&EPA
EPA/600/R-12/605 | August 2012 www.epa.gov/research
United States
Environmental Protection
Agency
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EPA R-EMAP Humboldt Basin Project
RESEARCH AND DEVELOPMENT
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Ecological Condition of
Streams in Northern Nevada
EPA R-EMAP
Humboldt Basin 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
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Table of Contents
Forward v
Acknowledgements vii
Executive Summary ix
Acronyms and Abbreviations xi
Glossary xiii
List of Tables xv
List of Figures xvii
List of Appendices xxi
I. Introduction 1
II. Basin Description 3
III. Project Description 7
A. Design - Selection of Stream Sites 7
B. Indicators - What to Measure at Each Selected Site? 15
IV. Analysis and Results 15
A. Water Column Chemistry 16
B. Physical Habitat Indicators 24
C. Biological Indicators 36
D. Sediment Respiration 42
E. Metals 44
F. Relationships Between Indicators and Stressors 55
G. Thresholds 57
V. Conclusion 64
VI. References 67
VII. Appendices 75
in
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IV
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Forward
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 Humboldt River Basin in northern 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.
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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 Humboldt River Basin. 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,
David Bradford and Sherman Swanson.
Notice
The information in this document has been funded in pan 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.
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Executive Summary
This report summarizes data collected from the wadeable streams in the Humboldt River Basin 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 Humboldt River Basin. 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 this project was to assess the water quality and biotic integrity of perennial and
intermittent streams over a three year sampling period for the Humboldt River Basin, using a combination
of macroinvertebrates, physical habitat measurements, water and sediment chemistry, and sediment
metabolism. The objectives of the Humboldt River R-EMAP were to describe the condition of surface
waters, relate ecological conditions to ecological stressors and examine relative risks to streams within the
Basin.
The report presents data collected during a three year study period beginning in 1998. 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 69 sample sites were sampled and ten of the 1998 sites
were revisited to capture seasonal variations.
This study has provided a substantial baseline data set for the Basin. While the percentage of impacted
streams varied, 38% 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 and 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 Humboldt
River Basin.
IX
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Acronyms and Abbreviations
AFDM Ash Free Dry Mass
BLM Bureau of Land Management.
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
NLCD National Land Cover Data
R-EMAP Regional Environmental Monitoring and Assessment Program.
SpC Specific Conductance
SEC Sediment Effect Concentration
UNR University of Nevada, Reno
USEPA United States Environmental Protection Agency
USFWS United States Fish and Wildlife Service
USGS United States Geological Survey
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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 waterbodies.
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.
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Glossary (cont.)
Riffle - An area of the stream with relatively fast currents and cobble/gravel substrate.
Sand - Small but visible particles between 0.06 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.
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List of Tables
Table 1. General EMAP Indicators 10
Table 2. Water Column Indicators 11
Table 3. Streams in the Humboldt River Basin by Stream Order 15
Table 4. Water Quality Standards for Nevada 17
Table 5. Nutrients in the Humboldt River Basin, Expressed as mg/L 19
Table 6. Definition of LWD Classes Based of Length and Diameter per 100m of
Stream Sample 26
Table 7. Mean LWD Quantity per 100m by Size Class by Streams Order 26
Table 8. Percent of Stream Substrate Sample Dominated by Major Substrate Classes 27
Table 9. Riparian Vegetation Category and Associated Height 30
Table 10. Index of Fish Cover Presence 33
Table 11. Riparian Disturbance Proximity to Stream and Associated Score 34
Table 12. Levels of Human Influence 35
Table 13. Description of Benthic Macroinvertebrate Indicator Metrics
(Resh and Jackson, 1993 andResh, 1995) 37
Table 14. Summary Statistics for Macroinvertebrate Metrics 39
Table 15. Final Metrics and Ceiling/Floor Values 41
Table 16. National Recommended Water Quality Criteria for Toxic Pollutants 44
Table 17. Summary of Selected Screening Level Concentration-Based Sediment Quality
Benchmarks for Freshwater Sediments 45
Table 18. 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' 46
Table 19. Possible Combinations of Stressors and Indicator Relationships 55
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Table 20. Thresholds for the Humboldt River Basin 57
Table 21. Relative Risk Analysis 62
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List of Figures
Figure 1. Ecoregions of the Humboldt River Basin 4
Figure 2. NLCD 2000 land cover for Humboldt River Basin 5
Figure 3. Location of the Humboldt Rivers and Main Tributaries 6
Figure 4. Humboldt River Basin Sample Sites 9
Figure 5. Example of a Cumulative Distribution Function (CDF) Showing a
Threshold Between Impared and Functional and the Associated Proportion of
Stream Length in Each Catagory 15
Figure 6. Cumulative Distribution Function and Condition Estimate of sStream
Total Phosphorus 17
Figure 7. Cumulative Distribution Function and Condition Estimate of pH
Of Streams 18
Figure 8. Cumulative Distribution Function and Condition Estimate of Stream
Conductivity 18
Figure 9. Cumulative Distribution Function and Condition Estimate of Stream
Dissolved Oxygen 19
Figure 10. Cumulative Distribution Function and Condition Estimate of Stream
Total Phosphorus 20
Figure 11. Total Phosphorus in Relation to Species Richness in all Sampling Sites 20
Figure 12. Cumulative Distribution Function and Condition Estimate of Stream
Nitrate Levels 21
Figure 13. Nitrate in Relation to Species Richness in all Sampling Sites 22
Figure 14. Cumulative Distribution Function and Condition Estimate of Stream
Total Kjeldahl Nitrogen 22
Figure 15. Cumulative Distribution Function and Condition Estimate of Stream
Ammonia 23
Figure 16. Cumulative Distribution Function and Condition Estimate of Stream
Chloride Levels 24
Figure 17. Strahler Stream Order (FISRWG 1998) 25
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Figure 18. Relationship Between Thalweg Depth and Wetted Width in Relation
to Stream Order 25
Figure 19. Percent of Streambed with Dominant Particle Size 27
Figure 20. Substrate Size by Stream Order 28
Figure 21. Cumulative Distribution Function of Condition Estimate
of Streambed Stability 29
Figure 22. Frequency of Pools by Depth Class 29
Figure 23. Percent Vegetation Cover by Vegetation Class 30
Figure 24. Percent Samples with Vegetation Cover by Class in Relation
to Stream Order 31
Figure 25. Mean Percent Riparian Canopy Cover by Species Type 31
Figure 26. Cumulative Distribution Function and Condition Estimate of
Mean Canopy Shade 32
Figure 27. Cumulative Distribution Function and Condition Estimate of
Mid-Channel Canopy Shade 32
Figure 28. Percent Mid-Channel and Bank Shade by Stream Order 33
Figure 29. Natural Fish Cover 34
Figure 30. Percentage of Riparian Zone Human Influences on Stream Reaches 35
Figure 31. Mean Riparian Zone Human Influence by Type 36
Figure 32. Cumulative Distribution Function and Condition Estimate of Total
Taxa Richness 37
Figure 33. Cumulative Distribution Function and Condition Estimate of EPT
Taxa Richness 38
Figure 34. Cumulative Distribution Function and Condition Estimate of Percent
Intolerant Taxa 38
Figure 3 5. Percent Functional Feeding Groups in Relation to Stream Order 40
Figure 36. Cumulative Distribution Function and Condition Estimate of
Macroinvertebrate IBI 42
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Figure 37. Map of Sediment Respiration Levels in the Humboldt Basin 43
Figure 38. Cumulative Distribution Function and Condition Estimate of
Aluminum in Stream Water and Sediment 47
Figure 39. Cumulative Distribution Function and Condition Estimate of
Arsenic in Stream Water and Sediment 48
Figure 40. Cumulative Distribution Function and Condition Estimate of
Copper in Stream Water and Sediment 49
Figure 41. Cumulative Distribution Function and Condition Estimate of
Iron in Stream Water and Sediment 50
Figure 42. Cumulative Distribution Function and Condition Estimate of
Lead in Stream Water and Sediment 51
Figure 43. Cumulative Distribution Function and Condition Estimate of
Manganese in Stream Water and Sediment 52
Figure 44. Cumulative Distribution Function and Condition Estimate of
Mercury in Stream Sediment 53
Figure 45. Cumulative Distribution Function and Condition Estimate of
Zinc in Stream Water and Sediment 54
Figure 46. Relationship between Total Dissolved Solids and EPT Taxa 56
Figure 47. Relationship between Percent Fines and Macroinvertebrate IBI 56
Figure 48. Relationship between Temperature and Sediment Metabolism 57
Figure 49. Extent of Stream Length in Most-Disturbed, Intermediate and Least-Disturbed
Condition for Selected Water Quality Indicators and Macroinvertebrate IBI 59
Figure 50. Extent of Stream Length in Most-Disturbed, Intermediate and Least-Disturbed
Condition for Selected Physical Habitat Indicators 60
Figure 51. Extent of Stream Length in Most-Disturbed, Intermediate and Least-Disturbed
Condition for Sediment Indicators 61
Figure 52. Summary Relative Extent of Stressors (Proportion of Stream Length with
Stressors in Most-Disturbed Condition) 61
Figure 53. Risk to Benthic Assemblage (IBI) Relative to the Environmental
Stressor Condition 63
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Figure 54. Summary of Extent of Stressors in Most-Disturbed Condition in Relation
to Relative Risk 64
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Appendices
Appendix 1. List of Sites 75
Appendix 2. Summary Statistics for Water Chemistry Indicators for the
Humboldt Basin 77
Appendix 3. Summary Statistics for Physical Habitat Metrics 78
Appendix 4. Streambed Stability 86
Appendix 5. Summary Statistics for Macroinvertebrate Metrics 90
Appendix 6. Criteria Used to Determine Least-Disturbed and Most-Disturbed Sites 91
Appendix 7. Candidate Macroinvertebrate Metrics and Results of Range Test 92
Appendix 8. F-Test Results for Candidate Microinvertebrate Metrics 94
Appendix 9. R2 Values for Redundancy Test 96
Appendix 10. Final IBI Scores 98
Appendix 11. Sediment Respiration 100
Appendix 12. Water Metals (|ig/L) 102
Appendix 13. Sediment Metals (mg/kg) 103
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 104
Appendix 15. 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)] 108
Appendix 16. USEPA Water Quality Criteria for Trace Metals 109
Appendix 17. Calculation of Freshwater Ammonia Criterion 113
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I. Introduction
Nevada's landscape is comprised primarily of arid and montane ecosystems (Omernik, 1987), and water
is of primary importance in both the economy and ecology of the region. Although most regions in the
United States have well established stream monitoring programs, many of the waters of Nevada have
received little attention in regards to systematic bioassessment prior to this study. The Humboldt River
Basin is of interest to water quality managers due to potential human impacts, and/or lack of adequate
historical baseline data.
