. The RTAG is composed of State,
Tribal, and Regional specialists that will help the Agency and States/Tribes establish nutrient criteria for
adoption into State/Tribal water quality standards. The RTAG is tasked with conducting an objective
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July 2000	Chapter 7. Nutrient and Algal Criteria Development
and exhaustive evaluation of regional nutrient information to establish protective nutrient criteria for the
ecoregional waterbodies located in their EPA Region.


The following discussions focus on three methods that can be used in developing nutrient and algal
criteria ranges. The first method requires identification of reference reaches for each established stream
class based on either best professional judgement (BPJ) or percentile selections of data plotted as
frequency distributions. The second method advocates refinement of trophic classification systems, use
of models, and/or examination of system biological attributes to assess the relationships among nutrient
and algal variables. The two methods described above should be based on data for the selected index
period (see Chapter 4). Finally, the third method provides several published nutrient/algal thresholds
that may be used (or modified for use) as criteria. A weight of evidence approach that combines one or
more of the three approaches described below will produce criteria of greater scientific validity. This
section also discusses how to develop criteria for streams that feed into standing receiving waters.


One approach that may be used in developing criteria is the reference reach approach. Reference reaches
are relatively undisturbed stream segments that can serve as examples of the natural biological integrity
of a region.  There are three ways of using reference reaches to establish criteria.

1.     Characterize reference reaches for each stream class within a region using best professional
     judgement and use these reference conditions to develop criteria.

2.     Identify the 75th percentile of the frequency distribution of reference streams for a class of streams
      and use this percentile to develop the criteria (see Figure 8 and the Tennessee case study,
      Appendix A).

3.     Calculate the 5th to 25th percentile  of the frequency distribution of the general population of a class
      of streams and use the selected percentile to develop the criteria (Figure 8).

Identification of reference streams allows the investigator to arrange the streams within a class in order
of nutrient condition (i.e., trophic state) from reference, to at risk, to impaired. Defining the nutrient
condition of streams within a stream class allows the manager to identify protective criteria and
determine priorities for management action. Criteria developed using reference reach approaches may
require comparisons to similar systems in States or Tribes that share the ecoregion so that criteria can be
validated, particularly when minimally-disturbed systems are rare.

Best professional judgement-based reference reaches may be identified for each class of streams within a
State or Tribal ecoregion and then characterized with respect to algal biomass levels, algal community
composition, and associated environmental conditions (including factors that affect algal levels such as
nutrients, light, and substrate).  The streams classified as reference quality by best professional
judgement may be verified by comparing the data from the reference systems to general population data
for each stream class.  Reference systems should be minimally disturbed and should have primary
parameter (i.e., TN, TP, chl a, and turbidity) values that reflect this condition. Factors that are affected

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July 2000	Chapter 7. Nutrient and Algal Criteria Development
by algae, such as DO and pH, should also be characterized. At least three minimally impaired reference
systems should be identified for each stream class (see Chapter 2).  Highest priority should be given to
identifying reference streams for stream types considered to be at the greatest risk from impact by
nutrients and algae, such as those with open canopy cover, good substrata, etc. [Conditions at the
reference reach (e.g., algal biomass, nutrient concentrations) can be used in the development of criteria
that are protective of high quality, beneficial uses for similar streams in the  ecoregion.]

Alternatively, a reference condition for a stream class may be selected using either of two frequency
distribution approaches. In both of the following approaches, an optimal reference condition value is
selected from the distribution of an available set of stream data for a given stream class.

In the first frequency distribution approach, a percentile is selected (EPA generally recommends the 75th
percentile)  from the distribution of primary variables of known reference systems (i.e., highest quality or
least impacted streams for that stream class within a region). As discussed in Chapter 3, primary
variables are  TP, TN, chl a, and turbidity or TSS.  It is reasonable to select a higher percentile (i.e., 75th
percentile)  as the reference condition, because reference streams are already acknowledged to be in an
approximately ideal state for a particular class of streams (Figure 8).

The second frequency distribution approach involves selecting a percentile of (1) all streams in the class
(reference and non-reference) or (2) a random sample distribution of all  streams within a particular class.
Due to the random selection process, an upper percentile should be selected because the sample
distribution is expected to contain some degraded systems. This option is most useful in regions where
the  number of legitimate "natural" reference water bodies is usually very small,  such as highly developed
land use areas (e.g., the agricultural lands of the Midwest and the urbanized east or west coasts). The
EPA recommendation in this case is usually the 5th to 25th percentile depending upon the number of
"natural" reference streams available.  If almost all reference streams are impaired to some extent, then
the  5th percentile is recommended.

Both the 75th percentile for reference streams and the 5th to 25th percentile from a representative sample
distribution are only recommendations. The actual distribution of the observations should be the major
determinant of the threshold point chosen. Figure 8  shows both options  and illustrates the presumption
that these two alternative methods should approach a common reference condition along a continuum of
data points. In  this illustration, the 75th percentile of the reference stream data distribution produces a
TP  reference  condition of 20 (Jg/L. The 25th percentile of the random sample distribution produces a
value of 25 (ig/L.  Because there is little distinction in this case, the Agency may select either 20 (jg/L, 25
(ig/L, or the intermediate 23  (ig/L value as illustrated in Figure 8.

Each State  or Tribe should similarly calculate its reference condition initially using both approaches to
determine which method is most protective. The more conservative approach is recommended for
subsequent reference condition calculations. A State or Tribe may choose to draw one single line
vertically through the data distribution to set their criterion (the equivalent of the line drawn at the
23(ig/L TP  concentration shown in Figure 8).  The obvious difficulty is choosing where the line is drawn.
If drawn to the  left of the central tendency point, most streams are in  unacceptable condition and
significant  restoration management should occur. If the line is drawn to the right of the central tendency
point, then  most streams would be in acceptable condition and far less effort would be  needed for
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July 2000
Chapter 7. Nutrient and Algal Criteria Development
                                 20    23   25      30

                              reference value
Figure 8. Selecting reference values for total phosphorus concentration (//g/L) using percentiles from
reference streams and total stream populations.
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July 2000	Chapter 7. Nutrient and Algal Criteria Development
restoration.  The establishment of a reference condition helps to set the position of the line as objectively
as possible.

It is important to understand that any line drawn through the data has certain ramifications; streams in
unacceptable condition (on the right) should be dealt with through restoration. The streams to the left of
the  line are in acceptable condition, and should not be allowed to increase their nutrient concentrations.
These streams should be protected according to the State's or Tribe's approved antidegradation policy,
and through continued monitoring to assure that no future degradation occurs.

If a State or Tribe desires greater flexibility in setting their criteria, the frequency distribution can be
divided into more than two segments (Figure 9). Using this approach, a criterion range is created and a
greater number of stream systems fall within the criterion range. This approach divides systems into
those that are of reference quality, currently in acceptable condition, or impaired. In this case,  emphasis
may be shifted from managing stream systems based on a central tendency (as shown above when a
single line is drawn through the frequency distribution) to managing systems based on the level of
impairment. This approach will also aid in prioritizing systems for protection and restoration.  Stream
data plotted to the right represent an increasingly degraded condition. Use of this approach requires that
subsequent management efforts focus on improving stream conditions so that, over time, stream data
plots shift to the left of their initial position.

State or Tribal water quality managers may also consider analyzing stream data based on designated use
classifications.  Using this approach, frequency distributions for specific designated uses could be
examined and criteria proposed based on maintenance of high quality systems that are representative of
each designated use.

In summary, frequency distributions can be used to aid in setting criteria. The number of divisions used
has significant implications with respect to system management. A single criterion forces the manager to
make decisions about the number of streams that will be in unacceptable condition, with considerable
ramifications from that decision.  If the distribution is divided into three segments, the majority of
streams will be  in acceptable condition (assuming that these  streams are meeting their specified
designated uses and do not contribute to downstream degradation of water quality), which will minimize
management requirements. The method that is used may depend on the goals of the individual State or
Tribe; some may wish to set criteria that encourage all State/Tribal stream systems to be preserved or
restored to reference  conditions.  Other managers may consider additional options, such as developing
criteria specific to protect the designated uses established for local streams.


The following section provides several options that can be used to evaluate nutrient and algal
relationships in stream systems. These options include use of trophic state classifications, models, and

Trophic State Classification
One challenge associated with setting criteria is defining the relative trophic state of a stream.  It is
difficult to determine whether a stream is excessively eutrophic if its trophic state is not known relative
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July 2000
                        Chapter 7. Nutrient and Algal Criteria Development
                            10          20          30            40         50

                                      meet criteria    do not meet criteria
Figure 9.  Frequency distribution divided into three segments that represent (from left to right)
high-quality reference streams, acceptable quality streams, and impaired streams.
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July 2000	Chapter 7.  Nutrient and Algal Criteria Development
to other streams. There is no generally accepted system for classifying the trophic states of streams
(Dodds et al.  1998). The only proposed system divides data plotted as cumulative frequency diagrams
into oligotrophic (lower third), mesotrophic (middle third), and eutrophic (upper third) categories (see
Chapter 2) (Dodds et al.  1998). This approach is similar to the reference reach method described in the
previous section.  More data are necessary to determine the applicability of such a classification scheme
to streams from different ecoregions.

A few models establish correlations between TN/TP and benthic algal biomass in streams (e.g., Lohman
et al. 1992; Dodds et al.  1997; Bourassa and Cattaneo 1998; Chetelat et al. 1999; Biggs 2000).  Such
models estimate algal biomass as a function  of water column nutrients (as has often been done for lakes
and reservoirs).

A regression model linking TP to river phytoplankton has been published (Van Nieuwenhuyse and Jones
1996). This model can be used to set TP criteria.  The TP levels can in turn be used to calculate
corresponding TN concentrations using the Redfield ratio (Harris 1986). This model captures additional
variance when watershed area is considered (as discussed in Chapter 6).

Finally, it is necessary to relate instream TN and TP concentrations to nonpoint and point sources of
nutrients. Models allowing prediction of nutrient loading in streams are needed. A method for
determining instream TN and TP concentrations based on loading from point sources has been developed
for  use in the  Clark Fork River (Dodds et al. 1997).  Simple correlation techniques using data available
from various regions may yield a nutrient and chlorophyll relationship that can be used to predict what
management strategies are necessary to bring nutrients from point sources, and consequently algal
biomass, to target levels.

Biocriteria involve the use of biological parameters to establish nutrient impairment in streams.  There
are  two ways  to use biocriteria to establish water quality criteria.  The first approach involves the
protection and restoration of ecosystem services, which is almost exclusively related to biological
features and functions in aquatic ecosystems. Although it is recognized that chemical and physical
factors play a critical role in the algal-nutrient relationship, it is felt that the effect of nutrients on algae
and other components of aquatic ecosystems is critical. This is why ecoregional and waterbody-specific
nutrient criteria are recommended and chl a and Secchi depth/turbidity,  arguably biocriteria, are
required. The second approach is based on the concept that attributes of biological assemblages vary less
in space and time than most physical and chemical characteristics. Thus, fewer mistakes in assessment
may occur if biocriteria are employed in addition to physical and chemical criteria.

Multimetric indices are a special form of biocriteria in which many metrics are used to summarize and
communicate in one number the state of a complex ecological system. Multimetric indices for
macroinvertebrates and fish are used successfully as biocriteria in many States.  A multimetric index of
trophic status could be developed to complement N, P, and chl a criteria (see Section 6.2, Developing
Multimetric Indices to Complement Nutrient Criteria).

The same approaches used to establish nutrient and algal criteria could be employed to establish criteria
for  other biological attributes, such as a Diatom Index of Trophic State (DITS).  Frequency distributions

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July 2000	Chapter 7.  Nutrient and Algal Criteria Development

of reference conditions or a random sample of streams would provide a target for management and
restoration efforts. Alternatively, dose-response relations (predictive models) between biocriteria and
nutrients could be used to set nutrient and biocriteria, based on a desired level of biotic integrity or other
valued ecosystem component.

A fourth approach is also possible when characterizing the responses of many biological attributes to
nutrients.  Some of these factors change linearly with increasing nutrient concentrations, for a number of
reasons, and some factors change non-linearly.  Non-linear changes in metrics indicate thresholds along
environmental gradients where small changes in environmental conditions cause relatively great changes
in a biological attribute.  These thresholds are valuable for setting nutrient criteria, but changes  in these
metrics are not necessarily the best indicators of biotic integrity. They can for example, remain
relatively constant as human disturbance increases until a stress threshold is reached.  Alternatively,
during restoration, they may not respond to remediation until a lower threshold is reached. Thus, metrics
or indices that change linearly (typically higher-level community attributes such as diversity or a
multimetric index) provide better variables for establishing biocriteria because they respond to
environmental change along the entire gradient of human disturbance. However, parameters changing
non-linearly along environmental gradients are valuable for determining where along the environmental
gradient the physical and chemical criteria should be set and, correspondingly, where to establish other


In addition to using the 'reference reach' concept or applying predictive relationships to establish criteria
for  trophic state variables, other methods to consider include using thresholds and criteria already
recommended in the literature.  These approaches might be used as limits if identifying reference reaches
proves difficult or as temporary measures until reference reaches can be adequately described.  The
following text describes potential criteria for several nutrient-related variables. Because most of the
following threshold concentrations were derived primarily for northern to mid-temperate cobble-bottom
streams, caution should be exercised when applying them to streams found in other geographic  areas
such as southern temperate and subtropical regions.  The nutrient/algal relationships described below
may not be valid for sandy streams of the southeast and southwest and should be tested on intermittent
and effluent-dominated systems.  Literature values may be used as criteria if a strong rationale is
presented that demonstrates the suitability of the threshold value to the stream of interest (i.e., the system
of interest should share characteristics with the systems used to derive the threshold, published values).

Criteria for nutrients in streams have been set or suggested by various agencies and investigators (Table
4).  However, in contrast to lake management schemes, there is much less agreement on whether to use
total nutrient concentrations, soluble nutrient concentrations,  or nutrient concentrations that might
produce a given biomass level or an undesirable effect in gravel-bed streams. Although much of the total
nutrient concentrations in the water column of streams is not immediately available (due to a high
fraction of detritus, as discussed previously), total concentrations probably have more general
applicability than soluble fractions.  While soluble fractions are more available, they also may be held at
low levels during high-biomass periods due to uptake (Dodds et al. 1997). Nevertheless, some
investigators have had considerable success relating soluble nutrients to algal biomass if annual mean or
seasonal values are used for nutrient concentrations. Using the Bow River as an example, mean TDP
during summer was more useful than TP (Table 4).
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July 2000
Chapter 7. Nutrient and Algal Criteria Development
Table 4. Nutrient (ng/L) and algal biomass criteria limits recommended to prevent nuisance conditions
and water quality degradation in streams based either on nutrient-chlorophyll a relationships or
preventing risks to stream impairment as indicated.
PERIPHYTON Maximum in mg/m2
TN TP DIN SRP Chlorophyll a Impairment Risk Source






nuisance growth
nuisance growth
nuisance growth
nuisance growth
nuisance growth
nuisance growth
reduced invertebrate
nuisance growth
Welch et al.
1988, 1989
Dodds et al.
Dodds et al.
Clark Fork
River Tri-State
Council, MT
Chetelat et al.
unpubl. data
UK Environ.
Agency 1988
Biggs 2000
Nordin 1985
Quinn 1991
Sosiak pers.
PLANKTON Mean in jig/L
TN TP DIN SRP Chlorophyll a Impairment Risk Source


chlorophyll action
and Jones 1996
OAR 2000
OECD 1992
(for lakes)
'30-day biomass accrual time
2Total Dissolved P
3Based on Redfield ratio of 7.2N: IP (Smith et al. 1997)
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July 2000	Chapter 7. Nutrient and Algal Criteria Development
Notwithstanding the sparse set of cases, there is an indication of some consistency for total and soluble P
criteria (Table 4).  In two separate data sets, the tendency for Cladophora to begin dominating the
periphyton was observed at TP concentrations of 10-20 (jg/L (Chetelat et al. 1999; Stevenson pers.
comm.).  This general range was also selected by the Clark Fork Tri-State Council to limit maximum
biomass to levels below  150 mg chl aim2.  Setting a criterion equivalent to 'no filamentous green algae',
even if chl a levels exceed 150 mg/m2, would protect aesthetic use and still may not limit fisheries

Using a criterion for periphytic or planktonic biomass to initially judge if nutrient concentrations are
excessive, may have a practical management and enforcement appeal. Advantages are several: (1) there
is general agreement among some investigators and agencies on a biomass level that minimizes risk to
recreational and aquatic life uses (see Table 4), (2) problems of algal control that result in poor dose-
response relationships of nutrients versus biomass (due to shading by riparian canopies or suspended
sediment and grazing) are averted, and (3)  TMDLs and resultant controls would be required only for
situations in which biomass criteria were exceeded. However, criteria for nutrients (specifically TN and
TP) will ultimately be required for all  stream classes within an ecoregion.

Algal Biomass
Criteria for levels  of periphyton algal biomass that present a nuisance condition in streams and impact
aesthetic use have been recommended by several investigators.  There is surprising consistency in these
values, with a maximum of about 150  mg/m2 chl a being  a generally agreed upon criterion (Table 4). As
objective support for that criterion, percent coverage by filamentous forms was less than 20 percent, but
increased with increased biomass and noticeably affected aesthetic quality (Welch et al. 1988). At this
level, there were no apparent effects on DO, pH, or benthic invertebrates, which, as described earlier,
occur at higher biomass levels.

Furthermore, a literature review of 19  cases indicated biomass levels greater than 150 mg/m2 tended to
occur with enrichment and when filamentous forms were more prevalent (Horner et al. 1983). As noted
earlier, Lohman et al. (1992) observed that biomass rapidly recovered following flood-scour events in 12
Ozark streams when biomass exceeded the 150 mg/m2 level at moderately to highly enriched sites. Pre-
disturbance biomass did  not recover as rapidly when initial levels did not exceed approximately 75
mg/m2 at unenriched sites.

A provisional guideline of  a maximum 100 mg/m2 chl a  and 40 percent coverage of filamentous forms
was proposed for New Zealand streams to  "protect contact recreation".  There was  insufficient evidence
for protection of other uses that require specific DO and pH thresholds, which in turn vary due to
atmospheric exchange (area:volume ratio)  and buffering capacity (Quinn 1991).

While the 150 mg/m2 level cannot be supported as an absolute threshold above which adverse effects on
water quality and benthic habitat readily occur, it nonetheless is a level below which an aesthetic quality
use will probably not be  appreciably degraded by filamentous mats or any other of the adverse effects
attributed to dense mats of filamentous algae (e.g., objectionable taste and odors in water supplies and
fish flesh, impediment of water movement, clogging of water intakes, restriction of intra-gravel water
flow and DO  replenishment, DO/pH flux in the water column, or degradation of benthic habitat) (Welch
1992).  Avoidance of these problems in many stream systems may be achieved with a maximum 150
mg/m2 chl a criterion.  As an example, control strategies were developed for the Clark Fork River,

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July 2000	Chapter 7. Nutrient and Algal Criteria Development
Montana, using a 100-150 mg/m2 maximum as a criterion (see Appendix A case studies) (Watson and
Gestring 1996; Dodds et al. 1997).


More stringent nutrient criteria may be required for streams that feed into lentic or standing waters. For
example, it is proposed that 35 |J,g/L TP concentration and a mean concentration of 8 |J,g/L chl a
constitute the dividing  line between eutrophic and mesotrophic lakes (OECD 1982).  In contrast, data
from Dodds et al. (1997) suggest that seasonal mean chlorophyll a values within stream systems of 100
mg/m2 are likely at concentrations of 221 (ig/L TP. Thus, unacceptable levels of chlorophyll may occur
in lakes at much lower nutrient concentrations compared to streams  (Dodds and Welch 2000).


During criteria derivation, the RTAG will provide expert assessment of any proposed criteria or criteria
ranges and their applicability to all streams within the class of interest.  Criteria will need to be verified
in many cases by comparing criteria values for a stream class within an ecoregion across State and Tribal
boundaries. In addition, prior to recommending any proposed criterion, the RTAG must consider the
potential for the proposed  criterion to cause degradation of downstream receiving waters. In developing
criteria, States/Tribes must consider the designated uses and standards of downstream waters and ensure
that their water quality standards provide for the  attainment and maintenance of water quality standards
in downstream waters.  Criteria recommended by the RTAG can be  adopted by the State or Tribe as
approved by EPA if there is documented evidence that no adverse effects will result downstream.
However, if downstream waters are not adequately protected at the concentration level associated with
the  proposed criteria, then the criteria should be adjusted accordingly. Load estimating models, such as
those recommended by EPA (USEPA 1999), can assist in this determination (see Section 4.2, Nutrient
Load Attenuation). Water quality managers responsible for downstream receiving waters should also be


After evaluating criteria proposed for each stream class, determining streams condition in comparison
with nutrient criteria can be made by following the steps:

1.    Calculate duration and frequency of criteria violations as well as associated consequences. This
      can be done using modeling techniques or correlational analysis of existing data.

2.    Develop and test hypothesis to determine agreement with criteria. Analyze for alpha and beta
      (Type I and II) errors (see Appendix C).

3.    Reaffirm appropriateness of criteria for protecting designated  uses and meeting water quality

The goal is to identify protective criteria and standards. Criteria should be based on ecologically
significant changes as well as statistically significant differences in compiled data. Although criteria are
developed exclusively  on scientifically defensible methods, assignation of designated uses requires

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July 2000	Chapter 7. Nutrient and Algal Criteria Development
consideration of social, political, and economic factors. Thus, it is imperative that some thought be
given during the criteria development process of how realistically the criteria can be implemented into
standards that are accepted by the local public.


Once  criteria have been selected for each indicator variable, a procedural rule to assess stream
concurrence with criteria should be established. The four primary criteria variables include two causal
variables (TN and TP) and two response variables (chl a and Secchi depth or a similar indicator of
turbidity). Failure to meet either of the causal criteria should be sufficient to require remediation and
typically the biological response, as measured by chl a and turbidity, will follow the nutrient trend.
Should the causal criteria be met, but some combination of response criteria are not met, then a
decisionmaking protocol should be in place to resolve the issue of whether the stream in question meets
the proposed nutrient criteria.

Sampling to evaluate agreement with the standards  implemented from nutrient and algal criteria will
have to be carefully defined to ensure that State or Tribal sampling is compatible with the procedures
used to establish the criteria.  If State or Tribal observations are averaged over the year, balanced
sampling is essential and the average should not exceed the criterion. In addition, no more than ten
percent of the observations contributing to that average value should exceed the criterion.

A load estimating model (e.g., BASINS [see Appendix C]) may be applied to a watershed to back-
calculate the criteria concentration for an individual stream from its load allocation. This approach to
criteria determination may also be  applied on a seasonal basis and should help States/Tribes relate their
stream reach criteria with their lake or estuarine criteria. It may also be particularly important for criteria
developed for streams and rivers that cross State/Tribal boundaries.

Algal Sampling for Comparison  to Criteria
Once  criteria for algal biomass have been established, certain sampling considerations must be addressed
to obtain meaningful samples. This section discusses some of the more relevant considerations, using
several questions as the basis for determining stream condition with respect to nutrients and algae.

1. How can algal criteria be applied to samples that come from only certain depths of the stream?
Aesthetic criteria should be applied to the wadeable portion of large rivers, as has been done in British
Columbia (Nordin 1985; see Table 4).  The level necessary to protect aquatic life is likely to be system-
specific and is best evaluated by determining how algal biomass affects DO, pH, and aquatic

2. How large an area must exceed an algal criterion (e.g.,  150 mg chl aim2) to be considered
unacceptable?  The area must be  large enough to interfere with aesthetics and recreation or to cause
undesirable water quality changes. Obviously, regional and site-specific testing of criteria will be
necessary. The related sampling question is: how large an area should be characterized when assessing
whether a reach exceeds a quantitative criterion? To ensure that a reasonably representative portion of a
reach  is sampled, replicate samples should be distributed over a reach at least 100 m long. Before
selecting a point for sampling, a walk upstream and downstream a few hundred meters should be
conducted to ensure that the preferred sampling point is not atypical of the reach being characterized.

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July 2000	Chapter 7. Nutrient and Algal Criteria Development
Low altitude aerial photos taken on a sunny day in mid-to-late growing season can be used to determine
the longitudinal extent of conditions similar to those at the sampling site. Floating the stream by boat
can serve a similar purpose.

3. For how long must algal biomass exceed criteria to be considered unacceptable?
Attached algal biomass does not change as rapidly as water column parameters. Hence, one sample a
month(from June to September) may be adequate to assess algal biomass, though weekly or bi-weekly
sampling is ideal. If only two samplings can be afforded, the likely period containing the highest biomass
levels should be bracketed.  However, such a sampling scheme may be regarded as unacceptable if both
sample values exceed aesthetic criteria. If algal biomass is high enough to cause excessive DO and pH
fluctuations that violate water quality standards or that release toxins at unacceptable levels, then the
time frames for those water quality violations should be used to judge the acceptability of algal biomass
levels. As an example, some States or Tribes might regard the exceedance of algal biomass criteria once
in 10 years (i.e., only during the 10-year low-flow) as acceptable, but more frequent exceedances may be
deemed unacceptable.

4. How many replicate samples at a site are needed to obtain acceptable precision of data in  order
to detect differences between sites and changes over time? This depends on the variability in algal
biomass in the particular system. The Kendall test with Sen slope estimate (Hirsch et al.  1982) allows the
determination of the number of replicate samples needed to detect a certain percent change in annual
means of a variable or a certain percent trend over a period such as 10  years (see Clark Fork River case
study, Appendix A).


There may be specific cases identified by States or Tribes that require modification of established
criteria, either due to unique stream system characteristics or specific designated uses approved for a
stream or stream reach.  Two examples of acceptable criteria modifications are presented below.

Site Specific Criteria
If a State/Tribe has additional information and data which indicate a different value or set of values is
more appropriate for specific stream systems than ecoregionally-derived criteria, a scientifically
defensible argument should be prepared that a "site specific" criteria modification is required. Once
approved by EPA, this value can be incorporated into State or Tribal water quality standards. If no
action is taken by the State or Tribe involved, EPA may propose to promulgate criteria based on the
regional values and best available supporting science at the time.

Designated Use Approaches
Once a regional criterion has been established, it is subject to periodic  review and calibration. Any State
or Tribe in the  region may elect to use the criterion as the basis for developing its own criteria to protect
designated uses for specific stream classes. This is entirely appropriate as long as the criteria are as
protective as the basic EPA criterion for that region. This ecoregional criterion represents EPA's
"304(a)" recommendation for protection of an aquatic life use.

The Clean Water Act as amended (Pub. L. 92-500 (1972), 33 U.S.C. 1251, et seq.) requires all States to
establish designated uses for their waters (Section 303 [c]). Designated uses are set by the State. EPA's

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July 2000	Chapter 7. Nutrient and Algal Criteria Development
interpretation of the Clean Water Act requires that wherever attainable, standards should provide for the
protection and propagation offish, shellfish, and wildlife and provide for recreation in and on the water
(Section 101 [a]). Other uses identified in the Act include industrial, agricultural, and public water
supply. However, no waters may be designated for use as repositories for pollutants (see 40 CFR
131.10[a]). Each water body must have legally applicable criteria or measures of appropriate water
quality that protect and maintain the designated use of that water. It is therefore proper for States and
Tribes to set nutrient criteria appropriate to each of their designated uses in so far as they are as
protective as the regional nutrient criteria established for those classes of waters.


Criteria, once developed and adopted into water quality standards by a State or Tribe, are submitted to
EPA for review and approval (see 40 CFR 131). EPA reviews the criteria (40 CFR 131.5) for
consistency with the requirements of the Clean Water Act and 40 CFR 131.6, which requires that water
quality criteria be sufficient to protect the designated use (40 CFR 131.6[c] and 40  CFR 131.11). The
procedures for State/Tribal review and revision of water quality standards, EPA review and approval of
water quality standards, and EPA promulgation of water quality standards (upon disapproval of
State/Tribal water quality standards) are found at 40 CFR 131.20 -22 (see Figure 1, Chapter 1).  The
Water Quality Standards Handbook (EPA 1994) provides guidance for the implementation of these
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Chapter  8.

This chapter provides information on regulatory and non-regulatory programs that may utilize or be
affected by nutrient criteria, as well as management solutions for problems associated with varying
streamflow conditions. This chapter is intended to inform resource managers and foster potential links
among regulatory and non-regulatory programs to best manage watersheds. Information about other
agency programs that may assist in implementing criteria and maintaining water quality is also included.

The information provided by nutrient surveys of stream systems in a region will permit the resource
manager to rank stream systems by trophic state; i.e., the manager should be able to classify systems
according to the degree of nutrient enrichment.  Stream systems can be selected for priority attention for
management action.  Documented stream nutrient and algal conditions and an understanding of regional
public preferences regarding limits of productivity can be used to establish three categories of streams:

     Systems with algal and/or nutrient problems. The most severely degraded waterbodies requiring
     extensive, expensive restoration.

     Systems with a strong potential for developing algal problems (factors other than nutrients are
     unlikely to be limiting). The intermediate streams in need of remedial management to improve
     conditions requiring various levels of expense and manpower depending on the characteristics and
     problems identified in each case.

     Systems with a low potential for developing algal problems that do not contribute to degraded
     nutrient conditions in downstream waterbodies. The systems in excellent condition requiring no
     restoration and for which management is essentially the  protection of this resource through careful
     watershed land use planning and diligent observation of conditions.  This is usually a relatively
     low cost option allowing for the protection of many such waterbodies with little expenditure of
     budget or personnel.
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July 2000                                                        Chapter 8. Management Programs

Systems with high nutrient loading but low potential for developing algal problems due to other limiting
factors should be prioritized based on the potential for degradation of downstream receiving waters. The
management strategies required for nutrient reduction within streams and those for lakes and estuaries
are not different, so these processes should be linked when management plans are being formulated.

The next logical action is the design of management plans to enhance collective water body resources.
The initial categorization helps set priorities for the best use of limited personnel and funds by selecting
some optimal combination of many low cost but effective projects combined with some important
restoration projects, and perhaps long range planning to begin to address major restoration of one or two
important stream systems on an incremental basis.

