&EPA
United States
Environmental Protection
Agency
EPA/600/R-14/256 | October 2014 www.epa.gov/research
Ecological Condition of Streams
in Eastern and Southern Nevada
EPA R-EMAP
Muddy-Virgin River Project
Photo: Las Vegas Valley Wash
RESEARCH AND DEVELOPMENT
-------
-------
Ecological Condition of Streams in
Eastern and Southern Nevada
EPA R-EMAP Muddy-Virgin River Project
Prepared by
Leah Hare1, Daniel Heggem1, Robert Hall2, Peter Husby3
1U.S. Environmental Protection Agency
Office of Research and Development
National Exposure Research Laboratory
Environmental Sciences Division
Las Vegas, NV89119
2U.S. Environmental Protection Agency
Region 9 WTR2
San Francisco, CA 94105
3U.S. Environmental Protection Agency
Region 9 Laboratory
Richmond, CA 94804
Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official
Agency policy. Mention of trade names and commercial products does not constitute endorsement or
recommendation for use.
U.S. Environmental Protection Agency
Office of Research and Development
Washington, DC 20460
-------
11
-------
Acknowledgements
The authors would like to apologize for the delay of this report relative to the sample collection.
We feel that this data will be of value as a baseline for the Muddy-Virgin River Project Area.
We strongly believe that reporting this data will greatly aid in the understanding of this unique
river system. We want to fully acknowledge the late Dr. Gary Vinyard for his vision and
leadership and we wish to dedicate this report to his memory. We are also grateful to those who
help us with this report in their time and effort including, Angela Hammond, Phil Kaufman,
David Peck, Tony Olsen, Heather Powell, Kuen Huang-Farmer, Pamela Grossmann, Tad Harris,
Richard Snell, Reviewer Steve Gardner and Reviewer Richard Tippit.
Notice
The information in this document has been funded in part by the United States Environmental Protection
Agency under Student Services Contract number EP10D000282 to Leah Hare and Cooperative
Agreement CR-826293-01 with the University of Nevada, Reno, Biological Resources Research Center. It
has been subjected to the Agency's peer and administrative review and has been approved for publication
as an EPA document.
in
-------
IV
-------
Executive Summary
This report summarizes data collected from the wadeable streams in the Muddy-Virgin River Project
Area of Nevada. The determination of current status is a critical step in the future management of these
stream resources, and, to that end, this study focuses on providing "baseline" data for the systems studied.
To provide the information needed to assess these streams, the USEPA's Regional Environmental
Monitoring and Assessment Program (R-EMAP) protocols were used for sampling stream reaches within
the Muddy-Virgin River Project Area. This work was done by personnel from the University of Nevada
Biological Resources Research Center (BRRC), in cooperation with US Environmental Protection
Agency (USEPA) Region 9 and the USEPA office of Research and Development (ORD).
The goal of the Muddy-Virgin River Project was to assess the water quality and biotic integrity of
perennial and intermittent streams over a one year sampling period for the Muddy-Virgin River Project
Area, using a combination of macroinvertebrates, physical habitat measurements, water and sediment
chemistry, and sediment metabolism. The objectives of the Muddy-Virgin River Project Area R-EMAP
were to describe the condition of surface waters, relate ecological conditions to ecological stressors and
examine relative risks to streams within the Area.
The report presents data collected during a one year study period beginning in May of 2000. Sampling
sites were selected using a probability-based design (as opposed to subjectively selected sites) using the
USEPA River Reach File version 3 (RF3). About 37 sites were sampled.
This study has provided a substantial baseline data set for the Basin. While the percentage of impacted
streams varied, many of stream reaches studied in the Basin were assessed to be in a "most-disturbed"
condition. We recommend that a next step for ecological condition analysis should be a landscape
ecology approach which would focus on the spatial relationships as related to the ecological processes of
the landscape, and which should provide a comprehensive basis for identifying and evaluating current and
historical land use practices.
Further, because riparian function is heavily influenced by the condition of adjacent and upland
ecosystems, we recommend that riparian Proper Functioning Condition (PFC) assessments be considered
in environmental and water management decisions for a more sustainable ecosystem for the Muddy-
Virgin River Project Area.
-------
VI
-------
Table of Contents
Notice iii
Executive Summary v
List of Appendices viii
List of Figures ix
List of Tables xiii
Acronyms and Abbreviations xiii
Glossary xiii
Foreward 1
I. Introduction 3
II. Basin Description 5
III. Project Description 10
A. Design- Selection of Stream Sites 11
B. Indicators - What to Measure at Each Selected Site 13
IV. Analysis and Results 18
A. Water Column Chemistry 20
B. Physical Habitat Indicators 32
C. Biological Indicators 44
D. Sediment Respiration 47
E. Metals 60
F. Relationships between Indicators and Stressors 72
G. Thresholds 76
V. Conclusion 83
VI. References 85
VII. Appendices 91
vn
-------
List of Appendices
Appendix 1. List of Sites 92
Appendix 2. Summary Statistics for Water Chemistry Indicators for the
Muddy-Virgin Project Area 93
Appendix 3. Summary Statistics for Physical Habitat Metrics 94
Appendix 4. Summary Statistics for Macroinvertebrate Metrics, Muddy-Virgin
Project 96
Appendix 5. Criteria Used to Determine Least-disturbed and Most-disturbed Sites 97
Appendix 6. Candidate Macroinvertebrate Metrics and Results of Range Test 98
Appendix 7. F-test Results for Candidate Microinvertebrate Metrics 109
Appendix 8. R2 Values for Final Metrics 102
Appendix 9. Final IBI Scores 104
Appendix 10. Periphyton 105
Appendix 11. Water Metals (|ig/L) 106
Appendix 12. Sediment Metals (mg/kg) 107
Appendix 13. Sediment Metabolism 108
Appendix 14. R Values of Significant Correlations (P<0.05) between Ecological
Indicators and Stressor Indicators. For Riparian Disturbances, used
Three Most Common Forms of Disturbances 109
Appendix 15. Estimating Relative Risk Estimate for Stressors. Data Used for Calculation
of Relative Risk Where A=Least-disturbed IBI Index and Least-disturbed
Stressor Metric Values, B=Most-disturbed IBI Index and Least-disturbed
Stressor Metric Values, C=Least-disturbed IBI Index and Most-disturbed
Stressor Metric Values, D=Most-disturbed IBI Index and Most-disturbed
Stressor Metric Values. Relative Risk Calculated as
= [D/(C+D)]/[B/(A+B)] Ill
Appendix 16. USEPA Water Quality Criteria for Trace Metals 112
Vlll
-------
List of Figures
Figure 1. Location of Major Rivers and Sampling Sites 6
Figure 2. Ecoregions of the Muddy-Virgin River Project Area 7
Figure 3. NLCD 2000 Land Cover for Muddy-Virgin River Project Area 9
Figure 4. Cumulative Distribution Frequency of Stream Total Phosphorus 20
Figure 5. Temperature and Latitude Graphed Separately for Muddy and
Virgin River Drainages, n= 22 22
Figure 6. Cumulative Distribution Function and Condition Estimate for
Stream Water Temperature 22
Figure 7. pH Values Graphed in Relation to Sampling Location in the
Muddy and Virgin rivers, n=22 23
Figure 8. Cumulative Distribution Frequency of pH of Streams 23
Figure 9. Conductivity Values Graphed in Relation to Sampling Location
in the Muddy and Virgin rivers, n=22 24
Figure 10. Cumulative Distribution Frequency and Condition Estimate of
Stream Conductivity 24
Figure 11. Dissolved Oxygen Values Graphed in Relation to Sampling Location
in the Muddy and Virgin Rivers, n=22 25
Figure 12. Cumulative Distribution Frequency of Stream Dissolved Oxygen 25
Figure 13. Total Phosphorus in Relation to Species Richness in all Sampling Sites
Included in the Study, R=-0.048,P=0.783,n=35 27
Figure 14. Cumulative Distribution Frequency and Condition Estimate of
Total Phosphorus 27
Figure 15. Cumulative Distribution Frequency and Condition Estimate of
Total Nitrogen 28
Figure 16. Comparison of Nitrate/Nitrite in the Muddy and Virgin Rivers, n=22 29
Figure 17. Nitrate/Nitrite Verses Species Richness for all Sampling Sites in the
Study Area R=-0.048.P=0.786,n=35 29
Figure 18. Cumulative Distribution Frequency and Condition Estimate of
Nitrate/Nitrite 30
Figure 19. Cumulative Distribution Frequency and Condition Estimate of Total
Kjeldahl Nitrogen 30
IX
-------
List of Figures (com.)
Figure 20. Cumulative Distribution Frequency of Ammonia 31
Figure 21. Cumulative Distribution Frequency and Condition Estimate of Chloride 32
Figure 22. Strahler Stream Order (FISRWG, 1998) 33
Figure 23. Relationship between Percent Slope to Basin Area and Stream Order,
R=-0.123,P=0.617, n=19 33
Figure 24. Relationship between Mean Thalweg Depth and Mean Wetted Width by
Stream Order, R=-0.049, P=0.771, n=37 34
Figure 25. Percent of Stream Samples within each Channel Type 35
Figure 26. Total Percent of Streambed with Dominant Substrate Class 36
Figure 27. Percent of Stream Samples Dominated by Different Substrate Classes
in Relation to Stream Order 37
Figure 28. Percent Vegetation Cover by Vegetation Class 39
Figure 29. Percent Samples with Vegetation Cover by Class in Relation to
Stream Order 39
Figure 30. Percent Mid-channel and Bank Shade by Stream Order 40
Figure 31. Cumulative Distribution Function and Condition Estimate of
Mid-channel Canopy Shade 40
Figure 32. Cumulative Distribution Function of Bank Shade 41
Figure 33. Level of Fish Cover 42
Figure 34. Percentage of Riparian Zone Human Influence, by Type, on Stream Reaches 43
Figure 35. Mean Riparian Zone Human Influence by Type 43
Figure 36. Cumulative Distribution Function and Condition Estimate of Total
Invertebrate Taxa Richness 45
Figure 37. Cumulative Distribution Function and Condition Estimate of EPT
Taxa Richness 45
Figure 38. Cumulative Distribution Function and Condition Estimate of
Intolerant Taxa 46
Figure 39. Cumulative Distribution Function and Condition Estimate of
Macroinvertebrate IBI 50
-------
List of Figures (com.)
Figure 40. Relative IBI Scores for Muddy-Virgin River Project Area Sampling Sites 51
Figure 41. Cumulative Distribution Function of the Autotrophic Index 52
Figure 42. Cumulative Distribution Function and Condition Estimate of Chlorophyll-a 53
Figure 43. Location of Muddy-Virgin R-EMAP Sample Sites with High Chl-a Levels
and Highest and Lowest AI Levels 54
Figure 44. Cumulative Distribution Function of Biomass 55
Figure 45. Map of Biomass (AFDM/cm2) in the Muddy-Virgin Proj ect Area 56
Figure 46. Biomass Values Graphed in Relation to Sampling Locations in the
Muddy and Virgin Rivers, n=18 57
Figure 47. Cumulative Distribution Function of Sediment Respiration 58
Figure 48. Map of Sediment Metabolism in the Muddy-Virgin Proj ect Area 59
Figure 49. Sediment Metabolism Values Graphed in Relation to Sampling Location
in the Muddy and Virgin Rivers, n=21 60
Figure 50. Cumulative Distribution Frequency and Condition Estimate of Aluminum
in Sediment 64
Figure 51. Cumulative Distribution Frequency and Condition Estimate of Arsenic in
Stream Water and Sediment 65
Figure 52. Cumulative Distribution Frequency of Copper in Stream Sediment 66
Figure 53. Cumulative Distribution Frequency of Iron in Stream Sediment 67
Figure 54. Cumulative Distribution Frequency and Condition Estimate of Lead
in Stream Water and Sediment 67
Figure 55. Cumulative Distribution Frequency and Condition Estimate of
Manganese in Stream Water and Sediment 68
Figure 56. Location of Muddy-Virgin River R-EMAP Sample Sites Containing
Mercury in Water and Sediment 69
Figure 57. Cumulative Distribution Frequency and Condition Estimate of Mercury
in Stream Sediment 71
Figure 58. Cumulative Distribution Frequency of Zinc in Stream Water and Sediment 72
Figure 59. Relationship Between Dissolved Oxygen and Proximity to Landfills.
R=0.613 P=0.0001, n=35 73
XI
-------
List of Figures (com.)
Figure 60. Relationship between Chloride and Width/depth Ratio. R=0.855
P=<0.0001, n=35 74
Figure 61. Relationship between Taxa Richness and % Sand/fine. R=-0.593
P=0.000, n=35 75
Figure 62. Relationship between Sediment Metabolism and Width/depth Ratio.
R=0.651P=<0.0001,n=35 76
Figure 63. Extent of Stream Length in Most-disturbed, Intermediate and Least-disturbed
Condition for Selected Water Quality Indicators and Macroinvertebrate IBI 78
Figure 64. Extent of Stream Length in Most-disturbed, Intermediate and Least-disturbed
Condition for Selected Physical Habitat Indicators 79
Figure 65. Summary Relative Extent of Stressors (Proportion of Stream Length with
Stressors in Most-disturbed Condition) 79
Figure 66. Risk to Benthic Assemblage (IBI) Relative to the Environmental Stressor
Condition 81
Figure 67. Summary of Extent of Stressors in Most-disturbed Condition in Relation to
Relative Risk. The Oval Emphasizes Stressor Indicators with both High Percent
of Stream Length in Most-disturbed Condition and with High Relative Risk.
Refer to Appendix 14 for Definition of Abbreviated Indicator Names in this
Figure 82
xn
-------
List of Tables
Table 1. General EMAP Indicators 14
Table 2. Water Column Indicators 14
Table 3. Streams in the Muddy-Virgin Project Area by Stream Order 19
Table 4. Water Quality Standards for Nevada 20
Table 5. Nutrients in the Muddy-Virgin area, Expressed as mg/L 27
Table 6. Percent of Stream Substrate Sample Dominated by Major
Substrate Classes 36
Table 7. Definition of LWD Classes Based of Length and Diameter Per 100m
of Stream Sample 37
Table 8. Riparian Vegetation Category and Associated Height 38
Table 9. Vegetation Category and Associated Vegetation Community of
Muddy-Virgin Project Area 38
Table 10. Index of Fish Cover Presence 41
Table 11. Riparian Disturbance Proximity to Stream and Associated Score 42
Table 12. Description of Benthic Macroinvertebrate Indicator Metrics
(Resh and Jackson, 1993 and Resh, 1995) 44
Table 13. Summary Statistics for Macroinvertebrate Metrics, Muddy-Virgin
Project 2000 47
Table 14. Examples of Expected Functional Feeding Group Rations from Resh (1995) 48
Table 15. Mean Percent of Functional Feeding Groups from the
Muddy-Virgin Project 48
Table 16. Final Metrics and Ceiling/Floor Values 50
Table 17. Sampling Sites with High chl-a Levels and Highest and Lowest AI Levels 55
Table 18. National Recommended Water Quality Criteria for Toxic Pollutants 61
Table 19. Summary of Selected Screening Level Concentration-Based
Sediment Quality Benchmarks for Freshwater Sediments 62
Table 20. Formulas to Calculate Specific CMC and CCC Values Based on Hardness 63
Table 21. Total Mercury Concentrations in Water and Sediment for Muddy River
Watershed R-EMAP 70
Table 22. Possible Combinations of Stressors and Indicator Relationships 72
Table 23. Thresholds for the Muddy-Virgin River Project Area 77
Table 24. Thresholds for the Muddy-Virgin River Project Area 80
Xlll
-------
Acronyms and Abbreviations
ACEC Area of Critical Environmental Concern
AFDM Ash Free Dry Mass
BLM Bureau of Land Management
BOD Biochemical Oxygen Demand
BRRC Biological Resources Research Center
EMAP Environmental Monitoring and Assessment Program.
CCC Critical Continuous Concentration
CDF Cumulative Distribution Frequency
CMC Critical Maximum Concentration
HUC Hydrologic Unit Code
LWD Large Woody Debris
NDEP Nevada Division of Environmental Protection
R-EMAP Regional Environmental Monitoring and Assessment Program.
SpC Specific Conductance
SEC Sediment Effect Concentration
UNR University of Nevada, Reno
USFWS United States Fish and Wildlife Service
USGS United States Geological Survey
xiv
-------
Glossary
Allochthonous - In limnology, organic matter derived from a source outside the aquatic system,
such as plant and soil material.
Benthic - Pertaining to the bottom (bed) of a water body.
Channel - The section of the stream containing the main flow.
Cobble - Substrate particles 64-256 mm in diameter.
Abiotic - Non-living characteristic of the environment.
Confidence interval - An interval defined by two values, called confidence limits, calculated
from sample data with a procedure which ensures that the unknown true value of the quantity of
interest falls between such calculated values in a specified percentage of samples.
Detritus - Non-living organic material.
Dissolved Oxygen (DO) - Oxygen dissolved in water and available for organisms to use for
respiration.
Ecological Indicator - Objective, well-defined, and quantifiable surrogate for an environmental
value.
Ecoregion - A relatively homogeneous area defined by similarity of vegetation, landform, soil,
geology, hydrology, and land use. Ecoregions help define designated use classifications of
specific water bodies.
Ephemeral River - A river that only flows when there is rain or snow has melted. The rest of the
year there is just a dry river bed with no water.
Embeddedness - The degree to which boulders, cobble or gravel in the stream bed are
surrounded by fine sediment.
Fine - Silt or clay less than 0.06 mm in diameter.
Functional Groups - Groups of organisms that obtain energy in similar ways.
Glide - Slow, relatively shallow stream section with little or no surface turbulence.
Gravel - Substrate particles between 2 and 64 mm in diameter.
Headwaters - The origins of a stream.
Laminar Flow - A smooth flow with no disruption between its layers.
Macroinvertebrate - Organisms that lack a backbone and can be seen with the naked eye.
Non-native species - A species that is not native to a particular location.
pH - A numerical measure of the concentration of the constituents that determine water acidity
(H+). Measured on a scale of 1.0 (acidic) to 14.0 (basic); 7.0 is neutral.
Rapid - Water movement is rapid and turbulent with intermittent white-water surface with
breaking waves.
xv
-------
Glossary (com.)
Riffle - An area of the stream with relatively fast currents and cobble/gravel substrate.
Sand - Small but visible particles between 0.05 to 2 mm in diameter.
Stream Order - A ranking of streams based on the presence and rank of its tributaries.
Stream Reach - Section of stream between two specific points.
Stressor - Any physical, chemical or biological entity that can induce an adverse response.
Substrate - The composition of the stream or river bottom ranging from rocks to mud.
Taxon (Plural Taxa) - A level of classification within a scientific system that categorizes living
organisms based on their physical characteristics.
Tolerance - The ability to withstand a particular condition, e.g., pollution-tolerant indicates the
ability to live in polluted waters.
xvi
-------
Foreword
The U.S. Environmental Protection Agency (USEPA) is charged by Congress to protect the
nation's natural resources. Under the mandate of national environmental laws, the USEPA
strives to formulate and implement actions leading to a compatible balance between human
activities and the ability of natural systems to support and nurture life. To meet this mandate, the
USEPA's Office of Research and Development (ORD) provides data and scientific support that
can be used to solve environmental problems, build the scientific knowledge base needed to
manage ecological resources wisely, understand how pollutants affect public health, and prevent
or reduce environmental risks.
The National Exposure Research Laboratory (NERL) is the Agency's center for investigation of
technical and management approaches for identifying and quantifying stressor exposures to
humans and the environment. Goals of the laboratory's research program are to: 1) develop and
evaluate methods and technologies for characterizing and monitoring air, soil, and water; 2)
support regulatory and policy decisions; and 3) provide the scientific support needed to ensure
effective implementation of environmental regulations and strategies.
The USEPA initiated the Environmental Monitoring and Assessment Program (EMAP) to assess
the current condition and trends of the ecological resources throughout the United States. Within
this context, the USEPA developed the Regional Environmental Monitoring and Assessment
Program (R-EMAP) to conduct studies on a smaller geographic and temporal scale.
This report presents stream data on the Muddy-Virgin River Project Area in southern Nevada
using the R-EMAP Program. Water is of primary importance to both the economy and the
ecology of the region. Many of the waters of Nevada have previously received relatively little
attention in regards to systematic bioassessment and this study is intended to address a lack of
adequate historical baseline data for the region.
Today, all of Nevada's major population centers are either situated near or bisected by one of its
major rivers. The cities and towns utilize the life giving water of those rivers; the vast reaches of
dryness demand this relationship. Las Vegas derives its water from the Colorado River via Lake
Mead. The rivers in the Muddy-Virgin River Project Area also drain into Lake Mead, supplying
additional water needs for a thirsty city. The water relied upon today will be used for future
generations. Though the assessment of Nevada's rivers and streams has gotten off to a slow start,
decisions made today regarding water management in the Great Basin region will be important
for years to come.
-------
-------
I. Introduction
"Water! It's about water."
Wallace Stegner, western author and lifelong resident of the arid regions of western North
America, was asked what a newcomer to the American West should know. The above statement
was his terse reply. In fact, life does not exist without water. This fact is nowhere more pertinent
than in the Nevada Great Basin where rivers are the flowing arteries in the midst of huge, arid,
and often desolate western landscape. These streams and rivers have been a critical resource to
both humans and wildlife for many thousands of years.
This report summarizes data collected from the wadeable streams in the Muddy-Virgin River
Project Area of Nevada. The determination of current status is a critical step in the future
management of these stream resources, and, to that end, this study focuses on providing
"baseline" data for the systems studied. To provide the information needed to assess these
streams, the USEPA's Regional Environmental Monitoring and Assessment Program (R-EMAP)
protocols were used for sampling stream reaches within the Muddy-Virgin River Project Area.
The goal of the this Muddy-Virgin River Project was to assess the water quality and biotic
integrity of perennial and intermittent streams over a one year sampling period for the Muddy-
Virgin River Project Area, using a combination of macroinvertebrates, physical habitat
measurements, water and sediment chemistry, and sediment metabolism. The objectives of the
Muddy-Virgin River Project Area R-EMAP were to describe the condition of surface waters,
relate ecological conditions to ecological stressors and examine relative risks to streams within
the Area.
This report presents stream data on the Muddy-Virgin River Project Area in southern Nevada
using the R-EMAP Program. Water is of primary importance to both the economy and the
ecology of the region. Many of the waters of Nevada have previously received relatively little
attention in regards to systematic bioassessment and this study is intended to address a lack of
adequate historical baseline data for the region.
Today, all of Nevada's major population centers are either situated near or bisected by one of its
major rivers. The cities and towns utilize the life giving water of those rivers; the vast reaches of
dryness demand this relationship. Las Vegas derives its water from the Colorado River via Lake
Mead. The rivers in the Muddy-Virgin River Project Area also drain into Lake Mead, supplying
additional water needs for a thirsty city. The water relied upon today will be used for future
generations. Though the assessment of Nevada's rivers and streams has gotten off to a slow start,
decisions made today regarding water management in the Nevada will be important for years to
come.
-------
-------
II. Basin Description
The Muddy-Virgin R-EMAP project area encompassed eastern and southern Nevada (NV). The
study area extended from Ely, NV, in east-central Nevada, south to Las Vegas, NV, to
southeastern Utah (Washington County), and the Lake Mead National Recreation Area of
Arizona. The study area encompassed 32,856 square miles in Nevada, 5,400 square miles in
Arizona and 2,400 square miles in Utah. Arizona and Utah were included to incorporate the
lower Virgin River Basin. All major drainages in this system with flowing surface water, during
the index period of May/June, were sampled for this study. These included the White River,
Pahranagat River, Beaver Dam Wash, Meadow Valley Wash, Muddy River, Las Vegas Valley
Wash, and Lower Virgin River (Figure 1).
The eastern and southern portion of Nevada is in Ecoregion III (Omernik, 1987), subecoregions
13 (Central Basin and Range) and 14 (Mojave Basin and Range) with a small portion of Arizona
and Nevada in subecoregion 22 (Arizona/New Mexico Plateau). The portion of the lower Central
Basin and upper Mojave Basin is comprised of north-south trending fault-bounded horst and
graben geomorphology. The Mojave Basin and Range physiography is a creosote bush-
dominated shrub community (Figure 2). This is distinct from the saltbush-greasewood and
sagebrush-grass associations that occur to the north in the Central Basin and Range. Major
vegetation communities include montane, pinyon-juniper, western juniper, sagebrush/grassland,
shadscale, and Mojavean (Mac et al., 1998). The mountains are steep and deeply incised with
alluvial/ colluvial deposits in the canyons with fine sediments becoming the dominant substrate
in the broad valleys. Fan deposits in the Mojave Basin and Range ecoregion are predominantly
composed of debris flows.
The Virgin River is the largest contributor to the Colorado River in Nevada. During low-flow
periods, most of the flow in the Virgin River originates from a highly saline, major spring system
in Littlefield, Arizona, located approximately 10 miles upstream of Mesquite (ADWR, 2009).