The Humboldt Drainage Area is sparsely populated with only one town (Elko) having a population of
over 15,000 (Figure 3). Fewer than 70,000 persons reside within the Humboldt Drainage. Sixty-six
percent of the basin is owned by the Federal Government and managed by the National Forest Service.
Thirty-two percent is privately owned and the remainder is held by Native Americans, State lands and
other Federal holdings.
There are a number of potential water quality impacts from anthropogenic sources in the Humboldt Basin,
including mining, cattle grazing, irrigated agriculture, and recreation. In the late 1800s, heavy grazing led
ranchers to supplement feed with water dependant hay crops, creating water conflicts. By the 1900s,
grazing-induced vegetation destruction and subsequent erosion was apparent. To date, all federal lands
are still used for grazing, creating pressures on the drainage system. Substantial effects on riparian and in-
stream resources have occurred, including streambank trampling, channel straightening and channel
incision. Rye Patch Dam, located 22 miles upstream of the Humboldt Sink, is one of the basin's
reservoirs. Because most of this water is diverted for irrigation for farmers, the Humboldt River only
reaches the sink during high water years (Glennen, 2002).
The Nevada silver boom began in the late 1800s and depended heavily on large amounts of wood for fuel.
Deforestation became evident near local mining towns. In the early 1900s gold mining was becoming
more prevalent, and today Nevada is the third largest producer of gold globally. Much of this gold is
mined in the Carlin Trend, which is a 50-by-5 mile belt within the Humboldt Basin. The belt is
characterized by very small gold particles, requiring extensive methods of removal. In 2000, numerous
gold mines were in operation, some over two thousand feet deep. These open pit mines are often below
the water table making it necessary to remove groundwater in order to facilitate mining activities. Pumped
waters are frequently discharged to surface-receiving water, creating the possibility for chemical and/or
thermal pollution or they are more recently used for agriculture.
Additionally, the groundwater resources being depleted are drawing down the water table. Questions have
arisen concerning the impacts of this extensive pumping. Pit lakes, one probable effect, form in the void
left once a mining project and groundwater pumping ceases and have the potential to create long-term
impacts. If the water is contaminated, it may flow to down-gradient groundwater or evaporate to become
a hazard for surrounding wildlife (Solnit, 2000).
Abandoned mines also pose issues relating to water quality in the region. In the state of Nevada, there are
over 150,000 known abandoned hardrock mines, many within the Humboldt River Basin (Nash, 2000).
Mine waste is known to impact water quality by increasing suspended solids, metal content and acidity.
Other impacts could include effects from chemicals used from mine processes, trash, and the erosion of
mine waste into stream channels.
For future management of the Humboldt River Basin stream sources, water managers and environmental
managers will need comprehensive historical data to address the above potential issues. The goal of this
report is to provide a sound set of baseline data to support those management efforts.
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II. Basin Description
The Humboldt River Basin study area is mainly within subecoregion (i.e., ecoregion Level III) 13
(Central Basin and Range), which is generally characterized by a wide variety of habitats ranging from
salt flats and sagebrush (Artemesia spp.) dominated basins to subalpine zones in montane environments
(Figure 1). The northern portion of the basin is a part of subecoregion 80 (Northern Basin and Range).
The lower elevation basin areas of subecoregion 13 receive low amounts of rainfall, but are characterized
as semi-desert, as they receive more than 15 cm of precipitation per year. The low annual precipitation for
this subecoregion is both a function of distance from the Pacific Ocean and the rain-shadow effects of the
Sierra Nevada mountain range.
Despite the characterization of the Central Basin and Range subecoregion as having ponderosa pine
(Pinus pondersosd) forests, few if any Ponderosa forests exist in the Humboldt River Basin. Forests in the
Humboldt River Basin are generally Pinyon Pine (Pinus edulis) and Juniper (Juniperus osteosperma and
occidentalis) dominated with upper elevations consisting of aspen (Populus tremuloides), bristlecone pine
(Pinus longaevd), white fir (Abies concolof), Limber pine (Pinus flexilis), and white bark pine (Pinus
albicaulis). The low altitude plains and valleys, which comprise most of the watershed, have sagebrush
(Artemisia sp.), bunch grasses and invasive nonnative cheatgrass (Bromus tectorum). The lower basin is
dominated by shadscale (Atriplex confertifolid) and black greasewood (Sarcobatus vermiculatus) (Benke
and Gushing, 2005). Figure 2 shows the general land cover for the Humboldt River Basin.
The Humboldt River Basin drainage covers an area of approximately 27,359 square kilometers (17,000
square miles) in the Great Basin, between Latitude 41°50' in the north and 38° 45' in the south. The
system generally drains northeast to southwest, with several major tributaries draining from the south or
north into the main stem (Figure 3). The snowmelt from the Jarbidge, Independence and Ruby Mountain
ranges are the primary source of water in the basin. 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. Volcanic rocks dominate the basin which can influence water chemistry.
The main tributaries to the Humboldt are the Reese, Marys, South, North and East Fork of the Humboldt,
and the Little Humboldt Rivers. Marys River originates in the Jarbidge Mountain range, and is considered
to be the headwaters of the Humboldt River. The mainstem of the Humboldt River is one of the longest
rivers in the Great Basin having an aerial extent of 483 kilometers (300 miles), 1610 meandering
kilometers (1000 meandering miles), from the headwaters to its terminus within the Humboldt Sink, south
of Lovelock, at an elevation of 1185 meters. Stream flow is at a maximum at Palisade Canyon with
streams downriver occasionally or often stopping before entry into the mainstem. As a function of this,
environmental conditions within and between lotic systems in this drainage are highly variable.
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Location Map
Ecoregion
IVEcoregions
High Elevation Carbonate Mountains
Wetlands
Lahontan andTonapah Playas
Lahontan Salt Shrub Basin
Lahontan Sagebrush Slopes
Lahontan Uplands
Upper Humboldt Plains
Mid-Elevation Ruby Mountains
High Elevation Ruby Mountains
Carbonate Sagebrush Valleys
Carbonate Woodland Zone
Central Nevada High Valleys
Central Nevada Mid-slope Woodland and Brushland
Central Nevada Bald Mountains
Upper Lahontan Basin
Dissected High Lava Plateau
Semiarid Hills and Low Mountains
High Lava Plains
Serniarid Uplands
Partly Forested Mountains
Figure 1. Ecoregions of the Humboldt River Basin (Omernik, 1987).
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EH
EEl
EH
Boundary
Cover
Open Water
Urban
Barren Rock/Sand/Clay
Deciduous Forest
Evergreen Forest
Mixed Forest
Shrub/Scrub
GrasslanoyHerbaceous
Pasture/Hay
Cultivated Crops
Woody Wetlands
Emergent Herbaceous Wetlands
No Data
Figure 2. National Land Cover Data 2001 for Humboldt River Basin (Homer, Dewitz, Fry, Coan, Hossain, Larson,
Herold, McKerrow, VanDriel, Wickham, 2007).
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Humboldt River Basin
N
Ruby Mountains
20 0 20 40 Kilometers
Location Map
Figure 3. Location of the Humboldt Rivers and Main Tributaries.
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III. Project Description
This report summarizes data collected from the wadeable streams in the Humboldt River Basin
Watershed. The determination of current status is a critical step in the future management of this 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 Humboldt River Basin. 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, 1997).
The goal of the this project was to assess the water quality and biotic integrity of perennial and
intermittent streams over a three year sampling period for the Humboldt River Basin, using a combination
of macroinvertebrates, physical habitat measurements, water and sediment chemistry, and sediment
metabolism. The objectives of the Humboldt River R-EMAP were to:
• Describe the ecological condition of surface waters in the Humboldt Basin.
• 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 Humboldt Basin.
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 version 3 (RF3)
1:100,000 scale Digital Line Graph (DLG) as a sample frame to represent the wadeable streams.
For the Humboldt River Basin Study, sites (Figure 4) were assessed for accessibility based upon the
knowledge of Dr. Gary Vinyard, who had more than 20 years of field experience in the Humboldt River
Basin, 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, 1994) over
the Humboldt River Watershed. 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 Humboldt River
Basin. The selection was weighted by stream length where more sites were selected for higher order
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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 Humboldt River Watershed
• Equal representation of stream courses
• Equal representation by year for the two study years of 1998 and 1999
• Detection of trends in a set of indicators by revisiting at least 10% of the sites sampled the previous
year (Stevens & Olson, 1991)
Optimal statistical representation of aquatic resources in the Humboldt Watershed 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 stastical extent
of the Humboldt River Basin resource was estimated at 12,427 km stream length.
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Humboldt River Basin
Legend
Sample Points
Basin Boundary
Hydrologic Units
Figure 4. Humboldt River Basin Sample Sites.