This chapter is separated into discussions of point source and nonpoint source programs. Each program
is discussed and a list of source information or contacts is provided. This chapter is intended to aid the
resource manager in identifying programs that may assist in implementation of nutrient criteria.  These
programs include regulatory and non-regulatory programs that address both point and nonpoint sources
of nutrients. Consultation with these programs is recommended for watershed and development planning
activities.  Linking with other programs may allow maximization of resources for addressing water
quality concerns.



Maintaining flow is often essential to habitat protection.  In many regions of the United States, stream
segments periodically lose  water due to irrigation, industrial and municipal withdrawals; and/or diversion
for hydroelectric power;  evaporation; and groundwater infiltration.  Additionally, during low-flow
conditions, impacts from point source discharges of chemical stressors are typically greatest, because
effluent constitutes a larger percentage of (or sometimes all)  stream water at low flow, with increased
pollutant concentration.  National Pollutant Discharge Elimination System (NPDES) permits based on
low flow conditions (e.g., 7Q10) often cannot antic-ipate various combinations  of climatic conditions
and water demand that lead to exceedingly low flows.

Impacts attributable to low flows caused by human  actions can be mitigated by several in-stream
restoration techniques, including:

         Reducing channelization,
         Restoring wetlands for conservation and storage purposes thereby restoring natural hydrologic
     •   Controlling evaporation through restoration of the riparian canopy,
         Replacing exotic riparian plant species that have high evapotranspiration rates with native
         species that have lower transpiration rates,
     •   Constructing drop structures to create pools that provide protection for aquatic life during
         low-flow periods,
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July 2000                                                        Chapter 8. Management Programs

      •   Increasing channel depth and undercut banks to provide protective areas for fish and other
         species during periods of low flow, and
         Increasing groundwater recharge to streams through increased infiltration (e.g., reduced
         imperviousness in recharge areas).

Minimum flows can also be addressed by applying techniques in the surrounding watershed, such as
managing watershed land use to prevent excessive dewatering. Restoration practices to mitigate low
velocity/low-flow conditions often require close collaboration with other resource management agencies
(e.g., USDA Forest Service), zoning authorities (e.g., county governments), and agricultural extension
agencies. Several agricultural activities contribute to low velocity/low flow conditions. Agricultural
extension agencies have developed specific techniques to modify the practices that result in low-flow
impact to streams. For example, irrigation plans can be optimized to reduce the demand for water that is
diverted directly from the stream. Changing crop rotations and using less water-intensive crop
alternatives are other tools that have been used effectively to address low velocity/low-flow situations.
Source: [http://www.epa.gov/owowwtrl/NPS/Ecology/chap3.html]


High-energy flows can erode substrate and bank materials, destabilize the physical structure of aquatic
habitats, eradicate resident aquatic organisms, and destroy eggs located in the benthic environment.
Seasonal cycles of high-energy flow events (e.g., spring floods) are typical in most aquatic systems.
Habitat alteration and degradation, however, may exacerbate impacts of high-energy  flows and
contribute to impairment of designated uses.  For instance, in a channelized stream with minimal riparian
vegetation, flow velocity and volume will likely be much greater than would be expected in a "natural
stream," thereby increasing its erosive potential.

Two aspects of flooding are considered here. It has recently been recognized that water retention
structures remove the natural flooding that is part of a normal stream ecosystem (the flood pulse
concept). Such floods are known to reduce levels of algae and macrophytes and may be beneficial to
stream communities otherwise. The floods appear destructive on the short term, but most stream
organisms are adapted to some level of flooding.

Alternatively, channel alteration and watershed modification can lead to abnormally high water
velocities through the stream channel and amplify the  effects of floods. For example, channelization can
reduce the amount of refugia used by stream organisms to escape floods. Removal of riparian
vegetation, urbanization, and deforestation of watersheds can lead to much greater peak flows during
floods for a given amount of rain. Watershed disturbance can also lead to increases in sedimentation,
which will scour away excessive algal biomass and, if deposited, make it difficult for periphyton to
become established. However, such sediment will compromise the ecological integrity by harming fish
and invertebrates in the stream channels.

In-stream and riparian techniques that can mitigate high flow impacts include:

         Restoring natural stream meander and channel complexity;
      •   Increasing substrate  roughness;
      •   Promoting growth of riparian vegetation, which serves as a drag on flows;

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July 2000                                                        Chapter 8. Management Programs

      •   Modifying land use along buffers and other source areas; and
         Creating plunge pools and flow baffles to decrease the high energy of discharged waters.

These in-stream practices may need to be accompanied by techniques applied in the surrounding
watershed, such as upland revegetation or the establishment of nonpoint source best management
practices (BMPs).

Resource management agencies, for example, can encourage or allow beavers to colonize stream
segments; beaver dams create wetlands and retain water that supplements low flow during dry periods.
Restored wetlands can have the same effect as a beaver dam.  In areas below dams where flow  is very
stable and excessive growths of macrophytes and periphyton are common, water releases to mimic
natural floods may be considered.  Local zoning authorities have also begun to encourage impervious
area reduction in watersheds through land-use ordinances. Increased infiltration and reduced peak flows
from rapid runoff contributes to a more sustained base flow to the stream from groundwater discharge.
Source: [http://www.epa.gov/owowwtrl/watershed/wacademy/acad2000/river/]


The term "point source" means any discernible, confined, and discrete conveyance, including but not
limited to any pipe, ditch, channel, tunnel, conduit, well, discrete fissure, container, rolling stock,
concentrated animal feeding operation, or vessel or other floating craft,  from which pollutants are or may
be discharged. This term does not include agricultural storm water discharges and return flows from
irrigated agriculture. This section describes some of the regulatory programs that permit point  source
discharges into rivers and streams. The regulatory programs discussed here apply to federal
requirements of the Clean Water Act (Section 303). State, Tribal, and local governments frequently have
regulatory programs that operate on agency specific requirements.  These agencies should be considered
in management planning activities.


Water quality standards include an anti-degradation policy and methods through which the State or Tribe
implements the anti-degradation policy. Anti-degradation is a policy required in State water quality
standards to protect waters from degradation. At a minimum, States must maintain and protect the
quality of waters to support existing uses. Anti-degradation was originally based on the spirit, intent,
and goals of the Clean Water Act, especially the clause "...restore and maintain the chemical, physical,
and biological integrity of the Nation's waters" (USEPA 1994).  The water quality standards regulation
sets out a three-tiered anti-degradation approach for the protection of water quality.

Tier 1
Maintains and protects existing uses and the water quality necessary to protect these uses (40 CFR
131.12[a][l]).  An existing use  can be established by demonstrating that fishing, swimming, or other uses
have actually occurred since November 28,  1975, or that the water quality is suitable to allow such uses
to occur, whether or not such uses are designated uses for the water body in question.
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July 2000                                                         Chapter 8. Management Programs

Tier 2
Protects the water quality in waters whose quality is better than that necessary to protect
"fishable/swimmable" uses of the water body (40 CFR 131.12[a] [2]). The water quality standards
regulation requires that certain procedures be followed and certain showings be made (an "anti-
degradation review") before lowering water quality in high quality waters.  In no case may water quality
for a tier 2 water body be lowered to a level at which existing uses are impaired.

Tier 3
Preserves outstanding national resource waters (ONRWs), which are provided the highest level of
protection under the anti-degradation policy (40 CFR 131.12[a][3]). ONRWs generally include the
highest quality waters of the United States. However, the ONRW anti-degradation classification also
offers special protection for waters  of "exceptional ecological significance," i.e., those water bodies
which are important, unique, or sensitive ecologically, but whose water quality, as measured by the
traditional parameters such as dissolved oxygen or pH, may not be particularly high. Waters of
exceptional ecological significance also include waters whose characteristics  cannot adequately be
described by traditional parameters (such as wetlands and estuaries).

Anti-degradation implementation procedures  address the measures used by States and Tribes to ensure
that permits and control programs meet water quality standards and anti-degradation requirements.

General Policies
The water quality standards regulation allows States and Tribes to include implementation in their
standards policies and provisions, such as mixing zones, variances,  and low-flow exemptions.  Such
policies are subject to EPA review and approval. These policies and provisions should be specified in
the State or Tribe's water quality standards document. The rationale and supporting documentation
should be submitted to EPA for review during the water quality standards review and approval process.

Mixing Zones
States and Tribes may, at their discretion, allow mixing zones for dischargers. The water quality
standards should describe the methodology for determining the location,  size, shape, outfall design, and
in-zone quality of mixing zones.  Careful consideration must be given to  the appropriateness of a mixing
zone where a substance discharged is bioaccumulative, persistent, carcinogenic, mutagenic, or

Low-Flow Provisions
State and Tribal water quality standards should protect water quality for the designated and existing uses
in critical low-flow situations. States and Tribes may, however, designate a critical low-flow below
which numerical water quality criteria do not apply. When reviewing standards, States and Tribes should
review their low-flow provisions  for conformance with EPA guidance.

Water Quality Standards Variances
As an alternative to removing a designated use, a State or Tribe may  wish to  include a variance as part
of a water quality standard, rather than changing the entire standard, especially if the State or Tribe
believes that it can ultimately be attained. By maintaining the standard rather than changing it, the State
or Tribe will assure that further progress is made in improving water quality and attaining the standard.
Variances are temporary, subject to review every three years, and may be extended upon expiration. If a

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variance specifies an interim criterion applicable for the duration of the variance for a particular
pollutant, a long-term underlying goal criterion is also specified that is adequate to protect the designated
use. EPA has approved variances in the past and will continue to do so if:

      •   The variance is included as part of the water quality standard;
         The variance is subjected to the same public review as other changes in water quality
      •   The variance is granted based on a demonstration that meeting the standard is not feasible due
         to the presence of any of the same conditions as if a designated use were being removed (these
         conditions are listed in section 131.10(g) of the water quality standards regulation); and
         Existing uses will be fully protected.

For additional information, see http://www.epa.gov:80/ostwater/econ/chaptr5.pdf


The Clean Water Act requires wastewater dischargers to have a permit establishing pollution limits, and
specifying monitoring and reporting requirements.  More than 200,000 sources are regulated by the
NPDES permits nationwide.  These permits regulate household and industrial wastes that are collected in
sewers and treated at municipal wastewater treatment plants.  Permits also regulate industrial point
sources and concentrated animal feeding operations that discharge into other wastewater collection
systems or that have the potential to discharge directly into receiving waters. Permits regulate discharges
with the goals of 1) protecting public health and aquatic life, and 2) assuring that every facility treats
wastewater.  Typical pollutants regulated by NPDES are "conventional pollutants" such as  fecal
coliforms or oil and grease from the sanitary wastes of households, businesses, and industries and "toxic
pollutants" including pesticides, solvents, polychlorinated biphenyls (PCBs), dioxins, and heavy metals
that are particularly harmful to animal or plant life.  "Non-conventional pollutants" are any additional
substances that are not conventional or toxic that may require regulation, including nutrients such as N
and P. [Source: http://www.epa.gov/owm/gen2.htm].

Discharge monitoring data for pollutants limited and/or monitored pursuant to NPDES permits issued by
States, Tribes, or EPA are required to be stored in the central EPA Permit Compliance System (PCS).
The assessment of point source loadings is not a simple process of assessing PCS data, even though PCS
is an important data source. The PCS database does not provide complete information for important N
sources. Most PCS N data is generated by water quality-based  permit limitations on ammonia, often
applied in discharges to smaller streams. Few data exist in PCS on other forms of N, or TN; and data for
TP is not frequently found in PCS.  This situation exists largely because most permits do not include
limits and/or monitoring requirements for N or P. The lack of nutrient limits and/or monitoring
requirements in permits is due to a general lack of State water quality standards for these parameters.
[Source: http://www.epa.gov/msbasin/protocol.html]

The NPDES Storm Water Permitting Program
Storm water runoff is one of the remaining causes of contaminated lakes, streams, rivers, and estuaries
throughout the country. Pollution in storm water runoff is responsible for closing beaches and shellfish
harvesting areas, contaminating fish, and reducing populations of water plants and other aquatic life.
High flows of storm water runoff cause flooding, property damage, erosion and heavy siltation. The

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Clean Water Act requires EPA and States/Tribes to implement a national storm water control program to
correct these problems. In the first phase of the program, discharges of storm water from municipal
separate storm sewers serving populations of over 100,000 and from industrial facilities are illegal unless
controlled by an NPDES storm water permit. Phase II of the program required that EPA, in consultation
with the States, conduct a study identifying additional sources of storm water contamination and
establish procedures and methods to control these discharges.
Source: [http://www.epa.gov/owmitnet/pipes/wetlib/disc_pap.txt]

Construction Permits
The 1987 Congressional Amendments to the Clean Water Act required EPA to control pollution from
storm water discharges.  Phase I storm water regulations were finalized by EPA in 1990, and NPDES
permit coverage was required for construction sites disturbing five or more acres beginning in 1992.
General permits provide EPA with an effective mechanism to regulate these discharge from tens of
thousands of construction sites, thus protecting and improving surface water quality across the nation.

EPA Regions 1, 2, 3, 7, 8, and 9 have reissued the general permit which authorizes the discharge of storm
water associated with construction activity disturbing five or more acres (Phase I sources) and smaller
Phase II sources that are designated by the Agency on a case-by-case basis.  This multi-regional permit is
know as the "Construction General Permit" (CGP). As used in the permit, the term "storm water
associated with construction activity" refers to category (x) of the definition of "discharge of storm water
associated with industrial activity" which includes construction sites and common plans of development
or sale that disturb five or more acres (See 40 CFR 122.26 [b][14]).  This permit replaces the Baseline
Construction General Permit issued by EPA in September 1992. Issuance of the new CGP will not affect
areas where the State is the NPDES permitting authority.

Region 4 has issued a separate construction general permit for the State of Florida and Indian Country
lands in Florida, Mississippi, Alabama, and North Carolina.  Region 6 is also issuing its own
construction general permit for the States of Texas and New Mexico; Indian Country lands in Texas,
New Mexico, Oklahoma and Louisiana; and construction activity at oil, gas, and pipeline facilities in
Oklahoma in the near future. [Source: http://www.epa.gov/owmitnet/cgp.htm]


Combined sewer overflows, or CSOs, are a significant water pollution and public health threat. EPA's
1994 CSO Control Policy addresses CSOs in a flexible, cost-effective manner that provides for local
decision-making and negotiation to achieve compliance with the Clean Water Act.  CSOs contain not
only storm water but also untreated human and industrial waste, toxic materials, and debris. This is a
major water pollution concern for cities with combined sewer systems. CSOs are among the major
sources responsible for beach closings, shellfishing restrictions, and other water body impairments.
During dry weather, these "combined sewer systems" transport wastewater directly to sewage treatment
plants. In periods of rainfall or snowmelt, however, the wastewater volume in a combined sewer system
can exceed the capacity of the sewer system or treatment plant. For this reason, combined sewer systems
are designed to overflow occasionally and discharge excess wastewater directly to nearby streams, rivers,
lakes, or estuaries.
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July 2000                                                        Chapter 8. Management Programs

EPA's CSO Control Policy published April 19, 1994, is a national framework for control of CSOs
through the NPDES permitting program. The Policy resulted from negotiations among municipal
organizations, environmental groups, and State agencies. It provides guidance to municipalities and State
and Federal permitting authorities on meeting pollution control goals of the Clean Water Act in a
flexible, cost-effective manner. Information on EPA's CSO Control Policy can be found on the
following Website. Source:  [http://www.epa.gov/OWM/cso.htm]


The Watershed Management Institute, Inc. recently published a new manual entitled Operation,
Maintenance, and Management of Stormwater Management Systems (1998). This manual presents a
comprehensive review of the technical, educational, and institutional elements  needed to assure that
stormwater management systems are designed, built, maintained and operated properly during and after
their construction.  The manual was developed in cooperation with the U.S. EPA Office of Water to
assist individuals responsible for designing, building, maintaining, or operating stormwater management
systems. It will also be helpful to individuals responsible for implementing urban stormwater
management programs.

The book includes fact sheets on 13 common stormwater treatment best management practices (BMPs).
These summarize operation, maintenance, and management needs and obligations, along with
construction recommendations. Other chapters review planning and design considerations,
programmatic and regulatory aspects, considerations for facility owners, construction inspection,
inspection and maintenance after construction, costs and financing, and disposal of stormwater
sediments.  Forms for inspecting BMPs during construction and determining maintenance needs
afterwards are included in the book and in a separate supplement.
Source: [http://www.epa.gov/owowwtrl/NPS/wmi/index.html]
Additional information: [http://www.epa.gov/owowwtrl/NPS/ordinance/osm6.htm] and


States, territories, and authorized Tribes establish section 303(d) lists of impaired waters based on
information contained in their 305(b) reports as well as other relevant and available water quality data.
The section 303(d) list is a prioritized list of waters not meeting water quality standards. The USEPA
has 30 days in which  to approve the lists or add waters to the State's lists, if the Agency determines the
list is not complete. Once a waterbody is placed on the 303(d) list, a TMDL must be prepared for the

A TMDL is a written, quantitative plan and analysis for attaining and maintaining water quality
standards in all seasons for a specific waterbody and pollutant. Specifically, a  TMDL is the sum of the
allowable loads of a pollutant from all contributing point, nonpoint, and background sources. Total
maximum daily loads may be established on a coordinated basis for a group of waterbodies in a
watershed. Total maximum daily loads must be established for waterbodies on the list of impaired
waterbodies and must include the following 11 elements:
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July 2000                                                        Chapter 8.  Management Programs

1.    The name and geographic location of the impaired waterbody;
2.    Identification of the pollutant and the applicable water quality standard;
3.    Quantification of the pollutant load that may be present in the waterbody and still ensure
      attainment and maintenance of water quality standards;
4.    Quantification of the amount or degree by which the current pollutant load in the waterbody,
      including the pollutant load from upstream sources that is being accounted for as background
      loading, deviated from the pollutant load needed to attain and maintain water quality standards;
5.    Identification of source categories, source subcategories or individual sources of pollutant;
6.    Wasteload allocations;
7.    Load allocations;
8.    A margin of safety;
9.    Consideration of seasonal variations;
10.   Allowance for reasonably foreseeable increases in pollutant loads including future growth; and
11.   An implementation plan.

Both the 1996 and 1998 section 303(d) lists, as well as more recent 305(b) reports  reflect similar
patterns: sediments, nutrients, and pathogens are the top three causes of waterbody impairment.
Source: [http://www.epa.gov/owowwtrl/tmdl/faq.html]

Waste Load Allocation
A waste load allocation (WLA) is the proportion of a receiving water's total maximum daily load that is
allocated to point sources of pollution. Water quality models are often utilized by  regulatory agencies in
conducting an assessment to determine a WLA. Models establish a quantitative relationship between a
waste load and its impact on water quality. WLAs are used  by permit writers to establish Water Quality
Based Effluent Limits (WQBELs).
Source: [http://www.epa.gov:80/owmitnet/permits/pwcourse/chapt_06.pdfJ

Continuing Planning Process (CPP)
Each State is required to establish and maintain a continuing planning process (CPP) as described in
section 303(e) of the Clean Water Act. A  State's CPP contains, among other items, a description of the
process that the State uses to identify waters needing water quality-based controls, a priority ranking of
these waters, the  process for developing TMDLs, and a description of the process used to receive public
review of each TMDL.  Descriptions may  be as detailed as the Regional office and the State determine is
necessary to describe each step of the TMDL development process.  This process may be included as
part of the EPA/State Agreement for TMDL development.
[Source: http://www.epa.gov/owowwtrl/tmdl/decisions/dec4.html]


Point and nonpoint source pollutant trading involves financing reductions in nonpoint source pollution in
lieu of undertaking more expensive  point source pollution reduction efforts. A trading program is
intended to produce cost savings for point source dischargers while improving water quality.
Implementing a trading program requires a waterbody identifiable as a watershed or segment, as well as
a measurable combination of point sources and controllable  nonpoint sources.  There must be significant
load reductions for which the cost per pound reduced for nonpoint source controls  is lower than the cost
for upgrading point source controls. Lastly, point source dischargers must face requirements to either

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July 2000                                                         Chapter 8. Management Programs

upgrade facility treatment capabilities or trade for nonpoint source reductions in order to meet water
quality goals.

Such a program allows the private sector to allocate its resources to reduce pollutants in the most
cost-effective manner, and it encourages the development of a watershed-wide or basin-wide
approach to water quality protection. A pollutant trading program also requires cooperation between
agencies, and requires a system to arrive at trading ratios between point and nonpoint source controls.

For example, in a North Carolina watershed, the Tar-Pamlico Basin Association (a coalition of point
source dischargers) and State and regional environmental groups have proposed a two-phased nutrient
management strategy that incorporates point and nonpoint source pollutant trading. The plan requires
association members to finance nonpoint source reduction activities in the basin if their nutrient
discharges exceed a base allowance.
Source: [http://www.epa.gov/OWOW/NPS/MMGI/funding.html#9]


During the first 15 years of the national program to abate and control water pollution, EPA and the States
have focused most of their water pollution control activities on traditional "point sources," such as
discharges through pipes from sewage treatment plants and industrial facilities. These point sources
have been regulated by EPA and the States through the NPDES permit program established by section
402 of the Clean Water Act. Discharges of dredged and fill materials into wetlands have also been
regulated by the U.S. Army Corps of Engineers and EPA under section 404 of the Clean Water Act.

The Nation has greatly reduced pollutant loads from point  source discharges and has made considerable
progress in restoring and maintaining water quality as a result of the above activities.  However, the
gains in controlling point sources have not solved all  of the Nation's water quality problems.  Recent
studies and surveys by EPA and by State/Tribal water quality agencies indicate that the majority of the
remaining water quality impairments in our nation's rivers, streams, lakes, estuaries, coastal waters, and
wetlands result from nonpoint source pollution and other nontraditional sources, such as urban storm
water discharges and combined sewer overflows.

Nonpoint source pollution  generally results from land runoff, precipitation, atmospheric deposition,
drainage, seepage, or hydrologic modification.  Technically, the term "nonpoint source" is defined to
mean any source of water pollution that does not meet the legal definition of "point source" in section
502(14) of the Clean Water Act, defined in the preceding section.  Although diffuse runoff is generally
treated as nonpoint source  pollution, runoff that enters and is discharged from conveyances such as those
described above is treated as a point source discharge and hence is subject to the permit requirements of
the Clean Water Act.  In contrast, nonpoint sources are not subject to Federal permit requirements.

The pollution of waters by nonpoint sources is caused by rainfall or snowmelt moving over and through
the ground.  As the runoff moves, it picks up and carries away natural pollutants and pollutants resulting
from human activity, finally depositing them into lakes, rivers, wetlands, coastal waters, and ground
waters.  Nonpoint source pollution can also be caused by atmospheric deposition of pollutants onto
waterbodies.  Furthermore, hydrologic modification is a form of nonpoint source pollution that often
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July 2000                                                        Chapter 8. Management Programs

adversely affects the biological and physical integrity of surface waters. A more detailed discussion of
the range of nonpoint sources and their effects on water quality and riparian habitats is provided in
subsequent chapters of this guidance. A summary of State laws related to nonpoint source pollution can
be found in the Almanac of Enforceable State Laws to Control Nonpoint Source Water Pollution (ELI
1988). This report can be accessed on the internet at http://www.eli.org/bookstore/research.htm.


Guidance Specifying Management Measures for Sources of Nonpoint Pollution in Coastal Waters
(USEPA 1993a) was developed by EPA for the planning and implementation of Coastal Nonpoint
Pollution Programs. The guidance focuses on controlling five major categories of nonpoint sources that
impair or threaten waters nationally.  Management measures are specified for (1) agricultural runoff; (2)
urban runoff (including developing and developed areas); (3)  silvicultural (forestry) runoff;  (4) marinas
and recreational boating; and (5) hydromodification (e.g., channelization and channel modification,
dams, and streambank and shoreline erosion).  EPA guidance also includes management measures for
wetlands, riparian areas, and vegetated treatment systems that apply generally to various categories  of
sources of nonpoint pollution.  Management measures are defined in the Coastal Zone Act
Reauthorization Amendments of 1990 as economically achievable measures to control the addition of
pollutants to waters, which reflect the greatest degree of pollutant reduction achievable through the
application of the best available nonpoint pollution control practices, technologies, processes, siting
criteria, operating methods, or other alternatives.

The following section outlines some of the management measures specified in the CZARA guidance for
the various types of nonpoint sources. These measures should be considered when implementing
programs targeting nutrient releases into waters of the U.S.

Agricultural Runoff
         erosion and  sediment control
      •   control of facility wastewater and runoff from confined animal facilities
      •   nutrient management planning on cropland
         grazing management systems
         irrigation water management

Urban Runoff
         control of runoff and erosion from existing and developing areas
         construction site runoff and erosion control
      •   construction site chemical control (includes fertilizers)
      •   proper design, location, installation, operation, and maintenance of on-site disposal systems
         pollution prevention education (e.g., household chemicals, lawn and garden activities, golf
         courses, pet waste, on-site disposal systems, etc.)
      •   planning, siting, and developing roads, highways, and bridges (including runoff management)

Silvicultural Runoff
         streamside management
      •   road construction and management
      •   forest chemical management (includes fertilizers)

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July 2000
Chapter 8. Management Programs
      •   revegetation
         preharvest planning, harvesting management

Marinas and Recreational Boating
      •   siting and design
         operation and maintenance
      •   storm water runoff management
      •   sewage facility management
      •   fish waste management
         pollution prevention education (e.g., proper boat cleaning, fish waste disposal, and sewage
         pump out procedures)

Hydromedification (i.e., channelization, channel modification, dams)
         minimize changes in sediment supply and pollutant delivery rates through careful planning and
      •   erosion and sediment control
         chemical and pollutant control (includes nutrients)
         stabilization and protection of eroding streambanks or shorelines

Wetlands, Riparian Areas, Vegetated Treatment Systems
         protect the NFS abatement and other functions of wetlands and riparian areas through
         vegetative composition and cover, hydrology of surface and ground water, geochemistry of the
         substrate, and species composition
      •   promote restoration of preexisting function of damaged and destroyed wetlands and riparian
         promote the use of engineered vegetated treatment systems if they can serve a NFS pollution
         abatement function


Efforts to control nonpoint source pollution include nonpoint source management programs, the National
Estuary Program, atmospheric deposition, coastal nonpoint pollution control programs, and Farm Bill
conservation provisions.  These efforts are described below.

Nonpoint Source Management Programs
In 1987, in view of the progress achieved in controlling point sources and the growing national
awareness of the increasingly dominant influence of nonpoint source pollution on water quality,
Congress amended the Clean Water Act to focus greater national efforts on nonpoint sources. In the
Water Quality Act of 1987, Congress amended section 101, "Declaration of Goals and Policy," to add the
following fundamental principle:

       It is the national policy that programs for the control of nonpoint sources of
       pollution be developed and implemented in an expeditious manner so as to
       enable the goals of this Act to be met through the control of both point and
       nonpoint sources of pollution.
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July 2000                                                       Chapter 8. Management Programs

More importantly, Congress enacted section 319 of the Clean Water Act, which established a national
program to control nonpoint sources of water pollution. Under section 319, States address nonpoint
pollution by assessing nonpoint source pollution problems and causes within the State, adopting
management programs to control the nonpoint source pollution, and implementing the management
programs.  While not required, many States have incorporated the management measures specified in the
1993 CZARA guidance into their State Nonpoint Source Management Programs.

Section 319 also authorizes EPA to issue grants to States to assist them in implementing those
management programs or portions of management programs which have been approved by EPA. As of
FY 2000, over $ 1 billion in grants have been given to States, Territories, and Tribes for the
implementation of nonpoint source pollution control programs.

For additional information on the Nonpoint Source Management Program and distribution of Section 319
grants in your State, contact your State's designated nonpoint source agency.  For many states, the
nonpoint source agency is the State Water Quality Agency. However, in several instances, other
agencies or departments are given nonpoint source responsibility (see Table 5).

National Estuary Program
EPA also administers the National Estuary Program under section 320 of the Clean Water Act. This
program focuses on point and nonpoint pollution in geographically targeted, high-priority estuarine
waters. Under this program, EPA assists State, regional, and local governments in developing
comprehensive conservation and management plans that recommend priority corrective actions to restore
estuarine water quality, fish populations, and other designated uses of the waters. For additional
information, contact your local estuary program. The following estuaries are currently enrolled in the

     •   Albemarle-Pamlico Sounds, NC
     •   Barataria-Terrebonne Estuarine Complex, LA
         Barnegat Bay, NJ
         Buzzards Bay, MA
     •   Casco Bay, ME
     •   Charlotte Harbor, FL
         (Lower) Columbia River Estuary, OR and WA
         Corpus Christi Bay, TX
     •   Delaware Estuary, DE, NJ, and PA
     •   Delaware Inland Bays, DE
         Galveston Bay, TX
         Indian River Lagoon, FL
     •   Long Island Sound, NY and CT
     •   Maryland Coastal Bays, MD
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July 2000
                                      Chapter 8. Management Programs
         Table 5. States for which the nonpoint source agency is not the water quality agency.
                 State Nonpoint Source Agency






State Department of Soil and Water Conservation

State Department of Soil and Water Conservation

State Department of Soil and Water Conservation

State Department of Agriculture

Department of Soil and Water Conservation (for agriculture)
Texas Water Quality Board (all other nonpoint sources)

State Department of Agriculture

State Department of Soil and Water Conservation
      •   Massachusetts Bays, MA
      •   Mobile Bay, AL
         Morro Bay, CA
      •   Narragansett Bay, RI
      •   New Hampshire Estuaries, NH
      •   New York-New Jersey Harbor, NY and NJ
         Peconic Bay, NY
      •   Puget Sound, WA
      •   San Francisco  Estuary, CA
      •   San Juan Bay,  PR
         Santa Monica Bay, CA
      •   Sarasota Bay, FL
         Tampa Bay, FL
      •   Tillamook Bay, OR

Atmospheric Deposition
While runoff from agricultural and urban areas may be the largest sources of nonpoint pollution, growing
evidence suggests that atmospheric deposition may have a significant influence on nutrient enrichment,
particularly from nitrogen (Jaworski  et al. 1997). Gases released through fossil fuel combustion and
agricultural practices are two major sources of atmospheric N that may be deposited in waterbodies
(Carpenter et al.  1998). Nitrogen and nitrogen compounds formed in the atmosphere return to the earth
as acid rain or snow, gas, or dry particles (http://www.epa.gov/acidrain/effects/envben.html). EPA  has
several programs that address the issue of atmospheric deposition, including the National Ambient Air
Quality Standards, the Atmospheric Deposition Initiative, and the Great Waters Program.
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July 2000                                                         Chapter 8. Management Programs

National Ambient Air Quality Standards
The Clean Air Act provides the principal framework for national, State, and local efforts to protect air
quality. Under the Clean Air Act, national ambient air quality standards (NAAQS) for pollutants which
are considered harmful to people and the environment are established.