Precipitation is low (e.g., <15 cm/year in subecoregion 14) in this region whose elevation ranges
from 367 to 3626 m. Surface water resources in the drainage basin are primary spring fed with
the Virgin River receiving drainage from snowmelt in central and eastern Utah. The Las Vegas
Valley Wash is currently an urban drainage system with few naturally flowing springs, but does
receive spring or autumnal monsoon rainfall. Flash flooding is an important ecological event in
eastern and southern Nevada. However, flash flooding does not occur with its historical
frequency or severity due to regulation of all streams and rivers.
The wadeable streams of eastern and southern Nevada do not represent a broad range of basin
areas and gradients. Most high elevation streams are dry throughout most of the year, with flow
alternating between the surface and hyporheic zone and returning to valley streams. Basin
streams, which have flowing water for most of the year, do not lend themselves to conventional
stream order, which classifies stream size based on a hierarchy of tributaries. It is important to
acknowledge that the basin morphology does influence stream processes. Unfortunately, how
basin morphology interacts with stream processes for eastern and southern Nevada is unknown.
The results of this study imply that paradigms of the relationships between stream order and
basin morphology are not applicable to desert, spring-fed stream systems. This is most likely a
result of the sensitive nature of the desert environment to anthropogenic stressors. Because this
-------
relationship is unknown, it is difficult to determine if the interpretation of stream condition is
confounded.
A
Pahranacfat River
m Wash
irgin Riyer
Las Vetias Valley Wash
20 0 20 40 Kilometers
Location Map
Legend
Basin Boundary
Sample Points
Major Rivers
Hydrologic Units
Figure 1. Location of Major Rivers and Sampling Sites.
-------
Location Map
Ecoregion III
22
| | Boundary
Ecoregions III (AZ) & IV (NV, UT)
I | Arid Footslopes
Arid Valleys and Canyonlands
Arizona/NewMexico Plateau
| | Carbonate Sagebrush Valleys
Carbonate Woodland Zone
Central Basin and Range
Creosote Bush-Dominated Basins
High E levation Carbonate M ountains
Middle E levation Mountains
I I Mojave Basin and Range
| | Mojave High Elevation Mountains
| | Mojave Mountain Woodland and Shrubland
I | Mojave F1 lavas
B Sagebrush Basins and Slopes
Shadscale-Dom inated Saline Basins
I | Tonopah Basin
Tonopah Sagebrush Foothills
Tonopah Uplands
Wetlands
I | Woodland- and Shrub-Covered LowM ountains
'Level IV not completed for Arizona
Figure 2. Ecoregions of the Muddy-Virgin River Project Area.
Heavy water use, approximately 75%, of existing flowing water and pumping of aquifers further
decreases the extent of river flow in the Muddy-Virgin project area. The Pahranagat and White
rivers are highly manipulated, and large portions of the rivers exist in straight ditches rather than
natural, meandering channels. The Meadow Valley Wash is an intermittent stream system, which
has primarily hyporheic flow in its lower-middle portion and only during flash floods will flow
into the Muddy and Virgin rivers. The Muddy and Virgin Rivers are also highly disturbed being
-------
moderately channelized and having regulated flow. These rivers are under pressure from
agricultural practices, ranching, dairy farming, a coal-fired power station (Muddy River), mining,
water treatment facilities, and urban influences. Additionally, the Las Vegas Valley Water
Authority plans to pump the aquifers at the head of the Muddy River, the effects of which are yet
unknown.
Streams in eastern and southern Nevada are home to several endemic and listed species. The
Muddy River has the endangered Moapa Dace (Moapa coriaced) and several endemic snails.
The Pahranagat roundtail chub (Gila robusta jordani) is endemic to the Pahranagat River, and
the Virgin River chub (Gila robusta seminude) to the Virgin River. Threats to these biotic
endemics include invasive organisms, [e.g., fish (Tilapia spp.) and plants (Tamarix sp.)], water
withdrawal, sedimentation and chemical and thermal pollution.
With the vast majority of the land in northeast Clark County under federal management, private
land is predominantly located along the Muddy and Virgin River flood plain corridors.
Agricultural irrigation is the primary water use. Pollutants of concern are total phosphorus and
metals including boron, iron and arsenic. Several dairy farms and feedlots identified in the
vicinity of the Muddy River can be key contributors of BOD loading, nitrates and bacteria in
downstream receiving waters. The only significant industrial operation in the lower Muddy River
is NV Energy's Reid Gardner Power Plant near the unincorporated area of Hidden Valley. While
runoff from a large stockpile of coal at this site is intercepted in a containment ditch, it has been
reported that during large discharge events, flow from the site may reach the Muddy River (Clark
County, 2008).
Soil erosion from agricultural lands can contribute significant amounts of nutrients, trace metals
and pesticides to receiving waters. Forms of nitrogen and phosphorus are associated with either
irrigation return flows or storm runoff. Along the lower reaches of the Muddy-Virgin River
system, the soils are highly susceptible to erosion (Clark County, 2000). As of 2000, Moapa
Valley, encompassing the lower part of the Muddy River, has 5,182 acres of agricultural lands,
of which 4,982 acres are irrigated. Virgin Valley, in the lower portion surrounding the Virgin
River, has 3,531 acres of agricultural lands, of which 3,068 acres are irrigated. Irrigation, along
with the effects of evapotranspiration, results in an increased salt concentration in irrigation
return flows. Fertilizers applied to agricultural areas can impact residual nitrogen and phosphorus
transported to receiving waters.
The Virgin River is designated as an Area of Critical Environmental Concern (ACEC) in the
BLM's Proposed Las Vegas Resource Management Plan (1998). The U.S. Fish and Wildlife
Service has established two fish recovery teams, one for the entire length of the Virgin River and
the other specifically in the lower Virgin River for the recovery of the federally endangered
woundfin (Plagopterus argentissimus), Virgin River chub (Gila robusta seminude), and three
additional species of special concern.
Originally, the Muddy River was bordered by willow (Salix sp.) and screwbean mesquite
(Prosopis Pubescens) (Longwell, 1928). Now the dominant trees along the spring systems in the
Warm Springs area are non-native palms and tamarisk (Tamarix sp.\ which is the most common
riparian species along the middle and lower Muddy River (Clark County, 2008).
-------
Except for the immediate riparian corridor, the southern desert shrub is the dominant vegetation
community mapped by BLM (1998). Riparian vegetation along the river includes rushes, cattails,
inland salt grass and stands of mesquite and greasewood (City of Mesquite, 2009). See Figure 3
for land cover in the Muddy-Virgin River Project Area.
A
30 0 30 Kilometers
Location Map
Legend
| | Project Area
Land Cover
^H Open Water
^^ Urban
| | Barren RockJSand/Clay
| | Deciduous Forest
| | Evergreen Forest
HI Mixed Forest
| | Shrub/Scrub
| | Grassland/Herbaceous
^B Pasture/Hay
| | Cultivated Crops
| | Woody Wetlands
| | Emergent Herbaceous Wetlands
I I No Data
Figure 3. NLCD 2000 Land Cover for Muddy-Virgin River Project Area.
-------
10
-------
III. Project Description
This report summarizes data collected from the wadeable streams in the Muddy-Virgin River
Project Area. The determination of current status is a critical step in the future management of
stream resources such as water quality, and, to that end, this study focuses on providing
"baseline" data for the systems studied. To provide the information needed to assess these
streams, the USEPA's Regional Environmental Monitoring and Assessment Program (R-EMAP)
protocols were used for sampling stream reaches within the Muddy-Virgin River Project Area.
This work was done by personnel from the University of Nevada Biological Resources Research
Center (BRRC), in cooperation with USEPA Region 9 and the USEPA Office of Research and
Development (ORD).
The USEPA initiated the Environmental Monitoring and Assessment Program (EMAP) to assess
the current condition and trends in the ecological resources in the United States. Within this
context, the USEPA developed the Regional Environmental Monitoring and Assessment
Program (R-EMAP) to conduct studies on smaller geographic and temporal scales within the
United States. The goal of R-EMAP is to provide environmental managers with statistically valid
analyses of stream ecosystems condition (Whittier & Paulsen, 1992). Three main objectives
direct the R-EMAP projects: (1) estimate the current status and trends in indicators of condition,
(2) define associations between human-induced stresses and ecological condition, and (3)
provide statistical reports to environmental managers and the public (Lazorchak & Klemm,
1998).
The goal of the this Muddy-Virgin River Project was to assess the water quality and biotic
integrity of perennial and intermittent streams over a three year sampling period for the Muddy-
Virgin River Project Area, using a combination of macroinvertebrates, physical habitat
measurements, water and sediment chemistry, and sediment metabolism. The objectives of the
Muddy-Virgin River Project Area R-EMAP were to:
• Describe the ecological condition of surface waters in the Muddy-Virgin River Project Area.
• Examine the relationship between indicators of ecological condition and indicators of
ecological stressors in these streams.
• Examine the relative risk of wadeable streams within the Muddy-Virgin River Project Area.
A. DESIGN - Selection of Stream Sites
Environmental monitoring and assessments are typically based on subjectively selected stream
reaches. Peterson et al. (1999) compared subjectively selected localized lake data with
probability-based sample selection and showed the results for the same area to be substantially
different. The primary reason for these differences was lack of regional sample
representativeness of subjectively selected sites. Stream studies have been plagued by the same
problem.
A more objective approach is needed to assess stream quality on a regional scale. Therefore,
sampling sites were selected using a probability-based design using the USEPA River Reach File
11
-------
version 3 (RF3) 1:100,000 scale Digital Line Graph (DLG) as a sample frame to represent the
wadeable streams.
For the Muddy-Virgin River Project Area, sites (Figure 1) were assessed for accessibility based
upon the knowledge of local experts with field experience in the Muddy-Virgin River Project
Area, combined with land ownership patterns, as represented on 1:100,000 maps. The
monitoring network was established by overlaying the national EMAP 40 km2 hexagonal frame
(Stevens, 1999, 2004) over the Muddy-Virgin River Project Area. Sites were selected using a
probability-based, or random, design to represent the first to sixth order streams (i.e., nominally
wadeable streams) within the Muddy-Virgin River Project Area The selection was weighted by
stream length where more sites were selected for higher order streams because of the larger
representation of stream miles, and the potential of these streams being dry. The site selection
requirements were:
• Equal area sampling representation of the Muddy-Virgin River Project Area
• Equal representation of stream courses
• Equal representation of one year, 2000
• Detection of trends in a set of indicators by revisiting at least 10% of the sites sampled the
previous year (Stevens & Olson, 1999)
Optimal statistical representation of aquatic resources in the Muddy-Virgin River Project Area is
best achieved with a sampling of at least 40 sites. It is difficult to discern from RF3 whether line
segments will in fact contain water, be accessible, and wadeable. In addition, it was anticipated
some landowners would refuse permission to enter sampling locations. Therefore, the number of
prospective sampling sites selected was increased to compensate for these discrepancies. As a
result, in 1998, 120 sites were initially selected to reach the statistical target of 40 sampled sites.
Due to the high number of dry sampling sites, only 35 sites were sampled in 1998. In 1999, 160
were initially selected, but only 34 sites were sampled. In addition, to assess inter-seasonal
variability, ten sites from 1998 were randomly selected and revisited. For this report, water
quality and physical habitat data were averaged for revisit sites. The statistical extent of the
Muddy-Virgin River Project Area resource was estimated at 12,427 km stream length.
The sampling index period for this study was May-June, 2000. The southern Great Basin and
Mojave Basin ecoregions receive approximately five to seven inches of rain per year with most
of the rainfall occurs during winter and summer. Tributaries to the Muddy River and Virgin
River are predominantly ephemeral. Because of the arid nature of the southern Great Basin and
Mojave Basin, to obtain a statically significant number of sampleable sites (-40) during the
index period, 1500 sites were randomly selected.
Reconnaissance of random site locations was conducted from December 1999 to May 2000. The
objective during the site selection process was to maximize the number of sites with flowing
water, limit the number of sites with no water, and to gain an understanding of the hydrographic
region as a whole. Sites were initially mapped onto DeLorme's Atlas and Gazetteer. Sites in
Utah and Arizona were reconnaissanced (and sampled) only if they were located on the Virgin
River. In the field, sites were located using 7.5" USGS and BLM topographical maps and a
12
-------
Garmin III Global Positioning System Unit. Actual site coordinates were recorded on the
USEPA R-EMAP datasheet.
In addition to reconnaissance by UNR field staff, to acquire local background knowledge on the
sites, possible R-EMAP sites were mapped onto USGS topographic maps and sent to the local
BLM office in Caliente, NV, and the U.S. Fish and Wildlife Service office in Las Vegas, NV. Of
the 1500 randomly generated sites, status of surface water (i.e., flowing water present) was
determined by ground verification of USEPA site coordinates with a GPS unit for 116 random
sites, and comparison of mapped location with field observations for 243 sites. Status of surface
water for all other sites were determined by comparing detailed field notes with mapped location
of each site. Only 37 sites had flowing surface water and thus were able to be sampled
(Appendix 1).
In relation to site accessibility, land ownership proved not to be an issue in this area. Twenty-
seven percent of sampled sites were on federal land (BLM, national parks, state parks, etc.), 12%
owned by the state of Nevada, and 61% privately owned. Private ownership was determined by
comparing sites mapped onto 1:60,000 USGS topographic maps to land ownership maps in
respective county assessor offices.
Landowners were contacted via telephone for access to sites on private lands and explained that
UNR is conducting an aquatic assessment project involving sampling water quality and biotic
parameters. It was clearly explained to the landowners the goal of this project is to develop a
baseline understanding of the current status of the watersheds surface waters. The objectives of
this study did not include identification of federally listed or endemic species. Of all sites with
flowing water, four sites were not physically able to be sampled and one site was not granted
access from private land owners.
The original site location was shifted when the site was not able to be sampled due to
morphological changes in location of the channel, channels with large hyporheic zones, or
vegetation or land use conflicts where the original site could not be reached. Seven percent of
original site locations were shifted up or downstream to accommodate land ownership. A
problem exists with the R-EMAP protocol of choosing random locations for sampling for eastern
and southern Nevada. Most areas mapped as surface water on USGS and BLM topographical
maps are actually dry washes that flow intermittently with heavy rainfalls. In these intermittent
stream channels, flow generally consists of flashflood events, which would not be samplable.
B. INDICATORS -Whatto Measure at Each Selected Site?
The objective of the Clean Water Act is to restore and maintain the chemical, physical and
biological integrity of the Nation's waters. In order to assess the Nation's waters, it is important
to measure water quality (water column parameters), physical habitat (watershed and instream
measurements) and biological (macroinvertebrates communities) condition as well as sediment
respiration and water and sediment chemistry (metals).
EMAP uses ecological indicators to quantify these conditions. Indicators are simply measurable
characteristics of the environment, both abiotic and biotic, that can provide information on
ecological resources. Table 1 is a general list of the indicator categories used in EMAP to detect
13
-------
stress in stream ecosystems. The following section describes EMAP measurements in each of
these indicator categories.
Table 1. General EMAP Indicators.
Indicator
Water column chemistry
Watershed condition
In-stream physical habitat and
riparian condition
Biological-Benthic
macroinvertebrates
Sediment Metabolism
Rationale
Water chemistry affects stream biota. Numeric standards are available to evaluate some water
quality parameters.
Disturbance related to land use affects biota and water quality.
Instream and riparian alterations affect stream biota and water quality. Physical
habitat in streams includes all physical attributes that influence organisms.
Benthic macroinvertebrates live on the bottom of streams and reflect the overall biological
integrity of the stream. Monitoring benthic invertebrates is useful in assessing the condition of the
stream.
Measures functionality of ecosystems by changes in dissolved oxygen, and can be used to
indicate ecosystem stress.
Reach Identification
In a stream assessment, the sampling reach length has to be long enough to ensure the collection
of representative samples. Proper functioning stream systems have repeating morphological
patterns (Rosgen 1996). Kaufmann et al., 1999, indicate that the sample reach needs to
incorporate this cyclic variation. Depending on the objective of the stream bioassessment study
and protocol used (Barbour et al. 1999; CDFG 2003; Ohio EPA 1987; OCC 1993; Kaufmann
and Robison 1997; Fitzpatrick et al. 1998; Lazorchak et. al. 1998; Meador et al. 1993) reach
length can vary from 20 - 40 times wetted or bankfull width. For this study the EMAP protocol
of 40 times the wetted width is measured at the center of the reach, or F transect. If the stream
wetted width is less than 4 meters, the stream reach length total is 150 meters. If the stream
wetted width is greater than 4 meters, the stream reach length total is 40 x wetted width to a
maximum of 500 meters or 12.5 meters in width. If the stream wetted width is greater than 12.5
meters the maximum stream reach length will be 500 meters.
Water Column Chemistry
Water chemistry characteristics influence the aquatic community structure. A great deal of
information is available on the effects of specific chemicals on aquatic biota. Data for 13 water
quality parameters were collected at all sites. Measurements of hydrogen ion activity (pH),
dissolved oxygen (DO), stream temperature (°C), specific conductance (SpC), nitrate (NOs),
nitrite (NO2), total phosphorus (TP), ammonia (NH3), chloride (Cl), sulfate, Total Kjeldahl
Nitrogen (TKN), Total Suspended Solids (TSS) and Total Dissolved Solids (TDS) were taken.
These samples were sent to USEPA Region 9 laboratory (Richmond, CA) or Region 5 laboratory
(Cincinnati, OH) for analysis. The rationale behind the selection of some of these water measures
is presented in Table 2.
14
-------
Table 2. Water Column Indicators.
Indicator
Stream Temperature
Dissolved Oxygen
(DO)
PH
Conductivity
Nutrients-
Total Kjeldahl
Nitrogen, Ammonia,
and Total Phosphorus
Chloride
Importance to Biota
-Influences biological activity
-Growth and survival of biota
-Growth and survival offish
-Sustains sensitive benthic invertebrates
-Organic material processing
-Fish production
-Benthic invertebrate survival
-Indicator of dissolved ions
-Simulates primary production
-Accumulation can result in nutrient
enrichment
-A surrogate for human disturbance (Herlihy et
al. 1998)
Examples of Human Activities that
Influence this Indicator
-Riparian shade reduction
-Altered stream morphology
-Erosion
-Addition of organic matter
-Riparian shade reduction
-Industrial and municipal waste
-Mining
-Addition of organic matter
-Agricultural returns, industrial input and mining
-Erosion
-Recreation and septic tanks
-Stormwater runoff
-Fertilization from agriculture, livestock waste
and sewage
-Industrial discharge, fertilizer use, livestock
waste, and sewage
Physical Habitat Observations and Indicators
Physical habitat in streams includes all structural characteristics that influence the organisms
within the stream. Physical habitat parameters were measured in order to quantify and provide an
understanding of the stream's ecological functioning.
Some Useful Definitions - Habitat:
Bankfull Width - The stream width measured at the average flood water mark.
Canopy - A layer of foliage in a forest stand. This most often refers to the uppermost layer of
foliage, but it can be used to describe lower layers in a multistoried stand.
Channel - An area that contains continuously or periodically flowing water that is confined by
banks and a stream bed.
Large Woody Debris - Pieces of wood larger than five feet long and four inches in diameter, in a
stream channel.
Riparian Area - An area of land and vegetation adjacent to a stream that has a direct effect on
the stream. This includes woodlands, vegetation and floodplains.
15
-------
Substrate Size - The composition of the grain size of the sediments in the stream or river bottom,
ranging from rocks to mud.
Thalweg - The deepest part of the stream.
All indicators vary naturally, thus expectations differ even in the absence of human caused
disturbance. The following three types of habitat variable are measured or estimated:
Continuous Parameters
Thalweg profile (a survey of depth along the stream channel), and presence/absence of fine
sediments were collected at points along the stream reach. Crews also tally large woody debris
along the reach.
Transect Parameters
Measures/observations of bankfull width, wetted width, depth, canopy closure, and fish cover
were taken at ten evenly spaced transects in each reach. Slope measurements and compass
bearing between each of the 10 transects were collected to calculate reach gradient. This
category includes measures and/or visual estimates of riparian vegetation structure, human
disturbance, and stream bank angle, incision and undercut.
Reach Parameters
Total stream discharge was also measured at or near the x-site, which is defined as the center
segment of the stream reach, using 15 to 20 individual velocity measurements, spaced at equal
widths across the stream. All velocity measurements were taken at 60% of the total stream depth
for each point sampled.
Biological Indicators
Due to the fact that many of the streams in the Great Basin do not support fish communities, it
was decided that biological sampling efforts should focus on macroinvertebrates and sediment
metabolism. In addition, a full suite of in-stream and riparian physical habitat data was taken, as
a means of correlating the biologic condition of the in-stream community to the condition of the
riparian and upland environments.
Taxonomy of benthic macroinvertebrates was done by BRRC personnel, U.C. Berkeley
personnel, and Bioassessment services, Folsom CA. Chemical analysis was done by the
USEPA's Cincinnati lab. Data compilation involved the quality assurance methods designed by
USEPA's Office of Science and Technology, Corvallis office (Kauffman et al., 1999).
Benthic Invertebrate Assemblage:
Benthic invertebrates inhabit the sediment or surface substrates of streams. The benthic
macroinvertebrate assemblages in streams reflect overall biological integrity of the benthic
community. Monitoring these assemblages is useful for assessing the status of the water body,
and for monitoring trends. Benthic communities respond to a wide array of stressors in different
ways, thus, it is often possible to determine the type of stress that has affected a
macroinverebrate community (Klemm et al., 1990). Because many macroinvertebrates have
16
-------
relatively long life cycles, of a year or more, and are relatively immobile, macroinvertebrate
community structures are a function of past conditions.
Benthic samples of substrate surface area were taken using a Surber sampler from riffle habitat
only, unless no riffle existed. If no riffle existed, samples were taken from glides at that site.
Riffles or glides used for benthic sampling were chosen randomly among the potential
appropriate sampling locations at each transect. Each chosen riffle was then divided into ten
equal lengths, and three sampling sites were determined randomly based on these ten segments.
All samples were preserved in 90% ethanol and transported to the UNR aquatic ecology lab. In
the laboratory, macroinvertebrates were sorted from the detritus by spreading the sample out
evenly in a large tray, which was divided into a grid with numbered squares. Detritus from
randomly chosen squares were moved to a smaller tray. With a microscope, macroinvertebrates
were then sorted from the detritus, placed into small, plastic vial and filled with ethanol.
Invertebrates were identified to lowest possible taxonomic unit.
Periphyton:
Periphyton samples were collected at the nine cross-sections at erosional and depositional
habitats of each sample reach. In erosional habitats, a sample of substrate was scrubbed within a
15 cm diameter to remove the periphyton, and placed in a funnel which then drained into a
bottle. In depositional habitats, the top 1 cm of a 12 cm2 area of soft sediments was vacuumed
into a syringe. The syringe was then emptied into a plastic bottle.
Four types of laboratory samples were prepared. An ID/enumeration sample determines
composition and abundance. Chlorophyll and acid/alkaline phosphatase activity (APA) samples
were analyzed for their relation to biomass and structure. A biomass sample was also taken. This
is a measurement of the organic matter of a sample, measured by weighing the difference in
mass after drying and incinerating the matter. The remains are ash free dry mass (AFDM). The
sample was then weighed against its dry mass to determine the biomass. This was done to
discount against any silt or other inorganic matter.
Sediment Metabolism
Sediment samples were collected from throughout the stream reach, using the top two
centimeters of sediment, until a volume of 1 liter was obtained. Sediment metabolism
measurements were taken by incubating 15 ml of sediment in 35 ml stream water (50 ml vials),
with five replicates plus two blank controls, at ambient stream temperature for two hours, and
determining the difference in dissolved oxygen between start and finish (details provided in
Section 3).
17
-------
Photo: Pahranagat River south of Upper Lake
18
-------
IV. Analysis and Results
Using the R-EMAP protocols described, data was collected from 37 sites in the Muddy-Virgin
project area. Data quality assurance procedures followed those outlined in USEPA bioassessment
guidelines. For this report, because of the large volume of data/information collected, only
indicators of significant interest are reported on. Additional indicators are summarized in
Appendix 3. In the project area, stream order, which classifies stream size based on a hierarchy
of tributaries, consisted of first, third, forth and fifth order streams, with the majority of samples
taken in the fifth order streams (Table 3).
Table 3. Streams in the Muddy-Virgin Project Area by Stream Order.