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B. INDICATORS - What to 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 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
used to indicate ecosystem stress.
be
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 1998; 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
10
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temperature (°C), specific conductance (SpC), nitrate (NO3), 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.
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
(Herlihyetal. 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.
11
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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.
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.
12
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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 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.
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).
13
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14
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IV. Analysis and Results
Using the R-EMAP protocols described, data was collected from 69 sites in the Humboldt River Basin, of
which five did not have continuous water flow. Site 101 is outside the designated Humboldt River Basin,
it is still reported on here for analysis. Physical habitat parameters were collected from all sites, and water
quality samples were collected from the 66 sites with adequate water flow. Benthic invertebrates were
collected from the 64 sites with continuous water flow. In the Humboldt River Basin, stream order, which
classifies stream size based on a hierarchy of tributaries, ranged from first to sixth order streams, with the
majority of samples taken in the second, third and fourth order streams (Table 3).
Table 3. Streams in the Humboldt River Basin by Stream Order.
Stream Order
1
2
3
4
5
6
# of Samples
2
18
21
22
4
2
% Total
2.9
26.1
30.4
31.9
5.8
2.9
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 Humboldt River Basin had a value greater than or equal to the value
selected on the x-axis. For example, Figure 5 shows that approximately 78% of the stream length has a
measurement of Total Phosphorus of < 0. 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.
15
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100-
90-
80-
70-
60-
50-
40-
30-
20-
10-
Functi
Impaired
- 3890
3501
3112
2723 -.
E
:nal
USEP A Aquatic Life Use Standard
2334
1945
1556
1167
• 778
ta
E
fS
389
0.05 0.1 0.15
Total Phosphorus (mg/l)
0.2
0.25
Figure 5. Example of a Cumulative Distribution Function (CDF) Showing a Threshold (0.1 mg/l) between
Impaired and Functional Condition for Total Phosphorus and the Associated Proportion of Stream Length
Sampled (left Y axis) and Extent of Stream Length Sampled (right Y axis) in each Category.
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).
16
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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 nS/cm
>5 mg/L (non-trout waters)
>6 mg/L (trout waters)
Data for water column indicators were collected from 66 sites in 1998 and 1999. Sites 139, 230 and 257
did not have adequate water for analysis. There were also nine revisit sites for water quality in 1999
which were averaged. 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.
Temperature
Water temperature is temporally variable and can vary daily and seasonally and by elevation, thus a single
measure of water temperature is limited in determining stream conditions. However, over the sampling
period, water temperature ranged from 8.2 to 27.7°C over all samples with a mean temperature of 17.7°C
(see Figure 6). Using Nevada State criteria as a reference, at the time of sampling, five samples exceeded
the 24°C standard and 22 sites exceeded the 20°C standard. Figure 6 shows the CDF and condition
estimate using 20°C as the condition standard.
100
90
SO
70
60
I 50
£
40
30
20
10
0
3890
3501
3112
2723 _
2334 j
s
1945 J
|
1556 £
tn
1167
778
389
0
13 IS 23
Temperature (°C)
Temperature
IGOOD BPOOR
Figure 6. Cumulative Distribution Function and Condition Estimate for Stream Water Temperature.
17
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Another important water column variable, hydrogen ion activity (pH), is a numerical measure of the
concentration of the constituents that determine water acidity. It is measured on a logarithmic scale of 1.0
(acidic) to 14.0 (basic) with 7.0 being neutral. The pH of the sampled sites ranged from 6.6 to 11.7 with a
mean of 8.3 (Figure 7). Three samples were greater than the standards for Nevada. Measurements of pH
collected during the day are typically elevated as CO2 is depleted due to photosynthesis which effectively
shifts the pH up. The condition standard determined by the authors using the standards and best
judgement for this pH analysis was: 0 to 6.5, poor; 6.6 to 8.9, good; 9 and above, poor.
• GOOD BPOOR 1NODATA
Figure 7. Cumulative Distribution Frequency and Condition Estimate 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 standard for specific conductance is 800 (iS/cm.
Five samples exceeded this standard. Conductivity ranged from 53 to 1514 |iS/cm with a mean of
328 |iS/cm. Figure 8 shows the CDF and condition estimate. 800 (iS/cm was used as the condition
estimate standard.
100
90 -
80 -
70 -
60 -
I 50 -
£
40 -
30 -
20 -
10 -
0 -
3890
3501
3112
2723 _
2334 ~
1945 jj
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1556 3
V,
1167
778
3B9
0
50
450 650 850 1050 1250 1450
Conductivity (uS/cm)
Conductivity
•GOOD IPOOR
Figure 8. Cumulative Distribution Frequency and Condition Estimate of Stream Conductivity.
18
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Dissolved Oxygen
Dissolved oxygen (DO) is simply the amount of gaseous oxygen (O2) 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 variable. Thus, single point-in-
time DO measurements may not reflect important diel patterns. DO values ranged from 2.4 to 15.5 mg/L
with a mean of 8.1 mg/L among samples (Figure 9). The condition estimate used for DO as determined by
the authors using the standards and best judgement was below 5 poor, between 5 and 9 good, and above 9
poor.
6 S 10 12
Disolved Oxygen (mg/l)
Dissolved Oxygen
IGOOD BPOOR 1MODATA
Figure 9. Cumulative Distribution Frequency and Condition Estimate of Stream Dissolved Oxygen.
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 eight water nutrient
parameters were collected at all sites but not for all years. Water samples were analyzed for chloride,
ammonia, nitrite, nitrate, total Kjeldahl nitrogen, phosphorus, total phosphorous (TP), and sulfate. Five
nutrients were selected for condition analysis and are shown in Table 5.
Table 5. Nutrients in the Humboldt River Basin, Expressed as mg/L.
Indicator
Total Phosphorus
Nitrate
Total Kjeldahl Nitrogen
Ammonia
Chloride
Mean
0.07
0.05
0.23
0.04
17.58
Min
0.01
0.02
0.06
0.01
0.2
Max
0.20
0.65
1.2
0.1
204.2
19
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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. Samples for total phosphorus (TP) in the Humboldt River Basin ranged from 0.01 to 0.20 mg/L
with a mean of 0.07 mg/L (Table 5). The state of Nevada water quality standard for TP is 0.1 mg/L. Ten
sites had TP levels above the Nevada water quality standard. The condition estimate level was set at 0.1
mg/1 for total phosphorus. Figure 10 shows that in the Humboldt River Basin the ecological condition for
total phosphorus is good in 84 percent of the Basin and in poor condition in 12 percent.
100
90
SO
70
60
| 50
!
40
30
20
10
3890
3501
3112
2334 j
s
1945 S
E
- 1556 £
1167
778
3E9
0.1 0-15
Total Phosphorus (mg/l)
Total Phosphorus
I GOOD HPOOR • NO DATA
Figure 10. Cumulative Distribution Frequency and Condition Estimate of Stream Total Phosphorus.
Phosphorus is an essential nutrient for plant and bacterial activity. Yet, an excess of phosphorus may
reduce habitat, disrupting ecological cycles and affecting macroinvertebrate communities. In the
Humboldt River Basin, there was no apparent correlation between TP level and macroinvertebrate species
richness (Figure 11).
A^
40 -
"V-i
* 30
o ou
c
•5 ?*,
'&.
HI 20
8
Q. 1^ -
w ID
10 -
5 _
• %»
•
• **\t
* » 4»
* I
*\ * •
»»» s
» 1 * » »
•
> • % *
•
USEPA Aquatic Life Use Standard for TP = 0. 1
0 0.05 0.1 0.15 0.2 0.25 0.3
Total Phosphorus (mg/L)
Figure 11. Total Phosphorus in Relation to Macroinvertebrate Species Richness in Sampling Sites.
20
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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.
In the Humboldt River Basin, nitrite and nitrate samples were only taken in the 1998 sampling period.
All nitrite values were at or below the detection limit of 0.02 mg/L. Total Nitrogen was not calculated for
this study because nitrite and nitrate measurements were only made the first year. The analysis of the first
year survey data for nitrate can be found in Figure 12. The nitrate level for condition determination was
set at 0.3 mg/1 Figure 12. Ninety-one percent of the stream length was found to be in good ecological
condition for nitrate and 8 percent was found to be in poor condition.
100
90
SO
70
60
I 50
£
40
30
20
10
778 E
I
0-2 0-3 0.4
Nitrate (mg/l)
Nitrate
• GOOD 1POOR BNODATA
Figure 12. Cumulative Distribution Frequency and Condition Estimate of Stream Nitrate Levels for 1998.
21
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Nitrogen is another nutrient that can affect macroinvertebrate communities, yet there was no apparent
correlation between nitrate and species richness (Figure 13).
AC.
4f)
Vi
» »*
; »
L *
•
•
*
R=0.131, P=0.301, n=64
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
Nitrate (mg/L)
Figure 13. Nitrate in Relation to Macroinvertebrate Species Richness in Sampling Sites.
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 14) shows that the TKN condition estimate for the Humboldt
River Basin is about 84 percent below that level which is considered in good condition and that 12
percent is above that level and is considered in ecologically poor condition.
100
90
SO
70 •
60
! 50 -
40 -
33
23
10
0
3890
3501
3112
2723
2334
- 1945
1556
1167
778
389
0
0.25 0.45 0.65 0.85 1.05
Total Kjeldahl Nitrogen (me/I)
Total Kjeldahl Nitrogen
• GOOD IPOOR BNODATA
Figure 14. Cumulative Distribution Frequency and Condition Estimate of Stream Total Kjeldahl Nitrogen.
22
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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 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 15) to be in good condition in 96 percent of the Humboldt
River Basin samples.
100
90
80
70
60 -
! 50 -
40
30
20
10
0
0.05 0.07
Ammonia (mg/l)
• GOOD BPOOR • NO DATA
Figure 15. Cumulative Distribution Frequency and Condition Estimate of Stream Ammonia.