The Clean Air Act established two types of national air quality standards. Primary standards set limits
to protect public health, including the health of "sensitive" populations such as asthmatics, children, and
the elderly. Secondary standards set limits to protect public welfare, including protection against
decreased visibility, damage to animals, crops, vegetation, and buildings

Atmospheric Deposition Initiative
In 1995, EPA's Office of Water established an "Air Deposition Initiative" to work with the EPA Office
of Air and Radiation to identify and characterize air deposition problems with greater certainty and
examine solutions to address them.  The Air and Water Programs are cooperating to assess the
atmospheric deposition problem, conduct scientific research, provide innovative solutions to link Clean
Air Act and Clean Water Act tools to reduce the of these pollutants, and communicate the findings to the
public. To date, most efforts have focused on better understanding of the links between nitrogen and
mercury emissions and harmful effects on water quality and the environment. Significant work has also
been done towards quantifying the benefits to water quality of reducing air emissions and developing
sensible, cost effective approaches to reducing the  emissions and their ecosystem and health effects

Great Waters Program
On November 15, 1990, in response to mounting evidence that air pollution contributes to water
pollution, Congress  amended the Clean Air Act and included provisions that established research and
reporting requirements related to the deposition of hazardous air pollutants to the "Great Waters."  The
waterbodies designated by these provisions are the Great Lakes, Lake Champlain, and Chesapeake Bay.
As part of the Great Waters Program, Congress requires EPA, in cooperation with the National Oceanic
and Atmospheric Administration, to monitor hazardous pollutants  by establishing sampling networks,
investigate the deposition of these pollutants, improve monitoring  methods, monitor for hazardous
pollutants in fish and wildlife, determine the contribution of air pollution to total pollution in the Great
Waters, evaluate any adverse effects to public health and the  environment, determine sources of
pollution, and provide a report to Congress every 2 years.  These reports provide an information base that
can be used to establish whether air pollution is a significant  contributor to water quality problems of the
Great Waters, determine whether there are significant adverse effects to humans or the environment,
evaluate the effectiveness of existing regulatory programs in  addressing these problems, and assess
whether additional regulatory actions are needed to reduce atmospheric deposition to the Great Waters.
For more detail, the  Great Waters biennial Reports to Congress discuss current scientific understanding
of atmospheric deposition (http://www.epa.gov/airprogm/oar/oaqps/gr8water/xbrochure/program.html).

Coastal Nonpoint Pollution Control Programs
In November 1990,  Congress enacted the Coastal Zone Act Reauthorization Amendments of 1990.
These Amendments were intended to address several concerns, a major one of which is the impact of
nonpoint source pollution on coastal waters.
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July 2000                                                        Chapter 8. Management Programs

To address more specifically the impacts of nonpoint source pollution on coastal water quality, Congress
enacted section 6217, "Protecting Coastal Waters," which was codified as 16 U.S.C. -1455b. This
section provides that each State with an approved coastal zone management program must develop and
submit a Coastal Nonpoint Pollution Control Program for EPA and the National Oceanic and
Atmospheric Administration (NOAA) approval. The purpose of the program "shall be to develop and
implement management measures for nonpoint source pollution to restore and protect coastal waters,
working in close conjunction with other State and local authorities."

States with Coast Nonpoint Pollution Control Programs are required to include measures in their
programs that are "in conformity" with the 1993 CZARA guidance, as discussed previously. A listing of
States with Coastal Nonpoint Pollution Control Programs is presented in Table 6. For additional
information on the programs in these States, contact the State water quality agency.

Farm Bill Conservation Provisions
Technical and financial assistance for landowners seeking to preserve soil and other natural resources is
authorized by the Federal Government under provisions of the Food Security Act (Farm Bill).
Provisions of the 1996 Farm Bill relating directly to installation and maintenance of BMPs are
summarized in the following sections.  Contact your Natural Resources Conservation Service (NRCS)
State Conservationist's office for State-specific information.

Environmental Conservation Acreage Reserve Program (ECARP)
ECARP is an umbrella program established by the 1996 Farm Bill which contains the conservation
Reserve Program (CRP), Wetlands Reserve Program (WRP), and Environmental Quality Incentives
Program (EQIP). It authorizes the Secretary of Agriculture to designate watersheds, multi-state areas, or
regions of special environmental sensitivity as conservation priority areas which are eligible for
enhanced Federal assistance. Assistance in priority areas is to be used to help agricultural producers
comply with NPS pollution requirements of the Clean Water Act and other State or Federal
environmental laws. The ECARP is authorized through 2002.

Conservation Reserve Program (CRP)
First authorized by the Food Security Act of 1985 (Farm Bill), this voluntary program offers annual
rental payments, incentive payments, and cost-share assistance for establishing long-term, resource-
conserving cover crops on highly erodible land.  CRP contracts are issued for a duration of 10 to 15 years
for up to 36.4 million acres of cropland and marginal pasture. Land can be accepted into the CRP
through a competitive bidding process through which all offers are ranked using an environmental
benefits index, or through continuous sign-up for eligible lands where certain special conservation
practices will be implemented.

The Conservation Reserve Enhancement Program  (CREP) is a new initiative of CRP authorized under
the  1996 Federal Agricultural Improvement and Reform Act. CREP is a joint, State-federal program
designed to meet specific conservation objectives. CREP targets State and Federal funds to achieve
shared environmental goals of national and state significance. The program uses financial incentives to
encourage farmers and ranchers to voluntarily protect soil, water,  and wildlife resources.
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July 2000
                               Chapter 8. Management Programs
Table 6. An alphabetical list of States and Territories with Coastal Nonpoint Pollution Control
            States and Territories with Coastal Nonpoint Pollution Control Programs


 American Samoa












New Hampshire

New Jersey

New York

North Carolina

Northern Mariana Islands


Puerto Rico

Rhode Island

South Carolina

Virgin Islands



Wetlands Reserve Program (WRP)
The WRP is a voluntary program to restore and protect wetlands and associated lands. Participants may
sell a permanent or 30-year conservation easement or enter into a 10-year cost-share agreement with
USDA to restore and protect wetlands.  The landowner voluntarily limits future use of the land, yet
retains private ownership. The NRCS provides technical assistance in developing a plan for restoration
and maintenance of the land. The landowner retains the right to control access to the land and may lease
the land for hunting, fishing, and other undeveloped recreational activities.

Environmental Quality Incentives Program
The EQIP was established by the 1996 Farm Bill to provide a voluntary conservation program for
farmers and ranchers who face serious threats to soil, water, and related natural resources. EQIP offers
financial, technical, and educational help to install or implement structural, vegetative, and management
practices designed to conserve soil and other natural resources.  Current priorities for these funds dictate
that one half of the available monies be directed to livestock-related concerns. Cost-sharing may pay up
to 75% of the costs for certain conservation practices. Incentive payments may be made to encourage
producers to perform land management practices such as nutrient management, manure management,
integrated pest management, irrigation water management, and wildlife habitat management.

Wildlife Habitat Incentives Program (WHIP)
This program is designed for parties interested in developing and improving wildlife habitat on private
lands.  Plans are developed in consultation with NRCS and the  local Conservation District. USDA will
provide technical assistance and cost-share up to 75% of the cost of implementing the wildlife
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July 2000                                                        Chapter 8. Management Programs

conservation practices.  Participants generally must sign a 5- to 10-year contract with USDA which
requires that they maintain the improvement practices.

Forestry Incentives Program (TIP)
Originally authorized in 1978, the FIP allows cost sharing of up to 65% (up to a maximum of $10,000
per person per year) for tree planting, timber stand improvement, and related practices on nonindustrial
private forest land. The FIP is administered by NRCS and the U.S. Forest Service. Cost share  funds are
restricted to individuals who own no more than 1,000 acres of eligible forest land.

Conservation of Private Grazing Land
This program was authorized by the 1996 Farm Bill for the purpose of providing technical and
educational assistance to owners of private grazing  lands.  It offers opportunities for better land
management, erosion reduction, water conservation, wildlife habitat, and improving soil structure.

Cooperative Extension
State land grant universities and Cooperative Extension play an important role in management
implementation. They have the expertise to research, transfer, and implement agriculture management
systems that will be needed to meet nutrient criteria. In addition, they have developed models and other
predictive management tools that will aid in selecting the most appropriate management activities.
Contact your local Cooperative Extension Agent, or the Agriculture Department at a State land grant
university for more information on the services they can provide.
                                           PAGE 124

Chapter 9.
Monitoring  and
Reassessment of
Nutrient Criteria
Monitoring and
Criteria Ranges

After criteria are set, compliance determinations made, and management plans implemented, resource
managers should continue to monitor river and stream systems while reassessing goals and nutrient
criteria.  This step should (1) evaluate the appropriateness of established nutrient criteria, (2) ensure that
river and stream systems are responding to management action, and (3) assess whether water quality
goals established by the resource manager are being met.

Those streams selected for management may be approached using a rational course of action beginning
with a statement of major problems or symptoms and progressing logically to a final assessment to
determine the relative success of the effort.  Throughout this process, the water quality manager must re-
examine (1) the initial goals identified for the stream system(s) prior to criteria development and (2)
subsequent management actions taken to evaluate the effectiveness of criteria and management plans.
The manager should assess the efficacy of management actions and potentially re-evaluate the
appropriateness of established criteria if monitoring data indicate that goals are not being met.


The management plan should always include "before," "during," and "after" water resource quality
monitoring to demonstrate the relative response of the system to management efforts, thus the
recommendation that initial survey stations should generally be maintained and expanded. Availability
of continuous, year-to-year monitoring data is critical and can be used as a bench mark for evaluating
progress. If monitoring data indicate that water quality is improved, monitoring should continue to
validate the progress made.  Should water quality decline, the criteria development process should be re-
visited and potentially revised. At a minimum, monitoring data should be reevaluated every five years to
gauge progress. The reevaluation of monitoring data should include seasonality and periodic data
assessment intervals for management review to provide the opportunity for responses to changing
circumstances, modifications of methods, schedules, and changes of emphasis as needed. Control of
point source nutrients may result in fairly quick system recovery from cultural eutrophication (Edmonson
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July 2000	Chapter 9. Monitoring and Reassessment of Nutrient Criteria Ranges

1994), although nutrient cycling mechanisms and changes in food web dynamics may result in a
persistent eutrophic state in many systems (Carpenter et al. 1999). Therefore, continued monitoring and
reevaluation of nutrient control strategies is of particular importance.


Management projects are frequently planned, initiated, and concluded with new initiatives undertaken to
meet pressing schedules without sufficiently evaluating what was or was not initially accomplished.
Review of  progress, original objectives or goals, and monitoring data will reveal whether the river or
stream trophic state was successfully protected or improved. Just as important, this evaluation will
provide the documentation necessary to determine if methods and techniques attempted in this instance
can be applied, perhaps with modification, elsewhere. Alternatively, it will also  reveal if mistakes were
made which should be noted and avoided in future projects and if perhaps a sequel to the current project
is required to fully accomplish that which was intended.


Monitoring programs initiated and expanded in the course of the project can now be reduced to the
periodic measuring of key variables at critical times and locations. At this stage, the purpose of
monitoring is to keep sufficiently informed of the status of the river or stream to  ensure that the
protection or remediation achieved is maintained. Intervention should be possible  at an early point to
minimize the costs of remediation if periodic maintenance monitoring indicates a return of trophic
decline. The evaluation and periodic monitoring steps of this process essentially close the loop. If new
issues arise, the manager returns to step one with a new problem statement.
                                            PAGE 126


Agbeti, M. D.  1992. The relationship between diatom assemblages and trophic variables: A
       comparison of old and new approaches. Can. J. Fish. Aquat. Sci. 49:1171-1175.

Alexander, R. B., J.R. Slack, A.S. Ludtke, K.K. Fitzgerald, and T.L. Schertz.  1996.  Data from selected
       U.S. Geological Survey National Stream Water-Quality Monitoring Networks: USGS Digital
       Data Series DDS-37, 2 compact disks.

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                                          PAGE 151

July 2000                                                            REFERENCES
                                    PAGE 152


The following five case studies are meant to capture some of the variability of stream systems located
throughout the country. Although these case studies exhibit varying levels of complexity, they are meant
to provide the reader with real-world examples of how criteria can be developed on a practical level and
several region-specific issues that may be encountered as one works through the criteria development
process. The ecoregional nutrient criteria process discussed in the Tennessee  case study involves
refinement of the Level III ecoregions found within the State; identification and monitoring of reference
stream systems; and correlational analyses of nutrient levels, conventional water chemistry parameters,
and biological indices to derive criteria. In contrast, the Clark Fork, Montana, case study delineates a
process for setting target nutrient and algal levels based on a combination of modified established
criteria, literature values, and observed thresholds for nuisance algal growth.  The Upper Midwest river
systems case study describes the results of a cooperative effort among three USGS NAWQA projects in
the upper Midwest Corn Belt region that evaluated algal and macroinvertebrate response to nonpoint
agricultural sources relative to naturally-occurring factors (e.g.,  riparian vegetation, hydrology).  The
Bow River, Canada, case study details the reduction of nuisance biomass (both periphyton and
macrophytes) over a 16-year period through decreases in nitrogen (-50%) and phosphorus (80%) from
domestic wastewater effluent. Finally, the desert stream case study discusses several of the determinants
of nutrient regimes in desert streams that should be  considered when developing nutrient criteria for
these, as well as other, complex, highly variable stream systems.
                                           PAGE A-l

July 2000	Appendix A.  Case Studies
                                           PAGE A-2

July 2000	Appendix A.  Case Studies


In 1992, the Tennessee DWPC (Division of Water Pollution Control) faced an important decision on how
water quality assessment would be done in the future.  When program status was assessed, there were
problems that were likely to be amplified in the future.  For example:

      •   The "one-size-fits-all" statewide numeric criteria approach provided stability, but lacked
         regional flexibility.  Statewide criteria were clearly overprotective in parts of the state, but
         arguably underprotective in other areas.

      •   Narrative criteria were based on a verbal description of water quality, rather than a number.
         Thus, they provided flexibility, but lacked an objective means of interpretation. As an
         example, the narrative criterion for biological integrity states "waters shall not be modified to
         the extent that the diversity and/or productivity of aquatic biota within the receiving waters is
         substantially reduced'. However, an interpretation of the word "substantially" was not

      •   Unlike biological integrity, nutrients did not have specific narrative criteria.  Nutrients were
         assessed under the more generic "free from" statements found in toxicity sections of the fish
         and aquatic life criteria and under "aesthetic" sections of the recreational criteria.  Thus, before
         any stream could be assessed as impacted by nutrients, the existence of a "problem" had to be

      •   Tennessee was encouraged by EPA to convert to a watershed approach for issuance of water
         quality permits.  Without a sense of regional variability in water quality, there was  a distinct
         disadvantage in goal setting for these watersheds. Additionally, the rigors of 303(d) listing and
         TMDL development required accurate interpretation of Tennessee's narrative water quality
         criteria. The specter of lawsuits by citizens and members of the regulated community required
         that assessments be defensible.

A method was needed for comparing the existing conditions found in a stream to unimpacted conditions.
This reference condition varied across the state. The reference condition established should be  within a
similar area, to avoid "apples and oranges" comparisons.  It was determined that ecoregions were the best
geographic basis upon which to make this assessment.
     An ecoregion is a relatively homogeneous area defined by similarity of climate, landform, soil,
          potential natural vegetation, hydrology, and other ecologically relevant variables.
The "Ecoregions of the United States" map (Level III) developed in 1986 by James Omernik of EPA's
Corvallis Laboratory delineated eight ecoregions in Tennessee. The DWPC arranged for Omernik and
Glenn Griffith to sub-regionalize and update state ecoregions.

The Tennessee Ecoregion Project began in 1993 and was envisioned to occur in three phases:

                                            PAGE A-3

July 2000	Appendix A. Case Studies


Phase I of the project involved geographic data gathering, development of a draft sub-regionalization
scheme, and ground-truthing of the draft into a final product. This product included new maps and
digitized coverages for use in the DWPC GIS system. This part of the project began in 1993 and was
completed in 1995. This refinement resulted in a total of 14 ecoregions for the state (Figure A-l).


EPA and DWPC staff identified potential reference streams.  Reference streams selected were located in
relatively unimpacted watersheds typical for that ecoregion (Figure A-2). When possible, watersheds
within state or federally protected areas were selected.
A reference stream is a least impacted waterbody within an ecoregion that can be monitored to establish
  a baseline to which other waters can be compared. Reference streams are not necessarily pristine or
  	undisturbed by humans.	
Division staff visited each candidate stream.  Chemical and benthic macroinvertebrate samples were used
to cull the list of streams down to a final list. Three reference streams per sub-ecoregion were considered
the minimum requirement.


Since August 1996, final selected reference sites have been monitored quarterly.  During the first year of
the project, water chemistry was monitored using grab samples collected on three consecutive days (if
possible).  Chemical sampling procedures followed modified clean technique methodology as outlined in
the Division's Chemical Standard Operating Procedure: Modified Clean Technique Sampling Protocol
(TNDEC 1996).

Chemical sampling at reference sites generally included all the parameters historically included by the
Division in its long-term ambient monitoring network.  As a concession to resource constraints, certain
parameters, such as mercury, were dropped after they were never detected the first year of sampling.
Additional parameters such as chlorophyll  a were considered to have value, but were not sampled due to
the need make the best use  of program funding. Division staff were recently trained in algal assessment
techniques and will likely incorporate rapid biological assessment protocols in future sampling efforts.

Macroinvertebrate samples were collected  at ecoregional  reference sites beginning in August 1996.
Habitat and flow were also assessed.  Outside expertise was sought to analyze the monitoring data to
determine how sub-ecoregions aggregate by aquatic habitat and biological community to form
ecosystems or bioregions. This step was essential for assessing benthic communities accurately and
                                           PAGE A-4

July 2000
Appendix A. Case Studies
Figure A-l. Tennessee Level IV ecoregions and locations of reference streams.
                                           PAGE A-5

July ZW.W
Appendix A. CUM.' S
       .\-2. rhe link River within the Great Smoky Mountains Naiional Park was selecled as a
id'.-i',-ni.v strain for
                                           I* ua A-Ci

July 2000	Appendix A.  Case Studies

How Are Reference Stream Data Being Used?
For the first time, the DWPC has regionally-based chemical, physical, and biological data representing
least impacted conditions in Tennessee.  These data are important to our program and have multiple

For some time, it was known that an ecoregion-specific approach to certain water quality standards
would provide greater accuracy.  This ecoregion project has provided the data necessary to initiate
nutrient criteria discussions.

Figures A-3 and A-4 illustrate the levels of total phosphorus (TP) and nitrate-nitrite (NO3-NO2),
respectively, documented at reference streams within each ecoregion.  The box and whisker plot shows
median measured concentrations and ranges. Based  on the data collected, TP at less impacted streams is
generally higher in West Tennessee than Middle and East Tennessee.

Finalizing the Ecoregion Reference Stream Nutrient Database
Additional steps are needed to finalize the ecoregion nutrient database:

          Incorporate data from other States. If reference streams in neighboring States are located
          within shared ecoregions and are selected  and sampled in a similar manner to those in
          Tennessee, the nutrient data can be added  into our database.

          Review the database for quality assurance. Data will be checked for outliers that may
          represent data entry errors. Outliers that indicate degrading conditions in reference streams
          will be identified. The Division considered eliminating outliers based on a consistent
          rationale, such as values more than two standard  deviations from the mean, but decided against
          such an approach.

Development of Regional Interpretations of Narrative Nutrient Criteria
Division staff will propose ecoregion-specific interpretations of the narrative nutrient criteria for TP and
nitrate-nitrite for the year 2000 triennial water quality standards review. These numeric goals will be
used primarily for water quality assessment purposes.

The specific goals will likely be based on the establishment of the nutrient concentration for each
ecoregion or subecoregions database at the 90th percentile of the reference stream data.  (However, the
Division has not ruled out the possibility of setting the  criteria at the 75th percentile.) As an important
part of the process, Division staff will statistically analyze nutrient levels and their ranges at each sub-
ecoregion. Where significant differences exist between sub-ecoregions, the nutrient criteria will be
established at the sub-ecoregion level. Where no significant difference is found between sub-ecoregions,
the data will be aggregated back to the ecoregion level.

These numeric goals will provide the means to assess nutrient levels at similar  streams within the same
ecoregion. Streams with nutrient levels less than the 90th (or 75th) percentile of the reference  stream
database will be considered to meet the narrative criteria. Streams with nutrient levels higher than the
reference  stream database range will be considered in violation of the narrative criteria. These streams

                                            PAGE A-7

July 2000
Appendix A.  Case Studies
                                      Total Phosphorus (mg/l)
Figure A-3.  Total phosphorus concentrations (yt/g/L) for reference streams within each ecoregion.

Key: 1 = Mississippi Alluvial Plain, 2 = Mississippi Valley Loess Plains, 3 = Southeastern Plains,
4 = Interior Plateau, 5 = Southeastern Appalachians, 6 = Central Appalachians, 7 = Ridge and Valley,
8 = Blue Ridge Mountains.
                                             PAGE A-8

July 2000
Appendix A.  Case Studies








                                             NO2+3 (mg/1)
Figure A-4. Total nitrate-nitrite concentrations (mg/L) for reference streams within each ecoregion.

Key: 1 = Mississippi Alluvial Plain, 2 = Mississippi Valley Loess Plains, 3 = Southeastern Plains,
4 = Interior Plateau, 5 = Southeastern Appalachians, 6 = Central Appalachians, 7 = Ridge and Valley,
8 = Blue Ridge Mountains.
                                             PAGE A-9

July 2000	Appendix A.  Case Studies

will be added to the 303(d) list for future TMDL generation. Additionally, the regional interpretation of
the narrative criteria will provide the goal for TMDL control strategies.

Data Relationships
Division staff have taken a preliminary look at the reference stream data in an attempt to investigate
relationships between sampled parameters. Examination of these relationships has three facets: (1)
consideration of possible nutrient data surrogates, (2) exploring relationships between nutrient levels and
biological indices, and (3) comparison of reference stream data to EPA's regional nutrient database.

1.     The initial investigation was whether there was a relationship between nutrient levels and other
      chemical constituents in the water column.  If a strong correlational relationship could be
      established, these other values could be used as data surrogates if nutrient data were unavailable or
      as a less costly substitute for nutrient sampling.

      Relationships were investigated primarily for turbidity, total organic carbon (TOC), and suspended
      solids.  We found numerous positive correlations, but the large number of data points at the
      detection level caused relationships to be suspect. For example, Figures A-5 and A-6  illustrate the
      relationship between total phosphorus and turbidity (r2 value = 0.282) as well as total phosphorus
      and TOC (r2 value = 0.163) in ecoregion 67g.

      We  intend to do the same type analysis with regional data from EPA's national nutrient database.
      At least in theory,  this database would contain fewer observations below detection level.

2.     If the correlation between either TP or nitrate+nitrite levels and the quality of biological
      communities can be established, a stronger rationale for ecoregion-specific numerical nutrient
      criteria can be provided.  However, it should be noted that even where correlation is strong,
      identifying a numeric nutrient criteria is dependent on knowing the biological integrity score above
      which, the community is considered impaired.  Fortunately, as in the case of nutrients, this
      biological integrity goal can be established from the reference stream  data.

      In sub-ecoregion 71h (Outer Nashville Basin), a preliminary comparison was done. Nitrate-nitrite
      levels were compared to two biological indices frequently used by the Division, the North Carolina
      Biotic Index (NCBI) and the Hilsenhoff Biotic Index (EPA Rapid Bioassessment Protocols, 1999).
      While there was some scatter in the dataset, a relationship was suggested which was slightly
      stronger for the Hilsenhoff index (Figure A-7) than the NCBI.  (Figure A-8).

      An additional test was done with the appearance of a relationship between nitrate-nitrite and NCBI
      scores.  According to the reference stream database for sub-ecoregion 71h,  the 75th percentile of the
      NCBI data is a score of approximately 5.0.  Presuming that an NCBI score of 5.0 is the biological
      goal for sub-ecoregion 71h, then according to the above chart, nitrate-nitrite levels should not
      exceed approximately 1.2 mg/L. Following the same approach with the Hilsenhoff scores also
      produced a similar nitrate-nitrite level, approximately 1.2 mg/L. It is interesting to note that the
      90th percentile of the reference stream nitrate-nitrite data for 71h is approximately 1.0 mg/L.
                                            PAGE A-10

July 2000
                                                 Appendix A. Case Studies








                         01    23456789    10

                                  Total Organic Carbon (mg/l)

Figure A-5. Relationship between total phosphorus and TOC (r2 value = 0.163) in ecoregion 67g.

July 2000
Appendix A. Case Studies
                                      20     30     40    50     60

                                           TURBIDITY (NTU)
Figure A-6. Relationship between total phosphorus and turbidity (r2 value = 0.282) in ecoregion 67g.
                                           PAGE A-12

July 2000
                                                                       Appendix A. Case Studies
                                                         R2 =0.450







             t    2.5


                       0     .2     .4     .6     .8      1     1.2   1.4    1.6

                                      Nitrate + Nitrite (mg/l)

Figure A-7. Relationship between nitrate-nitrite levels and the Hilsenhoff Biotic Index.

                                                   Y = 4.778+ 1.013 *ln(X)
                                          PAGE A-13

July 2000
                                                   Appendix A. Case Studies








                                                  R2 = 0.466
                                             Y = 4.81 + .853 * ln(X)
                  0     .2     .4     .6     .8     1     1.2   1.4   1.6

                                Nitrate* Nitrite (mg/l)

Figure A-8. Relationship between nitrate-nitrite levels and the North Carolina Biotic Index (NCBI).
                                      PAGE A-14

July 2000	Appendix A. Case Studies

     While the two values, 1.2 and 1.0 mg/L, are not exactly the same, clearly these two methods of
     criteria development can be used to strengthen the rationale for a final criteria recommendation or
     to justify a "margin of safety". It also demonstrates that should the Division set the nitrate+nitrite
     goal for 71h at 1.0 mg/L, that level should generally be protective of biological integrity.

3.    Another potential methodology for nutrient criteria development was examined. According to EPA
     draft guidance, the reference conditions may be compared to all other nutrient data to potentially
     provide a range for criteria selection.  EPA suggests that the range is established by comparing the
     reference stream data at the 75th percentile with the 25th percentile of all other data. We were
     curious to see if this approach would work and if so, would it provide values similar to those we
     had already identified.

     To assist in this effort, EPA provided us with the nutrient databases from STORET for the three
     large nutrient regions in Tennessee. (For purposes of this initial test, only Tennessee  STORET
     data were included.) Nutrient Region XI in east Tennessee is a combination of Level III
     ecoregions 66, 67, 68, and 69.  Nutrient Ecoregion IX in middle Tennessee is composed of
     Ecoregions 71, 65, and 74. Ecoregion 73 in west Tennessee is Nutrient Ecoregion X.

     The EPA nutrient database was primarily data collected by the Division of Water Pollution
     Control, the Tennessee Valley Authority (TVA), and  the U.S. Geological Survey (USGS).  As we
     were familiar with TVA's  monitoring program, we were concerned that some percentage of their
     data was from lakes or embayments. Since we were developing stream nutrient criteria, rather than
     lake or embayment criteria, we did not consider it appropriate to include non-stream data. Lacking
     the time to identify and cull only the embayment or lakes data from the database, we decided to
     exclude all TVA data.

     Figure A-9 illustrates a comparison of the National nutrient database for Nutrient Ecoregion
     Region XI and the reference stream database for the same geographic area.  The 75th percentile of
     the reference stream data and the 25th percentile of the National Nutrient database lined up well for
     some ecoregions (68, 69, & 66), but not for the Central Appalachian Ridge and Valley Region (67).

     We also  looked at EPA draft Nutrient Aggregate Ecoregion IX in West Tennessee (Figure A-10).
     Data for total phosphorus were elevated nearly an order of magnitude higher than the reference
     stream data.  We discovered that a few stations provided a sizable number of data points within the
     database. It is possible that some of these data represent "storm chasing" sampling events designed
     to quantify worst case nutrient loadings. Another possibility is  that  sampling in the phosphorus-
     rich soils of ecoregion 71 biased the database. If we can identify these sites and determine that
     these data are not representative of the ambient water quality in the ecoregion, these data could be
     excluded and the database re-formed.


With the assistance of EPA, the Tennessee Division of Water Pollution Control subdelineated ecoregions
from Level III to Level IV. Reference streams were identified in each sub-ecoregion to establish a
                                           PAGE A-15

July 2WH>
                 Appendix A.
Total Phdsphdru*
                  EPA Level III Nutrient Ecorcgiori XI Central and Eastern Forested Upland
                  Tennessee Ecoregion 66 Southwestern Appalachian*
                  Tennessee Ecore-giso n 69 Central Appalachlans
                  Tennessee Eciort-giah 67 Ridge and Valley
                  Tennessee Ecore^ion 66 Blue Ridge Mountains
       ,\-*>. Coroparison of EPA Nutrient Ecoregicm Region XT data to (he Tennessee reference stream
database for the same geographic area,
                                          P«;i A-16

July 2000
                Appendix A. Case Studies
                       Nitrate+Nitrite (mg/l)
Total Phosphorus (mg/l)
                EPA Level III Nutrient Ecoregion IX Southeastern
                TN Ecoregion 74 Mississippi Valley Loess Plains
                TN Ecoregion 65 Southeastern Plains
                TN Ecoregion 71 Interior Plateau
Figure A-10.  Comparison of EPA Nutrient Ecoregion Region IX data to the Tennessee reference stream
database for the same geographic area.
                                         PAGE A-17

July 2000	Appendix A.  Case Studies

database of least-impacted conditions.  These databases will be used to develop nutrient criteria based on
either the 75th or 90th percentile of the data.

Attempts to identify a relationship between nutrient levels and other parameters such as turbidity, TOC,
and suspended solids were confounded by the amount of data below the detection level. While data
relationships were indicated, they were not strong. Further investigations might include similar
comparisons using the national nutrient database values.