Stream Order
1
3
4
5
No. of Samples
1
13
6
17
% Total
1.6
23.4
10.1
64.9
Data Analysis and Interpretation
In this report, the primary method for evaluating indicators was cumulative distribution functions
(CDFs). The statistical design of the EMAP dataset allows for the extrapolation of results from
sampled sites to the greater target population. Any of the data metrics can be quantitatively
described using cumulative distribution functions (CDF's), which show the stream length
represented in the target population (or proportion of length) that has values for an indicator at or
below some specific value of interest. CDF graphs show the complete data population above or
below a particular value as shown by the red line. The grey dotted lines are the upper and lower
confidence boundaries of the data. To read a CDF graph, chose a particular value along the x-
axis. Draw a line straight up to the CDF line. Then, read over to the y-axis to determine what
percentage of Muddy-Virgin River Project stream reach had a value greater than or equal to the
value selected on the x-axis. For example, Figure 4 shows that approximately 95% of the stream
length has a measurement of Total Phosphorus of < O.lmg/1 and is considered functional. This is
an effective way to show the extent of functionality (good) or impairment (poor) based on a
particular metric for the entire population. Once this distribution is established, thresholds can be
drawn at any point in the distribution. The "population" in this report is the stream reaches in the
Muddy-Virgin project area.
19
-------
1 nn
±U J
on
y j
on
70
tT*~i
b J
«•
e
A i c. n
B ^O
4 40 -
sn
in
iU
i n
±u
/- ~~
Impaired
i
i
/
Functional
i
} USEPA Aquatic Life Use Standard
forTP=0.1 mg/l
300
- 250
•mf
1
-i H1 f*
:> LTI C
DOC
Stream Length
50
n
1 1 1 | U
0.01 0.11 0.21 0.31 0.41
Total Phosphorus (mg/L)
Figure 4. Cumulative Distribution Frequency of Stream Total Phosphorus.
A. Water Column Chemistry
In general terms, a water quality standard defines the goals for a body of water by designating
the use or uses to be made of the water, setting criteria necessary to protect those uses, and
preventing degradation of water quality through anti-degradation provisions. Water quality
standards apply to surface water of the United States, including rivers, streams, lakes, oceans,
estuaries and wetlands. Under the Clean Water Act, each state establishes water quality standards
which are approved by the USEPA. The State of Nevada has established water quality standards
that include water quality criteria representing maximum concentration of pollutants that are
acceptable, if State waters are to meet their designated uses, such as use for irrigation, watering
of livestock, industrial supply and recreation (Table 4).
20
-------
Table 4. Water Quality Standards for Nevada.
Indicator
Water Temperature
PH
Specific Conductivity
Dissolved Oxygen
Standards for Nevada
<24°C (non-trout waters)
<20°C (trout waters)
6.5-9.0
<800 uS/cm
>5 mg/L (non-trout waters)
>6 mg/L (trout waters)
Data for 11 water column indicators were collected from 37 sites (Appendix 2). The results
reported below are for only those variables that have applicable criteria and/or those that
influence the biota. See Appendix 2 for complete list of variables and summary statistics. Sites
were not continuously sampled and timing of sampling was not intended to capture the peak
concentration of chemical indicators. Data interpretation reflects a single view in time at these
representative locations. Stream location values were graphed using the data from the 22
sampling sites located on the Virgin River and Muddy River. Cumulative Distribution
Frequency and Condition Estimate were done with data from all 37 sites collected in the Muddy-
Virgin River Project Area.
Temperature
Water temperature is temporally variable and can vary daily and seasonally, thus a single
measure of water temperature is limited in determining stream conditions. However, during the
sampling period (May-June) water temperature ranged from 13.1 to 32.8°C over all sites with a
mean temperature of 23.1 °C. High stream temperatures were expected here as most of the study
streams are warm-spring fed. There was no relationship between temperature and latitude or
between water temperature and mid-channel shading (Figure 5). Using Nevada State criteria as a
reference, at the time of sampling, fifteen samples exceeded the 24°C standard and twenty-five
sites exceeded the 20°C standard. Figure 6 shows the CDF and condition estimate using 20°C as
the condition standard.
21
-------
Virgin River
Muddy River
upstream
downstream
Stream Location
Figure 5. Temperature and Latitude Graphed Separately for Muddy and Virgin River Drainages, n= 22.
130
90
SCI
70
60 -
I 50 -
i
40 -
30
20
10
0
150 =
18 23 28
Water Temperature (:C)
WaterTemperature |'C)
• GOOD BPOOR
Figure 6. Cumulative Distribution Function and Condition Estimate for Stream Water Temperature.
Another important water column variable, hydrogen ion activity (pH), is a numerical measure of
the concentration of the constituents determining water acidity. It is measured on a logarithmic
scale of 1.0 (acidic) to 14.0 (basic) and 7.0 is neutral. As seen in Figure 7, the pH values in the
upstream portions of the Virgin River range from 7.9 to 8.4, which is indicative of increased
alkalinity from the carbonate rock units which underlay the Basin. Measurements of pH collected
during the day are typically elevated as CC>2 is depleted due to photosynthesis, which effectively
shifts the pH up. The pH of the Muddy-Virgin area ranged from 7.2 to 8.6 with an average of 8.0
(Figure 8). All of the sampled stream reaches were within the state of Nevada's pH standard of
6.0 to 9.0. The condition estimate was not determined for pH as all the sample sites fell into the
22
-------
good category. This study indicated that pH was not a sensitive indicator of anthropogenic stress
within the basin.
-Virgin River
-Muddy River
6.5
upstream
Stream Location
downstream
Figure 7. pH Values Graphed in Relation to Sampling Location in the Muddy and Virgin Rivers, n=22.
100
90
SO
70 -
60
50
I
40
30 -
20
10
0
I
a
150 s
Figure 8. Cumulative Distribution Frequency of pH of Streams.
Specific Conductance
Conductivity, a measure of the ion concentration of water, is useful in determining
contamination from mining and agricultural practices. The state of Nevada's specific
conductance standard is 800 |iS/cm. The net increase from upstream to downstream for both the
Muddy River and Virgin River (Figure 9) was most likely a result of cumulative increase of salts
in the downstream direction resulting from the river systems draining carbonate rocks sequences
(Eakin, 1964) and agriculture return flows in the lower reaches. Conductivity in the Muddy-
23
-------
Virgin area ranged from 793 to 3800 |iS/cm with a mean of 1704 |iS/cm (Figure 10). In the
Muddy-Virgin River Basin, 80% of the samples exceeded this standard. This is most likely a
result of the natural background saline nature of the valley soil chemistry
Virgin River
Muddy River
0
upstream
Stream Location
downstream
Figure 9. Conductivity Values Graphed in Relation to Sampling Location in the Muddy and Virgin Rivers, n=22.
IOC
90
SO
70 -
60 -
! 50 -
40 -
30
20
10
• 200 *
310 810 1310 1310 2310 2810 3310 3810
Conductivity (us/cm)
Conductivity
IGOOD BPOOR
Figure 10. Cumulative Distribution Frequency and Condition Estimate of Stream Conductivity.
Dissolved Oxygen (DO)
Dissolved oxygen is the amount of gaseous oxygen (62) dissolved in water and available for
organism respiration. Dissolved oxygen can decrease with increased turbidity and temperature.
Increases in both of these parameters can reflect impacts of human disturbance. Decreases in DO
can be associated with inputs of organic matter, increased temperature, a reduction in stream
flow, and increased sedimentation. DO, like temperature, is highly spatially and temporally
24
-------
variable. Thus, single point-in-time DO measurements may not reflect important diel patterns.
The higher latitude sites tended to have higher DO values for the Virgin River, but the
relationship between DO and latitude was not significant (R=0.114, P=0.724). In the Muddy
River, DO levels were slightly higher downstream (R=-0.402, P=0.195) (Figure 11). DO values
ranged from 5.1 to 12.8 mg/L with a mean of 8.3 mg/L among sampling sites (Figure 12). All
sites had DO values exceeding 5 mg/L, with two sites below the 6 mg/L standard representing
the lower limits determined suitable by Nevada state standards. The condition estimate was not
determined for DO as all the sample sites fell into the good category.
-Virgin River
-Muddy River
D)
£
c
Q>
D)
>
X
O
I
o
(A
(A
upstream
Stream Location
downstream
Figure 11. Dissolved Oxygen Values Graphed in Relation to Sampling Location in the Muddy and Virgin Rivers, n=22.
Figure 12 Cumulative Distribution Frequency of Stream Dissolved Oxygen.
25
-------
Nutrients
Nutrients are essential to life and nutrient balance in streams is important to maintain a properly
functioning ecological condition. Abnormal inputs from anthropogenic sources can result in
increased algal growth (eutrophication) which can upset the ecological balance of the stream.
Likewise, loss of nutrients from human activities can reduce stream productivity. Historic land
use practices of mining, dairy, cattle grazing and landfills within the area could affect the
balance. Data for six water nutrient parameters were collected at all sites. Water samples were
analyzed for chloride, ammonia, nitrite/nitrate, total Kjeldahl nitrogen, total phosphorous (TP),
and sulfate. Total nitrogen was calculated. Sulfate summary statistics can be found in appendix
2. Five nutrients were selected for condition analysis and are shown in Table 5.
Table 5. Nutrients in the Muddy-Virgin Area, Expressed as mg/L.
Indicator
Total Phosphorus
Total Nitrogen
Nitrate/Nitrite
Total Kjeldahl
Nitrogen
Ammonia
Chloride
Mean
0.06
0.68
0.36
0.29
0.03
173.08
Min
0.01
0.09
0.00
0.06
0.01
1.0
Max
0.43
4.02
3.11
0.88
0.09
675.00
Total Phosphorus
Phosphorus, along with nitrogen, is often a limiting factor in growth of aquatic vegetation. An
increase in phosphorus, which could be the result of nutrient input from agriculture, is reflected
in increased growth of algae. The state of Nevada water quality standard for total phosphorus
(TP) is 0.1 mg/L, except for the reach from Glendale to Lake Mead which has a water quality
standard of 0.3 mg/L. Total phosphorus in eastern and southern Nevada streams ranged from
<0.01 to 0.43 mg/L with a mean of 0.06 mg/L (Table 5). As seen in Figure 13, very low
phosphorus concentrations had an impact on macroinvertebrate taxa richness. As concentrations
increased, taxa richness increased until the water quality standard was exceeded. As phosphorus
concentrations increased above the standard, there was a net impact to aquatic organisms. The
condition estimate level was set at 0.1 mg/1 for total phosphorus. Figure 14 shows that in the
Muddy-Virgin area the ecological condition for total phosphorus is good in 95 percent of the
Basin and in poor condition in 5 percent.
26
-------
in
8
c
.E
£
V)
5
-------
condition estimate level (Figure 15) was set at 0.38 mg/1 in accordance with USEPA Ambient
Water Quality Criteria Recommendations (USEPA December 2000).
100 -
90 -
80 -
70
60 -
£ 50 -
£
40 -
30 -
20 -
10 -
0 -
I
150 =
c
1 OS 2.08 3.OS
Total Nitrogen (me/I)
1- 0
4.08
Total Nitrogen
I GOOD •POOR • NO DATA
Figure 15. Cumulative Distribution Frequency and Condition Estimate of Total Nitrogen.
Nitrite/Nitrate
Inorganic nitrogen (nitrite and nitrate) is the major form of nitrogen in lotic systems available to
plants (Welch et al., 1998). As stated by MacDonald et al. (1991), concentrations of <0.3 mg/L
would probably prevent eutrophication. Water standards for beneficial uses for nitrite is <1 mg/L
and 10 mg/L for nitrate. Nitrite/nitrate in the Muddy-Virgin area ranged from <0.01 to 3.11
mg/L. As seen in Figure 16, there was an overall decreasing trend of nitrite/nitrate downstream.
This would indicate the state of the stream riparian function, which is the interaction of the
hydrologic, geomorphic and biotic processes within the riparian zone, had an impact on the
nitrogen fixation, thus impacting benthic community structure. Yet, there was not a significant
relationship between nitrite/nitrate and species richness (Figure 17). The nitrate/nitrite level for
condition determination was set at 0.3 mg/1 Figure 18. Eighty-two percent of the stream length
was found to be in good ecological condition for nitrate and 18 percent was found to be in poor
condition.
28
-------
3.5
3.0
B, 2.5
E,
J 2.0
£
*J
z 1.5
E 1.0
0.5
0.0
upstream
Stream Location
-Virgin River
-Muddy River
-#-
downstream
Figure 16. Comparison of Nitrate/Nitrite in the Muddy and Virgin Rivers, n=22.
4R
4D -
35 -
30,
en ju
c
o 25
E
o 20 -
i •
Q. •\ci
V> ^ ;
1
10 -
E
n -
> •
> * *
••
* » 4
r**t *
i%*
•
0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50
Nitrogen (mg/L)
Figure 17. Nitrate/Nitrite Verses Species Richness for all Sampling Sites in the Study Area R=-0.048. P=0.786, n=35.
29
-------
100
90 -
80 -
70 -
60 -
50 -
40 -
30 -
20 -
10 -
0 -
- 150 =
0.002 0.502 1.002 1.502 2.002 2.502 3.002
Nitrate/Nitrite (mg/1)
_• 250
Nitrate/Nitrite
• GOOD •POOR
Figure 18. Cumulative Distribution Frequency and Condition Estimate of Nitrate/Nitrite.
Total Kjeldahl Nitrogen
Total Kjeldahl Nitrogen (TKN) is the sum of organic nitrogen, ammonium and ammonia in a
waterbody. It is measured in milligrams per liter (mg/1). High measurements of TKN indicate
possible sewage and animal manure discharge into the water. Levels of 0.3 mg/1 or more may
indicate that pollution is present. Using that level of TKN, figure 19 shows that the TKN
condition estimate for the Muddy-Virgin area is about 32 percent below that level which is
considered in good condition and that 68 percent is above that level and is considered in
ecologically poor condition.
100 -
90 -
80
70 -
60
50 ]
40 -
30 -
20 -
10 -
D
3
0.06 0.16 0.26 0.36 0.46 0.56 0.66 0.76
Total Kjeldahl Nitrogen (nig/I)
Total Kjel.lah Nitrogen
Figure 19. Cumulative Distribution Frequency and Condition Estimate of Total Kjeldahl Nitrogen.
Ammonia
Abnormal levels of nitrogenous compounds found in water generally indicate pollution. Most of
the nitrogen in functional (i.e., not impaired) water bodies originates from the decay of the
remains of plants and animals. Ammonia nitrogen is the most common form of nitrogen in a
30
-------
water bodies involving the biological breakdown of animal waste products. High pH and
warmer temperatures can increase the toxicity of a given ammonia concentration. The ammonia
level of 1.8 mg/1 was used for this condition analysis and was taken from the USEPA's National
Recommended Water Quality Criteria - Aquatic Life Criteria. Ammonia levels were shown
(Figure 20) to be in good condition throughout the Muddy-Virgin area. No condition estimate
was done as all the sample sites fell into the good category.
100 -
90 -
80 -
70 -
60 -
E
£ 50 -
£
40 -
30 -
20 -
10 -
Q
J
f
j
^^___/
/""'
^/
j
J
- 300
- 250
_
- 200 —
1
1
150 1
t
M
- 100
- 50
n
0.015 0.025 0.035 0.045 0.055 0.065 0.075 0.085
Ammonia (mg/1)
Figure 20. Cumulative Distribution Frequency of Ammonia.
Chloride
Chloride, present in all natural waters at low concentrations, is considered a good water quality
tracer because it is involved in few reactions relative to other ions (Feth, 1981). The worldwide
chloride mean concentration in rivers is 7.8 mg/L, with a range from 1 to 280,000 mg/L (Hem,
1985). Found to be an indicator of human disturbance, anthropogenic sources can be ascribed to
urban and agricultural runoff. The state of Nevada water quality standard for chloride in the
Muddy-Virgin River system is 250 mg/L with a range from <1 to 675 mg/L. While the variation
in chloride concentrations in Nevada streams appears large, care should be taken to account for
solute input from spring sources. Where several sample sites were on one river, only sites with
elevated chloride levels, relative to other sites on the same river, should be considered for further
research. Using a level of 250 mg/1, Figure 21 shows that the chloride condition estimate for the
Muddy-Virgin area is about 40 percent below that level which is considered in good condition
and that 60 percent is above that level and is considered in ecologically poor condition.
-------
100 -
90
SO
70
60 -
50 -
40 -
30
20
10 -
0 -
3
- 150 s
100 200 300 400 500 600
Chloride (mg/l)
Chloride
IGOOO BPOOR
Figure 21. Cumulative Distribution Frequency and Condition Estimate of Chloride.
B. Physical Habitat Indicators
While there are currently no water quality criteria for physical habitat variables, they are very
important for supporting designated uses and directly support the goal of the Clean Water Act.
Physical habitat is described from measures taken at two scales: watershed and individual
stream. Physical habitat characteristics define how streams process inputs and respond to
disturbance. There can be much variation in physical habitat characteristics at either scale. This
section describes watershed scale features (basin size and slope), physical stream characteristics
(substrate, habitat units, fish cover), and riparian characteristics.
Channel Form
Strahler stream order describes the location of a stream in the watershed. A first order stream has
no tributaries, representing source streams. Two first order streams come together to create a
second order stream. Two second order streams come together to create a third order stream, and
so on. If two streams of different orders combine, the united stream takes on the larger of the two
sizes (Strahler, 1957) (Figure 22). Stream orders for sampling sites are listed in Appendix 1.
32
-------
1
Figure 22. Strahler Stream Order (FISRWG, 1998).
In the Muddy-Virgin project area within the Great Basin, this type of stream classification is not
appropriate. Many of the streams are ephemeral washes having flowing water only during
summer monsoonal thunderstorms. Most dry channels do not receive snowmelt runoff in eastern
and southern Nevada. Streams with flowing water are located in the valley floor and are fed
primarily from spring sources. Another contributing factor includes mid-summer monsoons with
flash flooding. Stream organization also shows no relationship to the spatial area of the basin
(R=-0.123, P=0.617) (Figure 23).
Relationship between Percent Slope to Basin Area and
Stream Order
A n -,
3C
T n
"5" o R
^5 ZD
0) on
0. ZU
O
— -| c; _
(/) 1.3
1 O1
0 ^ '
n n
•
*.
• A .
1 + • •
* A
• •• *
• 1
• 3
A4
• 5
0 1000 2000 3000 4000 5000 6000
Basin Area (m2)
Figure 23. Relationship between Percent Slope to Basin Area and Stream Order, R—0.123, P=0.617, n=19.
33
-------
Likewise, stream order was not related to stream wetted width and thalweg depth for all stream
orders (R=-0.049) (Figure 24). The first order stream of this study was narrow, shallow and
topographically constrained. The third (R=0.756) and fourth (R=0.934) order streams exhibited a
positive correlation to thalweg depth, and wetted width. This positive correlation indicated that
most of these streams were also constrained in their channels. Fifth order streams did not have a
significant correlation (R=-0.148). For all stream orders, mean stream wetted width ranged from
0.0 to 26.6 m and averaged 6.6 m. Mean thalweg depth ranges from 4.3 to 88.6 cm with a mean
of 43.3cm.
mn
an
•s- an
u
*" 7D
£
g- fin
a
O) en _
* 30
ra
* 20
g ^u
1 n
•
M •
f .
•
**..
A • •
,.
A
•
•
*1
• 3
A4
• 5
0 5 10 15 20 25 30
Mean Wetted Width (m)
Figure 24. Relationship between Mean Thalweg Depth and Mean Wetted Width by Stream Order, R=-0.049, P=0.771,
n=37.
In eastern and southern Nevada, stream flow does not scour alternating banks resulting in a
sequence of bars, pools, and riffles. Rather, streams are nearly straight channels with
homogenous laminar flow. In direct contradiction to the predicted pool-riffle channel
morphology typical of low gradient streams (Montgomery & Buffington, 1998), most of the
channels in eastern and southern Nevada have a glide morphology (Figure 25). A total of 92.7%
of stream samples were glide, while riffles comprised only 6.7%.
34
-------
riffle
pool 6.7%
0.5%
rapid
0.1%
glide
92%
Figure 25. Percent of Stream Samples within each Channel Type.
The wadeable streams of eastern and southern Nevada do not represent a broad range of basin
areas and gradients. Most high elevation streams are dry throughout most of the year, and the
relationship of dry channels to permanent water sources is unknown. Basin streams, which have
flowing water for most of the year, do not lend themselves to conventional stream order. The
basin morphology does influence stream processes and this is important to acknowledge.
Unfortunately, how basin morphology interacts with stream processes for eastern and southern
Nevada is unknown.
Substrate
Substrate describes the grain size of particles on the stream bottom, and ranges from rocks to
mud. Stream substrate is influenced by many factors including geology, transport capacity, and
channel characteristics.
Sand and fine sediment (< 2 mm) was the most common substrate size, comprising 72.6% of all
surface stream substrates (Figure 26). Gravel was the next dominant size, comprising 16.4% of
all surface stream substrates. Cobble, boulder, hardpan, and other substrate types comprised a
limited portion of dominant substrate type (Table 6).
35
-------
boulder
cobble 1 3o/0 /
7.7%
other
"2.0%
gravel
16.4%
sand/fines
72.6%
Figure 26. Total Percent of Streambed with Dominant Substrate Class.
Table 6. Percent of Stream Substrate Sample Dominated by Major Substrate Classes.
Description
Sand/Fines
Gravel
Cobble
Boulder
Wood/Other
Hardpan
Bedrock
1st
Order
98.18
1.81
0.00
0.00
0.00
0.00
0.00
3rd
Order
69.5
19.86
6.38
1.28
1.00
1.99
0.00
4th
Order
81.27
16.2
1.59
0.63
0.32
0.00
0.00
5th
Order
70.5
14.7
11.38
1.55
1.66
0.00
0.22
Total
72.63
16.41
7.73
1.26
1.16
0.71
0.10
Classifying the data by Strahler stream order did not further elucidate the data other than to
indicate the primary source material is fines (Figure 27). The sand and fine substrate size class
dominated stream substrate from each stream order. Fourth order streams had slightly more
variety in dominant substrate type. Gravel was less than 20% of dominant substrate in all
sampled streams. The dominance of fine grained material appears to be indicative of desert
stream systems which are subject to flooding. Sparse terrestrial vegetation makes fine grained
material readily available.
36
-------
100 T-=
n sand/fines
• gravel
D cobble
n boulder
• other
3 4
Stream Order
Figure 27. Percent of Stream Samples Dominated by Different Substrate Classes in Relation to Stream Order.
Large Woody Debris
Large woody debris (LWD), as single pieces or in accumulations (i.e., logjams), alters flow and
traps sediment, thus influencing channel form and related habitat features. LWD also plays a
major role in temperature dependent stream processes such as benthic respiration or fish
movement. The quantity, type and size of LWD recruited from the riparian zone and from hill
slopes are important to stream function in channels influenced by LWD. Loss of LWD, without a
recruitment source, can result in long-term alteration of channel form, as well as, loss of habitat
complexity in the form of pools, overhead cover, flow velocity variations, and retention of
sorting spawning-sized gravel.
LWD is compiled into classes based on the length and diameter of each piece (Table 7).
Although field data was collected for the stream reaches, the data is not reported on here because
of the overall low amount of LWD. See Appendix 3 for a complete summary.
Table 7. Definition of LWD Classes Based of Length and Diameter Per 100m of Stream Sample.
Diameter (m)
0.1-0.3
>0. 3-0.6
>0.6-0.8
Length (m)
1.5-5
Very small
Small
Small
>5-15
Small
Medium
Large
>15
Medium
Large
Large
Most streams in eastern and northern Nevada do not support large fish species, for which LWD
is very important. Native fish species are adapted to warm water, higher salt and trace metal
concentrations, and higher turbidity. Little to no research on the benefits of LWD in desert,
warm, spring-fed streams is available.
37
-------
Riparian Vegetation
Riparian (stream bank) vegetation is important for several reasons as it:
• influences channel form and bank stability through root strength;
• is a source of recruitment for LWD influences channel complexity;
• provides inputs of organic matter such as leaves, and shades the stream which influences
water temperature;
• provides allochthonous energy to the system.
Expressed as a proportion of the reach, riparian cover data are collected for three vegetation
heights as expressed in Table 8.
Table 8. Riparian Vegetation Category and Associated Height.
Vegetation Cover Type
Tree or canopy layer
Understory
Ground cover
Height
>5m
0.5-5m
<0.5m
Typical vegetation comprising each class is list in Table 9. The "Tree" category is primarily
composed of vegetation not native to this area.
Studies on the effects of nonnative vegetation on desert stream processes are limited to
ephemeral streams of the desert southwest and the Colorado system. While the results of
research from these areas may be applicable to eastern and southern Nevada streams, they are not
applicable to the warm, spring-fed streams of the Muddy-Virgin project area.
Table 9. Vegetation Category and Associated Vegetation Community of Muddy-Virgin
Project Area.
Vegetation Type
Tree
Understory
Ground cover
Typical Vegetation Community
Washington/a filifera, Tamarix sp., Cottonwood,
Ash, Alder, Sa//x, Prosopis
Pluchea sp., Baccharis sp.,
Distichylus sp., Bromus sp., mint, fords, herbs,
flowering plants.