Chloride
Chloride, present in all natural waters at low levels, is considered a good indicator as it is involved in few
reactions relative to other ions (Feth, 1981). The worldwide chloride mean concentration in rivers is
7.8 mg/1, 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 recommended
USEPA standards for beneficial uses in the Humboldt River Basin is <250.0 mg/L. Chloride samples
ranged from <0.2 to 204.2 mg/L in the Humboldt River Basin, with a mean of 17.6 mg/L. The condition
level for chloride in water was set at 250 mg/1. As found in Figure 16, none of the stream condition for
chloride was shown to be in poor ecological condition.
23
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100
90 •
SO
70
60
50 •
40
30
20 •
10
0 •
3890
3501
3112
2723
2334
1945 -
1556
1167
778
389
0
40 60 SO
Chloride (mg/l)
Chloride
• GOOD 1POOR
Figure 16. Cumulative Distribution Frequency and Condition Estimate of Stream Chloride Levels.
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 17). Stream orders for sampling sites are listed in Appendix 1.
24
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Figure 17. Example of Strahler Stream Order (FISRWG 1998).
Stream order was related to stream wetted width and depth for all stream orders combined (R=0.678, P=0.000) (Figure
18). The two first order streams were shallow and narrow. The second (R=0.770), third (R=0.780), four (R=0.756) and
fifth (0.444) order streams exhibited a positive correlation between depth and wetted width. There were two, sixth order
streams that were relative in size. Because data were collected over a period of many weeks, observed values do not
reflect a constant channel measurement. Water width/depth ratio would be expected to vary at each site and data do not
usually reflect bankfull width/depth ratios.
For all stream orders, mean stream wetted width ranged from 0.00 m (dry stream beds) to 16.68 m and averaged
3.03 m. Mean depth ranged from 0.00 cm to 110.49 cm with a mean of 23.79 cm.
190
100 -
80
?
o_
IT 60 -
Q.
-------
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. The quantity, type and size of LWD
recruited to channel from the riparian zone and from hillslopes are important to stream function in
channels that are influenced by LWD of various sizes. 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 and sorting of spawning-sized gravel.
LWD data were only collected during the 1998 sampling period. The data were then compiled into classes
based on length and diameter of each piece (Table 6). No medium or large class pieces were identified
and counted (Table 7). Most small and very small LWD were found at site 92, a second order stream
located east of Rye Patch Reservoir at the base of Humboldt Mountain Range.
Table 6. Definition of LWD Classes Based on Length and Diameter (Kaufmann, 1999).
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
Table 7. Mean LWD Quantity Per 100m by Size Class and Streams Order.
Size Class
Very small
Small
All
35.58
8.67
Stream Order
1st
0
0
2nd
35.30
8.67
3rd
0.28
0.00
4th
0
0
5th
0
0
6th
0
0
Substrate
Substrate describes the grain size of particles on the stream bottom and ranges from boulders to mud.
Stream substrate is influenced by many factors including geology, transport capacity and channel
characteristics.
Gravel (2 to 64 mm) was the most common substrate size, comprising 41.2% of all surface stream
substrates (Figure 19). Sand and fine sediment (<0.06 to 2 mm) was the next dominant size, comprising
33.7% of all surface stream substrates, followed by cobble (64 to 250 mm) at 20.6%. Hardpan, boulders,
bedrock and wood comprised a limited portion of dominant substrate type.
26
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boulder
3.3%
other
1.2%
cobble
20.6%
fine/sand
33.7%
gravel
41.2%
Figure 19. Percent of Streambed with Dominant Particle Size.
Table 8. Percent of Stream Substrate Types for each Stream Order.
Strahler
Order
Fine/Sand
Gravel
Cobble
Boulder
Other
1st
Order
3.64
61.82
29.09
1.82
3.64
2nd
Order
31.42
41.67
22.76
3.49
0.66
3rd
Order
44.53
30.36
16.91
7.04
1.17
4th
Order
46.90
30.72
14.66
6.73
0.99
5th
Order
33.86
42.50
21.82
0.91
0.91
6th
Order
41.82
40.00
18.18
0.00
0.00
All
Streams
33.70
41.18
20.57
3.33
1.23
Classifying the data by Strahler stream order, gravel dominates first order streams (Table 8; Figure 20).
Second through sixth order streams have a higher mix of gravel and sand and fine substrates. Third and
fourth order streams have similar substrate diversity with sand and fine substrate as the dominant type.
The surficial composition of the Humboldt Basin, consisting of thin alluvium (young sediment or freshly
eroded rock particles), intrusives (slowly cooled rocks originating from shallow magma having small to
medium sized grains), and tertiary sediments (river sediment, gravel), may provide some explanation for
the high percentage of gravel (Maxey & Shamberger, 1961).
27
-------
• fine/sand
D gravel
D cobble
• boulder
n other
.a
3
W
+*
0
o
o
a.
3 4
Stream Order
Figure 20. Substrate Size by Stream Order.
Relative Streambed Stability
Disturbances to the landscape can contribute large amounts of sediment to a stream. The stream must
maintain a balance between sediment deposit and transport. Too much fine sediment can reduce habitat
availability and water circulation, both of which are necessary for aquatic invertebrates and benthic
organisms (Kaufmann et. al., 2004). Relative streambed stability (LRBS) measures the ability of a stream
to transport sediment and is calculated utilizing bankfull channel dimensions, thalweg depth profiles,
slope, woody debris, and systematic pebble counts (Kaufmann et al., 2008).
Of the 69 sites, thalweg depth profiles were gathered for 59 of them. Sites that were inaccessible or did
not have data available do not have corresponding LRBS values. To account for stream "roughness" or
variables that impact stream flow, woody debris counts and the amounts of different sediments present in
the stream are factored in the LRBS calculation. Hardpan and bedrock measurements were not included
due to insignificant amounts present within the sampled areas (Faustini & Kaufmann, 2007). See
Appendix 4 for a full summary of calculations.
A large negative LRBS value indicates more fine sediments were present than expected, while a large
positive LRBS value indicates more coarse sediments present than expected. Either instance suggests
ecological disturbance/stress (Herger et. al., 2007).
Streambed stability values ranged from -5.615 to 1.320 with a mean of-0.325 (see Figure 21). The
streambed stability values used for the ecological condition analysis were; -5 to -3 poor,
-2.9 to -0.5 good, -0.49 to 2 poor. The most disturbed sites in terms of fines and the most disturbed sites
in terms of coarse substrate resulted in a 61 percent poor ecological condition for the stream length
represented. This analysis should be considered very preliminary. More information concerning
streambed characteristics to help refine the condition values in the Humboldt River Basin are needed.
28
-------
100
90 •
SO
70
60
50 •
40
30
20 •
10
0
3S90
3501
3112
2723 ,-.
2334 ^
1
1945 S
E
1556 £
K
1167
778
389
0
-6
-2 0
Streambed Stability
Streambed Stability
• GOOD 1POOR • NO DATA
Figure 21. Cumulative Distribution Function and Condition Estimate of Streambed Stability.
Pools
In streams, pools are areas of deeper, slower flowing water that are important habitat features for fish. The
abundance of pools and their size and depth depends on the stream's power and channel complexity.
Stream size, substrate size and abundance, and larger roughness element (e.g. LWD) availability all
contribute to the frequency and quality of pools. An estimated 6.5% percent of stream reaches were pools
which had a mean depth of 8.79 cm and a mean volume of 0.71 m3. Over 90% of the pools were less than
50 cm deep and there were no pools over 100 cm deep (Figure 22).
I/)
> 100cm
,
« 75-1 00cm |
O
f
1
o
o
Q.
|
50-75cm
F
j
1
<50cm
0 10 20
m percent
<50cm
97.0
30 40 50 60 70
50-75cm
2.5
75-1 00cm
0.6
•
80 90 100
> 100cm
0
Pools (%)
Figure 22. Frequency of Pools by Depth Class.
29
-------
Riparian Vegetation
Riparian (stream bank) vegetation is important for several reasons:
• influences channel form and bank stability through root strength;
• source of recruitment for LWD that 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 were collected for three vegetation heights as
expressed in Table 9.
Table 9. Riparian Vegetation Category and Associated Height.
Vegetation Cover Type
Tree or canopy layer
Understory
Ground cover
Height
>5m
0.5-5m
<0.5m
Visual estimates of cover density and general structural/species vegetation classes (e.g. coniferous,
deciduous) of each layer were recorded. Overall, riparian vegetation was dense and most streams had
abundant riparian vegetation (Figure 23).
Vegetation Cover (areal prop)
0 60
0 50 -
0 40 -
0 30 -
0 20
0 10
0 00
D Cover
tree
0.07
understory
0.33
Vegetation Type
ground
0.53
Figure 23. Percent Vegetation Cover by Vegetation Class.
30
-------
Vegetation from trees was relatively sparse with the greatest percentage in second order streams. There
was no tree cover at all in the fifth and sixth order streams. Ground cover was the dominant vegetation
type for all stream orders (Figure 24).
a.
o
-------
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
45.6% of stream banks shaded (Figure 26) and an average of 18.8% of stream mid-channels shaded
(Figure 27). Given the types of vegetation found in the range and basin ecoregions which comprise the
Humboldt River Basin, 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.
100 -
90 -
80 -
70 -
60 -
50 -
40 -
30 -
20 -
10 -
0 -
3890
3501
3112
2723
2334
1945
1556
1167
778
389
0
40 60 80
Mean Canopy Density (%)
Mean Canopy Density
• GOOD FAIR 1POOR
Figure 26. Cumulative Distribution Function and Condition Estimate of Mean Canopy Shade on Bank.