Relationships between nutrient data and biological indices were explored to see if positive correlations
could be established. Such correlations could be used to strengthen a criteria justification and to insure
that potential criteria values will be protective of biological integrity.  The preliminary results are

Tennessee's reference stream data were also compared to values from the national nutrient database. In
several ecoregions, the 75th percentile of the reference data corresponded well with the 25th percentile of
the national database. However, certain ecoregions did not correspond well, possibly suggesting that
there are distinct differences within the EPA nutrient ecoregions.  States would be well advised to
consider these differences in setting nutrient goals.

Additionally, states should examine the national nutrient database carefully and use local knowledge to
identify stormwater or embayment stations. Data from specific event sampling and reservoir or
embayment stations may not be representative of the ambient water quality in the region.  Such data
could inappropriately bias results.


TNDEC (Tennessee Department of Environment and Conservation). 1996. Standard operating
procedure for modified clean technique sampling protocol. Tennessee Department of Environment and
Conservation, Division of Water Pollution Control, Nashville, Tennessee.
                     Contact: Jim Harrison, Region 4 Nutrient Coordinator
                        United States Environmental Protection Agency
                        61 Forsyth Street, SW ^Atlanta, GA 30303-3104
                                           PAGE A-18

July 2000	Appendix A. Case Studies


V.J. Watson,2 Gary Ingman,3 and Bruce Anderson4

ABSTRACT: In recent decades, river bottom algal levels have interfered with beneficial uses of western
Montana's Clark Fork of the Columbia. The total maximum daily load analysis (TMDL)  required by the
Clean Water Act was addressed through a voluntary nutrient reduction plan developed by a stakeholder
group with the aid of scientists.  Targets for acceptable nutrient and algal levels were set  using
modifications of established criteria, literature values, and levels observed in the  Clark Fork where algae
problems did and  did not occur. These targets were considered starting points that would be refined as
more long-term data on the Clark Fork become available. Nutrient load reductions needed to meet
instream targets were estimated using a model that diluted loads in the 30 day 10 year low flows. It
appeared possible to achieve instream targets  in most of the river with reductions that the main
dischargers considered reasonably achievable, if other small dischargers and nonpoint sources were also
controlled. Hence 4 local governments and one large industry signed the VNRP, and a VNRP coordinator
was hired to obtain the participation of other sources.

KEY TERMS: nutrients, TMDL, benthic algae, benthic chlorophyll


River bottom algal levels were first recognized as a water quality problem in the Clark Fork River of
western Montana  in the 1970's when it was found to lower dissolved oxygen levels below state standards
on warm summer  nights (Braico 1973). Massive algae growths and low oxygen levels were noted
through the low flow summers of the 1980's (Watson 1989a; Watson and Gestring  1996) and identified
as a critical problem by the Montana governor's office (Johnson and Schmidt 1988). In 1987, the
reauthorization of the Clean Water Act called for a study and action plan to address nutrients and
associated nuisance growths in the Clark Fork basin from Montana to Washington.  The act also
established the Tristate Implementation Council to carry out the study and plan. The resulting study
(USEPA 1993b) documented that nuisance  levels of algae were interfering with beneficial uses in 250
miles of river in Montana.  The  Council convened a group of stakeholders (dischargers, local
governments, and conservation groups) which spent 4 years developing a voluntary nutrient reduction
plan or VNRP to restore the river's integrity. The plan was signed in August, 1998, and EPA accepted
the  VNRP as a TMDL because it had a rational, scientific basis and provided a margin of safety. The
VNRP will continue to serve as a TMDL as long as reasonable progress is shown toward its goals.

Unlike a TMDL, the VNRP did not require  that effluent limits be written into permits, rather permits
simply reference the VNRP which states the instream targets for algae and nutrient  levels and timetables
1 This paper was published previously and is used with permission of the publisher. Olsen, D. S. and J. P. Potyondy
(Eds.).  1999. WildlandHydrology. American Water Resources Association. Herndon, VA. TPS-99-3. 536pp.
 Professor, Environmental Studies, University of Montana, Missoula, MT
3 Chief, Data Mgt. & Monitoring, MT Dept. Env. Quality, Helena, MT
4 Hydrologist, Land & Water Consulting, Missoula, MT

                                           PAGE A-19

July 2000	Appendix A. Case Studies

to achieve these, suggests likely loading reductions needed to achieve these, and lists some methods
signatories agree to pursue to achieve reductions. By signing the VNRP, stakeholders agree to implement
certain efforts to achieve loading reductions, to monitor and evaluate results and to pursue additional
efforts if needed to reach targets. The VNRP also recognizes that the targets and reductions pursued are
based on the best information currently available and are subject to renegotiation as more information
becomes available. The VNRP references a long-term monitoring plan aimed at gathering more
information and evaluating the effect of load reduction efforts. The VNRP also explains the scientific
basis for the targets, load reductions, monitoring plan, margin of safety and areas of uncertainty. This
paper discusses the scientific basis of the VNRP by addressing a series of questions.


What Are Current and Desired Algae Levels in the River?
Summer algal levels in the Clark Fork vary dramatically in time and space, from highs of over 500 mg of
chlorophyll a/sq. m. in the  upper river in the 1980's to lows of 3 mg/sq. m. at some sites in recent years
(Watson and Gestring 1996; Watson unpublished data).

Currently, EPA is developing guidance to assist states in developing nutrient and algal criteria. It is likely
that this guidance will direct the states to develop criteria based on little-impacted reference water bodies
in each ecoregion. The Clark Fork VNRP committee found little guidance in the literature on what algal
levels were natural to this region or what levels were associated with water quality problems.

The British Columbia Ministry of the Environment considers that recreation and aesthetics are protected
when algal levels are below 50 mg chlorophyll a/sq. m.  and that undesirable changes in aquatic life will
be avoided at levels below 100 mg/sq. m. (Nordin 1985). Although these criteria were developed for
small, shallow streams, Nordin agrees that it is reasonable to apply them to the shallow parts of large
rivers (Nordin pers. comm.). Welch et al. (1988) demonstrated that filamentous algae tend to dominate
stream communities when  chlorophyll levels exceed 100 mg/sq. m. and proposed that nuisance levels
exist above 100-150 mg/sq. m. The VNRP committee decided to adopt these target algal  levels: less than
100 mg chlorophyll a/sq. m. when averaged over the growing season and 150 mg/sq. m. as the maximum
acceptable peak.

The committee agreed that these algal targets might be revised in time as more information becomes
available concerning what levels appear associated with water quality problems. In the mid 1980's, river
algal levels contributed to violations of the state dissolved oxygen standard. However, that standard has
since been raised and is no longer exceeded, changing this  view of what constitutes nuisance levels. But
it was recently discovered that river algae lower dissolved oxygen and pH sufficiently on summer nights
to release toxic heavy metals from old mine wastes in the river bed, violating water quality standards.
Further studies are needed to determine what algal levels would avoid this and other water quality

What Actions Seem Most Likely to Reduce Algal Levels?
Many factors affect river algal levels, including scouring, shading, grazing, toxic  chemicals and available
nutrients. The VNRP committee agreed that the factor that can best be managed to reduce algal levels in
the Clark Fork is available nutrients.

                                           PAGE A-20

July 2000	Appendix A.  Case Studies

How Much Must Nutrients Be Reduced to Achieve Algal Targets?
This question raised many others. What form of nutrients should be assessed, total or soluble? Which
nutrient is most limiting, nitrogen or phosphorus? At what levels do nutrients become limiting? Should
we focus on nutrient levels or loads?

Based on N:P ratios in the river, Watson (1989b) found that both N and P appear to be limiting at some
times in some river reaches. Hence, the committee concluded that both nutrients should be reduced if
possible. Artificial stream studies by Bothwell (1989) and Watson (1989) indicated what levels of
soluble nutrients are low enough to reduce algal levels in artificial streams. However, using a 200 river
database, Dodds et al. (1997) pointed out that total nutrient levels are better correlated with algal levels
than are soluble nutrient levels. So the VNRP committee opted to focus on total nutrients (while
monitoring soluble nutrients to insure they did not rise).  A variety of approaches suggested targets
ranging from 250-350 total N and 20-45 total P, so the committee adopted 300 ppb total N and 39 ppb
total P in the middle river and 20 ppb total P in the upper river (where a higher N:P ratio was desired to
discouraged the filamentous alga Cladophord).

What Are Major Nutrient Sources and How Much Reduction Is Needed?
The basin wide study called for in the  1987  Clean Water Act bill found that both point and nonpoint
sources accounted for significant portions of nutrient loading, hence both must be reduced (USEPA
1993b). However, the largest sources were found to be three municipal discharges (Butte, Deer Lodge
and Missoula), a pulp mill and a county (Missoula) with large areas of unsewered development. Hence
these 4 local governments and one private industry were initial signatories to the VNRP. Ultimately, the
VNRP committee hopes to convince smaller point sources and nonpoint sources (other developing
counties and large landowners) to agree to certain efforts to control nutrients and to sign the VNRP.

To estimate the amount of load reductions needed, the Montana Department of Environmental Quality
(DEQ) modified a model provided by EPA that estimates instream concentrations from loads, flows and
historic percent losses within each river reach. This model allowed DEQ  to  estimate how much loads
would need to be reduced from various sources to meet instream targets.  Once again, the committee
recognized that this simple model did not include  all the gains and losses and so provided only a rough
estimation of likely concentrations resulting from given loads. The model predicted that reductions the
committee felt were reasonably possible would achieve instream targets in almost all the impaired
reaches. The model suggested reaching targets in the few remaining miles of river would require
reductions of questionable feasibility. The committee agreed to use the model only as a general guide and
not to set required reductions. It was pointed out that algal uptake might reduce  nutrient levels lower than
the model predicted.

How Was a Margin of Safety Incorporated in the VNRP?
A margin of safety is provided by using instream nitrogen targets that are more protective than those
recommended by Dodds et al. (1997). In addition, needed load reductions were estimated using the
river's dilution capacity at very low flows—the 30 day 10 year low flow  (the lowest 30 day average flow
likely to be observed in one of 10 summers). Hence, targets will likely be met in almost all the river, in
all but one month out of 10 years.
                                           PAGE A-21

July 2000	Appendix A.  Case Studies

What Actions Are Expected to Achieve Needed Load Reductions?
All the municipalities in the area have adopted a phosphate detergent ban which has reduced P loads. The
city of Deer Lodge agreed to land apply its wastewater. The city of Butte agreed to augment stream flows
and pursue various land application options. The city of Missoula has reduced nutrient loading by
operating its activated sludge plant like a biological nutrient removal plant. It also plans to construct a
biological nutrient removal plant or use a combination of wetland treatment and land application in the
future. The pulp mill will reduce summer discharge, store its water so as to reduce seepage, and increase
use of a color removal process that also reduces nutrients. Missoula County will reduce and control
loading from septic systems through land use planning and controls.

The VNRP committee has hired a VNRP coordinator to work with small discharges, local governments
and land owners to identify ways these can reduce or at least control nutrient loads. These efforts are
needed to avoid losing ground given the rapid population growth occurring in the area.

How Will Progress Towards the Targets Be Determined?
The TriState Implementation Council contracted with Land & Water, Inc., to develop and carry out a
long term monitoring plan (Land & Water 1996) that will provide reliable information on nutrient related
water quality status and trends in the basin. The monitoring plan uses a statistically rigorous sampling
scheme designed to be able to detect trends in algal  and nutrient levels in the Clark Fork and to assess
compliance with instream targets. Using a seasonal Kendall with Sen slope estimate, the monitoring plan
is intended to be able to detect a 50% change in nutrient levels over a 10 year period with 95%
confidence and 90% power. In addition it can detect a 35% change in algal levels over a 10 year period
with 90% confidence and 80% power. Compliance with instream targets will be evaluated annually using
excursion analysis.

Monitoring consists of sampling 32 stations on the mainstem and major tributaries for total and soluble
nutrients monthly (with biweekly sampling in summer). Algal levels are sampled at 7 mainstem stations
twice  a summer. Because of the high spatial variability in algal distributions, 10-20 replicates are
collected. Details of the algal sampling scheme appear in Watson and Gestring (1996).

Timelines in the VNRP focus on timing of actions. However, the goal of the VNRP is to reduce algal
level to the point that beneficial uses are fully supported by the end of the 10 year plan. Hence, the plan
should be regarded as successful if a significant downward trend in nutrient and algal levels is detected 5
years into the plan, and if targets are no longer exceeded by the end of the 10 year plan. Of course, it will
be necessary to evaluate changes in these parameters in light of the flows observed over this 10 year


Bothwell, M. L. 1989. Phosphorus-limited growth dynamics of lotic  periphytic diatom communities:
areal biomass and cellular growth rate responses. Can. J. Fish. Aqua. Sci. 46:1293-1301.

Braico, R. D. 1973. Dissolved  oxygen and temperature diurnal variations in the Clark Fork River, August
1973. Rep. to MT Dept. Health and Env. Sciences (now the Dept. Env. Quality).
                                           PAGE A-22

July 2000	Appendix A. Case Studies

Brick, C. & J. Moore. 1996. Diel variation of trace metals in the upper Clark Fork River, MT. Env. Sci.
Tech. 30(6): 1953-60.

Dodds, W. K., V. H. Smith & B. Zander. 1997. Developing nutrient targets to control benthic chlorophyll
levels in streams: a case study of the Clark Fork River. Water Res. 31(7): 1738-50.

Ingman, G. 1992. A rationale and alternatives for controlling nutrients and eutrophication problems in the
Clark Fork River basin. Mt Dept. Health and Env. Sciences, Helena, MT.

Johnson, H. E. & C. L. Schmidt. 1988. Clark Fork basin status report & action plan. MT. Governor's
Office, Helena, MT.

Land & Water Consulting. 1996. Water quality status and trends monitoring system for the Clark Fork-
Pend Oreille Watershed. Rep. To MT Dept.  Env. Quality.

Nordin, R. N. 1985. Water quality criteria for nutrients and algae (technical appendix). British Columbia
Ministry of the Environment. Victoria, BC.  104 pp.

USEPA. 1993b. Clark Fork-Pend Oreille Basin Water Quality Study. EPA 910/R-93-006.

Watson, V. J. 1989a. Dissolved Oxygen levels in the Clark Fork River. Proc. Mont. Acad. Sci. 49:146-

	. 1989b. Control of attached algae by nitrogen and phosphorus in the Clark Fork River. Proc.
Symp. Headwaters Hydrology, Amer. Water Res. Assn. Missoula, MT pp 287-97.

	and B. Gestring. 1996. Monitoring algae levels in the Clark Fork River. Intermountain J. Sci.
2(2): 17-26.

Welch, E. B., J. M. Jacoby, R. R. Horner and M. R. Seeley. 1988. Nuisance biomass levels of periphytic
algae in streams. Hydrobiologia 157:161-8.
                 Contact: Debbi Hart (4304), Headquarters Nutrient Program
                        United States Environmental Protection Agency
                     Ariel Rios Building ^1200 Pennsylvania Avenue, NW
                                    Washington, DC 20460
                                          PAGE A-23

July 2000	Appendix A.  Case Studies
                                          PAGE A-24

July 2000	Appendix A.  Case Studies


Stephen D. Porter, U.S. Geological Survey, Water Resources Division, Denver, CO 80225


Extensive agricultural practices in the Midwestern Corn Belt region over the past 100 years have
contributed to nonpoint source degradation of water quality and biological integrity in many streams and
rivers.  For example, intensive row-crop production and confined animal-feeding operations in Iowa,
Illinois, and  southern Minnesota have resulted in accelerated nutrient and organic enrichment in tributary
streams, as well as in the Mississippi River (Goolsby et al. 1991; Coupe et al. 1995) and the Gulf of
Mexico (Turner and Rabalais 1994; Rabalais et al. 1996).  When ambient light and other algal-growth
factors are favorable, nutrient enrichment can promote excessive productivity and respiration in streams
and rivers, resulting in aesthetic and recreational impairments, departures from water quality  criteria, and
adverse effects to aquatic life.  The U.S. Environmental Protection Agency (USEPA) has been charged
with developing guidance for establishing regional water quality criteria to protect streams and rivers
from accelerated eutrophication processes (http://www.cleanwater.gov).  Results from State water quality
(305[b]) reports to Congress indicate that over 40% of streams and rivers in the U.S. are contaminated by
nutrient runoff and resultant indicators of excessive algal productivity.

Despite the prevalence of eutrophication, no implicit standards or criteria have been proposed to protect
beneficial water uses (e.g., no significant ecological changes) in streams and rivers, apart from drinking-
water standards for nitrate and chronic aquatic life criteria for elemental phosphorus in estuarine/marine
waters. Although predictive algal-nutrient relations have been established for classifying the trophic
status of lakes and reservoirs (Carlson 1977; Reckhow and Chapra 1983), there is no generally accepted
system for classifying streams and rivers (Dodds et al. 1998; Dodds and Welch 2000). Recent
approaches for classifying algal-nutrient relations in lotic systems have focused on constructing
frequency distributions of total nutrients and periphyton (Biggs  1996; Dodds et al. 1998) or seston
(suspended algae or phytoplankton) (Van Niewenhuyse and Jones 1996), and establishing boundaries
between oligotrophic-mesotrophic and mesotrophic-eutrophic conditions, similar to trophic criteria
established for lakes. Results from these investigations have suggested criteria for total nitrogen
(TN>1500 |-lg/L), total phosphorus (TP>75 |-lg/L), seston chlorophyll a (chl a>30 |-lg/L), and periphyton
(chl a> 100-200 mg/m2) to avoid adverse effects of stream eutrophication. Periphyton results  from these
and other such studies (Welch et al. 1988; Biggs and Close 1989; Lohman et al. 1992; Watson and
Gestring 1996; Dodds et al. 1997) are representative of streams with gravel or rock substrates that were
characterized by nuisance growths of filamentous green algae.  Relatively little is known about nutrient
and algal-productivity relations in low-gradient streams with unstable, sand, or silt bottoms. Even less is
known about natural and human factors that contribute to the predominance of seston or periphyton in
streams, relations with landscape factors such as agricultural intensity and riparian zones, and how
differences in algal-nutrient relations influence stream metabolism and biological integrity.

To provide better understanding of eutrophication conditions and processes in streams and rivers in the
upper Midwest Corn Belt region, the USGS National Water-Quality Assessment (NAWQA) Program

                                          PAGE A-25

July 2000	Appendix A.  Case Studies

conducted a large water quality study in the Minnesota, Wapsipinicon, Cedar, Iowa, Skunk, and Illinois
River basins during seasonal low-flow conditions in August 1997. The study was a cooperative effort
among three NAWQA projects:  the Upper Mississippi River basin, Eastern Iowa basins, and Lower
Illinois River basin study units. The objective of the study was to evaluate algal and macroinvertebrate
responses to nutrient, herbicide, and organic enrichment from nonpoint agricultural sources relative to
natural factors such as riparian vegetation, soil-drainage characteristics, and hydrology. This paper
summarizes the status of algal and nutrient conditions in portions of the Central and Western Corn Belt
Plains ecoregions (Omernik 1986), which could serve as a starting point for USEPA and State/Tribal
agencies to establish regional nutrient criteria in rivers and streams in relation to low-flow conditions.


Water chemistry and biological samples were collected from 70 streams and rivers in southern
Minnesota, eastern Iowa, and western Illinois during seasonal low-flow conditions in August 1997. The
study area is one of the most intensive and productive agricultural regions in the world; average row-crop
production of corn and soybeans in stream watersheds accounts for over 90 percent of land cover
(Sorenson et al. 1999). The density of riparian vegetation was quantified at two spatial scales: stream
reach and segment. The length of a stream reach was approximately 20 times the mean wetted channel
width (Fitzpatrick et al. 1998). The length of a stream segment was defined as the Iog10 of the basin area
upstream from each sampling location, ranging from approximately 3 km to 4.9 km. Basin soil-drainage
characteristics were quantified using information from the U.S. Soil Conservation Service STATSGO
database. Water chemistry samples were collected for total and dissolved nutrients, dissolved herbicides
and metabolites, and suspended and dissolved organic carbon (Shelton 1994).  Stream productivity and
respiration were estimated from continuous measurements of dissolved oxygen (DO) concentrations and
pH over a 48-hour period. Phytoplankton (algal seston) samples were collected in conjunction with
water-chemistry sampling, and quantitative samples of periphyton (benthic algae) and macroinvertebrates
were collected from submerged woody debris.  Water clarity was quantified using a light meter and
submersible quantum sensor; the depth of the euphotic zone was measured or estimated by comparing
subsurface photosynthetically-active radiation (PAR) with PAR measurements at the  bottom of the
deepest pool in the stream reach.  Stream flow and velocity were measured using standard USGS
procedures. Land-use and cover information was determined for each basin using ARC-INFO GIS
procedures with the most-recent (1996-97) agricultural data that were available. A summary of the study
design and methods, and data discussed in this report is presented by Sorenson et al. (1999;
http://wwwrcolka.cr.usgs .gov/nawqa).


Nutrient concentrations in many streams in the upper Midwest region are relatively higher than in other
areas  of the country, exceeding criteria proposed generally for temperate streams and rivers.  For
example, median concentrations of total nitrogen (TN; NH4+NO2+NO3+organic N) and total phosphorus
(TP; dissolved orthophosphate + particulate phosphorus) (Table A-l) exceeded the mesotrophic-
eutrophic boundaries of 1500 |_ig/L (TN) and 75 |_ig/L (TP) proposed for temperate streams (Dodds et al.
1998). Average stream concentrations of dissolved nitrite+nitrate nitrogen (NO2+NO3-N) and total
organic nitrogen (TON) were significantly (p<0.05) higher in the Minnesota River basin; nitrate
concentrations exceeded 8 mg/L in nearly one third of these streams.  Although concentrations and

                                           PAGE A-26

July 2000
Appendix A. Case Studies
annual loads of TN increase with the intensity of nitrogen sources (e.g., fertilizer application and other
land-use practices) nationally (Fuhrer et al. 1999), concentrations in Midwestern streams during seasonal,
low-flow conditions were not related to rates of fertilizer application or the number of livestock in
agricultural watersheds. Instead, NO2+NO3-N concentrations increased significantly with stream flow,
corresponding with differences in rainfall and runoff in the region during the months prior to the study,
and TON concentrations were correlated with the abundance of phytoplankton (seston), as indicated by
chl a concentrations. Concentrations of NO2+NO3-N decreased significantly with increases in seston chl
a concentrations.  Particulate phosphorus (total phosphorus as P; Table A-l) concentrations did not differ
significantly relative to human or natural factors; however, concentrations of dissolved orthophosphate
(DoP) varied in relation to the importance of ground-water discharge and the abundance of benthic algae
(periphyton) in Midwestern streams and rivers. Dissolved orthophosphate (available directly for algal
growth) accounted for about 28 percent of the concentration of TP.


Soil drainage and landform characteristics in the upper Midwest region were influenced profoundly by
patterns of glacial advance and retreat during the late Pleistocene era.  For example, soils on the
Wisconsin glacial lobe in north-central Iowa and southern Minnesota are characterized by fine-grained
materials through which water drains very poorly, whereas soils in eastern Iowa and western Illinois
contain relatively larger proportions of sand and coarser grained materials that constitute moderately-well
drained soils.  The proportion of stream water that is derived from ground-water inflow is substantially
less in  streams on the Wisconsin lobe than in streams located to the southeast of the Wisconsinan glacial
advance (Winter et al. 1998).  Land-surface  runoff, via tile drains, is probably an important contributor to
nutrient fluxes in streams that drain low-gradient, prairie-pothole landscapes. In contrast, ground-water
inflow contributes appreciably to stream flow, particularly during low-flow periods, in areas with
moderately-well drained soils such as the Wapsipinicon, Cedar, and Illinois River
Table A-l. Distribution of nutrient concentrations (in (ig/L) in Midwestern agricultural streams and
Water quality
Total Nitrogen1
Total Phosphorus2
Dissolved NHt-N
Total Organic N
Dissolved ortho-P
75th percentile
90th percentile
1 Sum of dissolved NH4-N + dissolved NO2+NO3-N + total organic N
2 Sum of dissolved ortho-PO4 + particulate phosphorus
3 Total phosphorus as P (USGS WATSTORE code 00665)
                                           PAGE A-27

July 2000	Appendix A. Case Studies

basins (Walton 1965; Heintz 1970; O'Hearn and Gibb 1980; Squillace et al. 1996).  Figure A-ll shows
soil-drainage relations among stream and river basins in the study (U.S. Soil Conservation Service
STATSGO data normalized to watershed area; Sorenson et al. 1999) and the correspondence with the
Wisconsinan glacial advance.

Concentrations of TN and TP varied in relation to soil-drainage and riparian-zone conditions in the upper
Midwest region (Figure A-12). Average TN concentrations were significantly higher in stream basins
with very-poorly drained soils, such as those in the Minnesota River basin. In basins with moderately-
well drained soils, concentrations of TN were significantly lower in streams with well-developed riparian
zones, suggesting that the presence of riparian trees may beneficially influence water quality conditions
in streams with appreciable ground-water discharge. Average TP concentrations were relatively lower in
streams with moderately- or poorly-drained basins and well-developed riparian zones (Figure A-12), but
concentrations of TP did not differ significantly in relation to riparian conditions. Average TP
concentrations were significantly less in streams with a low percentage of riparian trees and very-poorly
drained basins; however, average TP concentrations were generally (but not significantly) lower in
streams with well-developed riparian zones (Figure  A-13).

Dissolved nutrient concentrations differed in relation to basin soil-drainage properties and riparian-zone
conditions, but nutrient conditions were more related to algal abundance and productivity in streams and
rivers than physical factors. Average concentrations of dissolved ammonia-nitrogen (NH4-N) were
significantly higher in streams that drain basins with moderately well-drained soils, whereas average
dissolved NO2+NO3-N concentrations were significantly higher in streams with very-poorly drained soils,
such as those on the Wisconsin lobe. Similarly, average DoP concentrations were relatively higher in
highly-shaded  streams with moderately well-drained basins, whereas concentrations of DoP were
significantly lower in poorly-shaded, poorly-drained stream systems on the Wisconsin lobe. The
combination of very-poorly drained soils, high rainfall and land-surface runoff relations, and extensive
tile drainage in the Minnesota River basin may account for the higher-than-expected concentrations of
TN and dissolved NO2+NO3-N concentrations in these streams.  Relatively larger concentrations of NH4-
N and DoP in streams with moderately-well drained basins may indicate ground-water fluxes of these
constituents that reflect both present and past agricultural intensity.  The time of constituent transport
along local and regional ground-water flow paths can range from months to years.  Integration of these
results could indicate an interaction among land-use practices, stream hydrology, riparian shading, and
algal-nutrient relations.


Algal indicators of eutrophication in streams and rivers of the upper Midwest region are related to
agricultural intensity (fertilizer application and livestock in stream basins), soil-drainage conditions,
hydrology, and riparian-zone conditions along stream segments. Median and inter-quartile seston chl a
concentrations (Table A-2) are similar to those reported from mesotrophic-to-eutrophic lakes and
reservoirs (e.g., Carlson 1977), and seston (but not periphyton) chl a concentrations were significantly
higher in poorly-shaded than well-shaded streams (Figures A-13 and A-14). These results likely indicate
that ambient light conditions influence the development of large phytoplankton populations in
Midwestern streams and rivers.  Seston chl a values indicative of eutrophic conditions (greater than 30
|_lg/L) were found in streams that drain basins with poor soil drainage, high rates of fertilizer application,

                                           PAGE A-28

July ZW.W
Appendix A.
                                                 Southern aden! of

                                                  glacial advance


                 Pocrty *arij>T sals,

                 Vtery poo(% d-a rea
                                                                          lower «nnis Rmer
       A-l L Classification of MidweMcm streams and rivers relative lo basin soil-drainage
characteristks and relaiion wiih swthcrn extent of Wisconsin glacial advance.

July 2000
                                       Appendix A. Case Studies

O< 35% trees
• > 35% trees

                              Moderate         Poor          Very Poor
                                          Soil Drainage
                 f   0.3

                 I   0.2

                                                           O < 35% trees
                                                           • > 35% trees
                              Moderate          Poor         Very Poor
                                          Soil Drainage
Figure A-12. Total nitrogen and phosphorus concentrations relative to soil drainage and riparian
conditions in Midwestern streams and rivers.
                                          PAGE A-30

July 2000
Appendix A. Case Studies

I 5


O < 35% frees
• > 35% frees

5 i


o) 0.4

£ 0.3


O < 35% frees
• > 35% frees

- * * -

f 50

O< 35% frees
• > 35% frees


e 50

O < 35% frees
• > 35% frees


O ^

Figure A-13. Average concentrations of total nitrogen, total phosphorus, seston chlorophyll a, and
periphyton chlorophyll a in relation to riparian-zone conditions.
                                           PAGE A-31

July 2000
Appendix A. Case Studies
Table A-2. Distribution of algal seston, periphyton, ash-free dry mass, stream productivity and
respiration, suspended and dissolved carbon, total suspended solids, and water clarity (euphotic zone
depth) in Midwestern agricultural streams and rivers.
Water quality
chlorophyll a
chlorophyll a
Periphyton ash-
free dry mass
(g 02/m3/hr)
(g 02/m3/hr)
organic carbon
organic carbon
Suspended Solids
euphotic zone
depth (m)
10th percentile
25th percentile
50thperc entile
75th percentile
90th percentile
                                            PAGE A-32

July 2000
                     Appendix A. Case Studies
               1   50
               i  so
                                                        O < 35% frees
                                                        • > 35% frees
                           Moderate          Poor          Very Poor

                                        Soil Drainage
                                                        O < 35% frees
                                                        • > 35% frees
                           Moderate          Poor          Very Poor

                                        Soil Drainage
Figure A-14.  Seston and periphyton chlorophyll a values relative to soil drainage and riparian
conditions in Midwestern streams and rivers.
                                        PAGE A-33

July 2000	Appendix A.  Case Studies

and relatively large populations of hogs and other livestock. Stream productivity (Pmax) and respiration
(Rn,ax) values increased significantly with seston chl a concentrations. Concentrations of NO2+NO3-N
decreased significantly with increases in stream productivity, which is probably correlated with algal
uptake of dissolved nutrients.  Seston chl a concentrations were positively correlated with concentrations
of suspended organic carbon (SOC), TON, particulate phosphorus, and total suspended sediment (TSS),
which suggests that total nutrient and organic enrichment in Midwestern streams is reflected by large
populations of algal seston. Seston chl a concentrations were negatively correlated with euphotic zone
depth, indicating that water clarity decreases with increases in the abundance of suspended algae

Periphyton chl a values were significantly larger in streams with high water clarity and riparian shading,
and above-average stream velocity.  Concentrations of total and dissolved nutrients and seston chl a in
periphyton-dominated streams were generally moderate to low; however, productivity (Pmax) was about
average for Midwestern streams, suggesting that periphyton (rather than seston) influences the
productivity of streams with high riparian shading and appreciable ground-water discharge. Large
populations of diatoms and blue-green algae were observed growing on sand (near the hyporheic zone) in
these streams. Although concentrations of NH4-N and DoP were larger in streams  that drain basins with
moderately-well drained soils, regionally, periphyton uptake of dissolved nutrients from ground-water
discharges might account for the lower-than-expected concentrations of these constituents in the
Wapsipinicon and Cedar River basins of eastern Iowa. While  Pmax rates in periphyton-dominated streams
were near average regionally, rates  of stream respiration (R^) were generally low, and early-morning
concentrations of DO appeared to be favorable for aquatic life. In contrast, rates of R,^ were relatively
high in seston-dominated streams; DO concentrations during early-morning hours  were low and benthic
macroinvertebrate community structure was poor (Harris and Porter in review).