Vegetation cover from trees was relatively sparse, whereas, understory and ground cover were
more common (Figure 28). The first order stream had less vegetation cover and less variation in
type of cover compared to third to fifth order streams (Figure 29).
38
-------
an
70
i_ en
Q)
>
o
O en
c
•2 40
(0
+J
m
rn ^0
5
N? on
0"~ £\J
1 n
• Percent Cover
tree
24
under
71
ground
73
Vegetation Type
Figure 28. Percent Vegetation Cover by Vegetation Class.
• tree
D understory
• ground cover
3 4
Stream Order
Figure 29. Percent Samples with Vegetation Cover by Class in Relation to Stream Order.
Stream shading is determined from average densiometer readings for each sample site. Shading
was moderate with an average 31.7% of stream mid-channels shaded (Figure 30) and an average
56.3% of stream banks shaded. Figure 31 shows percent mid-channel and bank shade by stream
order. While it is expected that shade will decrease as one moves from headwaters downstream
39
-------
to the valley floor, this pattern was not illustrated in data collected in eastern and southern
Nevada streams.
I
27 47 67
Stream Bank Percent Shade
Figure 30. Cumulative Distribution Function of Bank Shade.
In addition to riparian vegetation presence, stream shading from riparian canopy was assessed at
each transect. Stream shading is determined from average densiometer readings for each
sampling site. Separate calculations from the bank and mid-channel were made. Shading was
low with an average of 56.3% of stream banks shaded and an average of 31.7% of stream mid-
channels shaded (Figure 32). Given the types of vegetation found in the range and basin
ecoregions which comprise the Muddy-Virgin area, the condition estimate should be used for
comparison purposes. The values of both shade condition measurements were poor 0 - 30, fair
31-70, and good, 71-100.
loo n
90
SO
70 -
60 -
I 50 -
i
40 -
30
20
10
0
150 E
20 40 60 80
Mid-channel Canopy Shade %
Mid-channel Canopv Shade
• GOOD FAIR BPOOR
Figure 31. Cumulative Distribution Function and Condition Estimate of Mid-channel Canopy Shade.
40
-------
80
70
60
a) 50
O)
3
40
30
20
10
0
h=
D % bank shade
• % mid channel shade
3 4
Stream Order
Figure 32. Cumulative Distribution Function of Bank Shade.
Fish Cover
Many structural components of streams are used by fish as concealment from predators and as
hydraulic refugia (e.g., bank undercuts, LWD, boulders). Although this metric is defined by fish
use, fish cover is indicative of the overall complexity of the channel, which is likely to be
beneficial to other organisms.
In the Muddy-Virgin project area, fish cover was analyzed according to its level of presence as
described in Table 10. Overall fish cover was sparse. The most common form of averaged fish
cover was overhanging vegetation, with a score of 1.26, followed by aquatic macrophytes (algae
mats provide cover), with a score of 0.78 (Figure 33).
Level of Presence
Absent
Sparse
Moderate
Heavy
Very Heavy
Description
None
<10%
10-40%
40-75%
>75%
Score
0
1
2
3
4
41
-------
Overhang Vegetation
Brush
> Aquatic Macrophytes
o
.E
.i2 Algae
•5
g. Undercut
>
Boulders
Woody Debris
Artificial Structures
I
I
|
I
I
D
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40
Score
Figure 33. Level of Fish Cover.
Riparian Disturbance Indicators
Removal or alteration of riparian vegetation reduces habitat quality and can result in negative
impacts on stream biota. Riparian disturbance data were collected by examining the channel,
bank and riparian area on both sides of the stream at each of transect, and visually estimating the
presence and proximity of disturbance (Hayslip et al., 1994). Eleven different categories of
disturbance were evaluated. Each disturbance category was assigned a value based on presence
and proximity to the stream (Table 11).
Table 11. Riparian Disturbance Proximity to Stream and Associated Score.
Criteria
In channel or on bank
Within 10m of stream
Beyond 10m from stream
Not present
Score
1.67
1.0
0.67
0
Not all types of disturbance were found. Row crops, logging, and mining were not observed in
the streams of the Muddy-Virgin area. Shown in Figure 34, the most common form of riparian
disturbance was pastures (31%), followed by roads (28%) and landfills (22%). In general, the
level of human influence was low for all forms of riparian disturbances, as the averaged scores
for all indicators were <0.67 (see Figure 35).
42
-------
Building
5%
Pasture
31%
Pavement
4%
Road
28%
Landfill
22%
Figure 34. Percentage of Riparian Zone Human Influence, by Type, on Stream Reaches.
Pasture
Road
Landfill
Wall
Building
Pavement
Park
Pipe
I I
I
i
I
a
a
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45
Proximity Weighted Index
Figure 35. Mean Riparian Zone Human Influence by Type.
43
-------
C. Biological Indicators
Benthic Invertebrates
Benthic macroinvertebrate assemblages indicate the overall biological integrity of the stream.
Monitoring these assemblages is useful in assessing the current status of the water body and
long-term changes that have occurred (Plafkin et al., 1989). Temporal and spatially infrequent
surface flows in desert ecosystems can create microhabitats which are chemically and
biologically distinct. Fragmentation will alter the function of these microhabitats resulting in
differing taxa composition of the benthic aquatic community. Ecological response to hydrologic
extremes will exhibit a response alternating between gradual change to a swift transition when a
habitat disappears or is fragmented (Boulton, 2003). Benthic macroinvertebrate data were
available from all sample reaches and collected at each transect using modified Serber samplers.
These samples were combined into three composite samples for each reach. Since riffles were
uncommon in the project area, a subset of each composite sample was identified. The following
three metrics were used in the analysis: taxa richness, EPT taxa richness, intolerant taxa richness
(Table 12).
Table 12. Description of Benthic Macroinvertebrate Indicator Metrics
(Resh and Jackson, 1993 and Resh, 1995).
Metric
Taxa Richness
EPT Taxa
Richness
Percent
Intolerant Taxa
Description
The total number of different taxa describes the
overall variety of the macro-invertebrate
assemblage. Useful measure of diversity of
variety of the assemblage.
Number of taxa in the orders Ephemeroptera
(mayflies), Plecoptera (stoneflies), and
Trichoptera (caddis flies).
Percent taxa of those organisms considered to be
sensitive to disturbances.
Rationale
Decreases with low water quality
associated with increasing human
influence. Sensitive to most
human disturbance.
In general, these taxa are
sensitive to human disturbance.
Taxa intolerant to pollution based
on classification from Wisseman
(1996).
The metric 'Taxa Richness' gives an indication of variability of macroinvertebrate communities
throughout eastern and southern Nevada. Total number of taxa ranged from 3 to 39 species
(Figure 36). Variability of taxa richness may be a result of difference in spatial location, flow
regimes, habitat, chemistry and/or temperature where the invertebrate fauna becomes dominated
by a few taxa. The condition analysis estimate of taxa richness measurement over the Muddy-
Virgin project area shows that there are many (72.7%) poor condition locations. As determined
by the authors using the existing standards and best judgement the values used for the condition
estimate were: 1-15 poor, 16-25 fair, and 26-40 good. Summary statistics are presented in
Appendix 4.
44
-------
100
90
80
70
60
50
40
30
20
10
0
a
I
10 15 20 25 30 35 40
Taxa Richness
Taxa Richness
• GOOD FAIR BPOOR
Figure 36. Cumulative Distribution Function and Condition Estimate of Total Invertebrate Taxa Richness.
EPT taxa ranged from 0 to 16 species (Figure 37). EPT taxa richness is the number of mayflies,
stoneflies and caddis flies found and in general these taxa are sensitive to human disturbance.
The condition analysis estimate of taxa richness measurement over the Muddy-Virgin area shows
that there are very few (7%) good condition locations. Condition estimate values were set at: 0-7
poor, 8-17 fair and 18-25 good. Summary statistics are presented in Appendix 4.
100 n
9D
80 -
7O
60
50
40 -
30 -
20
10 -
0
2 4 6 8 10 12 14 16
Number of EPT Taxa
Figure 37. Cumulative Distribution Function and Condition Estimate of EPT Taxa Richness.
Intolerant taxa are used as an indicator of disturbance. A high number of intolerant taxa
indicates a low amount of disturbance. The condition estimate values were; 1-20 poor, 21-40
fair, and 41 to 60 good. Given this set of estimate values, 91 percent of the Basin is in a poor
ecological condition as determined by intolerant taxa (Figure 38).
45
-------
100
90
SO -
70 -
60 -
50
40
30 -
20
10
o
150 =
20 30
Intolerant Taxa %
Intolerant Taxa
• GOOD FAIR BPOOR
Figure 38. Cumulative Distribution Function and Condition Estimate of Intolerant Taxa.
A total of 17 metrics were analyzed and are summarized in Table 13 (Appendix 4). Biotic
indices such as taxa richness, because of its high variability, may not be sufficient to determine
functional changes in a warm water, fine substrate stream system. Functional feeding groups
provide an indication on the available feeding strategies in the benthic assemblage. Functional
feeding groups across divergent stream systems can be successful in characterizing variability in
resource utilization (Karr et al., 1986; Karr & Chu, 1999; Resh, 1995). Without relatively stable
food dynamics, an imbalance in functional feeding groups will result.
Predators comprised 13.9% of the population. Scrapers, piercers, and shredders, are the more
sensitive organisms, and are considered to represent a healthy stream system. The mean shredder
(0.7%) and grazer (4.4%) densities were low. Cummins and Klug (1979) indicate collectors and
filterers (generalists) have a broader range of acceptable food materials than specialists (scrapers,
shedders, etc.). This makes generalist (collectors and filterers) more tolerant in stressed
environments.
46
-------
Table 13. Summary Statistics for Macroinvertebrate Metrics, Muddy-Virgin Project 2000.
Metric
Total Taxa
% EPT
EPT Taxa
% Ephemeroptera
Ephemoptera Taxa
% Plecoptera
Plecoptera Taxa
% Trichoptera
Trichoptera Taxa
Shannon H
% Collector
% Filterer
% Predator
% Grazers
% Shredders
% Burrower
% Climber
% Clinger
% Sprawler
% Swimmer
Community Tolerance (HBI)
% Intolerance (<4)
% Tolerance (>7)
Mean
16.83
41.79
5.51
26.72
2.86
0.02
0.06
15.06
2.60
1.73
58.79
22.02
13.90
4.42
0.66
19.32
0.50
1.75
7.29
13.98
5.36
4.77
15.31
Min
3.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.53
7.63
0.00
0.78
0.00
0.00
0.66
0.00
0.00
0.00
0.00
4.21
0.00
0.00
Max
39.00
81.19
16.00
75.89
7.00
0.68
2.00
70.42
9.00
2.73
95.32
71.95
87.94
39.42
12.45
68.35
3.67
19.92
28.09
53.00
8.18
46.06
85.41
Table 14 shows that collectors and filterers were dominant through all stream types. Grazers and
predators were evenly distributed throughout the different stream types within the Muddy-Virgin
River system. Shedders were highly variable throughout the system and were more abundant in
shaded small streams, indicating a more functional riparian system. Shredder population
decreased as streams became wider and riparian systems moved to a more non-functional status.
As seen Table 15, predators were most dominant in shaded small streams and open small
streams. Collectors-filterers increased in dominance in open medium streams, and open large
streams.
47
-------
Table 14. Examples of Expected Functional Feeding Group Rations from Resh (1995).
Metric
% Collectors- Filterers
%Grazers
% Predators
% Shredders
Shaded Small
Streams
>50%
<25%
-10%
>25%
Open Small
Streams
>40%
>25%
-10%
>10%
Open Medium
Streams
>50%
>25%
-10%
<5%
Table 15. Mean Percent of Functional Feeding Groups from the Muddy-Virgin Project.
Metric
% Collectors- Filterers
% Grazers
% Predators
% Shredders
Shaded Small
Streams
72.25
7.45
18.35
1.92
Open Small
Streams
77.69
3.86
17.59
0.55
Open Medium
Streams
91.08
3.34
5.38
0.03
The Muddy-Virgin River study area was dominated by the collector-filterers (72.3%).
Dominance of a particular group (i.e., collector-filterers) is an indication the Muddy-Virgin
system was reflecting stressed conditions.
Macroinvertebrate Assemblages
Benthic macroinvertebrates (BMI) can be used to understand how human influence affects the
ecological condition of streams and rivers. One method to understand the function of the BMI
assemblages is to compare the sites with low human disturbance (least-disturbed sites) with the
condition of the entire area. Using these reference sites as a benchmark, the BMI is evaluated by
comparing sites of unknown condition against this standard. The Multi-Metric Index (MMI) is an
approach used in the United States to analyze BMI assemblage data. This method evaluates
biological variables using a number of criteria, and a subset of the five best performing metrics
are then combined into a single, unitless index, often called an Index of Biotic Integrity (IBI).
These final variables, or metrics, should be sensitive to stressors, represent diverse aspects of the
biota and be able to discriminate between reference and stressed conditions. Multiple variables
are used to provide a solid, predictable analysis of the biological condition.
BMI assemblage data was attained using the Ecological Data Application System (EDAS). This
program, created by Tetra Tech, Inc., manages, integrates and analyzes data, such as benthic
macroinvertebrate information, through the use of Microsoft® Access. The Master Taxa Table
contains information about each taxon, including feeding habits, tolerance, habit and their
individual Taxonomic Serial Number (TSN). Taxa information not found in the Master Taxa
Table was input using Barbour et al. (1999) and the Integrated Taxonomic Information System
as references. For the Muddy-Virgin River Project Area, sixty-eight metrics were calculated
48
-------
from the data collected at thirty-five sites. Each metric was assigned one of five classes
demonstrating a separate element of biotic integrity:
• Richness- the number of different kinds of taxa
• Composition- the relative abundance of different kinds of taxa
• Functional Feeding Groups- primary method by which the BMI feed
• Habit- predominant BMI behavior
• Tolerance- a general tolerance to stressors, scores range from zero to 10, with higher
numbers representative of organisms more tolerant to organic waste, signifying lower water
quality
Reference Conditions
Setting expectations for assessing ecological condition require a reference, or benchmark, for
comparison. Since pristine conditions are rare, this report uses the concept of the "Least-
Disturbed Condition" as reference. This type of reference condition chooses sites through
numerous chemical and physical criteria verified through a GIS screening process achieving the
best conditions, or least-disturbed by human activities. Since reference conditions vary among
geographic regions (Omernik, 1987) the Muddy-Virgin Area utilized the criteria set for the South
Xeric basin, which encompasses the Central Basin and Range (ecoregion 13) and the Mojave
Basin and Range (ecoregion 14) (Appendix 5). For the Muddy-Virgin Area, five least-disturbed
sites (8, 10, 95, 128, 258) and five most-disturbed sites (232, 289, 669, 720, 1009) were chosen
(Figure 1 and Appendix 1).
Index for Biotic Integrity
To create the IB I, a number of steps were taken to choose one metric from each class with the
best behavior in terms of the tests described below. Any metric that failed a test was not
considered for further evaluation and not subjected to subsequent tests.
• Range: If the values of a metric are similar with little range, it is doubtful that the metric will
be able to differentiate between most-disturbed and least-disturbed sites. Metrics were
eliminated if more than 75% of the values the same.
• Richness metrics with a range less than four were not included in the next test (Appendix 6).
• Responsiveness: Metrics were examined in response to key stressors by evaluating scatter
plots of each metric versus stressor variables. F-tests, a statistically precise method to
determine the ability of metrics to detect any change, were performed to test the ability of
metrics to distinguish between least-disturbed and most-disturbed sites (Appendix 7).
• Redundancy: Redundant metrics do not provide additional information to the IBI. Thus, only
metrics not containing redundant information were included. A correlation matrix was used
to include only metrics with an r2 value less than 0.5. Metrics with the highest F-test values
were considered for inclusion first, but replaced with the next non-redundant metric of the
same class as needed (Appendix 8).
49
-------
Once the representative from each metric class has been determined, each needs to be scored
using a 0 to 10 scale. Scoring is needed since metrics respond differently. With increased
perturbation, total taxa decreases while percent tolerant organisms increase. For positive metrics
(those whose values are highest in least-disturbed sites), ceiling and floor values were set at the
5th and 95th percentile (Table 16). Values less than the 5th percentile were given a score of 0,
while those with values greater than the 95th percentile were given a score of 10. Values in
between were score linearly. Negative metrics were scored similarly with the floor at the 95th
percentile and the ceiling at the 5th percentile.
Table 16. Final Metrics and Ceiling/Floor Values
DipPct
PredPct
SwmmrTax
TotalTax
Hyd2TriPct
Ceiling
6.9
71.0
3
34
0
Floor
66.3
1.0
0
7
100
Metric Descriptions can be found in Appendix 6
Scores were summed for each site for a total score of 50. Scores were multiplied by 2.0 for a
maximum IBI score of 100 (Appendix 9). In the Muddy-Virgin River project area, the total
scores for macroinvertebrate IBI ranged from 4 to 84 (Figure 39). The condition estimate values
used for the IBI measurement are as follows: 100-70 good, 69-50 fair, and 40 -0 poor. See
Figure 40 for location of relative IBI scores.
100
90
SO
70
60
50
40
30
20
10
0
a
I
14 24 34 44 54 64 74 84
IBI
• GOOD FAIR 1POOR • NO DATA
Figure 39. Cumulative Distribution Function and Condition Estimate of Macroinvertebrate IBL
50
-------
[SI
O 4-24
O 25-40
• 41-52
• 53-68
• 69-84
Land Cover
^B Open Water
B Urban
Barren Rock/Sand/Clay
Deciduous Forest
Evergreen Forest
Mixed Forest
Shrub/Scrub
Grassland/Herbaceous
Pasture/Hay
Cultivated Crops
Woody Wetlands
Emergent Herbaceous Wetlands
No Data
Figure 40. Relative IBI Scores for Muddy-Virgin River Project Area Sampling Sites.
Periphyton
Periphyton consists of algae, fungi, bacteria, protozoa, and detritus found on or within moist
substrate in a stream channel. Periphyton can be used as indicators of environmental stress
because they are highly susceptible to disturbances. The main factor for accumulation of
periphyton is the level of resources, primarily nutrients and temperature, which influences
metabolism and growth. There has also been close correlations found between quantities of
periphyton and the type of substrate and flow of a stream reach. Water movement restores
necessary materials and removes metabolic byproducts. This action may select for and against
51
-------
certain organisms, correlating to low periphyton development. It has also been established that
concentrations of metals may have effects on certain species (Weitzel, 1979).
Periphyton samples were collected at the nine cross-sections of each sample reach at erosional
and deposit!onal habitats. From those samples, four types of laboratory samples were prepared:
an ID/enumeration sample, chlorophyll and acid/alkaline phosphatase activity (APA) samples,
and a biomass sample. Biomass is a measurement of the organic matter of a sample, measured by
weighing the difference in mass after drying and incinerating the matter. The remains are ash
free dry mass (AFDM). The sample is then weighed against its dry mass to determine the
biomass. This is done to discount against any silt or other inorganic matter (see Appendix 10 for
a complete list of periphyton samples). The cumulative distribution function and condition
estimate are not reported for periphyton in the report.
Ratios between chlorophyll and AFDM have been used to indicate community structure. The
autotrophic index (AI), which is the ratio between biomass and chlorophyll, has been used to
indicate organically polluted conditions. In theory, higher numbers reflect more polluted waters.
In the Muddy-Virgin River project area, site 8 had the highest AI value of 22740. Site 215 had
the lowest AI value of 112. The CDF for the Muddy-Virgin River project area is shown in Figure
41.
- 200 *
150 =
10112 15112
Autotrophic Index
Figure 41. Cumulative Distribution Function of the Autotrophic Index.
52
-------
Figure 42 shows the Muddy-Virgin River project area CDF and condition estimate for
chlorophyll-a. The condition estimate level for chlorophyll-a was determined as, good was less
than 10 jig/cm2 and poor was greater than 10 jig/cm2. Chlorophylla-a (chl-a) was selected as an
indicator of water quality because it is an indicator of phytoplankton biomass, with
concentrations reflecting the integrated effect of many of the water quality factors that may be
altered by restoration activities. Studies have examined chlorophyll-a (chl-a) to determine that
levels above 10 jig/cm2 (up to 15 jig/cm2) can indicate areas with higher levels (>20%) of
filamentous algae, or pond scum, coverage (Barbour, 1999). In the project area, sites 289 and
669 exceeded the 10 |ig/cm2chl-a level (Figure 43, Table 17).
100 -
90 -
BO
70
60
SO
40
30
20
10 -
G
6 S 10 12 14
Chlorophyll (re/cm2)
Chlorophyll-a
I GOOD BPOOR • NO DATA
Figure 42. Cumulative Distribution Function and Condition Estimate of Chlorophyll-a.
53
-------
* Sampling Points
/\/ Major Rivers
Stream Reach File
I | Boundary
Figure 43. Location of Muddy-Virgin R-EMAP Sample Sites with High Chl-a Levels and Highest and Lowest AI Levels.
54
-------
Table 17. Sampling Sites with High chl-a Levels and Highest and Lowest Al Levels.
Site ID
MV8
MV215
MV289
MV669
Chl-a
-
-
15.08|jg/cm2
13.68|jg/cm2
Al
22740
112
-
-
Figure 44 is the project-wide CDF of the Biomass parameter in mg/cm2. Figure 45 shows a map
of biomass values within the Muddy-Virgin project area. Within the Muddy River, the trend
indicated that biomass increased downstream. The inverse occurred within the Virgin River
(Figure 46). This may be due to differences in agricultural land use intensities between the two
river basins.
100 -
90 -
80
70 -
60 -
E
£ 50 -
£
40 -
30 -
20 -
10 -
0 -
f
1
,
1
> 5 10 15 20 2
- 300
- 250
- 200 *
1
- 150 E
1
- 100
- 50
- 0
5
Biomass mg/cm1
Figure 44. Cumulative Distribution Function of Biomass.
55
-------
Biomass (mg/cm2)
• 0-0.90
* 0.90-2.79
* 2.79-5.31
5.31-8.67
• 8.67-24.35
Reach File
| | Basin Boundary
Figure 45. Map of Biomass (AFDM/cm2) in the Muddy-Virgin Project Area.
56
-------
6000
5000
M
E
I 4000
Q
< 3000
1 2000
o
m
1000
0
• Virgin River
-Muddy River
7
upstream
downstream
Stream Location
Figure 46. Biomass Values Graphed in Relation to Sampling Locations in the Muddy and Virgin Rivers, n=18.
D. Sediment Respiration
Sediment respiration measures functionality of ecosystems and can be used to indicate ecosystem
stress. To assess benthic microbial community activity, stream water containing a given amount
of sediment were measured for changes in dissolved oxygen (DO) concentration. Using EMAP
protocol, along each stream reach, the top 2 cm of soft surface sediment were collected from
deposit!onal areas of the nine cross-section transects. Any visible organisms were removed. All
nine samples were combined to prepare one composite sample for each individual stream reach.
Initial temperature and DO measurements were taken and recorded. The sample was then
incubated for two hours in a small cooler filled with stream water, at which time the final DO
concentration was determined. The sediment was frozen until it can be analyzed to determine the
ash free dry mass (AFDM).
The respiration rate is the change in DO concentration per hour adjusted for AFDM. The end
result is a measure of sediment respiration for AFDM (See Appendix 11 for a summary list of
sediment respiration). Respiration, which is the oxidation of organic matter to CO2, provides
heterotrophs with energy for growth and is a step in the mineralization of organic matter.
Scientists have been studying the relationships between stream metabolism and other ecosystem
processes as a means to measure ecosystem health. Nutrient availability can limit algal growth.
Flow or stream discharge determines the amount of time available for settling. Nutrient
availability and other physical habitat parameters, such as riparian vegetation, substrate and
amount of pools, may all be important explanatory factors in evaluating and explaining
57
-------
respiration. Models have been developed to compare different types of stream systems, but
application is limited due to several factors such as extent of floodplains and flow variability.
Respiration values ranged from 1.53 (site 1310) to 36.51 (site 19) mg/g/h. Increased algal growth
can be stimulated by elevated anthropogenic input of nutrients. The sedimentation of algal
material has been found to increase benthic oxygen demand for benthic respiration production. In
this stage, high respiration values would be apparent. Oxygen-depleted bottom water, thus low
respiration values, is often the end result. (Hansen & Blackburn, 1992). Figure 47 shows the
cumulative distribution function of sediment respiration for the Virgin-Muddy project area.
Levels ranging for 1.5 mg/g/h to 21.5 mg/g/h are likely to be encountered over 90% of the
stream reach. The condition estimate was not reported as estimates of condition for this measure
in dry desert stream could not be found in the literature.
100 -
90 -
80
70 -
60 -
50 -
40 -
30 -
20 -
10 -
0
- 150 E
1.5 6.5 11.5 16.5 21.5 26.5 31.5 36.5
Sediment Respiration (mg/g/h)
Figure 47. Cumulative Distribution Function of Sediment Respiration.