100
90 -
80 -
70 -
60 -
50 -
40 -
30 -
20
10 -
0 -
3890
3501
3112
2723 f
2334 \
•
1945 |
1556 K
wi
1167
- 778
389
0
20 40 60 80
Mid-channel Canopy Shade (%)
Mid-channel Canopy Shade
• GOOD FAIR BPOOR
Figure 27. Cumulative Distribution Function and Condition Estimate of Mid-Channel Canopy Shade.
The accepted paradigm provides dynamics for stream characteristics relative to stream order. According
to Poole and Berman (2001) it is expected that shade will decrease as stream order increases. The
Humboldt River Basin exemplifies this. Mid-channel shade decreased fairly linearly as stream order
increased (Figure 28). Mean canopy shade varied with the lowest density for sixth order streams.
32
-------
• Mean Channel Shade
n Mid-channel Shade
3 4
Stream Order
Figure 28. Percent Mid-Channel and Bank Shade by Stream Order.
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
also indicative of the overall complexity of the channel which is likely to be beneficial to other organisms.
Fish cover was analyzed according to its level of presence, as described in Table 10. Overall fish cover
was moderate. The mean area covered by all types but algae was estimated to have an areal proportion of
0.415, area covered by natural objects (includes overhanging vegetation, undercut banks, LWD, brush and
boulders) was 0.412, and area covered by large objects was 0.156 (see Figure 29).
Table 10. Index of Fish Cover Presence.
Level of Presence
Absent
Sparse
Moderate
Heavy
Very Heavy
Description
None
<10%
10-40%
40-75%
>75%
33
-------
I
t
a
2
Q.
"55
o
<
0 45
n Ad
o ?*s
n TO
n 95
n 9n
n 1 ^
0 10
n 05
0 00
D Areal Prop.
area covered by all types
but algae
0.42
area covered by natural
objects
0.41
Fish Cover
area covered by large
objects
0.16
Figure 29. Natural Fish Cover.
Riparian Disturbance Indicators
Removal or alteration of riparian vegetation reduces habitat quality and can result in negative effects to
the stream biota. Riparian disturbance data were collected by examining the channel, bank and riparian
area on both sides of the stream at each of the transects, and visually estimating the presence and
proximity of disturbance (Hayslip et al., 1994). Eleven categories of disturbance were evaluated. Each
disturbance category is assigned a value based on its 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 observed in the riparian zone of the Humboldt Basin Streams. Piping
and lawns/parks were not observed in the riparian zone of any of the streams. Shown in Figure 30, the
most common form of riparian disturbance is pastures/hayfields (81.7%), followed by roads/railroads
(13.3%).
34
-------
buildings
1%
walls
^^^ 1% road/railroad
~n -^ 13%
pasture/
hayfield
82%
Figure 30. Percentage of Riparian Zone Human Influences on Stream Reaches.
Data were expanded to calculate a proximity-weight disturbance index for each reach (Kaufmann et al.,
1999). This index combines the extent of disturbance (based on presence or absence) as well as the
proximity of the disturbance to the stream. Categories of disturbances were defined using quartile ranges
of the data (Table 12).
Table 12. Levels of Human Influence.
Data Range
0-0.6
>0.6-1.3
>1.3-1.9
>1.9
Level of Human Influence
Low
Medium
High
Very High
Generally the level of human influence was low for all the separate categories, except for pastures/
hayfields which was medium (1.20) and accounted for the greatest percentage of riparian disturbance
(Figure 31). For all disturbance categories combined, the majority of sites have a high level of human
influence (1.5). See Appendix 3 for a full summary.
35
-------
other
buildings
0
a.
>,
i- roads
pastures
I
1
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40
Proximity Weighted Index
Figure 31. Mean Riparian Zone Human Influence by Type.
C. Biological Indicators
Benthic Invertebrates
Benthic macroinvertebrate assemblages reflect overall biological integrity of the stream because of their
sensitivity to numerous stream characteristics. Monitoring these assemblages is useful in assessing the
current status of the water body, as well as long-term changes (Plafkin et al., 1989). For example, these
communities are vulnerable to changes in temperature, which is in part regulated by the riparian
vegetation. Nutrients, such as phosphorus and nitrogen, are essential, but in excess, may become toxic,
reducing the amount of habitat available and disrupting biological communities.
Benthic macroinvertebrate data were available from 64 sample reaches and collected at each transect
using modified Serber samplers. The following three metrics were used in the analysis: taxa richness,
EPT taxa richness, and percent intolerant taxa (Table 13).
36
-------
Table 13. 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 taxa describes the
overall variety of the macroinvertebrate
assemblage. Useful measure of diversity of
the assemblage.
Number of taxa in the orders Ephmeroptera
(mayflies), Plecoptera (stoneflies), and
Trichoptera (caddis flies).
Percent taxa of 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 that are intolerant to pollution
based on classification from
Wisseman 1996.
The metric 'Taxa Richness' gives an indication of variability of macroinvertebrate communities in the
Humboldt Basin. The total number of taxa ranged from 9 to 40 species (Figure 32). 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 Basin shows that there are very few (7%) poor condition
locations. As determined by the authors using the 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 3.
100 -
90
80
70
60
i 50
40
30
20
10
0
3890
- 3501
• 3112
• 2723 _
2334*
s
- 1945 £
E
- 1556 £
1167
- 773
3E9
0
19 24 29
Total Number of Taxa
Total Number of Taxa
• GOOD FAIR BPOOR I
Figure 32. Cumulative Distribution Function and Condition Estimate of Total Taxa Richness.
37
-------
EPT taxa ranged from 2 to 24 (Figure 33) and percent intolerant taxa ranged from 0% to 57.2%
(Figure 30). Condition estimate values were set at: 0-7 poor, 8-17 fair and 18-25 good.
100
90 -
80
70 -
60 -
1 50
£
40 -
30 -
20 -
10 -
0 -
3890
3501
3112
2723
2334
1945
1556
1167
778
am
0
12 17
Number of EPT Taxa
EPT Taxa
• GOOD FAIR 1POOR BNODATA
Figure 33. 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, 57 percent of the Basin is in a poor ecological condition as determined
by intolerant taxa (Figure 34).
20 30 40
Intolerant Taxa %
Intolerant Taxa
• GOOD FAIR BPOOR BNODATA
Figure 34. Cumulative Distribution Function and Condition Estimate of Percent Intolerant Taxa.
A total of 24 metrics were analyzed and are summarized in Table 14 (Appendix 5). Biotic indices such as
taxa richness may not be sufficient to determine functional changes in a substrate system. Functional
feeding groups provide an indication of 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.
38
-------
Table 14. Summary Statistics for Macroinvertebrate Metrics.
Indicator
Taxa Richness
HBI
Shannon H
% EPT
EPT Taxa
% Ephemeroptera
Ephemeroptera Taxa
% Plecoptera
Plecoptera Taxa
% Trichoptera
Trichoptera Taxa
% Collector
% Filterer
% Predator
% Grazer
% Shredder
% Dominant Taxa
% Intolerant
% Tolerant
Mean
24.6
4.7
2.0
42.9
10.9
25.5
4.3
5.3
2.3
12.0
4.3
46.9
24.5
14.2
12.1
2.3
37.6
16.3
10.0
Min
9.0
2.3
0.7
1.8
2.0
0.9
1.0
0.0
0.0
0.0
0.0
7.3
0.4
1.9
0.2
0.0
13.9
0.0
0.0
Max
40.0
7.8
2.7
86.5
24.0
81.6
10.0
33.5
7.0
62.8
13.0
87.2
69.8
58.1
56.4
27.6
81.6
57.2
73.2
Standard Deviation
7.7
1.1
0.4
22.2
6.3
19.0
2.3
8.2
2.1
15.3
2.9
19.6
18.3
11.8
13.7
4.6
15.9
16.5
16.9
Predators comprised 14.2% of the population. Shredders are the more sensitive organisms to disturbance?
and are considered to represent a healthy stream system. In the Humboldt River Basin, shredder densities
(2.3%) 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 collectors and
filterers more tolerant in stressed environments. The Humboldt River Basin is dominated by the collector
(46.9%) and filterer (24.5%) feeding groups. Dominance of a particular group can be an indication that a
stream system is reflecting stressed conditions (Figure 35).
39
-------
D % Collector
• % Filterer
D % Predator
• % Grazer
• % Shredder
+- 40 —
-------
• Tolerance- a general tolerance to stressors, scores range from zero to 10, with higher numbers
representative of organisms more tolerant to organic waste.
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 selects 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, the Humboldt Basin utilized the
criteria from Stoddard et al (2005) set for the Southern Xeric Basin and Range, which encompasses the
Central Basin and Range (ecoregion 13) and the Mojave Basin and Range (ecoregion 14) (Appendix 6).
For the Humboldt Basin, six least-disturbed sites (29, 70, 108, 120, 166, 280) and six most-disturbed sites
(6, 11, 12, 96, 103, 245) were chosen.
Index for Biotic Integrity
To create the IBI, 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 were the same. In addition, richness metrics with a range less than
four eliminated (Appendix 7).
• 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 8).
• 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 9).
Once the representative metric from each metric class had been determined, each needed to be scored
using a 0 to 10 scale. Scoring is needed since metrics respond differently to disturbance and the scales
differ among metrics. For example, with increased perturbation, total taxa tends to decrease while percent
tolerant organisms tends to 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 15). 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 scored linearly. Negative metrics (those whose values are
highest in the most-disturbed sites) were scored similarly with the floor at the 95th percentile and the
ceiling at the 5th percentile.