Periphyton chl a and ash-free dry mass (AFDM) values were positively correlated; however, chl a and
AFDM relations (refer to Table A-2) differed with respect to precedent stream-flow conditions, water
clarity, and non-algal sources of carbon.  Ratios of chl a to AFDM were relatively low (less than one) in
over half the streams in the Minnesota River basin, where the organic content of soils is relatively high
and soil drainage is very poor. In addition, above-average stream flow and water turbidity, as well as a
higher frequency of hydrologic disturbances associated with summer storms during the months prior to
the study (Figure A-15) probably limited the growth of algal periphyton in the Minnesota River basin. In
contrast, chl a/AFDM ratios were larger (greater than one) in streams with relatively stable stream flow
and good water clarity.

Periphyton samples were analyzed for species composition and abundance (cells/cm2), and the biovolume
of each algal taxon was determined by measuring cell dimensions and calculating the average volume of
the cell (|-im3) in relation to the nearest geometric shape (e.g., sphere, cylinder, etc.). Biovolume
(|_im3/cm2) for each species was calculated by multiplying the volume of one cell by the abundance of the
species in the sampling reach. Total algal biovolume (cm3/m2) was estimated by summing biovolumes
for all species present in the sample. Total algal biovolume (TAB) is positively correlated with
periphyton chl a and AFDM, and periphyton chl a can be estimated from TAB using the following
regression relation:

       chl a = (4.229 + 2.733*log10(TAB))2           adjusted R2=0.570; p<0.001; n=67

                                           PAGE A-34

July 2000
                                                                    Appendix A. Case Studies
                1,500 -
            O-   1,500


            §   1,000

                           Wapsipinicon River
                           Wolf Creek
                        May         June
                                                                    Total streamflow

                                                                    Base-flow discharge
                                    July           August        September

                                     MONTH (1997)
Figure A-15. Total and base flow discharge for selected Midwestern streams and rivers in relation to
collection date of water quality samples.
                                               PAGE A-35

July 2000	Appendix A. Case Studies

where:   chl a = periphyton chlorophyll a (mg/m2)
         TAB = total algal biovolume (cm3/m2)

Unexplained variance associated with the regression is probably attributable to differences in chl a
content among algal species, differences in riparian shading or other factors that influence ambient light
conditions (e.g., Barley 1982; Rosen and Lowe 1984), and challenges with distinguishing live and dead
cells during taxonomic enumeration.

Periphyton communities were dominated by eutrophic microalgae (diatoms, blue-green algae, and green
algae). Filamentous red algae (Audouinella hermanii} were abundant in streams with above average
water clarity, velocity, and riparian-tree density (i.e., periphyton-dominated streams). Filamentous green
algae were relatively uncommon on submerged woody debris; however, sparse to moderate growths of
Cladophora glomerata were observed in flowing streams with bedrock or boulders, and moderate
growths ofSpirogyra spp. were present in pools  and slow-flowing sections of streams with sand or silt
bottoms. The predominance of fine streambed materials (sand and silt) in many Midwestern streams
probably precluded the establishment and growth of nuisance filamentous algal species.  These factors
probably account for the relatively lower periphyton chl a values observed in this study when compared
with those associated with eutrophic streams in the western U.S., that are dominated by filamentous
green algae (Welch et al. 1988; Watson and Gestring 1996; Dodds et al. 1997).


Streams were classified relative to the abundance of algae (seston, periphyton, or both) as indicated by
chl a values, and analysis  of variance (ANOVA) and Tukey multiple range tests were used to determine
whether water quality conditions differed significantly among stream classifications.  Approximately 30
percent of the streams contained above-average (relative to this data set) concentrations of seston chl  a
and below-average values for periphyton chl a (seston-dominated streams). Concentrations of TON,
dissolved organic carbon (DOC), and SOC were significantly higher in seston-dominated streams,
suggesting organic enrichment from autotrophic  (in-stream) processes. About 28 percent of streams
contained below-average concentrations of seston chl a and above-average  values for periphyton chl a
(periphyton-dominated streams). Water clarity in periphyton-dominated streams was good, as indicated
by significantly lower TSS concentrations and significantly larger euphotic-zone depths.

Stream productivity (Pmax) was moderate to high  in all streams with  above-average amounts of algae;
however, high rates of stream respiration (R^) were associated primarily with large populations of
seston. High R^ conditions were associated with low DO concentrations during early morning hours, at
levels that can adversely affect aquatic fauna.  Stream respiration was significantly higher in streams with
above-average chl a values for both seston and periphyton (algal-eutrophic streams; 22 percent of
streams in the study). Concentrations of dissolved (but not total) nutrients were relatively lower in algal-
eutrophic streams than in streams with below-average  seston and periphyton chl a (nutrient-eutrophic
streams; 20 percent of streams in the study). Stream productivity (Pmax) was significantly higher in algal-
eutrophic and seston-dominated streams than in nutrient-eutrophic and periphyton-dominated streams.
However, periphyton chl a decreased significantly with modest increases in the relative abundance of
macroinvertebrate scraper organisms (Harris and Porter, in review); therefore, monitoring of algal-

                                          PAGE A-36

July 2000	Appendix A. Case Studies

nutrient relations in Midwestern streams should probably consider the abundance of grazer organisms
that consume benthic algae.

The abundance of algal tychoplankton (species that are loosely associated with, but not attached to,
submerged benthic surfaces) in the periphyton community was a primary factor in identifying differences
in community structure among Midwestern streams. These species, including Microcystis, Anabaena,
other blue-green algae, and centric diatoms, are  found commonly in eutrophic lakes, reservoirs, and other
warm, slow-flowing water bodies such as large impounded rivers. The abundance of blue-green algae
increased with the concentration of triazine herbicides (atrazine, cyanazine, and degradation products).
The predominance of tychoplankton in periphyton communities in algal-eutrophic and seston-dominated
streams was associated with large populations of these species in the seston, probably indicating that they
had settled from the water column.  Indicators of organic enrichment (SOC, DOC, TON) and stream
metabolism (Pmax and R^ are consistent with the large abundance of algae in these streams, whereas
concentrations of dissolved nutrients were relatively low. The highest rates of stream respiration were
found in algal-eutrophic streams; benthic macroinvertebrate indicators of biological integrity (e.g., EPT
richness) indicated poor water quality conditions in algal-eutrophic and seston-dominated streams (Harris
and Porter in review).

In contrast, algal communities in periphyton-dominated and nutrient-eutrophic  streams were dominated
by diatoms, blue-green algae, and red algae that grow attached to benthic surfaces. These species are
found commonly in cool, flowing streams and rivers. A secondary factor in classifying differences in
algal community structure in the region relates to the age of the periphyton community as inferred by the
presence or dominance of certain algal species.  For example, periphyton communities in streams of the
Minnesota and upper Iowa River basins were characterized by diatoms (e.g., Fragilaria vaucheriae and
Achnanthidium minutissimum) that are typically found in abundance on bare or recently-scoured
substrates.  Algae that are associated with soils (e.g., Luticola mutica, Chlorococcum sp., and
Protococcus sp.) were also common in these streams.  Periphyton community structure in these streams
is consistent with recent hydrologic disturbance as indicated by relatively high  rainfall, surface-water
runoff, and elevated streamflow in the region (Figure A-15). Water quality in these streams is influenced
by relatively low rates of stream metabolism and high concentrations of nutrients (notably TN,
NO2+NO3-N and TP). In contrast, periphyton communities in  streams of the Wapsipinicon and upper
Cedar River basins consisted of species found commonly in diverse, mature algal communities (e.g.,
Audouinella hermanii, Navicula spp. and Gyrosigma spp.), which is consistent with relatively stable
hydrologic conditions, ground-water discharge,  and seasonally-typical streamflow (Figure A-15).


Nutrient concentrations and the abundance  of algae during low-flow conditions were not related directly
to rates of fertilizer application or the number of livestock in Midwestern stream basins; however, rates
of stream metabolism (Pmax and R^) increased significantly with indicators of agricultural intensity.
Algal-nutrient relations during August 1997 were more a function of landscape characteristics (riparian
zones and soil properties), hydrology (ground-water and surface-water relations), and rainfall-runoff
characteristics than agricultural land use, which is relatively homogeneous throughout the region. For
example, average nutrient concentrations were significantly higher in the Minnesota River basin despite
relatively lower agricultural intensity. Above-average rainfall  and runoff from poorly drained soils,
discharged through tile drains, probably explains the higher-than-expected nutrient concentrations in

                                           PAGE A-37

July 2000	Appendix A. Case Studies

these streams.  Average rates of stream metabolism were relatively lower in streams in the Minnesota
River basin, which is consistent with relatively higher concentrations of suspended solids and lower
water clarity. Over half of these streams contained above-average seston chl a concentrations, which
corresponds with relatively less riparian shading in Minnesota than in Illinois or Iowa. However, seston
and periphyton communities were dominated by species associated with soils or those with high rates of
colonization and reproduction.  Benthic invertebrate and periphyton communities contained relatively
fewer species;  however, reduced species richness was more indicative of hydrologic disturbance (high,
flashy stream flow and velocity) than organic enrichment.

In contrast, average dissolved nitrate concentrations in the Illinois River basin were significantly lower,
even though agricultural intensity in those stream basins was among the highest in the region. Below-
average rainfall (near drought conditions), resulting in significantly lower (surface water) nutrient yields
from stream watersheds, lower stream velocities, and high rates of stream metabolism, probably explain
the lower-than-expected dissolved nutrient and DO concentrations. However, concentrations of
dissolved NH4-N were relatively higher, probably attributable (in part) to ground-water fluxes in basins
with moderately well-drained soils.  Water quality conditions in Illinois streams during August 1997
were relatively degraded, as revealed by relatively high concentrations of SOC, DOC, and TON
(indicators of organic enrichment), low minimum dissolved-oxygen concentrations, high rates of stream
respiration, and poor macroinvertebrate communities (low taxa and EPT richness).

Water quality in Iowa streams differed in relation to basin soil properties and riparian shading. Overall
water quality was best in streams that drain basins with moderately well-drained soils and a high
percentage of riparian trees (Wapsipinicon and upper Cedar River basins). These periphyton-dominated
streams were characterized by low to moderate concentrations of nutrients and average stream
productivity. Seston chl a values and rates of respiration were relatively low, and macroinvertebrate
communities (e.g., EPT richness) indicated good water quality and habitat conditions.

Although phytoplankton chl a criteria are available to classify the trophic status of lakes and reservoirs
(e.g., Carlson 1977), comparable criteria have not been established for seston or periphyton in lotic water
bodies.  Average chlorophyll values in the upper Midwest region are considerably lower than criteria
proposed by Dodds et al. (1998) for temperate streams and rivers, whereas proposed criteria for total
nutrients (TN>1500 |ig/L; TP>75 |ig/L) are  exceeded in 74 percent (TN) to 89 percent (TP) of the
streams in this study. Periphyton chl a values exceeded 70 mg/m2 (proposed minimum eutrophic
criterion) in only 13 percent of the streams, and seston chl a values exceeded 30 |-ig/L (proposed
eutrophic criterion) in about one-third of the  streams in this study.  The higher recommended criteria for
periphyton chl a (100 mg/m2 to 200 mg/m2) (Welch et al. 1988; Watson and Gestring  1996; Dodds et al.
1998) was intended to protect streams and rivers from nuisance growths of filamentous algae such as
Cladophora glomerata, other macroalgae, or other aquatic plants. These taxa require stable benthic
surfaces (e.g., submerged rocks or bedrock) on which to colonize and grow to nuisance proportion.  Sand
and silt bottom streams of the Midwest, and submerged woody debris in these streams, do not generally
provide suitable habitat to sustain nuisance filamentous algal growths.  However, dense growths of
microalgae (primarily diatoms and blue-green algae) on sand or woody snags in Midwestern streams
could provide visible evidence  of stream eutrophication during low-flow periods; the proposed minimum
eutrophic criterion may be appropriate for indicating that condition.
                                           PAGE A-38

July 2000
Appendix A. Case Studies
Results from this study suggest that the abundance and composition of algal seston (phytoplankton) may
be one of the better indicators of trophic conditions in streams and rivers of the upper Midwest region.
Because of the highly significant correspondence between the standing crop (e.g., chl a) of algal seston
and concentrations of total nutrients and carbon, criteria established for seston (evaluated during stable,
low-flow conditions) is likely to represent total nutrient concentrations in the water and the extent to
which organic enrichment is a problem for maintaining biological integrity in streams and rivers.  Seston
criteria would also provide an index for evaluating the clarity of streams and rivers, an important
consideration relative to the public perception of trophic conditions, and water quality in general.
However, criteria for total nutrients (and perhaps total suspended solids) cannot be abandoned for
streams where algal growth is limited by inorganic turbidity or dense riparian-canopy shading. For
example, if best-management practices (BMPs) are applied in watersheds to reduce adverse effects of
sedimentation without consideration given to commensurate reductions in nitrogen or phosphorus loads
to streams, excessive algal growths could ensue when productivity is no longer limited by the availability
of light (e.g., in nutrient eutrophic streams and rivers). A consideration of water quality variables for
establishing and monitoring the trophic condition of temperate streams and rivers is presented in
Table A-3.
Table A-3.  Summary of water quality variables for establishing criteria and monitoring the trophic
condition of temperate streams and rivers.
Total nutrients
Dissolved nutrients
Stream metabolism
Water clarity
Aquatic fauna
Media (and frequency)
Water chemistry (monthly & in relation
to hydrology)
Water chemistry (monthly & in relation
to hydrology)
Water samples (growing season & in
relation to hydrology)
Natural substrates (growing season & in
relation to hydrology and aquatic
Estimates of system productivity &
respiration (low flow conditions with
chemical & biological measures)
Euphotic zone depth; water
transparency; secchi depth (seasonal;
with chemical & biological measures)
Natural substrates (low-flow
chemical indicator
chemical indicator
algal-nutrient relations
biological indicator
organic enrichment
food- web relations
biological indicator
organic enrichment
food- web relations
biological indicator
physical indicator
biological indicator
response to organic enrich-
aquatic life
aquatic life;
direct measure of
process; aquatic
life; biocriteria
aesthetic properties
light availability for
algal growth
receptor biocriteria
TMDL process
                                           PAGE A-39

July 2000	Appendix A. Case Studies

Improved understanding of natural factors and algal-nutrient relations that contribute to chemical and
biological indicators of eutrophication in lotic systems could enhance the development of water quality
criteria within and among ecoregions in the U.S. (e.g., Level III; Omernik 1986).  For example, results
from this study indicate larger variance within the Western Corn Belt Plains ecoregion than between the
Central and Western Corn Belt Plains ecoregions. Differences in soil drainage, ground-water/surface-
water relations, and precedent rainfall-runoff conditions account for part of this variance. Improved
understanding of dissolved nutrient relations with the abundance of seston and periphyton, rates of
stream metabolism, and organic enrichment processes in streams could assist water managers with
decisions concerning BMPs, total maximum daily load (TMDL) allocations, and the establishment of
appropriate biocriteria relative to natural  and human factors that contribute to the quality of streams and


Biggs, B.J.F. and Close,  M.E., 1989, Periphyton biomass dynamics in gravel bed rivers: the relative
effects of flows and nutrients. Freshwater Biology, v. 22, p. 209-231.

Biggs, B.J.F., 1996, Patterns in benthic algae in streams. In: Algal Ecology—Freshwater benthic
ecosystems, Stevenson, R.J., Bothwell, M.L., and Lowe, R.L., eds., Academic Press, San Diego, CA, p.

Carlson, R.E., 1977, A trophic state index for lakes. Limnology and Oceanography, v. 22, p. 361-369.

Coupe, R.H., Goolsby, D.A., Iverson, J.L., Markovichick, D.J., and Zaugg, S.D., 1995, Pesticide,
nutrient, water-discharge and physical-property data for the Mississippi River and some of its tributaries,
April 1991-September 1992. U.S. Geological Survey Open-File Report 93-406, 66 p.

Darley, W.M., 1982, Algal biology: A physiological approach. Blackwell Scientific Publications,
Oxford, U.K., 168 p.

Dodds, W.K., Jones, J.R., and Welch, E.B., 1998, Suggested classification of stream trophic state:
Distributions of temperate stream types by chlorophyll, total nitrogen, and phosphorus. Water Resources,
v. 32, no.5 p. 1455-1462.

Dodds, W.K., Smith, V.H., and Zander, B., 1997, Developing nutrient targets to control benthic
chlorophyll levels in streams: A case study of the Clark Fork River. Water Resources, v. 31,  no. 7, p.

Dodds, W.K., and Welch, E.B., 2000, Establishing nutrient criteria in streams. Journal of the North
American Benthological Society, v. 19, p. 186-196.

Fitzpatrick, F.A., Waite,  I.R., D'Arconte, P.J., Meador, M.R., Maupin, M.A., and Gurtz, M.E., 1998,
Revised methods for characterizing stream habitat in the National Water-Quality Assessment Program.
U.S. Geological Survey Water-Resources Investigations Report 98-4052, 67 p.

                                           PAGE A-40

July 2000	Appendix A. Case Studies

Fuhrer, G.J., Gilliom, R.J., Hamilton, P.A., Morace, J.L., Nowell, L.H., Rinella, J.F., Stoner, J.D., and
Wentz, D.A., 1999, The quality of our Nation's waters. Nutrients and pesticides. U.S. Geological Survey
Circular 1225, 82 p.

Goolsby, D.A., Coupe, R.C., and Markovchick, D.J., 1991, Distribution of selected herbicides and nitrate
in the Mississippi River and its major tributaries, April through June 1991. U.S. Geological Survey
Water-Resources Investigations Report 91-4163, 35 p.

Harris, M.A., and Porter, S.D., (unpublished manuscript), Relating epidendric macroinvertebrate
communities to physical and chemical factors in upper Midwest streams. U.S. Geological Survey Water-
Resources Investigations Report.

Heintz, A.J., 1970, Low-flow characteristics of Iowa streams through 1966: Iowa Natural Resources
Council Bulletin No. 10, 176 p.

Lohman, K., Jones, J.R., and Perkins, B.D., 1992, Effects of nutrient enrichment and flood frequency on
periphyton biomass in Northern Ozark streams. Canadian Journal of Fisheries and Aquatic Sciences, v.
49, p. 1198-1205.

O'Hearn, M.O., and Gibb, J.P., 1980, Groundwater discharge to Illinois streams. Illinois Institute of
Natural Resources, State Water Survey Division, Groundwater Section, SWS Contract Report 246,
Champaign, Illinois, 31 p.

Omernik, J.M., 1986, Ecoregions of the United States. U.S. Environmental Protection Agency, Corvalis
Environmental Research Laboratory, 1  p.

Rabalais, N.N., Turner, R.E., Justic, D., Dortch, Q., Wiseman, W.J., and Sen Gupta, B.K., 1996, Nutrient
changes in the Mississippi River and system responses on the adjacent continental shelf. Estuaries, v. 19,
no. 2B, p. 386-407.

Reckhow, K.H., and Chapra, S.C., 1983, Engineering approaches for lake management, Volume 1.
AnnArbor Science, Butterworth Publishing Company, Woburn, Mass., 340 p.

Rosen, B.H., and Lowe, R.L.,  1984, Physiological and ultrastructural responses ofCyclotella
meneghiniana (Bacillariophyta) to light intensity and nutrient limitation. Journal of Phycology, v. 20., p.

Shelton, L.R.,  1994, Field guide  for collection and processing stream-water samples for the National
Water Quality Assessment Program, U.S. Geological Survey Open-File Report 94-455, 42 p.

Sorenson, S.K., Porter, S.D., Akers, K.K.B., Harris, M.A., Kalkhoff, S.J., Lee, K.E., Roberts, L.R., and
Terrio, P.J., 1999, Water quality and habitat conditions in upper Midwest streams relative to riparian
vegetation and soil characteristics, August 1997: Study design, methods, and data. U.S. Geological
Survey Open-File Report 99-202, 53 p.

                                           PAGE A-41

July 2000	Appendix A.  Case Studies

Squillace, P.J., Caldwell, J.P., Schulmeyer, P.M., and Harvey, C.A., 1996, Movement of agricultural
chemicals between surface water and ground water, lower Cedar River basin, Iowa, U.S. Geological
Survey Water-Supply Paper 2448, 59 p.

Turner, R.E., and Rabalais, N.N., 1994, Coastal eutrophication near the Mississippi River delta. Nature,v.
368, p. 619-621.

Van Niewenhuyse, E.E., and Jones, J.R., 1996, Phosphorus-chlorophyll relationships in temperate
streams and its variation with stream catchment area. Canadian Journal of Fisheries and Aquatic
Sciences, v. 53, p. 99-105.

Walton, W.C., 1965, Ground water recharge and runoff in Illinois. Report of Investigation 48, Illinois
State Water Survey, Urbana, Illinois, 55 p.

Watson, V., and Gestring, B., 1996, Monitoring algae levels in the Clark Fork River. Intermountain
Journal of Sciences, v. 2, no. 2, p. 17-26.

Welch, E.B., Jacoby, J.M., Horner, R.R., and Seeley, M.R., 1988, Nuisance biomass levels of periphytic
algae in streams. Hydrobiologia, v. 157, p. 161-168.

Winter, T.C., Harvey, J.W.,  Franke, O.L., and Alley, W.M., 1998, Ground water and surface water—A
single resource. U.S. Geological Survey Circular  1139, 79 p.
                     Contact: Dave Pfeifer, Region 5 Nutrient Coordinator
                        United States Environmental Protection Agency
                     77 West Jackson Boulevard ^Chicago, IL 60604-3507
                                           PAGE A-42

July 2000	Appendix A. Case Studies


The Bow River is a documented case of recovery from point source nutrient loading rather than one of
setting criteria. In contrast to lakes, cases in which the recovery of streams or rivers from nutrient
reduction was thoroughly evaluated are scarce. The Bow River, Alberta, is an exception; it has been
monitored for over 16 years to evaluate the effect of a reduction in first phosphorus (80%) and later
nitrogen (~ 50%) from two domestic wastewater plants in Calgary (Sosiak pers. comm.). Algae and
macrophytes had caused problems in the river by clogging irrigation water intakes, interfering with
boating and angling, and causing low DO at night. Nitrogen removal was for the purpose of minimizing
risk of ammonia toxicity rather than control of algae or macrophytes.  Both periphyton and macrophytes
decreased downstream in response to nutrient reduction, but the distribution and timing of the decreases
were to some extent unexpected. The river's response to nutrient reduction offers pertinent implications
and guidance for setting nutrient criteria in large fast-flowing, gravel-bed rivers.  Median April to
October flow in the Bow River over the sampling period ranged from  approximately 75 to 130 m3/s.

Prior to P reduction, periphyton biomass consisted mostly of diatoms, although filamentous green algae
(including Cladophord) were also present (Charlton et al. 1986). Biomass reached summer maximums
downstream averaging approximately 300-400 mg chlorophyll a/m2, but occasionally up to 600 mg
chlorophyll a/m2.  Such maxima have persisted within 10 km of the effluent input since P reduction in
1983, but decreased markedly farther downstream over an approximately 90-330 km reach (Table A-4;
note that data from two stations between km 304 and 533 are not shown). The decrease in periphyton
occurred rather gradually over 13 years following P reduction as total dissolved P (TDP) declined to very
low levels (median 10 (ig/L) downstream (Sosiak pers. comm).  Within 10 km downstream of the effluent
input, however, TDP declined initially from a mean summer value of  111 |J,g/L to 19-24 |j,g/L and
periphyton biomass exhibited no change from the high pre-treatment levels of 300-400 mg chlorophyll
a/m2.  The data upstream and downstream demonstrated that if summer TDP consistently averaged <  10
(ig/L, maximum periphyton biomass typically averaged less than 100 mg chorophyll a/m2. Maximum
summer biomass averaged approximately 1.4 times mean values.

TDP and periphyton biomass decreased gradually over the 13-year period following treatment with the
largest decline occurring after 1989,  although this is not apparent from the data summary in Table A-4.
The delayed decrease in TDP may have been due to declining recycling from sediments, the TP content
of which declined downstream, but not upstream of Calgary (Sosiak pers. comm.).

This extensive data base also indicates that TDP was linked much closer to periphytic biomass than TP,
which decreased markedly following treatment upstream (Stier's Ranch). The change was only slight
downstream, in contrast to the 50% decrease in TDP (Table A-4). Note that average maximum biomass
varied from 77 to 428 over a range of summer mean TP of only 40 to 59 (ig/L. Periphytic biomass was
also correlated with TDP (r values of -.61 to .70), but not with TP (Sosiak pers. comm.). Sosiak
concluded that TDP was a much better indicator of periphytic biomass throughout the river than TP.

An  interesting contrast for this case study in comparison with the Clark Fork River involves the reduced
frequency of filamentous green algae and lower maximum biomass levels in the Bow River.  Cladophora
was the dominant taxa that extensively covered the bottom substrata and created the nuisance condition
interfering with recreational use in the Clark Fork River. In the Bow River, the periphyton was
dominated by diatoms, which can be highly visible if biomass is high.  Although  Cladophora was present
                                          PAGE A-43

July 2000	Appendix A. Case Studies

downstream from Calgary prior to nutrient reduction (Charlton et al. 1986), there was apparently not the
high percent cover of filamentous greens that interferes with recreation.  Part of the difference in
nuisance conditions between the two rivers may be related to the higher summer flows in the Bow.
Nevertheless, Cladophora and some other filamentous greens did largely disappear after nutrient
reduction (Sosiak pers. comm.).

These data indicate that:  1) periphyton biomass in streams and rivers does respond to nutrient reduction,
2) biomass levels below nuisance levels (-150 mg chlorophyll a/m2) can be attained if P can be
sufficiently reduced, 3) sufficient reductions are defined by levels approaching -10-15 (ig/L TDP, and 4)
response to nutrient reductions may not occur quickly even in rivers where water exchange is immediate.
The gradual reduction in river TDP suggests that there is a long-term, slow release of P stored in (or
adsorbed to) bottom sediments, even in rubble-bottom rivers.

In addition, macrophytes (mostly pond weeds) reached biomass levels of > 2000 g/m2 within 30 km
downstream of discharges prior to effluent treatment in 1987, but declined soon after N reduction,
reaching levels in 1995-1996 of < -200 mg/m2. The cause for macrophyte decline in response to N
reduction is not clear, but was hypothesized to be due to increased N limitation at plant roots (Sosiak
pers. comm., citing Barko  et al. 1991). Nitrogen in the water was never considered limiting to
macrophytes or algae, because DIN:TDP ratios were always well above 20:1 by weight even after N

The downstream change in periphyton biomass was simulated with a model that predicts spatial and
temporal biomass and nutrient (in this case SRP) concentrations in cobble/gravel-bed rivers during
summer low-flow conditions. SRP was not determined in the Bow River, but TDP was converted to SRP
using 0.65 X TDP. Of five years suitable for model calibration, a 4-week period in October 1997 was
selected (Elswick et al. 2000). Sloughing loss was assumed negligible during this period, as has been
observed in laboratory channel experiments during which periphyton is actively growing to a maximum
biomass (Horner et al. 1990; Anderson et al. 1999). The model was not verified, because there was
insufficient data for some processes, such as grazing, for which a constant value was used (10% of
existing biomass/day).

Model simulation compared favorably with actual data (Figure A-16). The largest discrepancy was at
Carsland (56 km) where biomass was overestimated by 100%. Biomass  was also overestimated at all
other sites, but by an average of only 25%. Part of this difference may have been related to P retention in
run-of-the-river impoundments located upstream from Carsland and not included in the model. Also,
grazing may have been greater than the assumed rate. Grazing rates per unit grazer biomass are available
in the literature and could be used in this model if grazer biomass were available. Nevertheless, the
model demonstrates the phenomenon of biomass reduction downstream following nutrient reduction at a
point source.  That is, while P concentrations were still too high to reduce periphyton biomass below the
nuisance level (-150 mg chl/m2), P concentrations and biomass declined downstream and the extent of
the  decline can be estimated with this model.


Anderson, E .L., J. M. Jacoby, G. M. Schimek, E .B. Welch, and R .R. Horner. 1999. Periphyton removal
related to phosphorus and grazer biomass level. Freshwater Biol. 41:633-651.
                                          PAGE A-44

July 2000	Appendix A. Case Studies

Barko, J. W., D. Gunnison, and S. R. Carpenter.  1991. Sediment interactions with submersed
macrophyte growth and community dynamics. Aquatic Botany 41:41-65.

Charlton, S. E. D., H. R. Hamilton, and P. M. Cross. 1986. The Limnological Characteristics of the Bow,
Oldman and South Saskatchewan Rivers  (1979-82). Alberta Environment, Edmonton, AL.

Elswick, D. A., B. W. Mar, and E. B. Welch. 2000. The use of dynamic modeling to predict periphyton
algal biomass in the Bow River, Canada.  Department of Civil and Environmental Engineering, University
of Washington, Seattle.

Horner, R. R., E. B. Welch, M. R. Seeley, and J. M. Jacoby. 1990.  Responses of periphyton to changes
in current velocity,  suspended sediment and phosphorus concentration.  Freshwater Biol. 24:215-232.