One factor that may affect levels of community respiration is the location of agricultural land use
along a river (Figure 48). In the Muddy River, respiration increased downstream. In the Virgin
River, values varied, but had an overall downward trend downstream (Figure 49). It is
interesting to note that higher sediment respirations rates are located along the Virgin River as it
exits the Zion National Park in southern Utah (Figure 48) and flows by high density agricultural
land use areas.
58
-------
Sediment Metabolism
• 1.53-3.96
• 3.96-6.31
• 6.31-9.17
9.17- 18.36
• 18.36-36.51
Reach File
| | Basin Boundary
'values mg/g/h
Figure 48. Map of Sediment Metabolism in the Muddy-Virgin Project Area.
59
-------
-Virgin River
-Muddy River
o>
(N
o
o>
E
2
'5.
(A
upstream
downstream
Stream Location
Figure 49. Sediment Metabolism Values Graphed in Relation to Sampling Location in the Muddy and Virgin Rivers,
n=21.
E. Metals
In 1998, the mining industry was required by the USEPA to list all toxics released that exceeded
the Toxic Release Inventory reporting levels. Consequently, it was recognized that mining
industries were one of the greatest producers of toxic pollutants in the country. Of the 57
facilities in USEPA Region 9 reporting toxic releases, the majority of them (63%) were in the
State of Nevada. A number of sites exceeded criteria for aquatic life. Comparison of trace metal
levels in the water and sediment to established USEPA criteria (Appendix 15) reveal arsenic,
mercury, manganese and nickel were at levels of concern at a number of sites. A total of 37 sites
were sampled at least once for water and sediment.
Water
In the Muddy-Virgin project area, a total of 37 samples were taken for analysis of water quality
pollutants. The USEPA National Ambient Water Quality Criteria (GOLD BOOK) (Office of
Water, 1986) was used in this report to determine whether the concentration of a pollutant
exceeded standards. Specifically, the three pollutant standards used in the report are the Federal
drinking water standard, the Criteria Continuous Concentration (CCC), and the Critical
Maximum Concentration (CMC). (Table 18). The CCC is designed as a benchmark to determine
if a particular body of water is safe for aquatic life over a chronic period of exposure (based on a
four day average concentration chronic limit). The CMC is designed to set a maximum allowable
concentration of a contaminant for aquatic life (one hour average acute limit). Standards have not
been set for all contaminants. Available USEPA's National Recommended Water Quality
Criteria - Aquatic Life Criteria were used for both acute and chronic effects (USEPA, Office of
water, 2014). See Appendix 11 for a complete list of data for each sampling point.
60
-------
Table 18. National Recommended Water Quality Criteria for Toxic Pollutants.
Chemical Name
Antimony
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Selenium
Silver
Zinc
CMC (M9/L)
-
HD
HD
HD
-
HD
-
-
HD
-
HD
HD
CCC (M9/L)
30
HD
HD
HD
-
HD
-
0.012
HD
5
HD
HD
Drinking Water
Standard (M9/L)
6
5
100
-
300 (2nd)
15
50 (2nd)
2
-
50
100 (2nd)
5000 (2nd)
(A secondary (2nd) Drinking Water Standard is not Mandatory. It is for Aesthetics or Voluntary Basis.) *HD= Hardness Dependent
Sediment
Using these benchmarks, the data from the Muddy-Virgin River project area were analyzed and
compared to the established benchmarks. See Appendix 13 for a complete list of data for each
sampling point. The ten revisit sites were included, but not averaged. Aluminum and chromium
concentrations in sediment did not exceed any benchmark standard. CDFs, condition estimates
and discussion are given in the following section (Results for Metals in Water and Sediment).
Metal concentrations in water may not adequately reflect all toxic exposure potential, as metal
concentrations may be higher in sediment than in water. Benthic macroinvertebrates and some
fish may be in close contact with or ingest sediments. The metals are taken into an organism
upon ingestion. For these reasons, metals concentrations in sediment are of concern in the
streams of the Muddy-Virgin River project area. Sediment was collected at least once at 37
sampling points.
Using numeric criteria to define sediment metals toxicity can be difficult. Toxic response may be
an inverse function of organic content because sorption of metals into organic substances may
increase bioavailability of the metal to many organisms. There is also variability in toxic
response between taxa, with some organisms exhibiting toxic response at much lower
concentrations than others. For these reasons, different benchmarks were used, adapted from
Jones et al. (1997). Toxicological benchmarks are used in assessing the contaminant levels of
organic or inorganic substances in the sediment. Using a number of benchmarks can give
stronger support for conclusions. In this report, three benchmarks were used: the Threshold
61
-------
Effects Concentration (TEC), the Probable Effect Concentration (PEC) and the High No Effect
Concentration (NEC).
Sediment effect concentrations (SEC) are laboratory data calculations of the toxicity of sediment
samples. The amphipod Hyalella azteca and midge Chironomus riparius are commonly used as
test organisms in observing their reduction in survival or growth. The following methodologies
were used to calculate the SECs: National Oceanic Atmospheric Administration (NOAA),
apparent effects threshold (AET)(Buchman, M.F., 1999) and Florida Department of
Environmental Protection (FDEP)(MacDonald, D.D. et al., 2003).
NOAA collects and analyzes marine and estuarine sediment samples to create effect based
criteria. Concentrations connected with biological effects are then ranked. Above a specified
chemical concentration (Table 19), statistically significant biological effects always occur. This
AET concentration is also known as the NEC. The FDEP approach calculates threshold and
probable effect levels using the data set by Long et al. (1995). Each SEC was then assessed to
establish whether they were able to correctly identify samples as toxic or nontoxic. A subset of
the SECs for each chemical was then selected based on these results. Table 19 displays a
summary list of benchmarks, which were selected according to a set of requirements, their
reliability and conservatism. There is no TEC benchmark for aluminum. If no benchmark or
standard could be found, local, State or Canadian criteria were applied.
Table 19. Summary of Selected Screening Level Concentration- Based Sediment Quality
Benchmarks for Freshwater Sediments.
Chemical Name
Aluminum
Arsenic
Cadmium
Chromium
Copper
Manganese
Lead
Nickel
Zinc
TEC mg/kg
-
12.1
0.592
56
28
1673
34.2
39.6
159
PEC mg/kg
58030
57
11.7
159
111
1081
396
38.5
1532
NEC mg/kg
73160
92.9
41.1
312
54.8
819
68.7
37.9
541
Results for Metals in Water and Sediment
Hardness:
Hardness values, which can also be expressed as calcium carbonate concentration, were
determined using the calculation method ([Ca, mg/L]*2.496 + [Mg, mg/L]* 4.118), as described
in Standard Methods for Examination of Water and Wastewater (APHA, 1998). This method is
the most accurate and is applicable to all waters. Certain metals (e.g. copper, zinc) require that
62
-------
hardness be taken into consideration when determining freshwater aquatic life protection criteria.
Depending of the hardness value, these metals can be toxic to aquatic organisms. In general, for
CCC standards, which are hardness dependent (HD), toxicity is proportional to hardness; in other
words, as hardness decreases, the concentration of metal required to cause toxic effects in the
aquatic community increases (Table 20). A basin-wide condition estimate was not determined
for hardness because only one year was measured.
Table 20. Formulas to Calculate Specific CMC and CCC Values Based on Hardness.
From: USEPA Office of Water, Office of Science and Technology (4304T) 2006 'National
Recommended Water Quality Criteria'.
Chemical
Cadmium
Copper
Lead
Nickel
Silver
Zinc
ma
1.0166
0.9422
1.273
0.8460
1.72
0.8473
ba
-3.924
-1.700
-1.460
2.255
-6.59
0.884
mc
0.7409
0.8545
1.273
0.8460
-
0.8473
bc
-4.719
-1.702
-4.705
0.0584
-
0.884
CMC
1.136672-[(ln
hardness)(0.041838)]
0.96
1.46203-[(ln
hardness)(0.145712)]
0.998
0.85
0.978
CCC
1.101672-[(ln
hardness)(0.041838)]
0.96
1.46203-[(ln
hardness)(0.145712)]
0.997
-
0.986
Hardness-dependant metal's criteria may be calculated from the following:
CMC (dissolved) = exp{mJSn(hardness)]+bs}(CF)
CCC (dissolved) = exp{mc[ln(hardness)]+bJ(CF)
Aluminum
Aluminum is an abundant element in the earth's crust. It is well tolerated by plants and animals.
Aluminum levels in water and sediment can be used to determine stream disturbance due to
mining. The USEPA's National Recommended Water Quality Criteria - Aquatic Life Criteria
chronic level for aluminum in fresh water is 87 |ig/l. Aluminum levels in water ranged from a
minimum of 200 |ig/l to a maximum of 500 |ig/l with a mean of 208 |ig/l. The cumulative
distribution frequency and condition estimate for aluminum in water is not given in this report.
The cumulative distribution frequency for aluminum in sediment is given in Figure 50.
The criterion for aluminum in fresh water sediment was not found so the condition estimate was
not calculated.
63
-------
100
90 -
BO -
70 -
60
50 -
40 -
30 -
20 -
10
0 --
1200
150 =
E
X
6200 11200 16200
Aluminum in Sediment (nig/Kg)
Figure 50. Cumulative Distribution Frequency and Condition Estimate of Aluminum in Sediment.
Antimony:
The analytical quantification limit for 33 of the sampling sites was 5 |ig/L. The quantification
limit is the lowest limit at which values can be determined. Sites 119, 232, 289 and 310 had an
analysis limit of 10 |ig/L. With a drinking water standard of 6 |ig/L, it was unable to be
determined whether the four sites with a higher quantification limit were over the standard. All
sites were below the CCC standard of 30 |ig/L. There is no CMC standard.
Arsenic:
Arsenic occurs in many minerals usually in conjunction with sulfur and metals. It is notoriously
poisonous to life. Arsenic contamination of groundwater affects millions of people across the
world including the western United States. It enters drinking water supplies from natural
deposits or from agricultural and industrial practices. Arsenic in surface waters may be
associated with mining, especially gold mining. The USEPA's National Recommended Water
Quality Criteria - Aquatic Life Criteria chronic level in freshwater for arsenic is 340 |ig/l for
acute effects and 150 jig/1 for chronic effects. The drinking water standard is 10 jig/1.
Freshwater sediment standards or clean-up criteria vary. Washington State Sediment Quality
Criteria for arsenic is 57 mg/kg and Quebec, Canada has established a threshold effect level of
5.9 mg/kg and a probable effect level of 17 mg/kg. The condition level for this analysis is below
10 jig/1 in water as good and below as poor. The condition estimate of arsenic in sediment is
below 10 mg/Kg as good, between 10 and 15 as fair and above 15 as poor. The results are
shown in Figure 51. 90 % of the stream length for arsenic in water is in poor condition and 69 %
of the stream length for arsenic in sediment is in good condition, 27% fair condition and 4% in
poor condition.
64
-------
E
200 *
10 20 30 40 50 60 70
Arsenic in Water (ug/l)
Arsenic in Water
• GOOD 1POOR
10O
90
80
70 -
60
! 50 -
I
40 -
30
20 -
10
0
150 =
13 IB 23 28 33
Arsenic in Sediment (mg/Kg)
Arsenic in Sediment (mg/Kg)
• Good Fair BFoor
Figure 51. Cumulative Distribution Frequency and Condition Estimate of Arsenic in Stream Water and Sediment.
Cadmium:
National ambient water quality criteria for cadmium is dependent on water hardness. The
quantification limit for 33 sites was 5 |ig/L. The remaining four sites had a limit of 10 |ig/L. Due
to high limits, it was not possible to report whether cadmium levels exceeded CCC standards,
which had an average of 0.8 |ig/L. Similarly, 12 sites had CMC standards that were below the
quantification limits. CMC levels ranged from 2.4 to 25.5 |ig/L. The drinking water standard for
cadmium is 5 |ig/L.
Chromium:
National ambient standards for chromium are also dependent on calcium hardness. All chromium
samples were at the quantification limit of 10 |ig/L. No samples exceeded the drinking water
standards of 100 |ig/L.
65
-------
Copper:
Calculating standards based on hardness, no samples exceeded CCC or CMC values for copper
in the Muddy-Virgin Project area. With samples ranging from quantification limits of 3 to 20
|ig/L, no samples exceeded individual CCC (10.6-111.4 |ig/L) or CMC (16.2-216.5 |ig/L)
values. There is no drinking water standard for copper. The condition estimate was calculated in
freshwater sediment as a possible indicator of mining waste contamination. The condition
estimate level was set at 31.6 mg/kg. Figure 52 shows the results of the analysis.
7 12
Copper in Sediment (rug/Kg)
Figure 52. Cumulative Distribution Frequency of Copper in Stream Sediment.
Iron:
Currently, the USEPA's National Recommended Water Quality Criteria - Aquatic Life Criteria
lists iron as a non priority pollutant. With a secondary drinking water standard of 300 |ig/L,
only one site (170) exceeded the standard at 400 |ig/L. No level was set for the freshwater
sediment but a cumulative distribution frequency was calculated for future reference. It may be
possible to associate high levels of iron with mining practices. The results of the analysis for
iron are shown in Figure 53.
66
-------
loo n
90
80 -
70 -
60
: so -
i
40 -
30
20 -
10
o --
Q
I
2000 4000 6000 8000 10000 12000 14000 16000
Iron in Sediment (nig/Kg)
Figure 53. Cumulative Distribution Frequency of Iron in Stream Sediment.
Lead:
National ambient CCC and CMC standards for lead are dependent on hardness. Quantification
limits for lead were 5 |ig/L for 33 sites and 10 |ig/L for the remaining four. All samples were
well below the CMC standard. Only one site (258) had a hardness calculated CCC value
(3.1 |ig/L) below the quantification limit. It could not be determined if that site exceeded the
standard. A stream sediment cumulative distribution frequency was calculated for future
reference. Results are shown in Figure 54.
6.6 11.6 16.6 21.6
Lead in Sediment (nig/Kg)
Figure 54. Cumulative Distribution Frequency and Condition Estimate of Lead in Stream Water and Sediment.
67
-------
Manganese:
There is no aquatic life CCC or CMC standards for manganese. Seven of the thirty-seven
samples exceeded the manganese secondary drinking water standard (50 |ig/L): 110 (68 |ig/L),
669 (120 |ig/L), 1100 (130 |ig/L), 1009 (160 |ig/L), 1190 (250 |ig/L), 285 (280 |ig/L), and 660
(290 |ig/L). Site 720 had a manganese level equal to the drinking water standard (50 |ig/L). The
condition estimates were determined for water and sediment for possible future associations with
mining practices. The level for water was set at 4 |ig/l which corresponded with a drinking water
level of 0.5 mg/1. No level was set for sediment. Results are shown in Figure 55.
100 -
90 -
80 -
70 -
60
50 -
40 -
30 -
20 -
10 -
0 -
- 250
200 *
I
150 =
I
VI
100
103 153 203
Manganese in H2O (|ig/IJ
Manganese in Water
IGOOD FAIR •POOR
270 370 470 570 670
Manganese in Sediment (nig/Kg)
Figure 55. Cumulative Distribution Frequency and Condition Estimate of Manganese in Stream Water and Sediment.
68
-------
Mercury:
In aquatic systems, mercury and other trace metals are strongly correlated with fine particulate
and organic matter. Fine silt and clay particles have a disproportionate amount of surface area
and adsorption sites than larger sediment particles (i.e. sand and gravel). Sediment particle size
affects the transport of oxygen, minerals and ions, which affects microbial activity and the
production of methyl mercury (Jones & Slotton, 1996).
• Sampling Points
/\/Major Rivers
Stream Reach File
| | Boundary
Figure 56. Location of Muddy-Virgin River R-EMAP Sample Sites Containing Mercury in Water and Sediment.
In the Muddy-Virgin River study area, mercury was detected in five of thirty-seven sites, four in
sediment with total mercury (HgT) concentrations ranging from 0.08 to 0.80 mg/kg dry weight,
and one site with an HgT concentration of 0.41 |ig/L (Table 21). Site 95 in Meadow Valley
69
-------
Wash had an HgT concentration of 0.10 mg/kg dry weight downstream of a few historic mine
workings (Figure 56). Site 128, located in Flatnose Wash, in the lower Virgin Watershed, had an
HgT concentration of 0.08 mg/kg, and was directly below several abandoned gold mines. Sites
185 and 875, located in the Pahranagat Wash had HgT concentrations of 0.80 mg/kg and 0.20
mg/kg dry weight, respectively. Site 185 and 875 exceed the lowest effect level (LEL) for
aquatic life. The LEL, developed by Persaud et al. (1993) indicates a level of contamination,
below which, the majority of benthic organisms will not be affected. Site 185 is approximately
eight miles further upstream than Site 875. The source of mercury for these two sites was not
apparent. There was a historic mine to the west of Site 185, but the drainage entered the
Pahranagat Wash between the two sites. Site 270 had an HgT concentration in water of 0.41
|ig/L, and had a not detected (ND) for mercury in sediment. Site 270 is located on the Muddy
River (Figure 15). Land use upstream of Site 270 consisted of agriculture, dairy and a landfill.
Between the landfill and Site 270 was a water impoundment (Damian Higgins, personal
communication). Microbial respiration in the impoundment was increasing the solubility of
mercury, which was then being released downstream. The source of the mercury in the
impoundment could have been deposited in the sediments prior to construction of the
impoundment, presently being transported downstream from historic mine sites, and/or resulting
from runoff or leaching from the landfill. Possible nutrient enrichment from dairy operations and
poor water circulation could be enhancing a potential reducing environment in the impoundment.
Table 21. Total Mercury Concentrations in Water and Sediment for Muddy River
Watershed R-EMAP.
*ND=Not Detected
Site ID
MV95
MV128
MV185
MV270
MV875
Total Mercury (HgT) ug/L
ND
ND
ND
0.41
ND
Total Mercury (HgT)
mg/kg dry weight
0.10
0.08
0.80
ND
0.20
With a drinking water standard of 2 |ig/L, 36 sites were well below the quantification limits of
0.02 |ig/L and 0.03 |ig/L. Site 270 was estimated at a mercury level of 0.41|ig/L. The Lowest
Effect Level (LEL), developed by Persaud et al. (1993) indicates a level of contamination, below
which, the majority of benthic organisms will not be affected. The LEL for sediment is
0.2 mg/kg. In the Muddy-Virgin Project area, the condition estimate (Figure 57) good was given
as less than or equal to 0.17 mg/kg and above 0.17 mg/kg was considered poor.
70
-------
0.02 0.12 0.22 0.32 0.42 0.52 0.62 0.72
Hg in Sediment mg/Kg
Mercurv in Sediment
•GOOD 1POOR
Figure 57. Cumulative Distribution Frequency and Condition Estimate of Mercury in Stream Sediment.
Nickel:
All samples were at or below the quantification limit of 50 |ig/L. With hardness dependent CCC
and CMC values, all sites were below these standards. There is no drinking water standard for
nickel.
Selenium:
All samples were at or below the drinking water standard of 50 |ig/L with a quantification limit
of 20 or 50 ng/L. With a federal CCC standard of 5 |ig/L, it is undetermined whether the samples
exceeded this limit. There is no CMC standard for selenium.
Silver:
Quantification limits of 5 |ig/L and 10 |ig/L were below the secondary drinking water standard
of 100 |ig/L. Calculating the hardness dependant CMC value, only one site (258) had a CMC
value (4.53 |ig/L) below its quantification limit of 5 |ig/L.
Zinc:
The CCC and CMC for zinc is hardness dependent. None of the sites exceeded their individual
CCC or CMC values. The USEPA's National Recommended Water Quality Criteria - Aquatic
Life Criteria for zinc in freshwater is 120 |ig/l for both acute and chronic effects. The
cumulative distribution frequency for zinc in the Muddy-Virgin Project area for water and
sediment are shown in Figure 58.
71
-------
100
90
80
70
60
50
40
30
20
10
0
,50
10 20 30 40 50 60 70 80 90
Zinc in H20 (|jg/l)
27 37 47 57
Zinc in Sediment (mg/Ke)
Figure 58. Cumulative Distribution Frequency of Zinc in Stream Water and Sediment.
F. Relationships Between Indicators and Stressors
The second objective of this report is to examine the relationship between indicators of
ecological condition and indicators of ecological stressors in these streams.
To examine indicator/stressor relationships, simple correlations tests (Pearson product-moment,
P<0.05 significance level) were run on different combinations of indicators (Table 22). Both
water chemistry and physical habitat are stressors, as well as indicators of stress, depending on
the relationship. Although correlations do not imply cause/effect relationships, they can provide
insight into the ecological processes that may be at work. Significant correlations are termed
weak, moderate, or strong where r <0.50, 0.5CK r <0.75, and r >0.75, respectively.
Table 22. Possible Combinations of Stressors and Indicator Relationships.
Indicators
Water
Chemistry
Physical
Habitat
Benthic
Inverts.
Periphyton
Sediment
Metabolism
Stressors
Water
Chemistry
--
--
X
X
X
Physical
Habitat
X
--
X
X
X
Riparian
Disturbance
X
X
X
X
X
Sedimentary
Metals
-
-
-
X
-
72
-------
Many correlations between indicators were detected as weak (Appendix 14). The following
statements summarize the outcome of correlations between indicators:
• Most statistically significant correlations for water chemistry were either weak or
moderate, but there were several correlations with high R-values. Water chemistry
indicators correlated with riparian disturbance stressors had a moderate correlation
between DO and landfills (Figure 59). Water chemistry indicators (conductivity, DO,
chloride and sulfate) were all negatively correlated to percent shade and tree cover, while
having a positive correlation to average width and width/depth ratio (Figure 60).
14 7
8 6
12
10 t
** * *
0.5 1 1.5
Landfills (prox. Index)
Figure 59. Relationship Between Dissolved Oxygen and Proximity to Landfills. R=0.613 P=0.0001, n=35.
73
-------
onn
ouu
700
_ 600
HT
"S) 500
£,
a 400
^
-™
| 300
O
200
100
n
^ * *
*
* *
%
.
V
A* 2 A
\J i — "~* — ^ ^^ 1 — ' — — i — — i — — i — — i
0.00 0.20 0.40 0.60 0.80 1.00
Width/Depth Ratio
Figure 60. Relationship between Chloride and Width/depth Ratio. R=0.855 P=<0.0001, n=35.
• Four correlations between physical habitat indicators and riparian disturbance stressors
were weak. One moderate positive correlation was found between percent pools and the
human riparian disturbance indicator proximity to walls (proximity to walls is based on
the proximity to the riparian area).
• Individual benthic macroinvertebrate indicators had two weak correlations to water
chemistry stressor temperature and TKN. Physical habitat stressors included stream
depth, embeddedness, vegetation cover, and percent sand/fine. Taxa richness had two
moderately negative correlations to embeddedness and percent sand/fine (Figure 61).
Macroinvertebrate IBI assemblage had three weak and two moderate correlations to
water chemistry, one weak correlation to physical habitat metric, and two weak
correlations to all riparian disturbances.
74
-------
45 -i
40
35
to Qn
to ou
o>
1 25
o
«20
X
£ 15
10
5
0
C
^
' *
* * *
* * * *
•% * t
i i i i i
) 0.2 0.4 0.6 0.8 1 1
% Sand/Fine
2
Figure 61. Relationship Between Taxa Richness and % Sand/fine. R=-0.593 P=0.000, n=35.
• Periphyton, defined as AFDM/cm2, had no correlations to water quality, physical habitat
or riparian disturbances. There were only two positive correlations between sedimentary
metals: cadmium and lead.
• Sediment metabolism indicators had primarily positively strong and weak correlations to
water chemistry. For water chemistry, only pH had a negative weak correlation. A
moderate positive correlation existed to width/depth ratio (Figure 62). A moderate
negative correlation existed for percent shade. Pipe and landfill riparian disturbances had
weak positive correlations.
75
-------
1)
E.
E
w
"o
1
s
s
1
\J 1 I I 1 I
0.00 0.20 0.40 0.60 0.80 1.00
Width/Depth Ratio
Figure 62. Relationship between Sediment Metabolism and Width/depth Ratio. R=0.651 P=<0.0001, n=35.
G. Thresholds
Understanding the importance and magnitude of stressors is essential for policy and decision
making. In this report, the relative importance of each stressor is defined by comparing the extent
of each stressor, expressed in km of stream, to other stressors. To characterize the magnitude, the
degree to which each stressor has on biotic integrity, was examined.
Thresholds for condition classes were based on the distribution of sampled values from least-
disturbed reference sites. If higher values denoted an improved condition, then scores lower than
the fifth percentile were considered in most-disturbed condition. Scores between the fifth the
twenty-fifth percentile were considered in intermediate condition, and scores greater than the
twenty-fifth percentile were classified as in least-disturbed condition. If the inverse were true,
then the least-disturbed, intermediate and most-disturbed classes were set by the seventy-fifth
and ninety-fifth percentile (Table 23).
76
-------
Table 23. Thresholds for the Muddy-Virgin River Project Area.