41
-------
Table 15. Final Metrics and Ceiling/Floor Values1
Tnyt2ChiPct
FiltrTax
ClngrTax
ChiroTax
TolerPct
Ceiling
69.1
0.5
0.0
5.0
53.0
Floor
0.0
40.9
8.0
2.0
0.1
1 Metrics are defined in Appendix 7.
Scores were summed for each site for a total score of 50, then multiplied by 2 for a maximum IBI score of
100, with 100 signifying the best attainable condition (Appendix 10). In the Humboldt River Basin, the
total scores for macroinvertebrate IBI ranged from 10 to 96 (Figure 36). The condition estimate values
used for the IBI measurement are as follows: 100-70 good, 69-50 fair, and 40 -0 poor.
• GOOD FAIR 1POOR BNOQATA
Figure 36. Cumulative Distribution Function and Condition Estimate of Macroinvertebrate IBL
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 depositional 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 is 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. This and other physical habitat parameters,
42
-------
such as riparian vegetation, substrate and amount of pools, may all be important explanatory factors in
evaluating and explaining respiration. Models have been developed to compare different types of stream
systems, but application is limited due to factors such as extent of floodplains and flow variability.
A total of 79 samples were taken, including 9 revisited sites in 1999 (Figure 37). For this report, revisit
sites were averaged. Respiration values ranged from -0.59 (site 52) to 13.43 (site 34) 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).
| | Boundary
Sample Point
. -0.59-1.78
1.78-3.38
* 3.38-5.57
• 5.57-8.23
• 8.23-13.43
/\/ Major Rivers
Stream Reach File
Units are mg/g/h
Figure 37. Map of Sediment Respiration Levels in the Humboldt Basin.
43
-------
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 16) reveal arsenic, mercury, manganese and nickel were at levels
of concern at a number of sites. A total of 68 sites were sampled at least once for water and sediment. Ten
of these sites were sampled a second time for assessment of inter-annual variability.
Water
A total of 75 samples were taken for water quality pollutants at 66 sites. Three sites (6, 139, and 259)
were not sampled in either 1998 or 1999. Nine sites were revisited (R) in 1999. Revisit sites were not
averaged because of changes in detected levels. See Appendix 12 for summary statistics. The USEPA
National Ambient Water Quality Criteria (GOLD BOOK) is used in this report as the means of
determining whether a particular pollutant exceeds standards. Specifically, the three pollutant standards
used in this report are the Federal drinking water standard, the Criteria Continuous Concentration (CCC),
and the Critical Maximum Concentration (CMC). The CCC is designed as a benchmark by which to
determine whether a particular body of water is safe for aquatic life over a chronic exposure, based on a
four-day average concentration. The CMC is designed to be a maximum allowable concentration of a
contaminant over a one-hour average exposure period for aquatic life. Standards have not been set for all
contaminants. Available USEPA's National Recommended Water Quality Criteria - Aquatic Life Criteria
(Table 16) were used for both acute and chronic effects.
Table 16. 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
44
-------
Sediment
Using these benchmarks, the data from the Humboldt Basin was 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 then released into an organism upon
ingestion. For these reasons, metals concentrations in sediment are of concern in the streams of the
Humboldt Basin Study. Sediment was collected at least once at 68 sampling points. Site 114 was not
sampled at all. The ten revisit (R) sites in 1999 were not averaged because of changes in detection limits.
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 paper, three benchmarks were
used: the Threshold 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 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) and Florida
Department of Environmental Protection (FDEP).
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, 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 is then selected based on
these results. Table 17 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 17. Summary of Selected Screening Level Concentration- Based Sediment Quality Benchmarks for
Freshwater Sediments.
Chemical Name
Aluminum
Arsenic
Cadmium
Chromium
Copper
TEC mg/kg
-
12.1
0.592
56
28
PEC mg/kg
58030
57
11.7
159
77.7
NEC mg/kg
73160
92.9
41.1
312
54.8
45
-------
Manganese
Lead
Nickel
Zinc
1673
34.2
39.6
159
1081
396
38.5
1532
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 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 18). A basin-wide condition
estimate was not determined for hardness because only one year was measured.
Table 18. 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{ma[ln(hardness)]+ba}(CF)
CCC (dissolved) = exp{mc[ln(hardness)]+bc}(CF)
46
-------
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/1. This level was used as the condition estimate (Figure 38). The
criterion for aluminum in fresh water sediment was not found so the condition estimate was not
calculated. The cumulative distribution frequency for aluminum in sediment is given in Figure 38.
100
90
80 •
70
60
! 50 -
I
40 •
30
20
10 -
0
3890
3501
3112
2723 f
- 2334 I,
B
1945 ^
1556 t
\fi
- 1167
778
389
0
200 300 400
Aluminum H20 (u£/l)
Aluminum H2O
•GOOD BPOOR
100 -|
90
80 -
70
60 -
i 50 -
40 -
30
20
10
- 3890
- 3501
3112
- 2723
- 2334
- 1945
- 1556
1167
778
389
0
8600 13600 18600
Aluminum in Sediment (nig/Kg)
Figure 38. Cumulative Distribution Frequency and Condition Estimate of Aluminum in Stream Water and Sediment.
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/1 for acute effects and 150 (ig/1 for chronic effects. The
drinking water standard is 10 ppb ((ig/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 10 (ig/1 in water and 10 mg/Kg in freshwater sediment. The results are shown in Figure
39.
47
-------
100
90
80
70
60
50
40
30
20
10
0
3890
3501
3112
2723 _
2334 J
|
1945 |
E
- 1556 £
1167
77S
389
0
10 15 20 25 30
Arsenic in H2O fti£/l)
40
Arsenic in H2O (ng/l)
• GOOD IPOOR • NO DATA
100
90
80
70
60
50
40
30
20
10
0
3890
3501
3112
2723
- 1556 £
trt
1167
773
389
0
10 IS 20
Arsenic in Sediment (ng/1)
Arsenic in Sediment
• GOOD BPOOR BNODATA
Figure 39. Cumulative Distribution Frequency and Condition Estimate of Arsenic in Stream Water and Sediment.
Antimony:
The detection limit, which is the lowest quantity available to be identified, changed between sampling
years. The 1998 detection limit was 32.3 (ig/L, while, in 1999, the limit was decreased to 8 (ig/L due to a
change in methods. With a drinking water standard of 6 (ig/L we were unable to determine if most
samples exceeded this. Site 133 positively exceeded the drinking water standard in 1999, with an
antimony concentration of 9.1 (ig/L. We were also unable to determine whether the aquatic CCC level of
30 (ig/L was exceeded in 1998 for most samples. Site 82 exceeded both Aquatic CCC levels and drinking
water standards for antimony, with a value of 35.9 (ig/L. No samples exceeded the CCC for antimony in
1999. There is no CMC standard.
Cadmium:
National ambient water quality criteria for cadmium is dependent on calcium hardness of the water
sampled. Detection limits for cadmium changed between 1998 (1.4 (ig/L) and 1999 (1.0 (ig/L) due to a
change of laboratory methods used. Aside from site 82, all samples were below detection limits. Site 82
exhibited a cadmium level of 1.6 (ig/L, which, for the calcium hardness of the sampled water
(111.1 CaCO3/l), was below federal aquatic life continuous criteria (Marschack, 1998). For CMC
standards, 22 samples had standards below the detection limits. All sampling sites had individual CCC
standards below the detection limit, thus it was not possible to determine if CCC standards were
48
-------
exceeded. Cadmium concentrations were well below the federal drinking standard of 5 (ig/L, for all
samples.
Chromium:
National ambient standards for chromium are also dependent on calcium hardness. Chromium detection
limits in the analysis used were 2.1 (ig/L (1998) and 1.5 (ig/L (1999). No samples exceeded CCC levels
for this metal. Drinking water standards (100 (ig/L) for chromium were likewise not exceeded in any
samples.
Copper:
Calculating standards based on hardness, no samples exceeded CCC or CMC values for copper in the
Humboldt River Study. 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 40 shows the results of the analysis.
100
90
SO
70 •
60
! 50 -
40 •
30
20
10
0
3890
3501
3112
2723
2334
- 1945
- 1556
1167
778
389
0
10 20 30 40
Copper in Sediment (mg/KE)
60
Copper in Sediment
• GOOD 1POOR • NO DATA
Figure 40. Cumulative Distribution Frequency and Condition Estimate of Copper in stream Water and Sediment.
49
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Iron:
Currently, the USEPA's National Recommended Water Quality Criteria - Aquatic Life Criteria lists iron
as a non priority pollutant. The condition estimate for this analysis as set at the chronic effect level of
1000 |ig/l for water. 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 41.
100 -
90 -
80 -
70 -
60 -
! 50 -
40 -
30 -
20 -
10 -
0 -
3890
3501
3112
2723 •
"34
1945
1556
1167
778
389
100 150 200
lrcmH2O(ne/ll
[ronH2O
• GOOD 1POOR • NO DATA
4000 9000 14000 19000 24000 29000 34000
Iron in Sediment (mg/Kg)
Figure 41. Cumulative Distribution Frequency and Condition Estimate of Iron in Stream Water and Sediment.
50
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Lead:
No samples for surface waters were above the drinking water standard of 15 (ig/L. Condition estimates
were not done. The condition estimate level for lead in freshwater sediment was set at: good < 35
mg/Kg, fair = 31-91 mg/Kg and poor > 91 mg/Kg. Results are shown in Figure 42.
100
90
SO
70 •
60
! 50 -
I
40
30
20
10
0
3890
3501
3112
"23 J
2334 .=
1
1945 3
|
1556 £
£
1167
773
389
0
20 30 40
Lead in Sediment Img/Kg)
Lead in Sediment (mg/Kg)
• GOOD FAIR 1POOR BNODATA
Figure 42. Cumulative Distribution Frequency and Condition Estimate of Lead in Stream Water and Sediment.
51
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Manganese:
There is no aquatic life CCC or CMC standards for manganese. 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/1 which corresponded with a drinking water level of 0.5 mg/1. No level was set for sediment.
Results are shown in Figure 43.