Sosiak, A. J., Alberta Environment Protection, Calgary, Alberta.  Personal communication (unpublished
manuscript, "Long-term response of periphyton and macrophytes to reduced municipal nutrient loading
to the Bow River [Alberta, Canada].")
                                          PAGE A-45

Table A-4. Summary of Phosphorus and Periphytic Algal Data from the Bow River, Canada1
85th St. bridge

Stier's Ranch

Bow City

Ronalane Bridge

Distance from
Headwaters, km




Data type
post- treatment
post- treatment

post- treatment
post- treatment
post- treatment
post- treatment
post- treatment
post- treatment
Data years

Average summer
periphytic biomass,

biomass, mg/m2

Mean summer total
phosphorus, [ig/L

Mean summer total
dissolved phosphorus,

:Data from Sosiak, Alberta Environment Protection, personal communication
                                 Contact: Debbi Hart (4304), Headquarters Nutrient Program
                                       United States Environmental Protection Agency
                         Ariel Rios Building^l200 Pennsylvania Avenue, NW ^Washington, DC 20460

     ,2 600

      g 400 -

      O 300
      g 200 ~

     "ft 100

     PH   0

D Model
T> J' +'
r reaiction
D Actual Datum

               Stier's Ranch (11)     Carseland (56)
Bow City (240)    Ronalane Br. (332)
                                       Station and Downstream Distance (km)
Figure A-16. Model simulation of periphyton biomass during low-flow conditions in the Bow River downstream from the Fish
Creek STP, Calgary, Alberta, compared with actual 1997 data.

July 2000	Appendix A.  Case Studies
                                          PAGE A-48

July 2000	Appendix A.  Case Studies


As a class of pollutants, nutrients are unique from toxicants such as mercury or DDT, in that they have
known biological functions. Macronutrients such as nitrogen and phosphorus, are at once biological
necessities and, in excess quantity, agents of change to community and ecosystem attributes. As such,
great care must be taken in the characterization of nutrient regimes in stream ecosystems.  Streams are by
their very nature dynamically changing ecosystems that must be studied at ecologically meaningful
temporal and spatial scales (O'Neill et al. 1986). The characterization of "ambient"  conditions with a
few grab samples is inappropriate, if not reckless.  The researcher must first learn what limits autotrophic
productivity, the major nutrient sources and sinks and how and where nutrient transformations take place
in order to make informed decisions and avoid the adoption of water quality standards that may allow or
even cause shifts in stream community structure or ecosystem process.

The nutrient regime of streams in general can be complex, however, desert streams present particular
complexities not found in more homogeneous, mesic landscape stream ecosystems.  Spatial and temporal
variability in physical structure, community composition, materials availability and the interactions
between these elements strongly control nutrient processes in desert streams.  Dent and Grimm (in press)
found a high coefficient of variability (as high as 145%) in the spatial distribution of nutrients in
Sycamore Creek, Arizona, with coefficients of variation increasing over successional time. Part of this is
due to hydrologic variability, in all its temporal, spatial and amplitude scales. However, stream
ecosystems are complex in time, space, composition and process, and extend beyond the limit of the
wetted surface stream. These ecosystems must be considered as a whole, temporally and spatially, and
not as disconnected, stand alone components in order for accurate characterization to take place.

The following discusses  a number of the many determinants of nutrient regimes in desert streams. As the
subject matter of this section deals with desert streams, and in particular, southwestern hot desert
streams, the  literature cited will concentrate on research done in those ecosystems. A hierarchical
structure (sensu Stevenson 1997) will be used to organize determinants into ultimate, intermediate, and
proximate categories.  These hierarchical levels operate as interconnected units, with a particular level
being limited by constraints imposed by higher levels with processes structured at lower levels (Pickett et
al. 1989).  Because of the interconnectedness of the differing hierarchical scales, it will be sometimes
necessary to "mix" scales in the discussion that follows. Hydrologic variability and  its effects on desert
stream nutrient regimes is also discussed.


Ultimately, the stream is a product of its parent geology, catchment configuration and climate. In desert
streams, these structural determinants combine to organize processes at lower hierarchical levels forming
ecosystems unique from more mesic ecosystems.  These desert stream ecosystems consist of four
interconnected and interacting subsystems, the surface stream, the hyporheic zone (zone of subsurface
flow), the parafluvial zone (lateral sandbars within the active channel) and the riparian zone. These
subsystems interact with and are ultimately a product of the geology and the climate/precipitation

                                           PAGE A-49

July 2000	Appendix A.  Case Studies

Parent geology can play a large role in the availability of nutrients to aquatic ecosystems. Because of the
impermeability of desert soils and the low biomass per unit area found in terrestrial desert ecosystems,
materials entrained by precipitation events readily move into aquatic ecosystems, assuring an ample
supply of nutrients associated with the parent material.  Soils of the arid southwest are rich in calcium
phosphate (Fuller 1975) and transfer that nutrient readily to  stream ecosystems. A survey of 196 sites on
157 streams in Arizona found  soluble reactive phosphorus  (SRP) and total dissolved phosphorus did not
differ significantly among stream types (Fisher and Grimm 1983; Grimm and Fisher 1986a).  This
uniformity in concentration may be due to solubility equilibria (Stumm and Morgan 1981) and indicate
physical rather than biological control of this nutrient. The ample supply of phosphorus coupled with the
low overall input of nitrogen from the surrounding landscape has lead to the condition in which nitrogen,
rather than phosphorus, is the nutrient that limits primary productivity (Grimm and Fisher 1986b).

The size of the soil particles moving into and staying within the channel can also have a large impact on
the nutrient dynamics of streams (Jones 1995). In Arizona desert streams,  the unglaciated terrain
provides little silt and clay to the stream (Fisher 1986) and the flashy hydrologic regime may cause what
little sediment that makes it into the stream to be deposited either laterally  or in unconstrained reaches.
Valett et al. (1990) found that in Sycamore Creek, Arizona,  most sediment ranged in size from coarse
sand to fine gravel (0.5 -5.0mm).  This paucity of fine sediments allows a relatively high rate of
hydrologic conductivity within the hyporheic (Valett et al. 1990), parafluvial (Holmes et al. 1994), and
riparian zone (Marti et al. in press [a]).

The hydrologically conductive sediments beneath and lateral to the wetted stream are an important zone
of biologically mediated nutrient processes.  Jones et al. (1995) observed significant rates of nitrification
(mineralization of organic nitrogen to ammonia and a subsequent transformation to nitrate) within the
hyporheic zone of Sycamore Creek.  This nitrate rich hyporheic water may then exchange with nitrogen
poor surface water (Dahm et al. 1987; Valett et al. 1990; Stanley and Valett 1992) where it is an
important nutrient source for primary producers and may strongly influence biomass and community
composition (Valett et al. 1994).

The parafluvial zone consists of sediments within the active channel but outside the wetted stream.
Results from Holmes et al. (1994) indicate that the parafluvial zone can be an area of net nitrification,
and increased algal productivity has been observed on the downstream edges of parafluvial sandbars.
However, Holmes et al. (1996) found significant denitrification (the reduction of nitrate to nitrous oxide
or dinitrogen) potential existed in hyporheic and parafluvial sediments. Conservative estimations by
these authors indicated that 5-40% of nitrate produced by nitrification may be consumed by this process.

The riparian zone can also be an important area of nutrient storage and transformation. Denitrification
and uptake by vegetation within riparian areas  may constitute a significant sink of nutrients within a
watershed (Peterjohn and Correll 1984; Pinay and Decamps 1988).  Chauvet and Decamps  (1989) found
denitrification and nutrient retention to be important processes in these areas. Marti et al. (in press [b])
found retention of nutrients in riparian areas to be affected by the length of the interflood period rather
than by the magnitude of the flood.

The overall geomorphological structure of the stream, which is a product of geology and climate,
determines the pattern of the four subsystems; surface stream, hyporheic, parafluvial, and riparian. This

                                           PAGE A-50

July 2000	Appendix A. Case Studies

spatial mosaic can have a strong influence on the retention, transformation, uptake, and emission of
nutrients (Fisher et al. 1998a).

The climate, while a contributing determinant of desert stream physical structure, is also an ultimate
determinant of biological structure and function. Desert streams receive high rates of insolation due to
the low amount of shading contributed by the relatively open riparian canopy.  This open canopy itself is
a product of the low precipitation rates and high pan evaporation rates found in southwestern deserts.
Although precipitation rates are low in desert landscapes, this sparse precipitation may contribute
substantial amounts of nitrate and ammonium to desert stream ecosystems (Grimm 1992).


Community structure and function are shaped in part by the constraints imposed from the higher
geological and climatic scale. Species composition and life history are ultimately products of the
physical components of aquatic ecosystems and, in turn, alter physical structure and chemical processing
at the ecosystem level. These interactions can significantly affect nutrient dynamics in aquatic

The change in the biotic community that occurs over time after a flood disturbance shapes and changes
nutrient processing. The concept of temporal succession has been put forward to conceptualize this
temporal change that occurs after a flood disturbance.  Fisher et al. (1982) described the recovery of
community and ecosystem attributes after flooding disturbance in Sycamore Creek, Arizona, as  a model
of temporal succession. In these ecosystems, biologically driven nutrient transformation, uptake, and
emission can vary significantly over spatial and temporal scales.

Changes in nutrient processing and species composition over successional time can drastically alter the
nutrient regime of streams in general, and, due to their open, autotrophic nature, in desert streams in
particular. A flood disturbance of sufficient magnitude can scour and shuffle hyporheic and parafluvial
sediments, removing attached biomass and essentially homogenizing ecosystem structure and function at
the reach level. The emergent physical structure confers organization to the biotic community
recolonizing the reach post flood.  During the interflood period, biological processes become a
progressively more prominent organizational force which,  given a sufficient interdisturbance interval,
can then confer organization to higher hierarchical levels.

The complexity of nitrogen processing interactions increases with successional time. Dent and Grimm
(in press) found nutrient spatial heterogeneity in the surface stream to increase with time post flood. Over
successional time, nitrogen uptake length decreases due to increased biological uptake (Fisher et al.
1982; Marti et al. 1997) and  retention of nitrogen in the surface stream increases from early to mid
successional stages and then declines during late succession (Grimm 1987). The changes seen in nutrient
processing length due to disturbance may vary according to the relative resistance of the individual
stream subsystem and recovery may vary over successional time due to relative resilience (Fisher et al.

Streams by their very nature  are spatially heterogeneous.  In desert streams, the spatial heterogeneity of
nutrients and nutrient processing is manifested in several ways. Hydrologic linkages between the surface

                                           PAGE A-51

July 2000	Appendix A.  Case Studies

stream and the parafluvial and hyporheic ecosystem components vary spatially due to the underlying
geomorphological structure of the stream ecosystem.  As stated earlier, these are areas where important
nutrient processing occurs. The extent and intensity of hyporheic upwelling and downwelling can change
or even reverse in response to flooding or drying (Stanley and Valett 1992; Valett et al.  1994)
considerably affecting concentrations of nitrate in the surface stream and influencing algal community
composition (Valett et al. 1994).

One of the most striking successional events in desert streams is the drying and contraction of the surface
stream ecosystem.  This phenomena can take place either at large spatial and temporal scales, or at the
scale of the reach during a 24 hour period. In Sycamore Creek, as the quantity of water delivered to the
surface stream ecosystem begins to diminish after an extended wet period or post flood, drying begins to

During dry periods, the wetted surface stream area can contract as much as eight fold at the scale of the
entire basin. (Stanley et al. 1997). At the scale of the individual run, drying may begin at the downstream
terminus and continue upstream to the area of hyporheic upwelling at the head of the run (Stanley et al.
1997). This contraction of the surface water ecosystem can strongly affect algal community composition.
Nitrogen fixing cyanobacteria species inhabiting the downstream extremity of the  drying run are exposed
to the atmosphere long before upstream mats of filamentous green algae situated closer to the source of
nitrogen rich hyporheic upwelling, potentially  altering nitrogen cycling (Stanley et al. 1997). At all
scales, drying of the surface stream increases the relative contribution of hyporheic processes to overall
ecosystem function (Stanley and Valett 1992).

The increase in the relative proportion of the wetted stream ecosystem occupied by subsurface
subsystems could have a profound effect on nitrogen processing and retention. With the decline of
surface stream area available to autotrophic production and nitrogen fixation, the nitrogen
transformations associated with subsurface flowpaths, nitrification, and denitrification will become
proportionally more prevalent (Stanley and Valett 1992).  This, coupled with the ample  organic carbon
available from decaying algae (Jones et al.  1995) and oxygen depletion due to respiration over extended
hyporheic flowpaths, could possibly cause subsurface subsystems to become net nitrogen emitters. This
emission of nitrogen gas would represent a real loss of nitrogen from the stream ecosystem.

The riparian component of the desert stream ecosystem, while ultimately a product of climate, geology,
and catchment configuration, also modifies environmental factors within the ecosystem of which it is a
part. At successional and reach scales, the presence of riparian vegetation is a strong determinant of the
shape of the surface stream channel. Given a long period between stand destructive  floods and ample
surface or near surface water, fast growing woody species such as seep willow (Baccharis salicifolia) will
progressively impinge on the surface stream. As the surface stream narrows, parafluvial ecosystem
components gradually convert to  riparian, considerably changing nutrient processing pathways.

The high pan evaporation rate (>300 cm year-1) found in hot desert ecosystems coupled with high
consumptive water use by phreatophytes (water-loving riparian plants) (1514 L day -1) (Blaney and
Criddle 1962) can significantly influence the size of a surface  stream reach on a diel basis. Large
changes in reach length during a 24 hour period have been observed on Sycamore  Creek (Stanley pers.
com.). This type of short term stress can effectively eliminate desiccation intolerant organisms from the
benthic community of large portions of a stream reach.
                                           PAGE A-52

July 2000	Appendix A. Case Studies

In contrast to more mesic streams, many desert stream riparian zones occupy a relatively narrow band
lateral to an underfit surface stream, providing minimal shading to the surface stream itself. The resultant
high rate of insolation to the surface stream favors high rates of primary productivity, high relative water
temperatures, and attendant increases in metabolic rates (Busch and Fisher 1981). The elevated rates of
primary productivity and metabolism are controlling factors in the short uptake lengths for nitrogen
covered earlier in this  document.


The nitrogen cycle, as it occurs within a desert stream, is essentially a biologically driven process. Given
the  physical organization conferred from higher hierarchical levels, the resultant biotic communities of
the  surface stream, riparian, parafluvial, and hyporheic control fixation, mineralization, nitrification and

Nitrogen fixation by heterocystous cyanobacteria such as Nostoc or Calothryx and diatoms with
phycoendosymbionts such as Epithemia sorex may be significant in nitrogen poor desert stream
ecosystems. Grimm and Petrone (1997) measured in-situ N2fixation rates as high as 51mg N2 m"2 h"1.
These rates were high in comparison to published values from more mesic inland systems. In this study,
as much as 85% of the net nitrogen flux to the benthos was accounted for by N2 fixation on five dates for
which nitrogen input/output budgets were constructed. Nitrogen fixation may be an extremely important
vector of nitrogen into desert stream ecosystems, as between precipitation events, little fixed nitrogen
from the surrounding uplands is transported to the stream ecosystem (Grimm and Petrone 1997).

As  stated earlier, nitrification, or the biologically mediated oxidation of ammonium to nitrate takes place
within hyporheic and parafluvial sediments. Jones et al. (1995) reported mean nitrification rates of 13.1
mg  NO3  L sediments"1 h"1 in downwelling zones in Sycamore Creek and Holmes et al. (1994) reported
increases in nitrate concentrations in water moving through parafluvial flowpaths. In both studies, the
highest rates of biotic  activity occurred at the interface where the surface stream infiltrated into
hyporheic/parafluvial  sediments. This effect suggests the importance of dispersed interfaces in a
heterogeneous system (Dahm et al. 1998)

Denitrification is well documented in anoxic environments such as riparian soils (Peterjohn and Correll
1984; Lowrance et al.1984), but in well oxygenated environments such as the coarse sand/gravel
hyporheic/parafluvial  subsystems found in desert streams, the occurrence of denitrification is somewhat
of a conundrum. Holmes et al. (1996) investigated denitrification potential in hyporheic, parafluvial and
riparian sediments and found field measured rates in excess of 150 mg N m2 h"1 at the stream/parafluvial
interface. This study also found the highest rates of biotic activity (denitrification) at the point of
infiltration at the surface-water-sediment interface.

Despite the low overall availability of the most probable limiting nutrient in southwestern hot desert
streams, nitrogen, high mid-summer instantaneous standing crops of algae (191 mg -1 m"2 chlorophyll a)
have been measured in Sycamore Creek (Busch and Fisher 1981). The spatial distribution of algal
standing crop  has been linked with areas of hyporheic upwelling and downwelling. Valett et al. (1994)
found significantly higher areal concentrations of chlorophyll a in upwelling zones when compared to
areas  of downwelling. These high  quantities of algal biomass and the associated autotrophic uptake of
nitrogen are the most probable cause for the declines in nitrogen concentrations of surface water found
                                           PAGE A-53

July 2000	Appendix A. Case Studies

downstream of spring sources (Grimm et al., 1981) and the lower concentrations found at points of
downwelling (Valett et al., 1994).

Organic carbon released as a result of autochthonous primary production has been hypothesized as the
energy source utilized in nitrification (Holmes et al.,  1994; Jones et al., 1995) and denitrification
(Holmes et al., 1996). However, allochthonous input of organic matter from riparian leaf litter was found
to play an insignificant role in nitrogen dynamics in Sycamore Creek (Schade and Fisher 1997).

Macroinvertebrates may also significantly affect nitrogen processing in desert streams.  Grimm (1988)
found that during a 20 day successional period, collector gatherer invertebrate standing stock increased
from 32,000 to 108,000 individuals  m2.  Twenty seven percent of the nitrogen ingested by the collector
gatherers during this period was converted to biomass, of which only 26% (7% of total ingested nitrogen)
remained in the stream  as macroinvertebrate biomass. One percent of collector gatherer biomass was lost
to the surrounding  upland ecosystem due to the emergence of adults, 19% was lost to mortality and 9-
31% was excreted  as ammonia.  The transformation of organic nitrogen to ammonia may be particularly
significant, as the ammonia form of nitrogen is readily taken up and utilized by primary producers or
available for utilization in nitrification/denitrification transformations.


While hydrologic variability is an important consideration in the development of nutrient  standards for
all streams, the spatial and temporal  heterogeneity found in arid regions, the stark contrast between wet
and dry, brings this variability into sharper relief. When viewing desert catchments from above, the
observer is often presented with a dry landscape of high relief bisected by the string of glistening beads
that is the spatially intermittent stream. The dry arroyos or quiet, disconnected pools and  short reaches of
wetted stream that  characterize desert streams  during dry periods are in complete contrast to the  raging
torrents that they can become at flood stage. This hydrologic variability and the unique chemical and
biological characteristics of arid lands aquatic  ecosystems may make the use of broad generalizations to
explain nutrient regimes impossible.

When analyzing stream nutrient regimes in the context of hydrologic variability, there is a continuum of
spatial and temporal scale (sensu Pickett et al.  1989; Fisher and Grimm 1991) beyond and including
discreet disturbance flows which must be considered. Ecologically important spatial and temporal scales
can vary from that  of a  discreet patch at a single point in time, to the fluvial geomorphological and
climatic factors determining the physical structure of an entire catchment. These spatial and temporal
scales exist as nested hierarchies, with structure at smaller scales being influenced by higher scales
(Pickett et al. 1989).

Use of a coherent hierarchical schema can confer useful organization to the analysis of nutrients and
primary productivity. The heterogeneity of benthic algal assemblages is determined at several
hierarchical levels, with proximate and intermediate determinants such as nutrient regime and flow
stability being governed by the ultimate determinants of climate and geology (Stevenson 1997).  It is
important to consider the determinants of structure  and function at different scales when designing
ecological studies.
                                           PAGE A-54

July 2000	Appendix A.  Case Studies

In arid landscapes, stream ecosystems are more dynamically linked with the surrounding upland
ecosystem than streams in more mesic regions. This close linkage is due to the higher percentage of
uninterrupted vectors of runoff and entrained materials from the surrounding uplands to the aquatic
ecosystem. The extensive riparian buffers and dense upland terrestrial vegetation found in more mesic
ecosystems are largely absent in spatially intermittent and ephemeral watercourses. The sparse
vegetative cover (5-50%; Barbour et al.  1980) and high orographic relief found in the upland terrestrial
catchments promote increased rates of short-term, sheetflow runoff during intense precipitation events,
leading to larger, more rapid movements of precipitation and entrained materials into watercourses (see
Graff 1988).  This "spiky"  oscillation in the hydrograph is then transferred downstream to the more
perennial sections of a stream.

In desert streams,  surface discharge regimes may vary from completely dry, to flows as much as three to
five orders of magnitude greater than mean annual flow,  all within a period of hours or days.  In
comparison to streams in more mesic regions, the coefficient of variation of annual flow is 467% greater
in arid land lands  streams (Davies et al.  1994). The aquatic ecosystems structured by these often
catastrophic and always chaotic flow regimes exhibit spatially and temporally heterogeneous structures
and functions (sensu Thorns and Sheldon 1996) which may not allow the application of nutrient criteria
derivation techniques applicable to more homogeneous environments.

Short-term disturbance of small spatial extent may cause considerable alteration in the chemical and
biological structure of a stream. Flooding may scour the benthic surface, reset the stream ecosystem to
an earlier successional stage (Fisher  1983) and transport large, short-term pulses of nutrients  (Fisher and
Minckley 1978).  Drying of a surface stream reach due to diel changes  in evapotranspiration can strand
algal mats (Stanley pers. com.) causing a stress disturbance (sensu Pickett et al.  1989). Recovery from
these types of small scale disturbances may be rapid in ecosystems where the  biota is disturbance adapted
(Gray 1981; Grimm and Fisher 1989) and when observed in the context of larger spatial and temporal
scales, these types of disturbances may represent normal oscillations in a steady state equilibrium.

Often, hydrologic regimes that effect a particular ecological structure or function may exist at spatial and
temporal scales that can only be measured using multiple measurements over  space and time. While the
flood pulse itself may cause considerable disturbance to a stream ecosystem, the entire hydrologic regime
must be considered biologically significant (Poff and Ward 1989). Variability in rates of rise  and fall,
timing, duration, magnitude and frequency of the flood pulse can have  a significant effect on  the biota of
a stream (Puckridge et al. 1998). At slightly longer temporal scales, it is the relatively short interval (1.5
year) bankfull discharge that forms and maintains the physical structure of the wetted channel (Dunne
and Leopold 1978) rather than the catastrophic long return interval flood.

During interflood  periods, flow regimes are comparatively stable as precipitation stored within the
watershed moves  into the stream. The stable flow allows the control of ecosystem state variables, such as
primary productivity, to shift from disturbance to morphometric/biotic  controls. If the interflood period is
of sufficient duration,  a phase shift from wetted surface to dry occurs as flow from the watershed
diminishes (Fisher and Grimm  1991). During this interval, primary productivity is a partial function of
the  number of days post flood (Fisher 1986; Fisher and Grimm 1988). Characterization of the interflood
period is an important tool which may allow the researcher to locate the point in successional time when
indexing biological data for inter or intra-stream comparison.

                                           PAGE A-55

July 2000	Appendix A. Case Studies

One portion of the hydrologic regime that is often overlooked is drying. Drying disturbance, or more
specifically the contraction and fragmentation of a stream ecosystem, occurs as a spatially or temporally
intermittent stream recedes after a wet period. Differing reach types (e.g., riffles, runs, constrained,
unconstrained) respond to this contraction and fragmentation differentially (Stanley et al. 1997) and
hyporheic, or subflow processes may come to dominate as a larger portion of the wetted volume of a
stream is subsurface. (Stanley and Valett 1992; Valett et al. 1990).  Drying is likely to be an important
determinant of biological pattern and process (Stanley et al. 1997; Stanley and Boulton 1995), especially
in streams where the dry period and extent may be greater than the wet.

Longer-term hydrologic/disturbance regimes are also an important consideration. Decadal climate
variability such as the El Nino and La Nina  phenomena can cause large, prolonged fluctuations in stream
flow (Molles and Dahm 1990). This long return interval climate variability and the attendant change in
short-term weather patterns can significantly affect the structure and function of aquatic ecosystems. The
establishment, maintenance and species composition of riparian associations are strongly dependant on
the  seasonality, periodicity, duration, sequentiality and magnitude of storm events and subsequent flow
regimes (Baker 1990; Stromberg etal. 1991).

Large, long return interval disturbances can also greatly alter the physical structure and pattern of
watercourses at greater than reach scales.  These large alterations may affect the physical equilibrium of
the  watercourse in several ways.  If the system is stable or dynamically stable, internal feedback
mechanisms will cause physical values such as bed load transport to return to original following a
disturbance. If a system is unstable or metastable,  the system may adjust to a new value causing changes
in channel pattern and shape  (sensu Chorley and Kennedy 1971).

In the event a large scale, destructive flood event significantly restructures a stream, changes may occur
in mean particle size, pattern of reach types or the ratio of the different stream ecosystem components
(surface, riparian, parafluvial, hyporheic). These changes in physical structure  may significantly alter the
prevailing nutrient regime (sensu Fisher et al. 1998a).

In order to properly characterize the nutrient regime of a stream ecosystem, the  flow of water, surface or
subsurface, flood or base  flow, wet or dry must be  considered at ecologically significant temporal and
spatial scales.  It is also important that the researcher address this hydrologic regime at the scale of the
question to be answered.  If a stream is dry for 75% of the average year, or 75% of its length, is it correct
to characterize it from surface water data alone?  If 50% of the entire annual load of a limiting nutrient
passes through a stream ecosystem in three discreet storm events, what is the effect of that nutrient on the
stream ecosystem itself?  What is the effect to downstream ecosystems? Due to the spatial and temporal
variability of flow patterns, the characterization of desert stream nutrient dynamics is an intricate
undertaking. However, it is  important to  recognize that all stream ecosystems posses complexities that
will only yield to proper inquiry.


The characterization of nutrient dynamics in streams with high temporal and spatial variability, such as
southwestern hot desert streams, may prove to be difficult without a commitment to addressing questions
at the appropriate ecological  scale. Variability in the products of climate and geology; precipitation, flow
regime and physical structure, define the limits of community composition and  nutrient processing.  The
                                           PAGE A-56

July 2000	Appendix A.  Case Studies

predictive power of any model designed to characterize nutrient dynamics without considering the
ultimate determinants is extremely limited. Conversely, relying on coarse generalizations generated at
the spatial and temporal scale of the ecozone to predict process at the scale of the reach is also
inappropriate.  Nutrient dynamics must be characterized and nutrient water quality standards  developed
considering the constraints and processes dictated at the different and interacting scales.


Selecting Index Sites and Periods
As in any investigation, the researcher must remove or account for as many of the differing sources of
variability as possible prior to gathering nutrient data.  In streams with high spatial and temporal
variability, the best case scenario would be to characterize the entire stream, source to terminus, in space
and time. While this may be the most scientifically sound methodology, it is infeasible in all but the
smallest basins. An alternative is to carefully choose and compare index sites (and periods) from which
reasonable extrapolations can be made.  This can be done using a similar hierarchical approach to that
outlined above, however, extrapolation beyond the specific index is risky. The number of sights required
to accurately characterize the nutrient regime in a stream type will vary with the complexity of that
nutrient regime.

First, at the largest spatial scale, the position of the stream reach within the watershed must be
determined. The areal extent of the basin above the sample reach, the watershed aspect (orientation to
weather patterns), mean stream gradient, parent material(s) and stream order are all attributes that should
be considered. At the largest temporal scale, the time since the last flood that restructured all of the
stream compartments (surface, hyporheic, parafluvial, and near stream riparian) should be determined as
well as any long-term fluctuations or trends in the hydrograph.

At the scale of the sample reach, the researcher should consider the landscape setting surrounding and
upstream of the sampling point.  It is important that the sample reach and surrounding landscape be
consistent with that found for a reasonable distance upstream. This distance will depend on stream
velocity, with greater distances being required in faster flowing streams.  The following is a list of the
major elements of a sample reach that should be addressed to characterize nutrient regime and increase
data conformity between sampling sights:

Physical/Structural Elements
         terrestrial vegetation association
      •   terrestrial land use
      •   Rosgen stream type
      •   physical setting - constrained or unconstrained? (canyon or open plane)
      •   reach gradient
         solar aspect - is the sun blocked by canyon walls at times during the day or year?
         riparian association - including understory plants
         riparian cover percent
         riparian canopy density - stream shading
      •   stream discharge and velocity
                                           PAGE A-57

July 2000	Appendix A. Case Studies

      •   substrate particle size distribution
      •   estimated subsurface compartment volume (hyporheic, riparian and parafluvial)
      •   location of upwelling and downwelling zones
         water temperature

Temporal Elements
      •   season
      •   photoperiod
      •   time since last flood
      •   flow regime the previous 30 days
         temperature regime the previous 30 days (air and water)

Chemistry (other than TN and TP)
      •   NH3/NH4, NO3, SRP
      •   CO2
      •   potassium (K), calcium (Ca), magnesium (Mg), sulphur (S), boron (B), chlorine (Cl), copper
         (Cu), iron (Fe) manganese (Mn), molybdenum (Mo) and zinc (Zn)
      •   O2 - dissolved and  % saturation
      •   pH - field measured
         electrical conductivity
         total dissolved solids
         total organic carbon
         turbidity - field measured
      •   total suspended solids
      •   volatile suspended solids
Biological Elements
         algal community composition
      •   benthic chlorophyl a
         benthic organic matter
         benthic community productivity and respiration
When taking physical, chemical or biological samples, it is extremely important to choose the sampling
point(s) and times carefully in order to accurately characterize the element in question for a particular
reach at a particular time. Multiple samples taken within the reach and analyzed separately is the
preferred method, however composite samples, or carefully taken grab samples can work well. The
researcher should avoid or account for samples taken in areas of the stream that differ from the main
body. Anoxic backwaters, upwelling or downwelling zones, highly aerated areas below waterfalls and
other sections that differ physically, chemically, or biologically from the main stream, usually account
for only a small portion of total stream area but may contribute significantly to materials processing.
Rather than characterizing these sections individually, a point can be chosen that integrates these areas
into the greater flow. A fast "run" with relatively uniform flow, biological, and bank characteristics for
20 meters that has neutral subsurface hydraulic head may be a good selection. Insolation rate (solar
                                           PAGE A-58

July 2000	Appendix A. Case Studies

energy per unit area per unit time) and diel curve should also be considered, although a viable alternative
would be careful consideration of time of day, time of year, riparian shading, and cloud cover.