Indicator
IBI
Conductivity (uS/cm)
Total Nitrogen (mg/L)
Total Phosphorus (mg/L)
Chloride (mg/L)
Sulfate (mg/L)
Densiometer(0-17 scale)
Fish Cover- Area Covered by Natural Objects
Riparian Disturbance Roads (prox. Index)
Riparian Disturbance All (prox. Index)
% Fine
% Sand/Fine
Embeddedness (%)
% Slow
Most-disturbed
Threshold
<56
>724
>0.337
>0.038
>16.89
<28
<1.07
<1.44
>0.46
>0.18
>0.75
>0.87
>92.46
<0.64
%
5th
95th
95th
95th
95th
95th
5th
5th
95th
95th
95th
95th
95th
5th
Least-disturbed
Threshold
>66
<550
<0.251
<0.018
<8.85
<27.20
>2.62
£1.73
<0.44
SO. 11
<0.47
<0.78
<84.55
>0.75
%
25th
75th
75th
75th
75th
75th
25th
25th
75th
75th
75th
75th
75th
25th
Understanding the relative magnitude or importance of potential stressors is important to making
policy decisions. The extent of each stressor in comparison to other stressors is one aspect to
consider in defining the importance of each potential stressor. Another issue to consider is the
severity to which each stressor has on biotic integrity, assessed by calculating relative risk. Each
view provides important input to policy decisions.
Relative Extent
The total length of the RF3 stream network in Project Area is 35015.0 km. Over ninety-nine
percent of this total was considered non-target - i.e., many streams within the project area are
ephemeral streams and dry for much of the year. The remaining target stream length (705.7 km)
represents the portion of the sampling frame that meets the criteria for inclusion in the
assessment. A stressor's extent is then estimated by calculating the proportion of the streams in
most or least disturbed condition compared to all stream lengths.
Results of water chemistry stressor metrics varied from 46% (total phosphorus) to 78% (sulfate)
for the stream extent in most-disturbed condition. Chloride had the largest percentage of stream
length in least-disturbed condition (24%) (Figure 63). Macroinvertebrate IBI had 77% of the
stream length in the most-disturbed condition category.
77
-------
Sulfate
Chloride
Total Phosphorus
Total Nitrogen
Conductivity
IBI
D Most-Disturbed n Intermediate n Least-Disturbed
0% 20% 40% 60% 80% 100%
% Stream Length
Figure 63. Extent of Stream Length in Most-disturbed, Intermediate and Least-disturbed Condition for Selected Water
Quality Indicators and Macroinvertebrate IBL
Physical habitat condition stressor results were fairly consistent (Figure 64). Sediment stressors
metrics had <31% of stream lengths in most-disturbed condition. Inclusion of the sand fraction
of the substrate rather than fines alone resulted in a slightly greater amount of stream length in
most-disturbed category (30% versus 14% for fine-sized alone). Riparian disturbance from all
human causes resulted in 32% of the stream length in most-disturbed condition compared to the
reference condition. The results for riparian disturbance from roads only were somewhat less
(24%). The metric that varies substantially was slow water habitat (% pools and glides). The
large majority of stream length was in the good category (91%) for this stress indicator. Figure
65 gives a summary of the relative extent of stressors.
78
-------
Embeddedness
% Sand/Fine
% Fine
Riparian Disturbance Roads
Riparian Disturbance All
Fish Cover
Canopy Density
% Slow
D Most-Disturbed D Intermediate D Least-Disturbed
1
| |
| |
| |
1 I
0%
20%
40% 60% 80%
% Stream Length
100%
Figure 64. Extent of Stream Length in Most-disturbed, Intermediate and Least-disturbed Condition for Selected
Physical Habitat Indicators.
Sulfate
Chloride
Total Phosphorus
Total Nitrogen
Conductivity
% Slow
Embeddedness
% Sand/Fine
% Fine
Riparian Disturbance Roads
Riparian Disturbance All
Fish Cover
Canopy Density
• 2.9%
|30.8°/i
113.!
1 29. 7%
%
H|24.3%
1 32.4
I30.8°/i
1 20. 5%
1 45. 9%
%
r
1 75
167.6%
175
?8.4%
7%
7%
0% 20% 40% 60% 80% 100%
% Stream Length
Figure 65. Summary Relative Extent of Stressors (Proportion of Stream Length with Stressors in Most-disturbed
Condition).
79
-------
Relative Risk
Relative risk is a term which assesses the association between stressors and biological indicators.
Relative risk is a ratio of two probabilities. For this report, the two probabilities, or risks,
measure the likelihood that a most-disturbed condition of a biological indicator will also occur in
streams with a most-disturbed condition of a particular stressor. A risk value of 1.0 or less,
indicates no association, while values greater than 1.0 represent a relative risk.
Relative Risk = Risk of poor biological condition, given poor stressor condition
Risk of poor biological condition, given good stressor condition
Stream weights, which are assigned to each stream based on their occurrence of stream order in
the reach file, are utilized in probability-based studies to statistically represent the target
population. Although using these weights to determine extent is the preferable method to
calculate relative risk to present a more accurate assessment, in the Muddy-Virgin Project area,
weight data was incomplete. For this study, the calculations are made from estimating the stream
length for the various combinations between biological indicator and stressor conditions.
Intermediate conditions were excluded to ensure there was no overlap in conditions classes. The
following (Table 24) is an example of how the data can be arranged and calculated.
Table 24. Thresholds for the Muddy-Virgin River Project Area.
Number of Sampling Sites
IBI
Good
Poor
Total
Total Nitrogen
Least-disturbed
A: 3
B: 3
A+B: 6
Most-disturbed
C: 2
D: 16
C+D: 18
The risk of finding a most-disturbed condition for benthic macroinvertebrates in streams that
have most-disturbed condition for total nitrogen is estimated as:
= D/(C+D) 16/18=0.9
The risk of finding a most-disturbed condition of benthic macroinvertebrates in streams that have
a least disturbed condition for nitrogen is estimated as:
= B/(A+B) 3/6=0.5
Comparing these two probabilities (0.9/0.5) yields a relative risk of 1.8. In other words, it is 1.8
times more likely to find a most-disturbed condition for benthic macroinvertebrates in streams
where total nitrogen is most-disturbed.
Before calculating relative risk, product-moment correlations were calculated between each
stressor pair to test for collinearity. If stressors are highly correlated, relative risk assessments
can be confounded. Relative risks at or below 1.0 are not considered significant.
80
-------
Embeddedness
% Sand/Fine
%Fine
Riparian Disturbance All
Riparian Disturbance Roads
Fish Cover
Chloride
Total Phosphorus
Total Nitrogen
0
1
|
1
|
1
|
1
1
0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
Relative Risk
Figure 66. Risk to Benthic Assemblage (IBI) Relative to the Environmental Stressor Condition.
Relative risk assesses the significance of the effects of stressors to stream biota. Benthic
macroinvertebrate IBI was the biotic indicator for this comparison. Thirteen stressors were
originally used to analyze extent. Only nine were useable for relative risk estimation due to
methods restrictions (Figure 66). The relationship was only reported for stressors where there
was adequate data. Not all stress indicators used in the relative risk analysis exceeded the
significance threshold of one (Appendix 14). Percent fine substrate had a relative risk value less
than one, while both fish cover and percent sand/fine substrate had values just over 1.0. Total
nitrogen and chloride had the highest relative risk values, both at over 1.5.
Combining Extent and Relative Risk
The most comprehensive assessment of the effect of stressors on ecological condition comes
from combining the relative extent and relative risk results-stressors that pose the greatest risk to
individual biotic indicators will be those that are both common and whose effects are potentially
severe. Viewing the relative risk in relation to the extent of indicators across the stream length
assessed, it was found that some indicators with a relative risk greater than one were not found to
be widely occurring problems (Figure 67). For example, canopy density was in most-disturbed
condition in only an estimated 21% of the stream length, but where this problem does occur the
biota is at a high risk of being in a most-disturbed condition. However, some stressors are both
broadly occurring and have high relative risk.
81
-------
80%
70% -
= 60%
5
g 50%
O
2 40% -
5 30%
20% -
10% -
0%
0.0
0.5
m TP
Fish Cover Rh>DistAII
% Sand/Fine
Embed
RipDist Roads
% Fine
1.0
Relative Risk
1.5
2.0
Figure 67. Summary of Extent of Stressors in Most-disturbed Condition in Relation to Relative Risk. The Oval
Emphasizes Stressor Indicators with both High Percent of Stream Length in Most-disturbed Condition and
with High Relative Risk. Refer to Appendix 14 for Definition of Abbreviated Indicator Names in this Figure.
82
-------
V. Conclusion
Physically, ecosystems are always in motion reacting to natural climatic and anthropogenic
conditions. These changes, in environmental condition, affect the chemical and biological
community structure, which cause further alterations to the environment. Data from this study
indicate that the statuses of many of the streams in the Muddy-Virgin River project area are in a
less than desirable condition. The percentage of impacted streams varied, with 41% of stream
reaches studied being in most-disturbed condition. Primary stressors in terms of both extent and
risk to biota are conductivity, sulfate, chloride and total nitrogen.
For this evaluation, only benthic macroinvertebrate IBI was used to determine risk to biota. It is
preferable to use more assemblages so that the conclusions are more robust. Using multiple
assemblages is preferred as a stressor that may be very relevant to one assemblage may have less
of a signal for another.
The baseline data obtained in this study will be of considerable use to local, state, federal and
tribal agencies concerned with the future of surface water resources in Nevada. Nevada's arid
environment, coupled with the fact that most of the biodiversity in this state is associated with
riparian or aquatic habitats, makes the management of these systems a matter of particular
importance. Although we have made considerable progress as a nation in managing our
watersheds, much remains to be learned, and studies such as this one play an integral role in
helping us meet the Clean Water Act's goal of maintaining the biological and chemical integrity
of the nation's waters.
It was beyond the scope of this study to evaluate each stream reach in relation to its own
potential and the attributes and processes relevant to that location in the watershed. However, to
address the aquatic impacts from environmental stressors, it is important to understand the
drivers of ecosystem function, and recognize the fundamental changes to the water cycle, water
quality, aquatic and terrestrial ecology and stream form and function. By identifying the
condition of a watershed and/or ecoregion (i.e., the degree to which interacting stream reaches
and wetland riparian areas are functioning properly) and their potential, managers can make the
connection between form, function, management and monitoring. Thus, they can address the
underlying causative factors behind restoration of biological values and ecosystems. A possible
next step for ecological condition analysis could be a landscape ecology approach which focuses
on the physical processes, spatial arrangements, and connections to ecosystem functions within
the watershed. To ecologists and environmental scientists, a landscape is more than a vista, but
comprises the features of the physical environment and their influence on environmental
resources. Landscape ecology integrates biophysical approaches with human perspectives and
activities to study spatial patterns at the landscape level, as well as the functioning of the region.
There are many applications of this approach. For example, areas most disturbed by
anthropogenic sources can be identified by combining information on population density, roads
and land cover with systematic assessments of riparian functionality. Vulnerability of areas can
also be identified by looking at the surrounding conditions. Potential erosion control issues can
The oval emphasizes stressor indicators -with both high percent of stream length in most-disturbed condition and -with high
relative risk. Refer to Appendix 15 for definition of abbreviated indicator names in this figure.
83
-------
be evaluated as well by considering variables such as precipitation, soils, vegetation, and the
steepness of slopes. Ecological processes connect the physical features of the landscape linking
seemingly separate watersheds.
Riparian function is heavily influenced by the condition of adjacent and upland ecosystems. An
ecosystem, or landscape, approach will provide a comprehensive basis for identifying and
evaluating current and historic land use practices. Riparian proper functioning condition (PFC)
assessments, in conjunction with remote sensing, can be used as tools to assist and connect local
and regional assessments. Future studies can use remote sensing and geospatial technology in
innovative ways to provide needed information on the status and condition of constructed and
natural wetland areas. Riparian vegetation is one of the primary ecological attributes affected by
human land uses (i.e., grazing, urbanization), and indicates succession to quantify functionality
trends. Analyzing spatial relationships and short- and long-term trends determine if goals and
objectives are being met. Improved functionality leads toward attainment of water quality
standards and many additional environmental services, values, and products, by determining
what changes are needed to move the riparian ecosystem towards the desired conditions and
helps develop and compare management alternatives. PFC should be considered when making
management decisions in the Muddy-Virgin River Project area to provide for a more sustainable
ecosystem.
84
-------
VI. References
Arizona Department of Water Resources (ADWR). (2009). Virgin river basin., 2009, from
http://www.azwater.gov/azdwr/StatewidePlanning/WaterAtlas/documents/Vol 6 VRG.pdf
Barbour, M. T., Gerritsen, J., Snyder, B. D., & Stribling, J. B. (1999). Rapidbioassessment
protocols for use in streams andwadeable rivers: Periphyton, benthic macroinvertebrates
and fish, second edition No. EPA 841-B-99-002. Washington, D.C.: U.S. Environmental
Protection Agency. Office of Water.
Beaty, M. (2005). Management pilot project: Protocol builder and manager, reclamation:
Managing water in the west., 2009, from
http://www.nwcouncil.org/dropbox/Data%20Sharing/All%20workshop%20materials/presen
taion%20materials%20and%20handouts/presentations/05 25 05 NED Protocol BuilderM
anager_2.ppt
Beaver, J. (1981). Apparent ecological characteristics of some common freshwater diatoms.
Ontario, Canada: Ontario Ministry of the Environment.
Biological Resource Research Center. (2001). Dominant vegetation in the great basin.
http://www.brrc.unr.edu/data/maps/grbasin.html
Boulton, A. J. (2003). Parallels and contrasts in the effects of drought on stream
macroinvertebrate assemblanges. Freshwater Biology, 48(7), 1173.
Buchman, M. F., 1999. NOAA Screening Quick Reference Tables, NOAA HAZMAT Report
99-1, Seattle WA, Coastal Protection and Restoration Division, National Oceanic and
Atmospheric Administration, 12 pages."
California Stream Bioassessment Procedure, (Protocol Brief for Biological and Physical/Habitat
Assessment in Wadeable Streams), California Department of Fish and Game, Water
Pollution Control Laboratory, Aquatic Bioassessment Laboratory Revision Date -
December, 2003 http://www.epa.gov/region9/qa/pdfs/csbp_2003.pdf
City of Mesquite. (2009). Mesquite master plan.
http://www.mesquitenv.com/generalinfo/masterplan
Clark County. (2000). Northest Clark County 208 water quality management plan amendment-
June 2000, Clark County comprehensive plan.
http://www.accessclarkcountv.com/DEPTS/COMPREHENSIVE PLANNING/Pages/home.
aspx
Clark County. (2008). Comprehensive plan elements: Water quality management
program. http://www.accessclarkcountv.com/depts/comprehensive_planning/compplanelem
ents/Pages/208water chapter 4.aspx
85
-------
Clesceri, L. S., Greenber, A. R., & Eaton, A. D. (Eds.). (1989). Standard methods for the
examination of water andwastewater, 20th edition. Baltimore, Maryland: American Public
Health Association, American Water Works Association and Water Pollution Control
Federation.
Cummins, K. W., & Klug, M. J. (1979). Feeding ecology of stream invertebrates. Annual Review
of Ecology and Systematics, 10, 147.
Eakin, T. E. (1964). Groundwater appraisal of Coyote Spring and Kane Spring Valleys and
Muddy River Springs area, Lincoln and Clark counties, Nevada. Groundwater Resources-
Reconnaissance Series Report Number 25.
Eakin, T. E. (1966). A regional interbasin groundwater system in the white river area,
southeastern Nevada .Water Resource Bulletin no. 33.
Federal Interagency Stream Restoration Working Group (FISRWG). (1998). Stream corridor
restoration: Principles, processes, and practices. GPO Item No. 0120-A.
Feth, L. H. (1981). Chloride in natural continental water-a review. Water Supply Paper 2176.
Washington, D.C.: U.S. Geological Survey.
Fitzpatrick, F.A., I.R. Waite, P.J. D'Arconte, M.R. Meador, M.A. Maupin, and M.E. Gurtz. 1998.
Revised, Methods for Characterizing Stream Habitat in the National Water Quality
Assessment Program. U.S. Geologic Survey, WRI Report 98-4052, Raleigh, NC. 67 pp.
http://pubs.usgs.gov/wri/wri984052/
Fore, L. S., Karr, J. R., & Wisseman, R. W. (1996). Assessing invertebrate responses to human
activities; evaluating alternative approaches. Journal of the North American Benthological
Society, 75(2), 212.
Fore, Leska S. 2003. Developing biological indicators: lessons learned from Mid-Atlantic
streams. EPA/903/R-03/003. Ft. Meade, MD. U.S. Environmental Protection Agency,
Office of Environmental Information and Mid-Atlantic Integrated Assessment Program.
Grace, M. R., & Imberger, S. J. (2006). Stream metabolism: Performing and interpreting
measurements. Water Studies Centre Monash University, Murray Darling Basin
Commission and New South Wales Department of Environment and Climate Change.
Hall, R. K., Olsen, A., Stevens, D. L., Rosenbaum, B., Husby, P., Wolinsky, G. A., & Heggem,
D. T. (2000). EMAP design and river reach file 3 (RF3) as a sample frame in the central
valley, California. Environmental Monitoring and Assessment, 64(1)., 69.
Hayslip, G., Klemm, D. J., & Lazorchak, J. M. (1994). 1994 field operations and methods
manual for streams in the coast range ecoregion of Oregon and Washington and the Yakima
River basin of Washington. Cincinnati, Ohio: Environmental Monitoring Systems
Laboratory, U.S. Environmental Protection Agency.
86
-------
Hayslip, G. A., & Herger, L. G. (2001). Ecological condition of upper Chehalis basin streams.
EPA/910/R-01/005. Seattle, WA: Environmental Monitoring and Assessment Program, U.S.
Environmental Protection Agency, Region 10.
Hem, J. D. (1985,1989). Study and interpretation of the chemical characteristics of natural
water. Water Supplemental Paper. 2254. U.S. Geological Survey.
Herger, L. G., & Hayslip, G. (2000). Ecological condition of streams in the coast range
ecoregion of Oregon and Washington. EPA/910/R-00/002. Seattle, WA: U.S.
Environmental Protection Agency, Region 10.
Herlihy, A. T., Larsen, D. P., Paulsen, S. G., Urquhart, N. S., & Rosenbaum, B. J. (2000).
Designing a spatially balanced randomized site selection process for regional stream
surveys; the EMAP mid-Atlantic pilot study. Environmental Monitoring and Assessment,
63, 95.
Herlihy, A. T., Stoddard, J. L., & Johnson, C. B. (1998). The relationship between stream
chemistry and watershed land cover data in the mid-Atlantic region. U.S. Water, Air and
Soil Pollution, 105, 377.
Hill, B. H., Hall, R. K., Husby, P., Herlihy, A. T., & Dunne, M. (2000). Interregional
comparisons of sediment microbial respiration in streams. Freshwater Biology, 44,213.
ITIS. (2009). Integrated taxonomic information system,. 2010, from http://www.itis.gov/
Jones, A. B., & Slotton, D. G. (1996). Mercury effects, sources and control measures: A special
study of the San Francisco estuary monitoring program. Contribution #20. San Francisco
Regional Monitoring Program.
Jones, D. S., & Sutler, G. W. I. (1997). Toxicological benchmarks for screening contaminants of
potential concern for effects on sediment-associated biota: 1997 revision. ES/ER/TM-
95/R4. Oak Ridge, TN: Lockheed Martin Energy System.
Karr, J. R., & Chu, E. W. (1999). Restoring life in running: Better biological monitoring.
Washington, D.C.: Island Press.
Karr, J. R., Fausch, K. D., Angermeier, P. L., Yant, P. R., & Schlosser, I. J. (1986). Assessing
biological integrity in running waters; a method and its rationale (Special Publication 5th
ed.). Champaign, IL: Illinois Natural History Survery.
Kaufmann, P. R., Levine, P., Robison, E. G., Seeliger, C., & Peck, D. V. (1999). Quantifying
physical habitat in wadeable streams. EPA/620/R-99/003. Corvallis, OR: Environmental
Monitoring and Assessment Program, U.S. Environmental Protection Agency.
Kaufmann, P.R. and E.G. Robison. 1997. Physical Habitat Assessment. Pages 6-1 to 6-38 in D.J.
Klemm and J.M. Lazorchak (editors). Environmental Monitoring and Assessment Program.
87
-------
1997 Pilot Field Operations Manual for Streams. EPA/620/R-94/004. Environmental
Monitoring Systems Laboratory, Office of Research and Development, U.S. Environmental
Protection Agency, Cincinnati, Ohio.
Klemm, D. J., Lewis, P. A., Fulk, F., & Lazorchak, J. M. (1990). Macroinvertebrate field and
laboratory methods for evaluating the biological integrity of surface waters. EPA/600/4-
90/030. Cincinnati, OH: Office of Research and Development, U.S. Environmental
Protection Agency.
Lazorchak, J.M., Klemm, D.J., and D.V. Peck (editors). 1998. Environmental Monitoring and
Assessment Program - Surface Waters: Field Operations and Methods for Measuring the
Ecological Condition of Wadeable Streams. EPA/620/R-94/004F. U.S. Environmental
Protection Agency, Washington, D.C.
Las Vegas Valley Water District. (2009). Southern Nevada Water Systems Water Quality Report.
(2010). http://www.snwa.com/assets/pdf/wq report snws.pdf
Legislative Counsel. (2008). Chapter 445A-water controls., 2009, from
http://www.leg.state.nv.us/nac/nac-445a.htmltfNAC445aSecll704
Long, E. R., MacDonald, D. D., Smith, S. L., & Calder, F. D. (1995). Incidence of adverse
biological effects within ranges of chemical concentrations in marine and estuarine
sediment. Environmental Management, 19(1), 81.
Longwell, C. R. (1928). Geology of the muddy mountains, Nevada with a section through the
virgin range to the grand wash cliffs, Arizona. Bulletin 798. U.S. Geological Survey.
Mac, M. J., Opler, P. A., Puckett Haecker, C. E., & Doran, P. D. (1998). Status and trends of the
nation's biological resources. Reston, VA: U.S. Department of the Interior, U.S. Geological
Survey.
MacDonald, D.D., C.G. Ingersoll, D.E. Smrong, R.A. Lindskoog, G. Sloane, T. Biernacki. 2003.
Development and evaluation of numerical sediment quality assessment guidelines for
Florida inland waters. Florida Department of Environmental Protection. Available at:
http://www.dep. state.fl.us/water/monitoring/docs/seds/SQAGs_for_Florida_Inland_Waters_
01_03.PDF
MacDonald, L. H., Smart, A. W., & Wissmar, R. C. (1991). Monitoring guidelines to evaluate
effects of forestry activities on streams in the Pacific Northwest and Alaska. EPA/910/9-
91/001. Seattle, WA: U.S. Environmental Protection Agency, Region 10, Water Division.
MacKenthun, K. M. (1973). Toward a cleaner aquatic environment. Washington, D.C.: U.S.
Government Printing Office.
88
-------
Meador, M.R., C.R. Hupp, T.F. Cuffney, and M.E. Gurtz. 1993. Methods for characterizing
stream habitat as part of the national water-quality assessment program. U.S. Geological
Survey Open-File Report, Raleigh, North Carolina. USGS/OFR 93-408.
Montgomery, D. F., & Buffington, J. M. (1993). Channel classification, prediction of channel
response, and prediction of channel response, and assessment of channel conditions. TFW-
SH10-93-002. Seattle, WA: University of Washington.
Montgomery, D. F., & Buffington, J. M. (1998). Channel processes, classification and response
in river ecology and management: Lessons from the pacific coastal ecoregion. In R. J.
Naiman, & R. E. Bilby (Eds.). New York: Spinger Press.
Office of Water. (1986). Quality criteria for water. EPA/440/5-86/001. Washington, D.C.: U.S.
Environmental Protection Agency.
Office of Water. (2004). Drinking water standards and health advisories table. EPA/822/R-
04/005. U.S. Environmental Protection Agency.
Ohio Environmental Protection Agency (Ohio EPA). 1987. Biological criteria for the protection
of aquatic life: volumes 1-111. Ohio Environmental Protection Agency, Columbus, Ohio.
Oklahoma Conservation Commission (OCC). 1993. Development of rapid bioassessment
protocols for Oklahoma utilizing characteristics of the diatom community. Oklahoma
Conservation Commission, Oklahoma City, Oklahoma.
Omernik, J.M., 1987, Ecoregions of the conterminous United States. Map (scale 1:7,500,000).
Annals of the Association of American Geographers 77(1): 118-125.
Overton, W. S., White, D., & Stevens Jr, D. L. (1990). Design report for EMAP, environmental
monitoring and assessment program. EPA/600/3-91/053. Corvallis, OR: U.S.
Environmental Protection Agency.