20 30 40
Manganese in H2O (
Manganese in H2O (tig/I)
• GOOD 1POOR • NO DATA
115 215 315 415 515 615 715 815
Manganese in Sediment (mg/KgJ
Figure 43. Cumulative Distribution Frequency and Condition Estimate of Manganese in Stream Water and Sediment.
52
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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).
Mercury samples were only collected during the 1998 sampling period. Total mercury concentrations in
sediment ranged from 0.1 to 1.5 mg/kg dry weight. In water, all sites were below the 0.1 (ig/L detection
limit. 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 Humboldt River Basin condition estimate (Figure 44) good was given as
less than or equal to 0.17 mg/Kg, fair was between 0.17 and 0.49 mg/Kg and poor was greater than or
equal to 0.49 mg/Kg.
0.06 0.26 0.46 0.66 0.86 1.06 1.26 1.46
Mercurv in Sediment (me/Kg)
Mercury in Sediment
• GOOD FAIR 1POOR BNODATA
Figure 44. Cumulative Distribution Frequency and Condition Estimate of Mercury in Stream Sediment.
Nickel:
Detection limits for nickel were 15.4 (ig/L in 1998, and 6 (ig/L in 1999. The nickel aquatic CCC is
hardness dependent. All samples were well below the lowest CMC of 52 (ig/L for low hardness waters.
Sites 4 (13.8 (ig/L) and 120 (10.6 (ig/L) had CCC levels that were below the detection limit, thus it was
unable to be determined if those sites exceeded the standard. There is no drinking water standard for
nickel.
Selenium:
The detection limit for selenium changed from 0.5 (ig/L (1998) to 14 (ig/L (1999). The drinking standard
for selenium is 50 (ig/L, and the CCC is 5 (ig/L. No samples exceeded either the Drinking or CCC
standards in 1998. In 1999, six sites (127, 164, 244, 245, 269, 87R) positively exceeded the aquatic life
CCC of 5(ig/L. The other samples are unreportable/unknown in relation to CCC standards, due to the
detection limit being higher than the CCC. There is no CMC standard for selenium.
Silver:
Although no CCC for silver has been established, the CMC standard for this silver is hardness dependent.
The detection limits used in the silver analysis were 3 (ig/L in 1998 and 0.8 (ig/L in 1999. Seven samples
53
-------
from 1999 had detection limits that were above CMC values for silver. Due to the detection limit for
silver in 1998, 17 samples have values which are at or below 3 (ig/L. These samples are
unreportable/unknown in terms of silver concentration relative to CMC values. No samples exceeded the
drinking water standard of 100 (ig/L.
Zinc:
The CCC for zinc is hardness dependent, and detection limits for this metal were 1.2 (ig/L in 1998, and
1.0 (ig/1 in 1999. The USEPA's National Recommended Water Quality Criteria - Aquatic Life Criteria
for zinc in freshwater is 120 (ig/1 for both acute and chronic effects. The condition estimate levels for this
analysis is 120 (ig/1 for water and sediment. Good being below 120 mg/Kg, fair is between 120 mg/Kg
and 310 mg/Kg and over 310 mg/Kg as being poor. Results for this condition estimate for zinc in the
Basin are shown in Figure 45.
100 -
90 -
80 -
70 -
60 -
: so -
I
40
30
20 -
10
0
3890
3501
3112
"" J
2334 I
1345 3
|
1556 E
X
1167
778
389
0
20 30
Zinc in H2O lug/I)
Zinc in H2O
•GOOD 1POOR
Zinc in Sediment
• GOOD FAIR BPOOR
100 -
90 -
80
70 -
60 -
50
40
30
20 -
10
0
3890
- 3501
- 3112
- 2723 —.
2334 T
1
- 1945 £
E
r 1556 £
K
1167
- 778
389
0
10
110 210 310 410
Zinc in Sediment (mg/Kg)
Figure 45. Cumulative Distribution Frequency and Condition Estimate of Zinc in Stream Water and Sediment.
54
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F. Relationships Between Indicators and Stressors
The second objective of this report was 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 all combinations of indicators (Table 19). Both water chemistry and
physical habitat variables can be 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, 0.500.75, respectively.
Table 19. Possible Combinations of Stressors and Indicator Relationships.
Indicator
Benthic Inverts.
Water Chemistry
Physical Habitat
Sediment Respiration
Stressors
Water Chemistry
X
-
-
X
Physical Habitat
X
X
-
X
Riparian Disturbance
X
X
X
X
Many significant correlations between indicators and stressors were detected yet many were weak
(Appendix 14). The following statements summarize the outcome of correlations between indicators and
stressors:
• Benthic invertebrate indicators had only two moderately negative significant correlations. These
were between EPT taxa and total dissolved solids (Figure 46) and between EPT txa and absent
vegetation in the canopy. All other correlations were weak. Macroinvertebrate IBI assemblages
had many weak correlations to stressors. There were two moderate correlations, % fine (Figure 47)
and % fast.
55
-------
30 -,
25
20
re
X
re
£15-
0.
HI
10
5
0
(
r* '
~ ?« »
»* \ 4> *
« •«•• R=0.496, P=0.000, n=64
** •
) 200 400 600 800 1000 1200
Total Dissolved Solids (mg/L)
Figure 46. Relationship between Total Dissolved Solids and EPT Taxa.
-ion
-inn
80, ^
•
•
m~ RO
4n
•
90,
0
R=0.615, P=0.000, n=64
•
• •
' * * •
* * * * *
(S * \
•
• \ * * *
* * *
• • *• A» *
«* » *
O » v»»*
% * *
• •
* • **
•
0 20 40 60 80 100 120
% Fines
Figure 47. Relationship between Percent Fines and Macroinvertebrate IBL
56
-------
There were five moderately significant correlations for water chemistry indicators. Only one of the
moderate correlations existed between total suspended solids and the proximity to building. All other
correlations were weak. Many of those were negative correlations between fish cover and several
water chemistry indicators.
All correlations between physical habitat indicators and riparian disturbances were weak. Most of
them were negatively correlated to the proximity to pastures. Only percent fine gravel had a positive
correlation to the proximity to pastures.
All correlations for sediment respiration were weak. Only two correlations existed to water chemistry
indicators (pH, Temperature) and none existed to riparian disturbances (Figure 48). Physical habitat
stressors included mean canopy density, fish cover, and riparian vegetation.
Sediment Metabolism (mg/g/h)
1R n
14 0
1? 0
m n
8n
R n
4 0
o n
n n
9 n
R=0.353, P=0.004, n=64
•
•
* * *
* *
« *• » .
;••*, 7X«V
* **«*«*»« •
A *
»* * ** *
*» * *
) 5 10 *15 20 25 3
Temperature (°C)
•
Figure 48. Relationship between Temperature and Sediment Metabolism.
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 of effect, 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 20).
57
-------
Table 20. Thresholds for Indicators in the Humboldt River Basin.
Indicator
Macroinvertebrate IBI
Sulfate (mg/L)
Total Suspended Solids (mg/L)
Total Phosphorus (mg/L)
Total Nitrogen (mg/L)
Conductivity (uS/cm)
Residual Pool Area (RP100)
% Fast (PCT_FAST)
% Slow (PCT_SLOW)
Canopoy+Mid+Ground Woody Cover (XCMGW)
Mean Mid-Channel Canopy Density (XCDENMID)
Fish Cover
Area Covered by Natural Objects (XFC_NAT)
All Riparian Disturbances
Riparian Disturbance from Pastures
% Fine
% Sand & Fine
Mean Mid-Channel Embeddedness (XCEMBED)
Streambed Stability (NOR)
Most-disturbed
Threshold
<58
>23.88
>27.90
>0.063
>0.478
>327.25
<0.09
>87.58
<12.42
<0.22
<2.87
<0.72
>1.48
>1.17
>53.32
>56.50
>73.62
<-1.28 or>0.91
%
5th
95th
95th
95th
95th
95th
5th
95th
5th
5th
5th
5th
95th
95th
95th
95th
95th
5th/95th
Least-disturbed
Threshold
>73
<6.25
<18.70
<0.040
<0.388
£131.50
£1.12
<58.43
>41.57
>0.42
>12.10
>0.79
<0.71
<0.62
<15.00
<28.18
<65.50
>0.39&<0.58
%
25th
75th
75th
75th
75th
75th
25th
75th
25th
25th
25th
25th
75th
75th
75th
75th
75th
25th/75th
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 (i.e., relative extent) is one aspect
to consider in defining the importance of each potential stressor. Another aspect to consider is the severity
that each stressor has on biotic integrity relative to other stressors (i.e., relative risk). Each aspect provides
important input to policy decisions.
Relative Extent
The total length of the RF3 stream network in Humboldt River Basin is 39,463.2 km. Eighty-six percent
of this total was considered non-target, i.e., irrigation canals, pipelines, dry streams. The remaining target
stream length (5637.4 km) represents the portion of the sampling frame that meets the criteria for
inclusion in the assessment. A stressor's extent is estimated by calculating the proportion of the streams in
most or least disturbed condition compared to all stream lengths.
Results of water chemistry indicator metrics varied from 36% (Total Phosphorus) to 71% (Sulfate) for
the stream extent in most-disturbed condition. Total Nitrogen had the largest percentage of stream length
in least-disturbed condition (57%) (Figure 49). Macroinvertebrate IBI had >50% of the stream length in
the most-disturbed condition category.
58
-------
Total Nitrogen
Total Phosphorus
Sulfate
Conductivity
IBI
D Most Disturbed Q Intermediate • Least Disturbed
I
I
0% 20% 40% 60% 80% 100%
% Stream Length
Figure 49. Extent of Stream Length in Most-Disturbed, Intermediate and Least-Disturbed Condition for Selected Water
Quality Indicators and Macroinvertebrate IBI.