It is extremely important that enough data be gathered to characterize a nutrient regime. While the
ancillary data requirement may seem large, lack of one or more of these data points may preclude
accurate interpretation of the nutrient data.


Baker,  William L. 1990. Climatic and hydrologic effects on the regeneration of Populus angustifolia
James along the Animas River, Colorado. Journal of Biogeography. 17(1): 59-73.

Barbour, M. G., J. H. Burk, and W. D. Pitts.  1980.  Terrestrial Plant Ecology. The
Benjamin/Cummings Publishing  Company, Menlo Park, CA.

Blaney, H. and W. Criddle, 1962. Determining consumptive use and irrigation water requirements.
USDA Technical Bulletin Number 1275, 59 pages.

Busch, D.E., and S.G. Fisher. 1981. Metabolism of a desert stream. Freshwater Biology 11:301-308.

Chauvet, E. and H. Decamps. 1989. Lateral interactions in a fluvial landscape: the River Garonne,
France. Journal of the North American Benthological Society. 8(1) p 9-17.

Chorley, R. J. and B. A. Kennedy.  1971. Physical geography: a systems approach. Prentice-Hall,

Dahm,  C.N., N.B.  Grimm, P. Marmonier, H.M. Valett, and P. Vender. 1998. Nutrient dynamics at the
interface between surface waters  and ground waters. Freshwater Biology 40:427-451.

Dahm,  C. N., E. H. Trotter and J. R. Sedell, 1987. Role of anarobic zones and processes in stream
ecosystem productivity. P 157-178 in R. A. Averett and D. M. McKnight, editors.  Chemical quality of
waterand the hydrologic cycle. Lewis, Chelsea, Michigan.

Davies, B. R., Thorns, M. C., Walker, K. F., O'Keeffe, J. H., and Gore, J. A. 1994. Dryland rivers: their
ecology, conservation and management, in Calow, P. and Pets, G. E. (Eds) The Rivers Handbooy, Vol. 2,
Blackwell Scientific, Oxford. 484-512

Dent, C.L., and N.B. Grimm. Spatial heterogeneity in stream water nutrient concentrations over
successional time. Ecology: in press.

Dunne, T. and L. B. Leopold, 1978. Water in environmental planning.  W. H. Freeman and Co. San
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July 2000	Appendix A. Case Studies

Fisher, S.G. 1983. Succession in streams. Pages 7-27 in J. Barnes and G.W. Minshall, editors. Stream
ecology: Application and testing of general ecological theory. Plenum Press, New York, New York,

Fisher, S.G. 1986. Structure and dynamics of desert streams. Pages 114-139. IN: W. Whitford (ed.).
Pattern and Process in Desert Ecosystems. University of New Mexico Press, Albuquerque.

Fisher, S.G., L.J. Gray, N.B. Grimm, and D.E. Busch. 1982. Temporal succession in a desert stream
following flash flooding. Ecological Monographs 52:93-110.

Fisher, S.G., and N.B. Grimm. 1983. Water quality and nutrient dynamics of Arizona streams. OWRT
Project Completion Report A-106-ARIZ. Office of Water Research and Technology.

Fisher, S. G., and N. B. Grimm. 1988. Disturbance as a determinant of structure in a Sonoran Desert
stream ecosystem. Internationale Vereinigung fur Theoretische und Angewandt Limnologie,
Verhandlungen 23:1183-1189.

Fisher, S.G., and N.B. Grimm. 1991. Streams and disturbance: are cross-ecosystem comparisons useful?
pp 196-221 in J.C. Cole, G.M. Lovett, and S.E.G. Findlay, editors. Comparative analyses of ecosystems:
patterns, mechanisms and theories. Springer-Verlag, New York, New York, U.S.A.

Fisher, S.G., N.B. Grimm, E. Marti,  and R. Gomez.  1998a. Hierarchy, spatial configuration, and nutrient
cycling in streams. Australian Journal of Ecology 23: 41-52.

Fisher, S.G., N.B. Grimm, E. Marti., J.B. Jones, Jr.,  and R.M. Holmes. 1998 (b). Material spiralling in
river corridors: a telescoping ecosystem model. Ecosystems  1:19-34.

Fisher, S.G., and W.L. Minckley.  1978. Chemical characteristics of a desert stream in flash flood. Journal
of Arid Environments 1:25-33.

Fuller, W. H. 1975. Soils of the desert southwest. University of Arizona Press.  102p

Graff, W. L.  1988. Fluvial Processes in Dryland Rivers. Springer-Verlag, New York.

Gray, L.J. 1981. Species composition and life histories of aquatic insects in a lowland Sonoran Desert
stream. American Midland Naturalist 106:229-242.

Grimm, N.B. 1987. Nitrogen dynamics during succession in a desert stream. Ecology 68:1157-1170.

Grimm, N. B. 1988. Role of macroinvertebrates in nitrogen dynamics of a desert stream. Ecology 69:

Grimm, N.B. 1992. Biogeochemistry of nitrogen in arid-land stream ecosystems. Journal of the
Arizona-Nevada Academy of Science 26:130-146.

                                          PAGE A-60

July 2000	Appendix A. Case Studies

Grimm, N.B., and S.G. Fisher. 1986a. Nitrogen limitation potential of Arizona streams and rivers.
Journal of the Arizona-Nevada Academy of Science 21:31-43.

Grimm, N.B., and S.G. Fisher. 1986b. Nitrogen limitation in a Sonoran Desert stream. Journal of the
North American Benthological Society 5:2-15.

Grimm, N.B., and S.G. Fisher. 1989. Stability of periphyton and macroinvertebrates to disturbance by
flash floods in a desert stream. Journal of the North American Benthological Society 8:293-307.

Grimm, N.B., S.G. Fisher, and W.L. Minckley. 1981. Nitrogen and phosphorus dynamics in hot desert
streams of Southwestern U.S.A. Hydrobiologia 83:303-312.

Grimm, N.B., and K.C. Petrone.  1997. Nitrogen fixation in a desert stream ecosystem. Biogeochemistry

Holmes, R.M., S.G. Fisher, and N.B. Grimm.  1994. Parafluvial nitrogen dynamics in a desert stream
ecosystem. Journal of the North American Benthological Society 13:468-478.

Holmes, R.M., J.B. Jones, Jr., S.G. Fisher, and N.B. Grimm. 1996. Denitrification in a nitrogen-limited
stream ecosystem. Biogeochemistry 33:125-146.

Jones Jr., J.B. 1995. Factors controlling hyporheic respiration in a desert stream. Freshwater Biology

Jones, J.B., Jr.,  S.G. Fisher, and N.B. Grimm. 1995. Nitrification in the hyporheic zone of a desert stream
ecosystem. Journal of the North American Benthological Society 14:249-258.

Lowrance, R., R. Todd, J. Fail Jr., O. Hendrickson Jr., R. Leonard and L. Asmussen. 1984. Riparian
forests as nutrient filters in agricultural watersheds. Bioscience 34(6) p 374-377.

Marti, E., S.G. Fisher, J.J. Schade, and N.B. Grimm, in press (b) Effect of flood frequency on
hydrological and chemical linkages between streams and their riparian zones: an intermediate disturbance
model. J.B. Jones, Jr., and P.J. Mulholland, editors. Surface-subsurface interactions in streams. Book

Marti, E., S.G. Fisher, J.J. Schade, J.R. Welter, and N.B.  Grimm, in press (a) Hydrological and chemical
linkages between streams and their riparian zones: an intermediate disturbance model. Internationale
Vereinigung fur Theoretische und Angewandt Limnologie, Verhandlungen 27.

Marti, E., N.B. Grimm, and S.G. Fisher. 1997. Pre- and post-flood nutrient retention efficiency in adesert
stream ecosystem. Journal of the North American Benthological Society  16:805-819.

Molles, M. C., Jr., and C. N. Dahm. 1990. A perspective on El Nino and La Nina: global implications for
stream ecology. Journal of the North American Benthological Society. 9:68-76.

                                           PAGE A-61

July 2000	Appendix A. Case Studies

O'Neill, R. V., D. L. DeAngelis, J. B. Waide and T. F. H. Allen, 1986. A hierarchical concept of
ecosystems. Princton University Press, Princton, New Jersey.

Peterjohn, W. T. and D. L. Correll.  1984. Nutrient dynamics in an agricultural watershed: observations
on the role of a riparian forest.  Ecology 65(5) p 1466-1475.

Peterson, C.G., and N.B. Grimm. 1992. Temporal variation in enrichment effects during periphyton
succession in a nitrogen-limited desert stream ecosystem. Journal of theNorth American Benthological
Society 11:20-36.

Pickett, S. T. A., J. J Kolasa, and S. L. Collins. 1989. The ecological concept of disturbance and its
expression at various hierarchical levels. Oikos 54: 129-136.

Pinay, G. and H. Decamps. 1988.  The role of riparian woods in regulatimg nitrogen fluxes between the
alluvial aquifer and surface water: a conceptual model. Regulated Rivers; Research and Management
Volume 2. p 507-516.

Poff, N.L., and J.V. Ward. 1989. Implications of streamflow variability and predictability for lotic
community structure: a regional analysis of streamflow patterns. Canadian Journal of Fisheries and
Aquatic Sciences.  46:1805-1818.

Puckridge, J.T., Sheldon, F., Walker, K.F. & Boulton, A.J. 1998. Flow variability and the flood pulse
concept in river ecology. Australian Journal of Marine and Freshwater Research.

Schade, J.D., and S.G. Fisher.  1997. The influence of leaf litter on a Sonoran Desert stream ecosystem.
Journal of the North American Benthological Society 16:612-626.

Stanley, E.H. 1999.  Personal Communication Department of Zoology, University of Wisconsin,
Madison, WI

Stanley, E.H. and A.J. Boulton. 1995. Hyporheic processes during flooding and drying in a Sonoran
Desert stream. I. Hydrologic and chemical dynamics. Archiv fur Hydrobiologie 134:1-26.

Stanley, E.H., S.G. Fisher, and N.B. Grimm. 1997. Ecosystem expansion and contraction: a desert stream
perspective. BioScience 47:427-435.

Stanley, E.H. and H.M. Valett. 1992. Interaction between drying and the hyporheic zone  of a desert
stream ecosystem, pp 234-249 in P. Firth and S.G. Fisher, editors. Climate Change and Freshwater
Ecosystems. Springer-Verlag, New York, New York, U.S.A.

Stevenson, R. J. 1997. Scale dependent determinants and consequences of benthic algal heterogeneity.
Journal of the North American Benthological Society. 16(l):248-262

Stromberg, J. C., D.  T. Patten and B. D. Richter. 1991. Flood flows and dynamics of Sonoran riparian
forests. Rivers 2(3):221-235.	
                                           PAGE A-62

July 2000	Appendix A. Case Studies

Stumm, W. G. and J. J. Morgan, 1981. Aquatic chemistry, John Wiley and Sons, New York.

Thorns, M.C. and Sheldon, F. 1996. The importance of channel complexity for ecosystem processing: An
example of the Barwon-Darling River. Pp: 111-118 in Rutherfurd, I. (ed) Stream Management in
Australia. CRC for Catchment Hydrology, Melbourne.

Valett, H.M., S.G. Fisher and E.H. Stanley. 1990. Physical and chemical characteristics of the hyporheic
zone of a Sonoran Desert stream. Journal of the North American Benthological Society 9:201-215.

Valett, H.M., S.G. Fisher, N.B. Grimm, and P. Camill. 1994. Vertical hydrologic exchange and
      ;     ;           ;            ;                           j     o        O
ecological stability of a desert stream ecosystem. Ecology75:548-560.
                 Contact: Suesan Saucerman, Region 9 Nutrient Coordinator
                       United States Environmental Protection Agency
                       75 Hawthorne Street +San Francisco, CA 94105
                                         PAGE A-63

July 2000	Appendix A.  Case Studies
                                          PAGE A-64


Several methods used to analyze certain water quality variables are discussed briefly in this section.
Additionally, relevant publications are referenced as appropriate. Some tips on analysis will also be
presented to help users to be efficient in determinations.  As with any environmental analysis, the most
efficient strategy when learning a new technique is to visit a laboratory where it is routinely performed.
The methods that will be discussed include those for light transmission; total suspended solids; total
nitrogen, total phosphorus, and dissolved inorganic nitrogen and phosphorus; conductivity; chlorophyll a
and ash free dry mass (AFDM) for algal biomass; and microscopic identification to determine the algal
taxa present.  Brief discussion of secondary indicators of eutrophication (algal production, dissolved
oxygen concentrations, limiting nutrients and macroinvertebrates) will also be presented.  As discussed
above, determination of other factors such as hydrology, geology, soil characteristics may also be



Total suspended solids and dissolved humic  compounds  can absorb light and limit algal biomass. As
periphyton biomass increases, particulate matter sloughed and eroded from the periphyton also increases,
reducing transparency. Light transmission measurements may be required. Light transmission can be
measured using turbidity meters (transmissometers or turbidometers). Use of these meters is described in
Standard Methods (APHA 2000).  A quick method for determining light transmission is use of a black
disk and an underwater periscope (Davies-Colley 1988). The path length for transparency is measured
horizontally in shallow streams, as opposed to vertically in lakes, reservoirs and deep rivers or estuaries.
The vertical water column in relatively clear-water, gravel/cobble bed streams/rivers is usually
insufficient to determine Secchi disk depth.


Light availability can be measured directly with a light meter as photon flux density (|_imole quanta m"2
s"1), but such measurement vary temporally.  Measures of % canopy cover, TSS and average water depth,
light transmission with a black disk or periscope, and stream direction provide measures of relative
availability of light which can be related to a regional average. Light intensity varies so much during a
day or with weather from day to day that indicators of relative light intensity may be a more precise
indicators of light availability than one-time  measurements of light intensity.

Light availability for photosynthesis can be reduced by the amount of total suspended sediment (TSS) in
the water column, light attenuation caused by dissolved compounds, river depth,  and channel shading. In
addition to scouring algae, TSS also attenuates light to benthic algae. Dissolved  organic humic
compounds can absorb light, and if they are present in high enough concentrations, they can prohibit
algal growth. Similarly,  forest canopies can  shade stream channels (Dodds et al.  1996). This shading
can lead to rivers with relatively high nutrient concentrations, but with negligible sestonic or benthic
algal biomass. In such cases, nutrient control may have few immediate benefits.

If there is seasonally high TSS  or shading (e.g., deciduous forests), the high nutrients may cause
excessive periphyton algal biomass only during certain times of the year. An example of this would be

                                           PAGE A-65

July 2000	Appendix B. Laboratory and Field Methods and Analyses

streams where snow melt is common in the spring; this could lead to high levels of TSS and low algal
biomass, but during stable flows in summer, low TSS and high algal biomass. Finally, very deep channels
will not usually have excessive algal biomass except at the margins, since limited amounts of light reach
most of the bottom (Allan 1995), and sestonic algae are mixed frequently throughout the water column,
which reduces available light while increasing respiration (Welch 1992). Therefore, net productivity
(gross production minus respiration) decreases with depth of mixing.


Flow and velocity measurements are important for determining nutrient loadings, concentrations, and
distributions.  Flow volume or discharge is easily calculated based on stream channel area and velocity.
Velocity is typically measured with a stream gauge or current meter. See
http://water.usgs.gov/pubs/circll23/collection.html for more details.


It can be useful to quantify total suspended solids because of their effect on light attenuation, and the
determination of volatile solids may be of interest to determine if the total suspended solids are from
organic sources. The methods for total suspended solids and volatile solids are presented in Standard
Methods (APHA 2000).


Temperature can be an important variable in determining alkalinity, saturation, and rates of chemical and
biological reactions. It is a simple but useful measurement to include in a sampling regime. Methods for
temperature measurement in the field and laboratory are described in Standard Methods (APHA 2000).



Nutrient analyses are the most important indicators for determining sources of nutrients and for
monitoring the effectiveness of control programs.  The analyses for soluble reactive phosphorus and
dissolved inorganic nitrogen are mentioned first because they are the forms available for algal uptake and
because they are the forms  determined (after digestion) for total nitrogen and total phosphorus. In
general, determinations of nutrient concentrations by field kits are only adequate to identify potential
problems.  If many nutrient assays are required to define the problem accurately, laboratory procedures
are more cost effective and have greater sensitivity.

In nutrient-poor systems, levels of dissolved inorganic nutrients are generally near the limits of detection
of the assays used.  For example, phosphate levels in excess of 30 |ig/L saturate uptake by algae, but this
is the lower limit of detection in many laboratories. Care must be taken that the assay procedure used
matches the question being asked.
                                           PAGE A-66

July 2000	Appendix B. Laboratory and Field Methods and Analyses

The assay for dissolved or soluble reactive phosphorus from Standard Methods (APHA 2000) should be
followed.  A common source of contamination that causes problems with soluble reactive phosphorus
analysis is the use of phosphate containing detergents to wash laboratory equipment. It is good practice
to use phosphate-free detergents in the laboratory for this reason.  Another important problem is the
source of low-phosphorus water for dilution and blanks. Absorbance should be very low (0.001-0.003
absorbance units per cm) for such purposes.

The soluble reactive phosphorus assay does not determine only phosphate, because the chemicals in the
assay react with some dissolved organic compounds that contain phosphorus other than ortho-
phosphorus. It has been demonstrated that increased phosphorus deficiency in algae in natural systems
leads to a lower percentage of biologically available phosphate in the chemically determined soluble
reactive phosphorus (e.g., Dodds 1995). Unfortunately, the identity of the remaining fraction of soluble
reactive phosphorus is unclear, so soluble reactive phosphorus values from natural waters are difficult to
interpret, unless the values are fairly high (e.g., above 10 mg/L).  In some such cases (e.g.,  groundwater
or wastewater input), a large portion of the  soluble reactive phosphorus may  actually be in the form of
phosphate, and the assay will provide  a fairly accurate measure of the phosphate immediately available
for  algal consumption. The soluble reactive phosphorus assay is particularly useful to determine
phosphate in sewage (where most soluble reactive phosphorus is phosphate) and to analyze digested
samples for total phosphorus.  A method for the analysis of PO43" (orthophosphate) is also available in
Standard Methods (APHA 2000).

Analysis of ammonium is straightforward with the phenate method (APHA 2000). Note that ammonium
(NH4+) is the ion that identifies the available nutrient, and ammonia (NH3)  is  the gas, known as unionized
ammonia, which is the fraction that can cause toxicity. Contamination of ammonium assays can occur
from scratched glassware and airborne ammonia gas, which can come from smoke (tobacco and
otherwise), cleaning products with ammonia, and newly cut grass.  Care should be taken to avoid these
potential sources of contamination.

Nitrate is commonly measured by reduction to  nitrite in a copper-cadmium reduction column (APHA
2000). Nitrite can be analyzed alone to correct estimates of nitrate, but in most studies of streams, nitrite
is assumed to be a relatively small fraction of nitrate and as such is not accounted for. Cadmium is toxic
and difficult to handle and dispose.  Some packaged nitrate kits use cadmium pillows that are added to
the  sample. Appropriate precautions for handling  and disposing of samples are recommended if these
kits are used.  Other (e.g., hydrazine) nitrate techniques may be more prone to interference or reduced
efficiency. Automated analysis methods with segmented flow autoanalyzers  are commonly used to speed
processing and maintain sensitivity. Ion chromatography can be used successfully for nitrate
determinations, but it should be kept in mind that this method is not sensitive enough for  nitrate values
typical of many moderately productive systems.

Total nitrogen and total phosphorus require digestion to dissolved inorganic forms before analysis.
There are a number of available techniques. An important point is that the efficiency of digestion of
organic materials varies with procedures and waters being analyzed. Regardless of the procedure chosen,
solutions with known concentrations of organic compounds (e.g., urea for nitrogen,  ATP  for phosphorus)
should be  added to natural water samples in known concentrations and analyzed to check for complete
                                           PAGE A-67

July 2000	Appendix B.  Laboratory and Field Methods and Analyses

Persulfate digestion is commonly used for total phosphorus. This procedure can be modified to oxidize
organic phosphorus to phosphate, as well as organic nitrogen to nitrate (Ameel et al. 1993). Careful
attention to pH of the samples is necessary in these digestions (the digest must remain alkaline for
nitrogen digestion,  but if too much persulfate is used, it may not become acidic later in the digestion and
incompletely decompose the phosphorus) and appropriate concentrations of fresh reagents should be
used to allow for complete digestion of both organic nitrogen and phosphorus.

Persulfate digestion converts all forms of nitrogen except N2 gas to nitrate. If nitrate analysis is not
easily accomplished in the laboratory, it may be desirable to use a Kjeldahl digestion procedure (APHA
2000) for total nitrogen analysis. In this procedure, all nitrogen forms but nitrate, nitrite and nitrogen gas
are digested to ammonium. If this procedure is employed, it is still necessary to analyze for nitrate and
nitrite to determine total nitrogen. Because the sensitivity and accuracy of the cadmium reduction method
for nitrate are greater than analyses for  ammonium, and the toxicity and corrosiveness of the digestion
procedure are less,  persulfate digestion and nitrate analysis is usually preferred to Kjeldahl.

Analyses for TN, TP, phosphate, and nitrate can also be used to calculate water column N:P ratios.


Conductivity may serve as a first indicator of total nutrients (although it indicates total ions which are
much more abundant  than, and not always closely correlated to, nutrients), and pH  may be of interest as a
variable indicating  impairment. Both of these analyses are most easily accomplished with electronic
probes. Refer to Standard Methods (APHA 2000) for the particulars of the analysis.


Analyses of dissolved oxygen, for measurements of primary production and determination of low oxygen
demand should be done with a titrametric method or polarographic sensor. The titrametric is more
accurate, but more time consuming. Standard Methods should be consulted for these analyses (APHA
2000).  If diurnal measurements of oxygen are performed, procedures outlined by Marzolf et al. (1994)
should be followed for small streams.


Analysis of organic carbon (dissolved) may be problematic because incomplete digestion of dissolved
organic carbon is common. This has been most thoroughly investigated for marine samples (Perdue et al.
1993).  However, similar problems have been documented for freshwater samples (Kaplan 1992). High
temperature catalyzed analyzers provide more complete digestion and generally yield reliable results.



The choice of methods for sample collection is dependent upon the intent of algal sample analysis.
These methods are  reviewed in the Revised Rapid Bioassessment Protocols for Streams and Rivers
(Stevenson and Bahls 1999), so only a brief overview will be presented in this document. Sampling for

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July 2000	Appendix B.  Laboratory and Field Methods and Analyses

assessments of the biotic integrity of algal assemblages should be more thorough and extensive spatially
than sampling for algal assessments of water quality. Thorough assessments of biotic integrity would
call for multihabitat sampling over large reaches of the stream to find as many species and habitats within
the stream or river as possible. Targeted habitat sampling (most commonly samples of algae from rocks
in riffles) can provide collections that provide indications of biotic integrity or water quality.  A third
major alternative is to the use of artificial substrata that have the advantage of controlling variability
among streams due to substratum type, but the disadvantage of having to visit the field two times (to
place and retrieve substrata) and the concern that non-natural  assemblages  are being sampled. Targeted
habitat sampling is usually recommended, is employed by most State programs, and is known to be
successful. Efforts should be made to sample more than one riffle, particularly if an important goal of
sampling is to assess benthic algal biomass in a stream.

The collection of algal samples can be a complex exercise due to the variability of stream features such
as depth, substrata, flow velocity, and bottom characteristics.  Holding some of these variables relatively
constant by selecting a habitat zone with a narrow range for these variables was suggested earlier.
Another approach is using artificial substrata which are easier to sample than natural substrata but which
have several drawbacks. Artificial substrata are more likely to be vandalized, and they often tend to alter
the flow regime around them resulting in silt deposition. The use of artificial substrata limits the ability
to move to a different area where conditions are more acceptable, as can be done when using natural
substrata.  Perhaps the biggest drawback of artificial substrata is their inability to promote colonization
by certain forms of algae, especially the massive filamentous forms. This issue  is discussed further below
in connection with the best methods of sampling various algal growth forms.

While there is a great variety of algal taxa,  there are two main growth forms of algal communities: thin
biofilms and long filaments. Many single-celled and colonial forms of attached algae appear to the naked
eye as a biofilm of slippery, gelatinous material (often referred to technically as slime) on river rocks.
This material can be easily sampled by using a template method.

Template Method
A template is a piece of flat, flexible, waterproof material in which a window of about 2.5 cm to 5 cm per
side is  cut. This template is placed in the center of the upper surface of a rock collected from the sample
site, and a razor blade is used to scrape together all the  material in the window. The material is then
placed in a small water tight container (snap-shut plastic petri dishes, vials, or a piece of aluminum foil),
and stored on ice in the dark until frozen.

This procedure is greatly facilitated by selecting smooth rocks. To avoid bias, sample points should be
selected randomly. Then, rocks are selected blindly until one is chosen that is between 10 and 20 cm (in
some regions of the country one is allowed to take a quick look for snakes  first). If the rock's surface is
too rough to sample, it should be replaced and the process continued until a rock of the right size and
smoothness is selected.

The biofilms sampled by the above method form fairly quickly on artificial substrata and often the
thickness and composition of this film is quite similar to that on nearby natural  substrata in a matter of
weeks (Watson unpublished). However, some of the more complex attached algae, most noticeably
Cladophora glomerata, attach to rocks using a basal holdfast cell which supports a long filament.
Cladophora holdfasts often survive short exposure and drying out and the scour that removes the

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July 2000	Appendix B. Laboratory and Field Methods and Analyses

filament. The holdfasts spread over the rock and support more massive growths in subsequent years.
After several years of flows that are too low to dislodge and roll the river rocks over, Cladophora may
take the form of massive tangled branched filaments streaming several meters long. Since the massive
growths take several years to develop, they can not be produced on artificial substrata which are likely to
wash away during spring floods.  Hence, such growth forms must be sampled from natural substrata. An
example of a method for sampling from natural substrates is the hoop method.

Hoop Method
The template method does not work well for sampling the massive growth form (long string filaments)
mentioned above. It is possible to  be standing in a sea of waving Cladophora and pick up a random rock
that has no Cladophora on it, or that has a tangled mass hanging by  a few threads a few inches from the
rock.  The preferred way to sample such a growth form is to place a heavy metal hoop about 0.3 to 0.5
meter in diameter on the bottom of the stream (at the randomly selected point) and collect all the
filamentous material inside the hoop. This often involves cutting the filaments around the hoop and
picking up the filaments and rocks inside the hoop. The collection should be brought to shore in a tub
where the filaments should be removed from the rocks. Razor blades and paint scrapers work well; hack
saws are generally unnecessary. Wrapping these large samples in aluminum foil will facilitate the
drying, weighing and ashing process. The collection of 10 to 20 replicates of such samples at a series of
high biomass  sites will represent a large volume.

Freezing samples not only helps preservation, but cells are ruptured, facilitating chlorophyll extraction.
Samples collected by templates should be frozen at  -10°C on return to lab, and analyzed for chlorophyll
a and AFDM within 2 weeks to a  month.  Laboratory methods for analyzing algal biomass for
chlorophyll and ash free dry weight (AFDM) are discussed below. The same sample can be analyzed for
both chlorophyll a and AFDM.  After chlorophyll analysis, the extracted sample is poured into an
aluminum weigh boat, the solvent is evaporated, and AFDM analysis is performed on the boat. This
facilitates determining the chlorophyll to AFDM ratio on these samples.

Due to the abundance of material collected using the hoop method, it is not possible to extract all the
chlorophyll from these samples. Hence, only small subsamples of each large sample are  analyzed for
chlorophyll and AFDM, and the large samples are analyzed for AFDM only. Their chlorophyll content is
estimated using the chlorophyll to AFDMratio determined from the  subsamples. These samples are
handled as follows: 1) before freezing the samples collected by the hoop method, take each sample and
spread it out; 2) collect many tiny subsamples from all over this bulk sample; 3) chop and mix the
subsamples; 4) make at least 4 replicate composite samples from this well mixed pile; 5) place these in
small containers and process as you do the template samples; 6) analyze the remaining bulk sample for
AFDM; and 7) use the chlorophyll to AFDM ratio of the small composite samples to estimate the
chlorophyll in the bulk sample (consider the variability in the chlorophyll/AFDM ratio of the composite
subsamples as well as the variability in biomass of the large samples).


Macrophyte sampling is commonly performed 1) to qualitatively assess the distribution of vegetation in
an area or 2) to quantitatively measure primary productivity (gauged by changes in biomass).  Caution
must be taken when sampling macrophytes for biomass determination to ensure that the  appropriate
portions of macrophytes (above and below ground) are collected.  (Macrophytes may have up to 90%

                                          PAGE A-70

July 2000	Appendix B. Laboratory and Field Methods and Analyses

underground biomass.) After collection, macrophyte samples may be dried and combusted to determine
AFDM in a manner comparable to that for algal samples. Macrophyte sampling and biomass
determinations are discussed in Wetzel and Likens (1991).


Methods have been described in the literature (e.g., Sheath and Burkholder 1985) to estimate algal
biomass in the stream by visual observation.  In the Revised Rapid Bioassessment Protocols for Rivers
and Streams (Stevenson and Bahls 1999), a rapid periphyton survey is described that provides an in-
stream assessment of algal biomass. The technique is simple and can be used by professionals or
volunteers with little training.  Two steps are involved as the stream bottom is observed at multiple sites
(usually >9) through a viewing bucket (clear-bottom bucket submerged in stream for clear observation of
the stream bottom). First, percent cover of filamentous algae over the stream bottom is assessed. Then
thickness and percent cover of microalgae  is assessed.  A ranking system is used to quantify thickness of
microalgal mats.  The advantages of this rapid periphyton survey are that it allows for rapid assessment of
algal biomass, particularly filamentous algal green biomass,  and it covers large regions of the stream
(thus accounting  for the great spatial variability in algal biomass).


The most commonly used determinant of benthic algal biomass is chlorophyll a.  Chlorophyll a is often a
superior indicator of biomass compared to determination of AFDM because non-algal material can
contribute to biomass.  Chlorophyll a is used because it occurs in all common photosynthetic organisms.
Other forms of chlorophyll can inflate estimates of algal biomass, because the amount per cell can be
more variable. In addition, counts of algal cells and biovolume are often used as a determinant of
biomass. These counts are time consuming and require taxonomic expertise, and thus are rarely done and
will not be considered here. The general methods for biomass determination are well described by
Steinman and Lamberti (1996) and Stevenson (1996); the interested reader should consult these
references and others cited herein.