Persaud, D., Jaagumagi, R., & Hayton, A. (1993). Guidelines for the protection and management
of aquatic sediment quality in Ontario. Toronto, Canada: Ontario Ministry of the
Environment and Energy, Water Resource Branch.
Peterson, S. A., Urquhart, N. S., & Welsh, E. B. (1999). Sample representativeness; a must for
reliable regional lake condition estimates. Environmental Science and Technology, 33, 1559.
Plafkin, J. L., Barbour, M. T., Porter, K. D., Gross, S. K., & Hughes, R. M. (1989). Rapid
bioassessment protocols for use in streams and rivers: Periphyton, benthic
macroinvertabrates and fish. EPA/444/4-89/001. Washington, D.C.: U.S. Environmental
Protection Agency.
Powell, H., Peacock, M., Tracy, C. R., & Vinyard, G. (In Review). Ecological condition of
streams in eastern and southern Nevada. Reno, NV: University of Nevada Reno.
89
-------
Resh, V. H. (1995). Freshwater benthic macroinvertebrates and rapid assessment procedures for
water quality monitoring in developing and newly industrialized countries. In W. S. Davis,
& T. P. Simon (Eds.), Biological assessment and criteria: Tools for water resource
planning and decision making (pp. 167). Boca Raton, FL: Lewis Publishers.
Resh, V. H., & Jackson, J. K. (1993). Rapid assessment approaches to biomonitoring using
benthic macroinvertebrates. In D. M. Rosenberg, & V. H. Resh (Eds.), Freshwater
biomonitoring and benthic macroinvertebrates (pp. 195). New York: Chapman and Hall.
Rosgen, D. 1996. Applied River Morphology. Wildland Hydrology, Pagosa Spings, CO.
Stevens, D., & Olsen, A. (1999). Spatially restricted surveys overtime for aquatic resources.
Journal of Agricultural Biological and Environmental Statistics, ¥,415.
Stevens, D., & Olsen, A. (2004). Spatially balanced sampling of natural resources. Journal of the
American Statistical Association, 99, 262.
Stoddard, J.L., Peck, D.V., Paulsen, S.G., Van Sickle, J., Hawkins, C.P., Herlihy, A.T., Hughes,
R.M., Kaufmann, P.R., Larsen, D.P., Lomnicky, G., Olsen, A.R., Peterson, S.A., Ringold,
P.L., and Whittier, T.R. (2004). An ecological assessment of western streams and rivers.
EPA 620/R-05/005. Washington DC: U.S. Environmental Protection Agency.
Stolte, K. W., & Smith, W. D. (In Review). 1998 forest health monitoring national technical
report. USDA Forest Service.
Strahler, A. N. (1957). Quantitative analysis of watershed geomorpholy. American Geophysical
Union Transaction, 38, 913.
U.S. Department of the Interior, Bureau of Land Management, Record of Decision for the
Approved Las Vegas Resource Management Plan and Final Environmental Impact
Statement, October, 1998.
http://www.blm.gov/pgdata/etc/medialib/blm/nv/fi el d_offices/las_vegas_fi el d_office/las_ve
gas resource.Par.28808.File.dat/ROD LV RMP.pdf
U.S. Environmental Protection Agency. (2002). National recommended water quality criteria.,
2009, from http://www.epa.gov/waterscience/criteria/wqctable/
U.S. Environmental Protection Agency. 2002. Consolidated assessment and listing methodology:
toward a compendium of best practices. Office of Wetlands, Oceans and Watersheds.
U.S. Environmental Protection Agency. (2009). Documentation for the probabilistic sampling
databrowser., 2009, from
http://www.epa.gov/bioiwebl/statprimer/ProbabilisticSampling.html
U.S. Environmental Protection Agency. (2009). Technicalfactsheet on: nitrate/nitrite. 2009,
from http://www.epa.gov/OGWDW/pdfs/factsheets/ioc/tech/nitrates.pdf
90
-------
U.S. Environmental Protection Agency. (2014). National Recommended Water Quality Criteria,
http://water.epa.gov/scitech/swguidance/standards/criteria/current/index.cfm
Wang, L. H., & Kanehl, P. (2003). Influences of watershed urbanization and in-stream habitat on
macroinvertebrates in cold water streams. Journal of the American Water Resources
Association, 36(5), 1181.
Weitzel, R. L. (Ed.). (1979). Methods and measurements ofperiphyton communities: A review.
Baltimore, MD: Library of Congress.
Welch, E. B., Jacoby, J. M., & May, C. W. (1998). Stream quality. In R. J. Naiman, & R. E.
Bilby (Eds.), Stream quality in river ecology and management: Lessons from the pacific
coastal ecoregion (pp. 69)
Whittier, T. R., & Paulsen, S. G. (1992). The surface waters component of the environmental
monitoring and assessment program: An overview. Journal of Aquatic Ecosystem and
Health, 7, 119.
Wisseman, R. W. (1996). Benthic invertebrate biomonitoring and bioassessment in western
montane streams. Corvallis, OR: Aquatic Biology Associations, Inc.
91
-------
VII. Appendices
Appendix 1. List of Sites
Site
8
10
19
95
110
119
128
144
170
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
Stream Order
3
4
5
5
5
5
3
1
5
3
3
5
5
4
3
3
5
5
3
5
5
3
4
3
4
5
4
5
5
3
4
3
5
5
5
3
3
Stream Name
Meadow Valley Wash
White River
Virgin River
Meadow Valley Wash
Virgin River
Virgin River
Flatnose Wash
Unnamed
Muddy River
Las Vegas Wash
Pahranagat River
Meadow Valley Wash
Meadow Valley Wash
Las Vegas Wash
Beaver Dam Wash
Muddy River
Meadow Valley Wash
Virgin River
Meadow Valley Wash
Virgin River
Virgin River
Meadow Valley Wash
Muddy River
Muddy River
Muddy River
Virgin River
Muddy River
Virgin River
Virgin River
Pahranagat River
Muddy River
Muddy River
Virgin River
Virgin River
Muddy River
Muddy River
Muddy River
Longitude
-114.3552778
-115.1608333
-113.9191667
-114.5672222
-114.2283333
-114.2675
-114.102778
-115.144444
-114.52881
-115.041944
-115.191944
-114.664444
-114.510278
-115.036111
-114.058056
-114.666944
-114.57416
-113.681944
-114.346667
-114.033889
-113.928056
-114.332778
-114.496389
-114.687222
-114.551389
-114.073611
-114.417222
-114.171667
-114.219444
-115.134444
-114.468333
-114.708889
-114.129722
-114.084167
-114.566944
114.598056
-114.626111
Latitude
37.834167
38.9325
36.919167
37.436944
36.723889
36.689444
37.919167
38.379444
36.641667
36.148333
37.439444
36.869444
37.086944
36.134137
37.49222
36.673889
37.551389
37.013056
37.841667
36.801667
36.883056
37.853333
36.620556
36.704444
36.650833
36.795556
36.526389
36.756111
36.734167
37.314722
36.582222
36.714444
36.782778
36.791667
36.661944
36.655556
36.654167
92
-------
Appendix 2. Summary Statistics for Water Chemistry Indicators for the Muddy-Virgin
Project Area
Indicator
Water Temp
Dissolved O2
PH
Conductivity
Total
Phosphorus
Total Nitrogen
Nitrate/Nitrite
Ammonia
Chloride
Sulfate
Total Kjeldahl
Nitrogen
Units
°c
mg/L
PH
units
uS/cm
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
Mean
23.06
8.33
8.03
1703.89
0.06
0.68
0.36
0.03
173.08
498.56
0.29
Median
23.00
8.30
8.04
1004.00
0.03
0.49
0.12
0.03
65.93
246.12
0.27
Min.
13.10
5.10
7.18
310.00
0.01
0/09
0.00
0.01
1.00
1.00
0.06
Max.
32.80
12.80
8.62
4090.00
0.43
4.02
3.11
0.09
675.00
1854.00
0.88
Range
19.70
7.70
1.44
3780.00
0.42
3.94
3.11
0.08
674.00
1853.00
0.82
Variance
23.90
3.01
0.09
1610325.16
0.01
0.63
0.51
0.00
40861.20
269639.20
0.03
Standard
Deviation
4.89
1.74
0.31
1269.0
0.08
0.80
0.71
0.02
202.1
519.3
0.17
Standard
Error
0.88
0.29
0.05
208.53
0.01
0.68
0.12
0.00
32.99
85.10
0.03
93
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics
Type
channel
& subba
riparian
Indicator
stream length
wetted width
bankfull width
width of mid
channel bars
ave depth
thalweg depth
% mid channel
shade
%bank shade
incision height
%fast
%slow
%pool
discharge
slope of reach
bearing
bank angle
undercut bank
distance
embedded
canopy layer big
trees
canopy layer
small trees
canopy layer total
trees
understory woody
Units
m
m
m
m
cm
cm
%
%
m
%
%
%
m/s
%
degree
degree
m
%
%
%
%
%
Indicator
reach_length_m
wt_wid
bankwid
barwid
ave depth
depth
_mid_channel_shade
_bank_shade
incision height
%fast
%slow
%pool
discharge
slope
bearing
angle
undercut
embed
big trees
small trees
total trees
understory wood
Mean
252.89
6.79
9.26
2.06
19.17
43.34
31.74
56.26
0.45
0.38
0.92
0.01
10.62
1.01
162.36
41.68
2.16
83.49
8.97
39.74
24.36
84.77
Lower
95%
Conf.
205.71
4.84
6.90
1.00
14.71
34.87
21.20
45.72
0.41
-0.25
0.89
0.00
6.26
0.76
141.01
35.24
-1.99
77.42
2.06
28.25
16.97
75.59
Upper
95%
Conf.
300.08
8.73
11.63
3.13
23.62
50.25
42.29
66.80
0.49
1.02
0.96
0.01
14.98
1.26
183.70
48.11
6.31
89.55
15.87
51.24
31.74
93.95
Med.
160.00
4.45
5.63
0.00
14.20
34.61
25.00
64.97
0.47
0.27
0.96
0.00
7.13
0.84
154.24
33.09
0.00
87.36
0.00
40.91
27.27
95.45
Min.
150.00
0.00
1.52
0.00
1.75
4.26
0.00
7.22
0.17
0.00
0.61
0.00
0.01
0.23
37.50
13.64
0.00
0.00
0.00
0.00
0.00
0.00
Max.
500.00
26.18
25.60
10.28
47.15
88.56
93.05
95.99
0.72
11.00
1.00
0.06
52.23
3.42
307.65
85.05
80.00
100.00
100.00
100.00
100.00
100.00
Range
350.00
26.18
24.08
10.28
45.4
84.30
93.05
88.77
0.55
11.00
0.39
0.06
52.22
3.19
270.15
71.41
80.00
100.00
100.00
100.00
100.00
100.00
Var.
20028.10
35.97
53.28
10.79
167.13
504.31
1000.45
999.42
0.01
3.42
0.01
0.00
161.17
0.50
4336.65
393.70
163.68
350.08
428.70
1188.48
490.31
757.82
Std.
Dev.
141.52
6.00
7.30
3.28
12.97
22.39
31.63
31.61
0.12
1.85
0.10
0.01
12.70
0.71
65.85
19.84
12.79
18.71
20.71
34.47
22.14
27.53
Std.
Error
23.27
0.96
1.17
0.53
2.19
3.78
5.20
5.20
0.02
0.31
0.02
0.00
2.15
0.13
10.54
3.18
2.05
3.00
3.40
5.67
3.64
4.53
94
-------
cover
woody
understory
nonwoody
understory total
ground cover
woody
ground + canopy
woody
ground barren
ground cover total
filamentous algae
boulders
brush/woody
debris
aquatic
macrophytes
overhang
vegetation
artificial structures
undercut
woody debris
bankfull very
small
bankfull small
bankfull medium
bankfull small
bankfull medium
bankfull small
bankfull large
above bankfull
very small
%
%
%
%
%
%
frac
frac
frac
frac
frac
frac
frac
frac
#/100m
#/100m
#/100m
#/100m
#/100m
#/100m
#/100m
#/100m
understory nonwood
total understory
gcw
ground cnw
barren ground
total ground
algae
bouldr
brush
macphy
ovrhng
struct
undcut
woody
wetsdsl
wetsdml
wetsdll
wetmdsl
wetmdml
wetldsl
wetldml
drysdsl
58.19
71.48
66.58
78.83
89.82
72.71
0.69
0.11
0.86
0.78
1.26
0.04
0.25
0.11
0.30
0.06
0.00
0.01
0.01
0.00
0.00
0.05
45.96
65.11
53.72
68.99
81.69
64.80
0.46
0.03
0.67
0.45
0.94
0.00
0.13
0.05
0.15
0.01
0.00
0.00
0.00
0.00
0.00
70.42
77.85
79.45
88.67
97.96
80.61
0.91
0.19
1.04
1.11
1.59
0.09
0.38
0.18
0.46
0.11
0.02
0.02
0.01
0.01
0.11
63.64
70.45
86.36
90.91
100.00
79.55
0.60
0.00
0.82
0.40
0.91
0.00
0.00
0.00
0.10
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
38.64
0.00
0.00
0.00
4.55
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
100.00
100.00
100.00
100.00
100.00
100.00
3.09
1.00
2.27
4.00
3.45
0.82
1.18
1.00
2.10
0.80
0.00
0.20
0.20
0.10
0.10
0.80
100.00
61.36
100.00
100.00
100.00
95.45
3.09
1.00
2.27
4.00
3.45
0.82
1.18
1.00
2.10
0.80
0.00
0.20
0.20
0.10
0.10
0.80
1345.07
364.86
1489.00
870.89
595.11
561.88
0.49
0.06
0.34
1.02
1.00
0.02
0.15
0.04
0.23
0.02
0.00
0.00
0.00
0.00
0.00
0.03
36.68
19.10
38.59
29.51
24.39
23.70
0.70
0.25
0.58
1.01
1.00
0.14
0.38
0.21
0.48
0.15
0.00
0.04
0.04
0.02
0.02
0.17
6.03
3.14
6.34
4.85
4.01
3.90
0.11
0.04
0.09
0.16
0.16
0.02
0.06
0.03
0.08
0.02
0.00
0.01
0.01
0.00
0.00
0.03
95
-------
human
mesosub
above bankfull
small
above bankfull
medium
wall (prox. index)
building (prox.
index)
pavement (prox.
index)
road (prox. index )
pipe (prox. index)
landfill (prox.
index)
park (prox. index)
crop (prox. index)
pasture (prox.
index)
logging (prox.
index)
mining
activity(prox.
index)
mean substrate
size left center
mean substrate
size right center
mean substrate
size center
mean substrate
size left
mean substrate
size right
#/100m
#/100m
frac
frac
frac
frac
frac
frac
frac
frac
frac
frac
frac
mm
mm
mm
mm
mm
drysdml
drysdll
wall
bldg
pvmt
road
pipe
landfill
park
crop
pasture
logging
minact
xsublctr
xsubrctr
xsub_ctr
xsubjft
xsub_rgt
0.00
0.00
0.10
0.07
0.05
0.37
0.01
0.30
0.02
0.00
0.42
0.00
0.00
2.47
2.45
2.69
1.85
1.78
0.00
0.00
0.01
-0.01
0.29
0.00
0.13
-0.01
0.21
0.00
2.14
2.13
2.36
1.52
1.48
0.01
0.19
0.13
0.10
0.46
0.02
0.47
0.06
0.62
0.00
2.80
2.77
3.02
2.18
2.07
0.00
0.00
0.00
0.00
0.00
0.34
0.00
0.03
0.00
0.00
0.00
0.00
0.00
2.67
2.22
2.60
1.40
1.50
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
1.00
1.00
1.00
0.88
0.10
0.00
1.18
0.67
0.70
0.84
0.21
1.67
0.67
0.00
1.67
0.00
0.06
4.60
4.60
5.00
4.33
4.50
0.10
0.00
1.18
0.67
0.70
0.84
0.21
1.67
0.67
0.00
1.67
0.00
0.06
3.60
3.60
4.00
3.33
3.63
0.00
0.00
0.08
0.03
0.03
0.06
0.00
0.25
0.01
0.00
0.37
0.00
0.00
0.98
0.93
0.99
0.96
0.78
0.02
0.00
0.28
0.18
0.16
0.25
0.04
0.50
0.11
0.00
0.61
0.00
0.01
0.99
0.96
0.99
0.98
0.88
0.00
0.00
0.05
0.03
0.03
0.04
0.01
0.08
0.02
0.00
0.10
0.00
0.00
0.16
0.16
0.16
0.16
0.15
96
-------
Appendix 4. Summary Statistics for Macroinvertebrate Metrics, Muddy-Virgin
Project
Metric
Total Taxa
% EPT
EPT Taxa
%
Ephemeroptera
Ephemoptera
Taxa
% Plecoptera
Plecoptera Taxa
% Trichoptera
Trichoptera
Taxa
Shannon H
% Collector
% Filterer
% Predator
% Grazers
% Shredders
% Burrower
% Climber
% Clinger
% Sprawler
% Swimmer
HBI
% Intolerance
(<4)
% Tolerance
(*7)
Mean
16.83
41.79
5.51
26.72
2.86
0.02
0.06
15.06
2.60
1.73
58.79
22.02
13.90
4.42
0.66
19.32
0.50
1.75
7.29
13.98
5.36
4.77
15.31
Upper
95%
Conf.
19.66
49.75
6.67
32.97
3.42
0.06
0.17
21.59
3.29
1.91
67.67
29.93
21.02
7.13
1.38
24.69
0.80
3.08
10.17
18.86
5.66
8.03
21.68
Lower
95%
Conf
14.00
33.83
4.36
20.47
2.29
-0.02
-0.05
8.52
1.91
1.54
49.92
14.10
6.78
1.70
-0.06
13.95
0.20
0.42
4.41
9.10
5.06
1.51
8.94
Median
15.00
42.58
5.00
25.32
3.00
0.00
0.00
5.78
2.00
1.71
60.45
11.82
5.05
1.29
0.00
15.11
0.00
0.22
4.39
8.29
5.08
1.39
8.11
Min
3.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.53
7.63
0.00
0.78
0.00
0.00
0.66
0.00
0.00
0.00
0.00
4.21
0.00
0.00
Max
39.00
81.19
16.00
75.89
7.00
0.68
2.00
70.42
9.00
2.73
95.32
71.95
87.94
39.42
12.45
68.35
3.67
19.92
28.09
53.00
8.18
46.06
85.41
Range
36.00
81.19
16.00
75.89
7.00
0.68
2.00
70.42
9.00
2.19
87.69
71.95
87.16
39.42
12.45
67.69
3.67
19.92
28.09
53.00
3.97
46.06
85.41
Variance
72.85
577.26
12.14
355.74
2.89
0.01
0.11
388.84
4.36
0.32
717.35
570.52
461.92
67.22
4.69
262.49
0.82
16.12
75.77
216.97
0.82
96.85
369.58
Std.
Dev.
8.54
24.03
3.48
18.86
1.70
0.12
0.34
19.72
2.09
0.56
26.78
23.89
21.49
8.20
2.17
16.20
0.90
4.02
8.70
14.73
0.91
9.84
19.22
Std.
Err.
1.44
4.06
0.59
3.19
0.29
0.02
0.06
3.33
0.35
0.09
4.53
4.04
3.63
1.39
0.37
2.74
0.15
0.68
1.47
2.49
0.15
1.66
3.25
97
-------
Appendix 5. Criteria Used to Determine Least-disturbed and Most-disturbed Sites.
Criteria Used by Alan Herlihy to Identify Least- and Most-disturbed Sites
Herlihy
Criteria
Least
Most
Total
Phosphorus
(ug/L)
<50
>150
Total
Nitrogen
(ug/L)
<1500
>5000
Chloride
(ueq/L)
<1000
>5000
PH
<9
<6
Riparian
Disturbance
(W1JHALL)
<1.5
>3.0
% Fines
<50%
>90%
Canopy
Density
(XCDENBK)
>50%
<10%
Criteria Used by John Stoddard to Identify Least- and Most-disturbed Sites
Stoddard
Criteria
Least
Most
Total
Phosphorus
(ug/L)
<50
>300
Total
Nitrogen
(ug/L)
<1500
>4000
Chloride
(ueq/L)
<1000
>2500
Sulfate
(ueq/L)
<10000
>15000
PH
<9
>9
Riparian
Disturbance
(W1_HALL)
<1.5
>3.0
RBS
>-2.0
>-2.8
Variables Used in Whittier Ranking to Identify least- and Most-disturbed Sites
Chemical
TN
Turbidity
Chloride
Sulfate
Habitat
%Fines
Riparian
Disturbances
Natural Fish Cover
Riparian Vegetation
Catchment Variables
Road Density
Population Density
%Urban
%Agriculture
98
-------
Appendix 6. Candidate Macroinvertebrate Metrics and Results of Range Test.
Mertric ID
Shan_e
Shan_2
Shan_10
AmphPct
BivalPct
ChiroPct
ColeoPct
CorbPct
CrCh2ChiPct
CrMolPct
DipPct
EphemPct
EPTPct
GastrPct
Iso Pet
NonlnPct
OdonPct
OligoPct
Orth2ChiPct
PlecoPct
TanytPct
Tnyt2ChiPct
TrichPct
CllctPct
FiltrPct
PredPct
ScrapPct
ShredPct
CllctTax
FiltrTax
PredTax
ScrapTax
ShredTax
BrrwrPct
ClmbrPct
ClngrPct
SprwIPct
SwmmrPct
BrrwrTax
ClmbrTax
ClngrTax
SprwITax
SwmmrTax
ChiroTax
ColeoTax
CrMolTax
DipTax
Metric Class
Diversity
Diversity
Diversity
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Composition
Feeding
Feeding
Feeding
Feeding
Feeding
Feeding
Feeding
Feeding
Feeding
Feeding
Habit
Habit
Habit
Habit
Habit
Habit
Habit
Habit
Habit
Habit
Richness
Richness
Richness
Richness
Metric Description
Shannon's Evenness Index base e
Shannon's Evenness Index base 2
Shannon's Evenness Index base 10
% Amphipoda
% Bivalvia
% Chironomidae
% Coleoptera
% Corbicula
% Cricotopus + Chironomus of Chironomidae
% Crustacea Mollusca
% Diptera
% Ephemeroptera
% EPT
% Gastropoda
% Isopoda
% Non Insect
% Odonata
% Oligochaeta
% Orthocladiinae of Chironomidae
% Plecoptera
% Tanytarsini
% Tanytarsini of Chironomidae
% Trichoptera
% Collectors
% Filterers
% Predators
% Scrapers
% Shredders
Collector Taxa Richness
Filterer Taxa Richness
Predator Taxa Richness
Scraper Taxa Richness
Shredder Taxa Richness
% Burrowers
% Climbers
% Clingers
% Sprawlers
% Swimmers
Burrower Taxa Richness
Climber Taxa Richness
ClingerTaxa Richness
Sprawler Taxa Richness
Swimmer Taxa Richness
Chironomid Taxa Richness
Coleoptera Taxa Richness
Crustacea Mullusca Taxa Richness
Diptera Taxa Richness
Range Test
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Fail
Fail
Pass
Pass
Pass
Pass
Pass
Fail
Pass
Pass
Pass
Pass
Fail
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
99
-------
Appendix 6. Candidate Macroinvertebrate Metrics and Results of Range Test (cont.).
Metric ID
EphemTax
EPTTax
OligoTax
OrthoTax
PlecoTax
PteroTax
TanytPct
TotalTax
TrichTax
BeckBI
HBI
NCBI
DomOIPct
Baet2EphPct
Hyd2EPTPct
Hyd2TriPct
IntolPct
TolerPct
IntolTax
InMolTax
TolerTax
Metric Class
Richness
Richness
Richness
Richness
Richness
Richness
Richness
Richness
Richness
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Metric Description
Ephemeroptera Taxa Richness
EPT Taxa Richness
Oligochaeta Taxa Richness
Orthocladiinae Taxa
Plecoptera Taxa Richness
Pteronarcys Taxa
Tanytarsini Taxa
Total Taxa Richness
Trichoptera Taxa Richness
Beck Biotic Index
Hilsenhoff Biotic Index
North Carolina Biotic Index
% Dominant 01 taxa
% Baetidae of Ephemeroptera
% Hydropsychidae of EPT
% Hydropsychidae of Trichoptera
% Intolerant
% Tolerant
Intolerant Taxa Richness
Intolerant Mollusca Taxa
Tolerant Taxa Richness
Range Test
Pass
Pass
Fail
Fail
Fail
Fail
Fail
Pass
Pass
Pass
Pass
Fail
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Fail
Pass
100
-------
Appendix 7. F-test Results for Candidate Microinvertebrate Metrics.