Chlorophyll is determined in seston on filtered material and from benthic material either from cores,
artificial substrata, or scraped and extracted substrata. In general, artificial substrata yield higher
chlorophyll alAFDM values than natural substrata (Dodds et al., unpublished), and this should be kept in
mind when selecting the method to be used. However, measurement of area and extraction of pigment is
easier with artificial substrata.

Chlorophyll analyses without an acidification step to correct for chlorophyll degradation products
(phaeophytin  correction) are occasionally encountered. This acidification is essential for periphyton
because dead cells that contain phaeophytin can remain in the assemblage, and lead to biomass
overestimates. A fluorometric method with narrow band filters that correct for phaeophytin but omit the
acidification step was recently introduced (Welschmeyer 1994).

Determination of phaeophytin concentrations  may be useful not only for correcting chlorophyll a
concentrations, but also as an indicator of periphyton degradation. Wetzel and Likens (1991) give a
method for determining both chlorophyll a and phaeophytin concentrations. The ratio of chlorophyll a to
phaeophytin gives an indication of periphyton growth and activity.

                                           PAGE A-71

July 2000	Appendix B. Laboratory and Field Methods and Analyses

Generally, a ratio of 9:1, acetone:water, is used as an extractant. We have found that hot 90% ethanol
extraction (Sartory and Grobbelaar 1984) offers some advantages.  Primarily, material need not be
scraped from the substratum, and grinding of the sample is not required. Rather, the entire sample of
substratum and periphyton is placed in a heat resistant (autoclavable) plastic bag with extractant and
heated to 80 °C for 5 min.  Ethanol fumes are also less noxious than acetone fumes.

The preferred procedure is to use a spectrophotometer to read absorbance, because the relatively dense
solutions of extracted chorophyll are common for periphyton samples.  Very dense solutions of chl must
be avoided for spectrophotometry and fluorometry to prevent analytical errors; the problem is of greater
concern in fluorometry. In spectrophotometry, solutions of greater than 1.5 absorbance units per cm at
665 nm should not be analyzed. Fluorometric analysis should not be attempted with samples having
more than 0.5 absorbance  units per cm at 665 nm. Dilution with extractant can bring samples to within
the appropriate absorbance range.


Methods for AFDM and algal cell biovolume are covered by Steinman and Lamberti (1996) and Wetzel
and Likens (1991), respectively.  Ash-free dry-weight values have been used in conjunction with
chlorophyll a as a means of determining the trophic status (autotrophic vs. heterotrophic) of streams
(Weber 1973). The Autotrophic Index (AI) is calculated as:

                      AI = AFDM (mg/m2) / chlorophyll a (mg/m2).

As suggested before, these should be relied upon as supplementary methods, and the large degree of time
required for biomass determinations by cell counts and biovolume estimates should be considered.


Analysis of alkaline phosphatase activity (APA) is used to determine phosphorus limitation in algae.
Alkaline phosphatases are enzymes produced by algae to break down organic phosphorus compounds and
release bioavailable (PO4) P (Steinman and Mullholland 1996). Studies have shown that lower levels of
P result in higher levels of APA and vice versa (Klotz 1992). The most common method for APA
analysis is a fluorometric method described by Hill et. al.  (1968).


Different methods can be used to assess algal species composition depending upon the objective of the
assessment (Whitton et al. 1991; Whitton and Rott 1996; Lowe and Pan 1996; Stevenson 1998;
Stevenson and Pan 1999; Stevenson and Bahls 1999).  For example, if the objective of the assessment is
to determine if nutrient conditions meet a drinking water use, then analysis of all algae in samples may be
desirable to determine if taste and odor algae are present. If the objective is to get an indication of
nutrient conditions, trophic status, or biotic integrity, then analysis of species composition of diatoms
only may be sufficient.  The latter is less time consuming that an analysis of all algae in samples. The
methods for analysis of algal species composition in samples can be found in Standard Methods (APHA
2000), the Revised Rapid Bioassessment Protocols (Stevenson and Bahls 1999) or in Lowe and
LaLiberte (1996).

                                          PAGE A-72

July 2000	Appendix B. Laboratory and Field Methods and Analyses

Although time consuming, it may be desireable to determine the types of algae present that are thought to
be creating problems. The methods necessary for such determinations are described in Lowe and
LaLiberte (1996) and in Standard Methods (APHA 2000). In general, taxa determination, especially to
species, requires expertise, similar to that required for precise water chemistry and macroinvertebrate
assays.  Such fine level determinations may be useless if not conducted by experienced taxonomists.
Some companies provide algal identification and analysis services that may be useful for those lacking
such expertise.  The reputation of prospective companies should be verified. In general, total algal
biomass is of greater concern than taxonomic composition to those wishing to control eutrophication and
its effects.


Macroinvertebrates may indicate water quality problems and some monitoring programs may want to
evaluate biomass and diversity of macroinvertebrates. There is little precedence for this in stream
eutrophication studies, and the analysis of macroinvertebrates to species is time consuming. Methods  to
assess stream macroinvertebrates have recently been reviewed (Hauer and Resh 1996).  Generally,
identification of most animals to species is required for accurate indices to be constructed, so it is
important that such analyses be carried out by individuals with taxonomic expertise.


Productivity/respiration (P/R) ratios can  be determined by the upstream-downstream method with
dissolved oxygen data and estimates of atmospheric reaeration (Odum 1956; Marzolf et al. 1994) or
light/dark, flow-through chambers (Hickey 1987; Dodds and Brock 1998).  P/R ratios measured using
chambers are generally higher than those measurements obtained from upstream-downstream methods.
Even in streams with heavy algal growths, it is rare to find P/R ratios in excess of one (1) using upstream-
downstream methodology. Both methods convert the diel  changes in dissolved oxygen into actual rates
of productivity. The diel range in dissolved oxygen indicates the magnitude of gross  productivity and
can be used to monitor ecological integrity in streams and rivers of similar velocity, depth, and


Hill, D., G. K. Summer, and M.D. Waters. 1968. An automated fluorometric assay for alkaline
phosphatase using 3-0-methylfluorescein phosphate. Anal. Biochem. 24:9-17.

R. L. Klotz.  1992.  Factors influencing alkaline phosphatase activity of stream epithilon.  Journal of
Freshwater Ecol. 7(2):233-242.

APHA.  2000. Standard Methods for the Examination of Water and Wastewater. 21st ed. Eaton, A. D.,
L. C. Clesceri, and A. E. Greenberg (eds.). American Public Health Association, Washington, DC.

Steinman, A. D., and P. J. Mulholland. 1996. Phosphorus limitation, uptake, and turnover in stream
algae. Methods in Stream Ecology. Academic Press, Inc.

Wetzel, R. G., and G. E. Likens. 1991. Limnological Analyses.  2nd Edition. Springer-Verlag.  New
York. Flow  and velocity:  http://water.usgs.gov/pubs/circll23/collection.html.
                                           PAGE A-73

July 2000	Appendix B. Laboratory and Field Methods and Analyses
                                          PAGE A-74



In order to use parametric tests, (Student t test, ANOVA, MANOVA, etc.) assumptions about the
population distribution must be made. When the data are not normally distributed, transformations of the
data to obtain a normal distribution are commonly made (e.g., log transformation). Less powerful, non-
parametric tests of significance must be used in cases where the data do not fit the assumption of a
normal distribution (Atlas and Bartha 1993).


The validity of hypotheses is frequently tested using the Student t test. There is a family of distributions
for the t statistic that vary as a function of degrees of freedom.  The t distributions are symmetrical about
a mean of 0, as are normal distributions, though the t distributions are more spread out than on the
normal curve. As degrees of freedom increase, the t distribution more closely approximates the normal
curve.  There are published tables of critical values for  t that allow one to compare a calculated t value
from one's own data with a t value determined by the level of significance.  This comparison allows one
to decide whether or not to reject the null hypothesis (Atlas and Bartha 1993). An in-depth discussion of
the use of the t statistic for analyzing environmental data can be found in Ott (1995). Most statistics texts
include the published tables  of the t statistic and information on it's application.


The analysis of variance (ANOVA) method is used to determine the significance or validity of data
when information is collected from different populations. ANOVA is generally used to confirm that
there are not significant differences in sample population means.  ANOVA determines whether there is
greater variability among sample populations or within population groups. ANOVA is performed by
summing the variance of all  sample points and comparing it to the sum of the variance of all the sample
means (Remington and Schork 1985). ANOVA is useful for calculating the unbiased variance of
samples that have been composited or parts of samples  (such as a 10 mL water sample analyzed for TP
taken from a 50 mL total sample) (Gilbert 1987).


A common non-parametric statistical test is the X2 (chi  square) test. When attempting to analyze the
apportionment of a characteristic within a population, the chi square test is valuable for determining the
independence of categorical variables. The raw data for a chi square test should be on a scale for which
data are placed into discrete  groups (nominal scale) (Atlas and Bartha 1993).


The Mann Whitney U test is one of the most powerful non-parametric statistical tests.  This test may be
employed in place of the t test when data are on an ordinal scale.  This test is used with two independent
groups. The null hypothesis is that both samples are drawn from populations with the same distributions.
The alternative hypothesis is that the parent populations from which the samples are taken have different
medians. This test assumes that the distributions have the same form, but have different medians. This
                                           PAGE A-75

July 2000	Appendix C. Statistical Tests and Modeling Tools

test ranks scores from lowest to highest while retaining the identity of the group from which they came
(control or experimental group), to determine the distribution of the U statistic.  U represents the number
of times the n: value precedes the n2 value. U is large if the n: population is located below the n2


In regression analysis a relationship of best fit is used to describe the data. The experimenter must
decide the type of relationship that best describes the data. If the relationship is linear, a linear regression
may be appropriate. When the data are not linear, they may be log transformed to fit the linear
assumption.  The slope of the regression line is called the regression coefficient.  In constructing a
regression line of best fit, it is necessary to define the slope of the line and the intercept of an axis.
Regression analysis minimizes the variance, though a residual variance remains.  The statistical
significance  of the regression coefficient using the student t test described above.  The null hypothesis in
such a test, is that there is no difference between the calculated regression coefficient and a true
population regression coefficient 0. In other words, the population regression coefficient indicates that
no prediction ofy can be made from x, nor of x from y (Atlas and Bartha 1993).


Multiple regression is based on the same principle as linear regression (where y=mx+b), but involves
more than one regression variable (i.e., multiple sets of x values). Multiple regression is often performed
using matrices and least squares approximations (Myers 1990). Applications may include developing
relationships between response variables for various indicators.


Bayesian analysis is most useful when incorporating historical data or comparing probabilities of various
competing hypotheses.  It allows use of all available data from various studies and weighing of different
outcomes. A discussion of the uses of Bayes  Theorem in statistical analysis can be found in Hilborn and
Mangel (1997).


The models discussed in this appendix may be used in criteria derivation when data are not sufficient.
However, only the WASP model predicts periphyton biomass. The other models described here use
periphyton as a forcing function for predicting nutrients or DO.


Better Assessment Science Integrating Point and Nonpoint Sources, or BASINS, is a tool developed by
EPA to facilitate water quality analysis on a watershed level and for specific waterbodies or stream
segments. BASINS was designed to integrate national water quality data, modeling capabilities, and
geographic information systems (GIS) so that regional, State, local and Tribal agencies can easily address
the effects of both point and nonpoint source pollution and perform sophisticated environmental

                                           PAGE A-76

July 2000	Appendix C. Statistical Tests and Modeling Tools

BASINS is made up of five components: (1) national databases; (2) assessment tools (TARGET,
ASSESS, and Data Mining) for evaluating water quality and point source loadings at a variety of scales;
(3) utilities including local data import, land-use and DEM (Digital Elevation Model) reclassification,
watershed delineation, and management of water quality observation data; (4) watershed and water
quality models including NPSM (Nonpoint Source Model), HSPF (Hydrologic Simulation Program
Fortan), TOXIROUTE, and QUAL2E; and (5) post processing output tools for interpreting model

The three analytical tools (TARGET, ASSESS, and Data Mining) within BASINS allow the user a range
of environmental assessment options.  TARGET examines large area watersheds on a State/Tribal or
regional level to analyze point source loads or general water quality. ASSESS gives information about
specific water bodies and the monitoring stations or discharge points near them. Data Mining integrates
historical,  geographic, and water quality data using maps and tables. In addition, models such as the
NPSM, QUAL2E, and TOXIROUTE can be used to predict the fate, transport,  and effects of loadings
from various sources.  The BASINS package can be used for many water quality management analyses,
particularly the development of total maximum daily loads (TMDLs). In addition, the GIS component of
BASINS allows the user to virtually traverse the watershed.

BASINS is a software package that is installed on the user's computer.  It may be downloaded from the
EPA website (http://www.epa.gov/ost/BASINS/download.htm) or ordered on CD-ROM from the
National Service Center for Environmental Publications (NSCEP). A printed copy of BASINS version
2.0 Users'  Manual is also available through NSCEP. BASINS training courses  are available in some
areas of the country. For more information on BASINS, see the BASINS website


HSPF is a comprehensive package developed by EPA for simulating water quantity and quality for a
wide range of organic and inorganic pollutants from agricultural watersheds (Bicknell et al. 1993). The
model uses continuous simulations of water balance and pollutant generation, transformation, and
transport.  Time series of the runoff flow rate, sediment yield, and user-specified pollutant concentrations
can be generated at any point in  the watershed. The model also includes instream quality components for
nutrient fate and transport, biochemical oxygen demand (BOD), dissolved oxygen (DO), pH,
phytoplankton, zooplankton, and benthic algae.  Statistical features are incorporated into the model to
allow for frequency-duration analysis of specific output parameters.  Data requirements for  HSPF are
extensive,  and calibration and verification are recommended.  The program is maintained on IBM
microcomputers and DEC/VAX systems.  Because of its comprehensive nature, the HSPF model requires
highly trained personnel. It is recommended that its application to real case studies be carried out as a
team effort. The model has been extensively used for both screening-level and  detailed analyses. Moore
et al. (1992) describe an application to model BMP effects on a Tennessee watershed. Scheckenberger
and Kennedy (1994) discuss how HSPF can be used in subwatershed planning.  The HSPF model can be
downloaded at EPA's BASINS website given above.
                                          PAGE A-77

July 2000	Appendix C.  Statistical Tests and Modeling Tools


The Enhanced Stream Water Quality Model (QUAL2E), originally developed in the early 1970s, is a
one-dimensional water quality model that assumes steady-state flow but allows simulation of diurnal
variations in temperature or algal photosynthesis and respiration (Brown and Barnwell 1987).  QUAL2E
represents the stream as a system of reaches of variable length, each of which is subdivided into
computational elements that have the same length in all reaches. The basic equation used in QUAL2E is
the one-dimensional advection-dispersion mass transport equation. An advantage of QUAL2E is that it
includes components that allow quick implementation of uncertainty analysis using sensitivity analysis,
first-order error analysis, or Monte Carlo simulation.  The model has been widely used for stream waste
load allocations and discharge permit determinations in the United States and other countries.  EPA's
Office of Science and Technology recently developed a Microsoft Windows-based interface for
QUAL2E that facilitates data input and output evaluation, and QUAL2E is one of the models included in
EPA's BASINS tool. More information on QUAL2E, including downloadable program files, can be
found at EPA's website (www.epa.gov/docs/QU AL2E_WINDOWS/index.html).


The one-dimensional Hydrodynamic and Water Quality Model for Streams (CE-QUAL-RIV1) was
developed through the Waterways Experiment Station of the Corps of Engineers. The model was
designed to simulate water quality conditions associated with the highly unsteady flows that can occur in
regulated rivers  (e.g., storm water flows and streams below peaking hydropower dams). The model has
two submodels for hydrodynamics (RIV1H) and water quality (RIV1Q).  Output from the hydrodynamic
solution is used to drive the water quality model. Water quality constituents modeled include
temperature, dissolved oxygen, carbonaceous biochemical oxygen demand, organic nitrogen, ammonia
nitrogen, nitrate nitrogen, and soluble reactive phosphorus. The effects of algae and macrophytes on
water quality can also be included as external forcing functions specified by the user. A limitation of CE-
QUAL-RIV1 is that it is only applicable to situations where flow is predominantly one-dimensional.
Currently, this model can only be downloaded for USCOE use.  More information on CE-QUAL-RIV1
can be found at the  WES website (www.wes.army.mil/el/elmodels/riveinfo.html).


CE-QUAL-W2  is a two-dimensional, longitudinal/vertical water quality model that can be applied to
most waterbody types.  It includes both a hydrodynamic component (dealing with circulation, transport,
and deposition) and a water quality component. The hydrodynamic and water quality routines are
directly coupled, although the water quality routines can be updated less frequently than the
hydrodynamic time step to reduce the computational burden in complex systems. Water quality
constituents that can be modeled include algae, dissolved oxygen, ammonia-nitrogen, nitrate-nitrogen,
phosphorus, total inorganic carbon, and pH.  http://www.wes.army.mil/el/elmodels/w2info.html


The Water Quality Analysis Simulation Program is a general-purpose modeling system for assessing the
fate and transport of conventional and toxic pollutants in surface waterbodies. Its EUTRO5  submodel is
designed to address eutrophication processes and has been used in a wide range of regulatory and water

                                          PAGE A-78

July 2000	Appendix C. Statistical Tests and Modeling Tools

quality management applications. The model may be applied to most waterbodies in one, two, or three
dimensions and can be used to predict time-varying concentrations of water quality constituents. The
model reports a set of parameters, including dissolved oxygen concentration, carbonaceous biochemical
oxygen demand (BOD), ultimate BOD, phytoplankton, carbon, chlorophyll a, TN, total inorganic
nitrogen, ammonia, nitrate, organic nitrogen, total inorganic nitrogen, organic phosphorus, and inorganic
phosphorus. Although zooplankton dynamics are not simulated in EUTRO5, their effect can be
described by user-specified forcing functions. Lung and Larson (1995) used EUTRO5 to evaluate
phosphorus loading reduction scenarios for the Upper Mississippi River and Lake Pepin, while Cockrum
and Warwick (1994) used WASP to characterize the impact of agricultural activities on instream water
quality in a periphyton-dominated stream.  http://www.epa.gov/earthlOO/records/wasp.html
                                           PAGE A-79

July 2000	Appendix C.  Statistical Tests and Modeling Tools
                                            PAGE A-80



Adopt-A-Stream Foundation
Ash-Free Dry Mass
Ash-Free Dry Weight
Algal Growth Potential
Autotrophic Index
Analysis of Variance
Alkaline Phosphatase Activity
Benthic Macroinvertebrate Index of Biological Integrity
Best Management Practice
Biochemical Oxygen Demand
Best Professional Judgement
U.S. Department of the Interior, Bureau of Reclamation
Committee on Environment and Natural Resources
Hydrodynamic and Water Quality Model for Streams
Code of Federal Regulations
Construction General Permit
Clean Lakes Program
Corps of Engineers
Continuing Planning Process
Conservation Reserve Enhancement Program
Conservation Reserve Program
Combined Sewer Overflow
Costal Zone Act Reauthorization Amendment
Department of Environmental Quality
Dissolved Inorganic Nitrogen
Diatom Index of Trophic Status
Dissolved Oxygen
Dissolved Organic Carbon
Division of Water Pollution Control
Ecological Community Analysis
Environmental Conservation Acreage Reserve Program
Ecological Data Application System
Environmental Monitoring and Assessment Program
Ephemeroptera (mayflies), Plecoptera (stoneflies), and
Trichoptera (caddisflies)
Environmental Quality Incentives Program
Filamentous Green Algae
Forestry Incentives Program
Geographical Information Systems
Harmful Algal Bloom
Hydrologic Benchmark Network
Hydrologic Simulation Project FORTAN
                                        PAGE A-81

July 2000
Appendix D: Acronym List & Glossary
 HUC              Hydrologic Unit Code
 IBI               Index of Biological Integrity
 LDC              Legacy Data Center
 MITS             Multimetric Index of Trophic Status
 N                 Nitrogen
 NASQAN         National Stream Quality Accounting Network
 NAWQA          National Water-Quality Assessment
 NIST             National Institute of Standards and Technology
 NOAA            National Oceanic and Atmospheric  Association
 NPDES            National Pollutant Discharge and Elimination System
 NFS              Nonpoint Source
 NPSM            Nonpoint Source Model
 NRCS             Natural Resources Conservation Service
 NSCEP            National Service Center for Environmental Publications
 NSS              National Stream Survey
 NSWS            National Surface Water Survey
 NTU              Nephelometric Turbidity Units
 NWIS             National Water Information System
 ONRW            Outstanding National Resource Waters
 P                 Phosphorus
 PAR              Photosynthetically-active Radiation
 PCS              Permit Compliance System
 P/R               Productivity/Respiration
 QA               Quality Assurance
 QC               Quality Control
 QUAL2E          Enhanced Stream Water Quality Model
 RAD              Reach Address Database
 RCC              River Continuum Concept
 RF3              Reach File 3
 RTAG            Regional Technical Assistance Groups
 SAV              Submerged Aquatic Vegetation
 SRP              Soluble Reactive Phosphorus
 STORET          Storage and Retrieval
 TAB              Total Algal Biomass
 TOP              Total Dissolved Phosphorus
 THM             trihalomethane
 TIA              Total Impervious Area
 TKN              Total Kjeldahl Nitrogen
 TMDL            Total Maximum Daily Load
 TN               Total Nitrogen
 TP                Total Phosphorus
 TSS              Total Suspended Solids
 TVA              Tennessee Valley Authority
 TWINSPAN       Two Way Indicator Species Analysis
 USGMA          Unweighted Pair Group Method Using Arithmetic Averages
                                        PAGE A-82

July 2000	Appendix D: Acronym List & Glossary

 USGS             United States Geologic Survey
 VNRP             Voluntary Nutrient Reduction Plan
 WASP            Water Analysis Simulation Program
 WES              Waterways Experiment Station
 WHIP             Wildlife Habitat Incentives Program
 WLA             Waste Load Allocation
 WQBEL           Water Quality B ased Effluent Limits
 WQN             Water Quality Networks
 WQS              Water Quality Standards
 WRS              Wetlands Reserve Program
 %2                Chi Square
                                         PAGE A-83

July 2000	Appendix D: Acronym List & Glossary


algal biomass
The weight of living algal material in a unit area at a given time (Wetzel 1983).

An organism or substance foreign to a given ecosystem (Atlas and Bartha 1993); describes organic
matter reaching an aquatic community from the outside in the form of organic detritus or organic matter
adsorbed to sediment (Wetzel 1983).

ash-free dry weight
An algal biomass measurement that measures the standing crop of algae to estimate net production (see
Appendix B) (APHA 2000).

Microorganisms and/or substances indigenous to a given ecosystem; the true inhabitants of an
ecosystem; refering to the common nicrobiota of the body or soil microorganisms that tend to remain
constant despite fluctuations in the quantity of fermentable organic matter (Atlas and Bartha 1993);
describes organic matter originating within a waterbody / aquatic community (Wetzel 1983).

autotrophic index (AI)
A means of determining the trophic nature of the periphyton community; calculated by dividing the
biomass (ash-free weight of organic matter) by chlorophyll a. High AI values indicate heterotrophic
associations or poor water quality (APHA 2000).

The assemblage of organisms associated with the bottom, or the solid-liquid interface of the aquatic
system.  Generally applied to organisms in the substrata (Wetzel 1983).

(biological criteria) Narrative or numeric expressions that describe the desired biological condition of
aquatic communities inhabiting particular types of waterbodies and serve as an index of aquatic
community health. (USEPA 1994).

Biochemical Oxygen Demand. Oxygen required to break down organic matter and to oxidize reduced
chemicals  (in water or sewage) (APHA 2000).

chlorophyll a
A complex molecule composed of four carbon-nitrogen rings surrounding a magnesium atom; constitutes
the major pigment in most algae and other photosynthetic organisms; is used as a reliable index of algal
biomass (Darley 1982).

A common nuisance filamentous green alga (Dodds et al. 1997).
                                          PAGE A-84

July 2000	Appendix D: Acronym List & Glossary
community metabolism
The relationship between gross community production and total community respiration (Odum 1963).

Elements of State water quality standards, expressed as constituent concentrations, levels, or narrative
statements, representing a quality of water that supports a particular use.  When criteria are met, water
quality will generally protect the designated use (USEPA 1994).

cultural enrichment
Human activities that result in increased nutrient loads to a waterbody.

designated uses
Uses defined in water quality standards for each water body or segment whether or not the use is being
attained (USEPA 1994).

Unconsolidated sediments comprised of both inorganic and dead and decaying particulate organic matter
inhabited by decomposer microorganisms (Wetzel 1983).

Abundant in nutrients and having high rates of productivity frequently resulting in oxygen depletion
below the surface layer (Wetzel 1983).

The increase of nutrients in [waterbodies] either naturally or artificially by pollution (Goldman and
Home  1983).

existing uses
The use that has been achieved for a waterbody on or after November 28, 1975 (USEPA 1994).

Conveys water between points in the stream system. Examples of flow paths are a stream channel,  canal,
storm sewer, or reservoir (http://il.water.usgs.gov/proj/feq/feqdoc/chap3_l.html).

Describes organisms that need organic compounds to serve as a source of energy for growth and
reproduction (Atlas and Bartha 1993).

Characteristic of the hypolimnion, the deep, cold, relatively undisturbed stratum of a lake (Wetzel  1983).

hydrologic unit codes (HUC)
An 8-digit code, determined by the U.S. EPA, that is used as a standard method for watershed
identification throughout the United States.
                                           PAGE A-85

July 2000	Appendix D: Acronym List & Glossary

hyporheic zone
The subsurface zone where stream water flows through short segments of its adjacent bed and banks
(Winter et al. 1998).

Relatively still-water environment (Goldman and Home 1983).

Running-water environment (Goldman and Home 1983).

macrophyte (also known as SAV-Submerged Aquatic Vegetation)
Larger aquatic plants, as distinct from the microscopic plants, including aquatic mosses, liverworts,
angiosperms, ferns, and larger algae as well as vascular plants; no precise taxonomic meaning (Goldman
and Home 1983).

Small benthic organisms which are retained on sieves with a mesh size >2 mm (Thorp and Covich 1991).

mesotrophic (2-4)
Having a nutrient loading resulting in moderate productivity (Wetzel 1983).

morphological characteristics (2-2)
The morphological characteristics of a waterbody are the characteristics that comprise the shape of the
waterbody.  In stream systems, morphology usually refers to the shape of the stream channel.

National Pollutant Discharge Elimination System. The EPA program that regulates point source
discharges through the issuance of permits to discharges and enforcement of the terms and conditions of
those permits.

oligotrophic (2-4)
Trophic status of a waterbody characterized by a small supply of nutrients (low nutrient release from
sediments), low production of organic matter, low rates of decomposition, oxidizing hypolimnetic
condition (high DO) (Wetzel 1983).

Sediments within the active channel, outside the wetted stream; lateral sandbars (Holmes et al. 1994).

Associated aquatic organisms attached or clinging to stems and leaves of rooted plants or other surfaces
projecting above the bottom of a water body (USEPA 1994).

primary production
Quantity of new organic matter created by photosynthesis or chemosynthesis, or stored energy which that
material represents (Wetzel 1983).
                                          PAGE A-86

July 2000	Appendix D: Acronym List & Glossary

probability sampling
A sampling process wherein randomness is a requisite (Hayek 1993).

production/respiration ratio
The primary production to respiration ratio is a measure of community or whole system metabolism.
This measurement can be used to assess ecosystem health and determine if the system is
heterotrophically or autotrophically dominated.

The estimated discharge often year flood (USEPA 1994).

random sampling
Generic type of probability sampling, randomness can enter at any stage of the sampling process (Hayek

RTAG (Regional Technical Assistance Group)
Group of technical experts assembled at the EPA Regional level to assist in establishing criteria for
States, Tribes and nutrient ecoregions.

reference conditions
Describe the characteristics of water body segments least impaired by human activities. As such,
reference conditions can be used to describe attainable biological or habitat conditions for water body
segments with common watershed/catchment characteristics within defined geographical regions.

Riverside, usually referring to vegetation (riparian vegetation) (Goldman and Home 1983).

Secchi disk
A white or black and white disk used to measure transparency of a waterbody. The Secchi disk
transparency is measured as the mean depth of the point where a weighted white (or black and white)
disk, 20 cm in diameter, disappears when viewed from the shaded side of a vessel, and that point where
the disk reappears upon raising it after it has been lowered beyond visibility (Wetzel 1983).

secondary production
New organic material created by an organism that uses organic substrates (i.e. uses material from
primary producers) (Wetzel 1983)

organic matter suspended in the water column generally comprised of phytoplankton, bacteria and fine
detritus  (Thorp and Covich 1991).

EPA's computerized water quality database that includes physical, chemical, and biological data
measured in water bodies throughout the United States (USEPA 1994).
                                          PAGE A-87

July 2000	Appendix D: Acronym List & Glossary

Stratification, stratified random sampling
Type of probability sampling where a target population is divided into relatively homogenous groups or
classes (strata) prior to sampling based on factors that influence variability in that population (Hayek
1993).  In stratified sampling, a heterogenous environment is divided into homogenous strata or parts.
Analysis of variance can be used to identify statistically different parameter means among the sampling
strata or classes.  The strata are the analysis of variance treatments (Poole 1972).

Total maximum daily loads (TMDLs) are defined by calculating the assimilative capacity of a waterbody
for a substance (e.g. total phosphorus) and identifying the sources to determine the maximum load the
waterbody is capable of carrying without causing detrimental effects.

trophic state
The trophic status of a waterbody (Carlson 1977).

TSS (total suspended solids)
Particulate matter suspended in the water column.

Cloudiness or opaqueness of a suspension. In our context, refers to the amount of suspended matter in
the water column, usually measured in nephelometric turbidity units (Atlas and Bartha 1993).

TVSS (total volatile suspended solids)
Volatile particulate matter suspended in the water column.

The area of land that drains water, sediment,  and dissolved materials to a common outlet at some point
along a stream channel. In American usage,  watershed is synonymous with the terms drainage basin
and catchment (Dunne and Leopold 1978).
                                           PAGE A-88