Composition
Feeding
Habit
Richness
Metric ID
Orth2ChiPct
Shan_e
DipPct
ChiroPct
EphemPct
Tnyt2ChiPct
AmphPct
OdonPct
ColeoPct
BivalPct
GastrPct
TanytPct
EPTPct
TrichPct
NonlnPct
OligoPct
CrMolPct
ShredTax
PredPct
ShredPct
PredTax
CllctTax
Scrap! ax
ScrapPct
FiltrPct
FiltrTax
CllctPct
BrrwrPct
SwmmrTax
ClngrTax
BrrwrTax
SprwITax
SprwIPct
ClmbrPct
SwmmrPct
ClngrPct
ClmbrTax
TotalTax
CrMolTax
DipTax
EPTTax
EphemTax
ChiroTax
ColeoTax
TrichTax
F
8.892
6.568
5.098
4.883
3.802
3.671
3.633
2.134
2.611
2.016
1.532
0.912
0.865
0.550
0.442
0.354
0.002
16.000
7.791
7.570
7.433
5.570
4.840
4.245
3.056
0.640
0.022
6.548
5.565
4.545
1.960
1.600
0.435
0.260
0.172
0.025
0.200
9.948
7.579
6.698
3.681
2.700
2.632
2.592
2.262
P-value
0.018
0.034
0.054
0.058
0.087
0.092
0.093
0.182
0.145
0.193
0.251
0.368
0.380
0.480
0.525
0.568
0.970
0.004
0.024
0.025
0.026
0.046
0.059
0.073
0.119
0.447
0.885
0.034
0.046
0.066
0.199
0.242
0.528
0.624
0.690
0.879
0.667
0.014
0.025
0.032
0.091
0.139
0.143
0.146
0.171
101
-------
Appendix 7. F-test Results for Candidate Microinvertebrate Metrics (cont).
Tolerance
Metric ID
TolerTax
Hyd2TriPct
DomOIPct
IntolPct
Hyd2EPTPct
IntolTax
BeckBI
HBI
Baet2EphPct
TolerPct
F
19.755
14.761
6.256
3.541
2.664
1.835
0.883
0.574
0.062
0.050
P-value
0.002
0.005
0.037
0.097
0.141
0.213
0.375
0.470
0.810
0.829
102
-------
Appendix 8. R2 Values for Final Metrics.
Metric ID
Shan_e
ChiroPct
DipPct
Orth2ChiPct
PredPct
ShredPct
CllctTax
PredTax
ScrapTax
ShredTax
BrrwrPct
SwmmrTax
CrMolTax
DipTax
TotalTax
DomOIPct
Hyd2TriPct
TolerTax
Shan_e
1.00
0.11
0.04
0.76
0.05
0.24
0.88
0.76
0.43
0.67
0.16
0.19
0.26
0.81
0.89
0.83
0.36
0.71
ChiroPct
0.11
1.00
0.91
0.12
0.33
0.30
0.06
0.10
0.17
0.23
0.98
0.08
0.49
0.18
0.14
0.26
0.25
0.39
DipPct
0.04
0.91
1.00
0.09
0.35
0.24
0.01
0.08
0.17
0.11
0.92
0.11
0.41
0.09
0.08
0.11
0.16
0.29
Orth2ChiPct
0.76
0.12
0.09
1.00
0.04
0.41
0.70
0.83
0.64
0.61
0.21
0.33
0.19
0.82
0.91
0.48
0.27
0.75
PredPct
0.05
0.33
0.35
0.04
1.00
0.28
0.01
0.04
0.00
0.29
0.30
0.18
0.26
0.00
0.03
0.20
0.49
0.18
ShredPct
0.24
0.30
0.24
0.41
0.28
1.00
0.28
0.20
0.45
0.62
0.37
0.10
0.33
0.30
0.35
0.31
0.29
0.69
CllctTax
0.88
0.06
0.01
0.70
0.01
0.28
1.00
0.59
0.46
0.70
0.09
0.11
0.27
0.86
0.87
0.65
0.35
0.68
PredTax
0.76
0.10
0.08
0.83
0.04
0.20
0.59
1.00
0.52
0.46
0.18
0.53
0.12
0.72
0.86
0.56
0.29
0.60
ScrapTax
0.43
0.17
0.17
0.64
0.00
0.45
0.46
0.52
1.00
0.29
0.27
0.10
0.26
0.64
0.67
0.27
0.04
0.74
103
-------
Appendix 8. R2 Values for Final Metrics (cont.).
Metric ID
Shan_e
ChiroPct
DipPct
Orth2ChiPct
PredPct
ShredPct
CllctTax
PredTax
ScrapTax
ShredTax
BrrwrPct
SwmmrTax
CrMolTax
DipTax
TotalTax
DomOIPct
Hyd2TriPct
TolerTax
ShredTax
0.67
0.23
0.11
0.61
0.29
0.62
0.70
0.46
0.29
1.00
0.28
0.27
0.32
0.59
0.65
0.71
0.75
0.74
BrrwrPct
0.16
0.98
0.92
0.21
0.30
0.37
0.09
0.18
0.27
0.28
1.00
0.13
0.49
0.26
0.22
0.28
0.25
0.48
SwmmrTax
0.19
0.08
0.11
0.33
0.18
0.10
0.11
0.53
0.10
0.27
0.13
1.00
0.00
0.19
0.28
0.19
0.46
0.18
CrMolTax
0.26
0.49
0.41
0.19
0.26
0.33
0.27
0.12
0.26
0.32
0.49
0.00
1.00
0.32
0.29
0.29
0.20
0.51
DipTax
0.81
0.18
0.09
0.82
0.00
0.30
0.86
0.72
0.64
0.59
0.26
0.19
0.32
1.00
0.94
0.55
0.28
0.74
TotalTax
0.89
0.14
0.08
0.91
0.03
0.35
0.87
0.86
0.67
0.65
0.22
0.28
0.29
0.94
1.00
0.64
0.32
0.81
DomOIPct
0.83
0.26
0.11
0.48
0.20
0.31
0.65
0.56
0.27
0.71
0.28
0.19
0.29
0.55
0.64
1.00
0.50
0.66
Hyd2TriPct
0.36
0.25
0.16
0.27
0.49
0.29
0.35
0.29
0.04
0.75
0.25
0.46
0.20
0.28
0.32
0.50
1.00
0.37
TolerTax
0.71
0.39
0.29
0.75
0.18
0.69
0.68
0.60
0.74
0.74
0.48
0.18
0.51
0.74
0.81
0.66
0.37
1.00
104
-------
Appendix 9. Final IBI Scores.
Station ID
8
10
19
95
110
119
128
144
170
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1300
1310
IBI
74
74
22
66
32
46
84
62
62
46
30
52
24
54
52
58
34
64
38
36
44
38
68
42
40
24
4
56
40
34
64
58
48
58
46
105
-------
Appendix 10. Periphyton
Site
Number
8
10
19
95
110
119
128
144
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1300
1310
Area
(cm2)
60
60
48
48
0
48
72
96
108
96
48
36
60
36
0
24
48
24
36
36
36
60
60
108
36
60
48
36
72
72
60
48
48
60
108
chl-a
(ug/cm2)
1.07
0.17
3.10
2.79
-
0.00
1.19
0.38
0.52
0.26
3.04
9.20
1.87
0.62
-
1.61
15.08
4.83
1.81
0.91
1.62
2.75
0.37
0.69
0.17
13.68
1.13
0.68
1.99
3.15
0.66
0.58
1.96
0.75
0.30
Biomass
AFDM/cm2
(mg/cm2)
24.35
1.06
1.57
2.79
-
0.24
1.34
4.03
1.77
4.64
3.11
1.03
0.51
5.31
-
4.46
2.24
1.48
1.22
3.73
0.00
1.68
0.60
0.75
0.17
4.85
0.78
0.88
8.67
3.41
1.01
0.90
2.02
1.15
0.33
Autotrophic Index
(Biomass/chl-a)
22739.58
6276.37
506.96
1000.00
-
-
1130.76
10703.46
3424.55
17618.51
1022.44
112.36
275.69
8605.53
-
2762.17
148.31
307.05
678.03
4090.41
-
610.52
1605.14
1089.55
1008.35
354.19
687.92
1301.01
4347.24
1084.26
1547.99
1541.14
1028.48
1542.71
1097.26
106
-------
Appendix 11. Water Metals (H9/L).
Name
Aluminum
Antimony
Arsenic
Barium
Beryllium
Cadmium
Calcium
Chromium
Cobalt
Copper
Iron
Lead
Magnesium
Manganese
Mercury
Nickel
Potassium
Selenium
Silver
Sodium
Thallium
Vanadium
Zinc
Mean
208.11
5.54
25.14
48.59
1.00
5.54
146054.05
10.00
5.27
9.08
107.03
5.46
63051.35
46.76
0.04
50.00
17432.43
23.24
5.54
168378.38
5.54
19.73
21.35
Lower 95%
Conf.
191.66
5.02
20.13
40.92
5.02
109038.48
4.68
7.11
90.38
4.91
43075.45
20.86
0.02
13748.43
20.09
5.02
127585.24
5.02
19.18
16.07
Upper 95%
Conf.
224.55
6.07
30.14
56.27
6.07
183069.63
5.86
11.06
123.68
6.01
83027.25
72.65
0.06
21116.43
26.39
6.07
209171.52
6.07
20.28
26.63
Median
200
5
20
42
1
5
80000
10
5
5
100
5
36000
12
0.03
50
13000
20
5
120000
5
20
20
Min
200
5
10
16
1
5
39000
10
3
3
60
3
5900
3
0.02
50
3000
20
5
13000
5
10
10
Max
500
10
80
130
1
10
350000
10
10
20
400
10
290000
290
0.41
50
46000
50
10
390000
10
20
90
Range
300
5
70
114
0
5
311000
0
7
17
340
7
284100
287
0.39
0
43000
30
5
377000
5
10
80
Variance
2432.43
2.48
225.68
529.91
0.00
2.48
1.23E+10
0.00
3.15
35.08
2493.69
2.70
3.59E+09
6030.52
0.00
0.00
1.22E+08
89.19
2.48
1.50E+10
2.48
2.70
250.90
Standard
Deviation
49.32
1.57
15.02
23.02
0.00
1.57
111019.00
0.00
1.77
5.92
49.94
1.64
59912.74
77.66
0.06
0.00
11049.23
9.44
1.57
122348.85
1.57
1.64
15.84
Standard
Error
8.11
0.26
2.47
3.78
0.00
0.26
18251.41
0.00
0.29
0.97
8.21
0.27
9849.59
12.77
0.01
0.00
1816.48
1.55
0.26
20114.03
0.26
0.27
2.60
107
-------
Appendix 12. Sediment Metals (mg/kg).
Name
Aluminum
Antimony
Arsenic
Barium
Beryllium
Cadmium
Calcium
Chromium
Cobalt
Copper
Iron
Lead
Magnesium
Manganese
Mercury
Nickel
Potassium
Selenium
Silver
Sodium
Thallium
Vanadium
Zinc
Size
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
36
Mean
8180.56
32.22
7.83
110.00
0.54
1.49
57111.11
8.72
5.92
7.81
7805.56
7.95
10908.33
259.17
0.07
13.22
2308.33
5.56
3.25
388.06
12.00
14.44
33.44
Lower
95% Conf.
6555.95
26.67
5.36
90.45
0.44
1.13
45382.25
6.40
4.62
6.30
6566.14
6.03
8283.67
203.70
0.02
9.65
1823.36
4.78
2.70
319.10
9.99
11.93
26.98
Upper
95% Conf.
9805.16
37.77
10.31
129.55
0.65
1.84
68839.97
11.04
7.21
9.31
9044.97
9.86
13533.00
314.63
0.11
16.79
2793.31
6.33
3.80
457.01
14.01
16.96
39.91
Median
8700
30
6
100
0.6
1
48000
8
5
7
7500
6.5
7600
220
0.04
10
2000
5
3
300
10
13
35
Min
1200
20
3
20
0.1
0.5
16000
2
3
2
2000
1.6
2800
70
0.02
6
600
2
2
70
2
4
7
Max
19000
100
40
290
1.1
6
150000
42
20
20
17000
27
38000
820
0.8
60
6000
10
10
900
30
34
81
Range
17800
80
37
270
1
5.5
134000
40
17
18
15000
25.4
35200
750
0.78
54
5400
8
8
830
28
30
74
Variance
2.31E+07
269.21
53.40
3337.14
0.09
1.12
1.20E+09
47.06
14.71
19.70
1.34E+07
32.01
6.02E+07
26870.71
0.02
111.26
2.05E+06
5.28
2.65
41536.11
35.43
55.11
364.94
Standard
Deviation
4801.54
16.41
7.31
57.77
0.30
1.06
34664.74
6.86
3.83
4.44
3663.09
5.66
7757.22
163.92
0.13
10.55
1433.35
2.30
1.63
203.80
5.95
7.42
19.10
Standard
Error
800.26
2.73
1.22
9.63
0.05
0.18
5777.46
1.14
0.64
0.74
610.52
0.94
1292.87
27.32
0.02
1.76
238.89
0.38
0.27
33.97
0.99
1.24
3.18
108
-------
Appendix 13. Sediment Metabolism
Site
Number
8
10
19
95
110
119
128
144
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
DO/AFDM/TIME
(mg/g/h)
3.06
4.55
36.51
9.04
12.94
15.16
5.87
9.17
6.13
4.93
5.48
3.12
14.98
6.31
5.76
7.16
28.76
3.12
13.92
18.36
3.96
4.27
5.96
4.33
21.62
24.78
21.56
21.33
3.56
7.65
5.83
20.91
27.06
2.61
2.60
1.53
Temp (°C)
20.9
13.3
23.8
17.9
20
28.3
18.2
22.4
23.8
28.8
17.3
15.8
27.3
16.2
26.8
21.5
20.9
18
21.9
22.4
13.9
28
29.3
25.1
30.8
25.2
26
28.5
19.4
20.3
31.1
26.1
23.5
27.8
28.8
29.8
109
-------
Appendix 14. R Values of Significant Correlations (P<0.05) between Ecological
Indicators and Stressor Indicators. For Riparian Disturbances, used Three Most
Common Forms of Disturbances.
Water Chemistry Indicators and Physical Habitat Stressors:
Water
Temperature
Conductivity
DO
PH
TKN
Chloride
Sulfate
Physical Habitat
Depth
0.359
-0.388
-0.409
-0.373
Wetted
Width
0.712
0.797
0.754
Width/Depth
0.733
-0.383
0.338
0.857
0.820
%
Bank
Shade
-0.626
-0.712
-0.616
% Mid
Channel
Shade
-0.568
-0.446
-0.597
-0.545
%
Sand/Fine
0.371
Discharge
0.374
0.470
0.515
0.494
Vegetation
Canopy
Cover
-0.423
-0.449
-0.353
-0.343
Water Chemistry Indicators and Riparian Disturbance Stressors:
Water
Temperature
Conductivity
DO
PH
Ammonia
Nitrate/Nitrite
TKN
Chloride
Sulfate
Riparian Disturbance
Wall
-0.391
Building
0.374
0.345
0.479
Pavement
0.342
0.457
0.397
Pipe
0.439
-0.420
Landfill
0.420
0.587
0.396
Mining
-0.347
All
0.373
0.358
Physical Habitat Indicators and Riparian Disturbance Stressors:
% Sand and Fine
% Pools
Discharge
Tree Cover
Riparian Disturbance
Wall
-0.391
0.614
Road
-0.423
Pasture
0.476
Landfill
-0.366
110
-------
Appendix 14. R Values of Significant Correlations (P<0.05) between Ecological
Indicators and Stressor Indicators (cont.).
Benthic Invertebrate Indicators and Water Chemistry, Physical Habitat and
Riparian Disturbance Stressors:
Richness
EPT Taxa
% Intolerant
Water Chemistry
Temp
-0.339
0.368
TKN
-0.379
Physical Habitat
Depth
0.435
Embeddedness
-0.550
% Sand/Fine
-0.603
-0.339
Vegetation
Cover-Ground
0.481
0.448
IBI
Water Chemistry
SpC
-0.587
DO
-0.384
TKN
-0.537
Chloride
-0.481
Sulfate
-0.516
Physical
Habitat
Wetted
Width
-0.355
Riparian
Disturbances
Landfill
-0.441
All
-0.500
Periphyton Biomass Indicator and Sedimentary Metal Stressors:
Biomass (AFDM/cm2)
Sedimentary Metals
Cd
0.352
Pb
0.548
Community Respiration Indicator and Water Chemistry Stressors:
Metabolism
Water Chemistry
SpC
0.791
PH
-0.415
TP
0.403
TKN
0.486
Cl
0.818
S
0.740
Community Respiration Indicator and Physical Habitat and Riparian Disturbance
Stressors:
Metabolism
Physical Habitat
Depth
-0.435
Wetted
Width
0.636
Width/Depth
0.663
%
Bank
Shade
-0.600
% Mid
Channel
Shade
-0.517
Discharge
0.408
Riparian Disturbance
Pipe
0.422
Landfill
0.359
111
-------
Appendix 15. Estimating Relative Risk Estimate for Stressors. Data Used for Calculation of Relative Risk Where
A=Least-disturbed IBI Index and Least-disturbed Stressor Metric Values, B=Most-disturbed IBI Index and Least-
disturbed Stressor Metric Values, C=Least-disturbed IBI Index and Most-disturbed Stressor Metric Values,
D=Most-disturbed IBI Index and Most-disturbed Stressor Metric Values. Relative Risk Calculated as
Type
TN
TP
SO4
Fish Cover
RipDist Road
RipDistAII
% Fine
% Sand/Fine
Embed
Indicator
Total Nitrogen
Total Phosphorus
Sulfate
Area Cover from Natural Features
Riparian Disturbance from Roads
All Riparian Disturbance
% Fine
% Sand/Fine
Embeddedness
Units
3
2
3
4
4
4
3
3
3
Indicator
3
5
4
16
13
8
14
14
7
Mean
2
1
2
1
1
1
1
1
1
Lower 95% Conf.
16
8
18
5
9
7
3
7
9
Upper 95% Conf.
1.8
1.2
1.6
1.0
1.2
1.3
0.9
1.1
1.3
112
-------
Appendix 16 - USEPA Water Quality Criteria for Trace Metals
Aquatic Life Criteria Table
Pollutant XTCAf
Number
Alkalinity —
Aluminum pH 747nn05
6.5 - 9.0 /4/yyio
Ammonia 7664417
Arsenic 7440382
Bacteria —
Boron —
Cadmium 7440439
Chloride 16887006
Chromium (111) 16065831
Chromium (VI) 18540299
Copper 7440508
Hardness —
Iron 7439896
Lead 7439921
Mercury 7439976
Methylmercurv 22967926
Nickel 7440020
Nutrients —
Oxygen, Dissolved
Freshwater 7782447
pH -
Phosphorus 7723140
Elemental
Selenium 7782492
Silver 7440224
Solids Suspended
and Turbidity
Sulfide-Hydrogen nno~n...
„ .,,. . //ojUo4
Sulfide
Temperature —
Zinc 7440666
Freshwater Saltwater
CMC1 CCC1 CMC- CCC-
P/NP* (acute) (chronic) (acute) (chronic)
(Hg/L) (ug/L) (ug/L) (ug/L)
NP 20000 C
NP 750 1 87 I,S
FRESHWATER CRITERIA ARE pH, Temperature and Life-stage
DEPENDENT
NP
SALTWATER CRITERIA ARE pH AND TEMPERATURE
DEPENDENT
P 340 A,D 150 A,D 69A,D 36A,D
FOR PRIMARY RECREATION AND SHELLFISH USES— SEE
DOCUMENT
NP NARRATIVE STATEMENT— SEE DOCUMENT
P 2.0 D,E 0.25 D,E 40 D 8.8 D
NP 860000 230000
P 570 D,E 74 D,E
P 16D 11D 1,100D SOD
D Freshwater criteria calculated using the . 8 „ , , „
1 ~T -. - ~ T-~ 4.O LJ,CC J . I LJ,CC
BLM mm - See Document — —
NP NARRATIVE STATEMENT— SEE DOCUMENT
NP 1000 C
P 65D,E 2.5 D,E 210 D 8.1 D
1.4D,hh 0.77 D,hh 1.8D,ee,hh 0.94 D,ee,hh
P
P 470 D,E 52D,E 74 D 8.2 D
See USEPA's Ecoregional criteria for Total Phosphorus, Total
NP Nitrogen, Chlorophyll a and Water Clarity (Secchi depth for lakes;
turbidity for streams and rivers) (& Level III Ecoregional criteria)
WARMWATER AND COLD WATER MATRIX— SEE
NP DOCUMENT
NP 6.5 -9 C 6.5-8.5C,P
NP
P L 5.0 290 D, dd 71 D, dd
P 3.2D,E,G 1.9D,G
NP NARRATIVE STATEMENT SEE DOCT TMENT C
NP 2.0 C 2.0 C
NP SPECIES DEPENDENT CRITERIA— SEE DOCUMENT M
P 120 D,E 120 D,E 90 D 81 D
Publication
Year
1986
1988
1999
1995
1986
1986
2001
1986
1995
1995
2007
1986
1986
1980
1995
1995
1986
1986
1986
1995
1980
1986
1986
1986
1995
"P/NP - Indicates either a Priority Pollutant (P) or a Non Priority Pollutant (NP).
113
-------
Human Health Criteria Table
Human Health for the Consumption of
Pollutant
Nutrients
CAS Number P/NP*
Water + Organism
Organism Only
Alkalinity
Aluminum pH
6.5-9.0
Antimony
Arsenic
Barium
Beryllium
Cadmium
Chromium (III)
Chromium (VI)
Copper
Manganese
Mercury
Methylmercury
Nickel
Nitrates
—
7429905
7440360
7440382
7440393
7440417
7440439
16065831
18540299
7440508
7439965
7439976
22967926
7440020
14797558
NP
NP
P
P
NP
P
P
P
P
P
NP
P
P
NP
5.6 B
0.018 C,M,S
1,000 A
Z
Z
Z Total
Z Total
1,300 U
50 Q
610 B
10,000 A
640
0.1'
100
o.:
4,6(
See USEPA's Ecoregional criteria
Publication
Year
2002
1992
1986
0.3 mg/kg J
1992
2001
1998
1986
NP
pH
Selenium
Solids Dissolved
and Salinity
Thallium
Zinc
—
7782492
—
7440280
7440666
NP
P
NP
P
P
5-9
170 Z
250,000 A
0.24
7,400 U
Total Nitrogen, Chlorophyll a and Water Clarity
(Secchi depth for lakes; turbidity for streams and
rivers) (& Level III Ecoregional criteria)
4200
0.47
26,000 U
1986
2002
1986
2003
2002
*P/NP - Indicates either a Priority Pollutant (P) or a Non Priority Pollutant (NP).
114
-------
Parameter
Criteria
Units
Temperature
pH
Conductivity
Dissolved Oxygen
Turbidity
TDS
TSS
Nitrite (NO 2)
Nitrate (NO"3)
Total Kjeldahl
Nitrogen(TKN)
Ammonia (NH3)
Total Phosphorus
Orthophosphate
TOC
Sulfate
Sulfide
Alkalinity
Hardness
17
6.0-8.5
800
5.0
25/3
500
1000
1
10
1.2
0.1
0.05
4.0
60
2.0
20
°C change
pH units
|lS/cm
mg/L
Stream/Lake NTU
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
ug/L
ug/L
mg/L
mg/L
Parameters for Calculating Freshwater Dissolved Metals Criteria That Are Hardness-Dependent
Freshwater Conversion Factors (CF)
CMC CCC
1.136672- 1.101672-
[(/«hardness)(0.041838)] [(/«hardness)(0.041838)]
Chromium III 0.8190 3.7256 0.8190 0.6848 0.316 0.860
Chemical
Cadmium
niA !JA nic be
1.0166 -3.924 0.7409 -4.719
Copper
Lead
Nickel
Silver
Zinc
0.9422 -1.700 0.8545 -1.702 0.960
1.46203-
1.273 -1.460 1.273
-4.705
0.960
1.46203-
[(/«hardness)(0.145712)] [(/whardness)(0.145712)]
0.8460 2.255 0.8460 0.0584 0.998 0.997
1.72 -6.59 — — 0.85 —
0.8473 0.884 0.8473 0.884 0.978 0.986
Hardness-dependant metals'criteria maybe calculated from the following:
CMC (dissolved) = exp{mA [ln(hardness)]+ bA} (CF)
CCC (dissolved) = exp{mc [ln(hardness)]+ bc} (CF)
115
-------
-------
&EPA
United States
Environmental Protection
Agency
Office of Research
and Development (8101R)
Washington, DC 20460
Please make all necessary changes on the below label,
detach or copy, and return to the address in the upper
left-hand corner.
If you do not wish to receive these reports CHECK HERE D;
detach, or copy this cover, and return to the address in the
upper left-hand corner.
PRESORTED STANDARD
POSTAGE & FEES PAID
EPA
PERMIT No. G-35
Official Business
Penalty for Private Use
$300
EPA/600/R-14/256
October 2014
www.epa.gov
Recycled/Recyclable
Printed with vegetable-based ink on
paper that contains a minimum of
50% post-consumer fiber content
processed chlorine free
------- |