The relative extents of physical habitat condition stressors were variable (Figure 50). Riparian disturbance
stressors were substantial in many streams resulting in >70% of the stream length in most disturbed
condition. The extents of riparian vegetation and mid-channel canopy density had evenly distributed
condition classes with the largest class in the least-disturbed category. Most stream length assessed for
fish cover (78%) was in most-disturbed condition. Channel complexity stressor metrics were fairly
consistent with each other with most stream lengths in least-disturbed condition (>70%).
*Sulfate and Total Nitrogen were only Sampled in the 1998 Sampling Period.
59
-------
All Riparian Disturbance
Riparian Disturbance
(Pasture)
Riparian Vegetation
Canopy Density
Fish Cover
Residual Pool Area
% Slow
% Fast
D Most Disturbed D Intermediate • Least Disturbed
| |
I I I
I I
| |
=
I
I I
I I
0% 20% 40% 60% 80% 100%
%Stream Length
Figure 50. Extent of Stream Length in Most-Disturbed, Intermediate and Least-Disturbed Condition for Selected Physical
Habitat Indicators.
Sediment stressor metrics yielded varied results, with the relative extents of stream length in most-
disturbed condition ranging from 9 % to 54% (Figure 51). Streambed stability had the majority of extents
classified in intermediate 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 (25% versus 19% for
fine-sized alone). Figure 52 summarizes all relative extent stressors.
60
-------
Streambed Stability
TSS
Embeddedness
% Fine and Sand
% Fine
D Most Disturbed n Intermediate • Least Disturbed
|
I I I
I I
I
0% 20% 40% 60% 80% 100%
% Stream Length
Figure 51. Extent of Stream Length in Most-Disturbed, Intermediate and Least-disturbed condition for Sediment Indicators.
Streambed Stability
% Fine
% Fine and Sand
Embeddedness
TSS
% Fast
% Slow
Residual Pool Area
Fish Cover
Canopy Density
Riparian Vegetation
Riparian Disturbance (Pasture)
Riparian Disturbance All
Conductivity
Sulfate
Total Phosphorus
Total Nitrogen
] 9.0%
—111.6°X
.7%
17.4%
] 24.6%
31.3'
53.6%
34.8%
38.5%
4.3%
K>
37.1 %
73.
77.9%
9%
725%
0.0%
20.0%
40.0% 60.0%
% Stream Length
80.0%
100.0%
Figure 52. Summary Relative Extent of Stressors (Proportion of Stream Length with Stressors in Most-Disturbed Condition).
61
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Relative Risk
Relative risk, a ratio of two probabilities, assesses the association between stressors and biological
indicators. For this report, the two probabilities, or risks, measure the likelihood that a most-disturbed
condition of a biological indicator will also occur in a stream with a most-disturbed condition of a
particular stressor metric. 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 Humboldt River Basin, weight data was incomplete. For this study, the
calculations are made using the number of sampling sites 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 is an example of how the data can be arranged and calculated.
Table 21. Relative Risk Analysis.
Number of Sampling Sites
mi
Least-disturbed
Most-disturbed
Total
All Riparian Disturbances
Least-disturbed
A: 7
B: 3
A+B: 10
Most-disturbed
C: 15
D: 23
C+D: 38
The risk of finding a most-disturbed condition for benthic macroinvertebrates in streams that have most-
disturbed condition for all riparian disturbances is estimated as:
= D/(C+D) 23/38=0.61
The risk of finding a most-disturbed condition of benthic macroinvertebrates in streams that have a least
disturbed condition for riparian disturbance is estimated as:
= B/(A+B) 3/10=0.30
Comparing these two probabilities (0.61/0.30) yields a relative risk of 2.02. In other words, it is 2.02
times more likely to find a most-disturbed condition for benthic macroinvertebrates in streams where
riparian disturbance condition 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 may be confounded.
Relative risks with a value at or below 1.0 are not considered significant. Variables percent fast, riparian
disturbances (pasture), percent fine, percent sand/fine and conductivity were eliminated due to multiple
correlations.
62
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Streambed Stabiltiy
Residual Depth
Riparian Vegetation
Fish Cover
Total Nitrogen
Total Phosphorus
Sulfate
Embeddedness
Riparian Disturbance All
Canopy Density
%Slow
0.0 1.0 2.0 3.0 4.0
Relative Risk
5.0
6.0
Figure 53. Risk to Benthic Assemblage (IBI) Relative to the Environmental Stressor Condition.
Relative risk assesses the significance of the effects of stressors to stream biota. Using multiple species
assemblages is preferred as a biological indicator because a stressor that may be very relevant to one
assemblage may have less of a signal for another. Yet, for this evaluation, only one biotic assemblage,
benthic macroinvertebrate IBI, was used to determine risk to biota. Seventeen stressors were originally
used to analyze extent, but only eleven were useable for relative risk estimation due to methods
restrictions. Two stressors, percent slow and residual depth had relative risk values and/or confidence
intervals significantly less than 1.0 (Figure 53). Fish cover had the highest relative risk value of 5.4. For a
complete list of relative risk calculations and results, see Appendix 15.
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. For
example, riparian vegetation was in most-disturbed condition in only an estimated 25% of the stream
length, but where this condition occurs the biota is at risk of being in a most-disturbed condition.
However, some stressors are both broadly occurring (i.e., high relative extent) and have high relative risk
(Figure 54). Primary stressors in terms of both extent and risk to biota are fish cover, riparian disturbance,
and embeddedness.
63
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90%
80% -
£
| 60% -
o 50%-
•S 40% -
30% -
20% -
10% -
0%
TN
TP
SO4
Density
RipVeg
LRBS
% Slow
RP100
0.00
1.00
2.00 3.00 4.00
Relative Risk
5.00
6.00
Figure 54. Summary of Extent of Stressors in Most-Disturbed Condition in Relation to Relative Risk*.
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 indicates that the status of many
of the streams in the Humboldt River Basin are in less than desirable condition. The percentage of
impacted streams varied, with 38% of stream reaches studied in the Humboldt River Basin being in most-
disturbed condition. The quality of a stream and wetland riparian ecosystem is directly related to the
condition of adjacent uplands. Studies since have shown that improved knowledge of aquatic and upland
interactions, at local to watershed scales, is essential in evaluating and designing land management
alternatives for stream and wetland resources. Nevada's arid environment, coupled with the fact that
much of the biodiversity in this state is associated with riparian or aquatic habitats, makes the
management of these systems a matter of particular importance. 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. Considerable progress, as a nation, has been made in managing our
watersheds. However, 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
64
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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 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.
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.
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 Humboldt River Basin to provide for a more sustainable
ecosystem.
65
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66
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74
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VII. Appendecies
Appendix 1. List of Sites.
Site
3
4
5
6
7
11
12
14
15
22
25
29
34
35
37
49
52
53
55
66
69
70
71
82
87
92
96
101
103
108
109
114
116
118
120
127
129
Stream Order
5
4
1
3
3
3
2
2
6
3
2
4
4
3
2
4
3
3
6
4
4
3
2
5
3
2
4
2
3
2
2
3
4
4
2
2
3
Stream Name
Middle Reese River
Upper Reese River
Brewer Canyon
Reese River
Millinex
Evans Creek (lower)
Evans Creek (upper)
Boulder Creek
Rock Creek (lower)
Thomas Creek
Elbow Canyon
Oregon
Kelly Creek
Spaulding
Panther
Hank's Creek
Boulder Creek
Dorsey Creek
North Fork Humboldt
Smith Creek
Dixie Creek
Long Canyon Creek
Talbot
Maggie Creek
Blue Basin Creek
Trout Creek
Reese River
Robert's Mountains
Huntington Creek
Chimney Creek
Hot Creek
Gance Creek
Willow Creek
Martin
Buckskin
Welsh Canyon
Beaver Creek
Longitude
-117.34889
-117.47056
-117.23139
-117.14417
-117.53889
-117.00389
-116.90056
-116.33722
-116.70874
-117.73333
-117.67833
-116.86389
-117.15722
-117.79667
-117.50361
-115.34139
-115.24528
-115.74972
-115.53083
-115.70250
-115.85028
-115.52361
-115.44750
-116.11500
-115.97861
-116.94639
-117.16111
-116.23806
-115.76139
-115.38556
-115.14278
-115.94056
-116.41806
-117.44722
-117.50083
-116.29778
-116.22528
Latitude
39.17194
38.85000
39.23861
39.55667
41.56139
41.11083
41.16778
41.10361
40.95036
40.89861
40.75639
41.32983
41.13611
40.53972
40.55667
41.38556
40.97417
41.05806
41.01278
40.46056
40.66750
40.55722
40.73861
40.75028
41.00750
40.38472
38.74917
39.67500
40.14000
41.56417
41.59889
41.29917
41.21750
41.69472
41.80250
40.79028
41.11194
75
-------
Appendix 1. List of Sites (cont).
Site
130
133
134
139
140
158
161
164
166
170
176
181
183
184
190
193
196
199
204
215
230
235
244
245
247
250
257
259
263
269
278
280
Stream Order
3
4
3
3
3
4
2
4
2
1
4
2
4
5
3
4
4
5
4
3
3
2
2
3
3
4
2
3
4
4
4
4
Stream Name
Marysville Creek
Little Humboldt River
Boulder Creek
Red Hills (dry)
Hot Creek
South Fork
Round Corral Creek
Willow Creek
Iowa Canyon
Rock Creek
Pine Creek
Table Mountain (dry)
Jake Creek
Mary's River
Upper Beaver Creek
Kelly Creek
Reese River
Martin Creek
Hank's Creek
Henderson Creek
Rock Creek (dry)
Robert's Mountains
Pole Creek
Susie Creek
Sherman Creek
Beaver Creek
Coyote Creek (dry)
Gance Creek
Kelly Creek
Upper Little Humboldt
Dixie Creek
Reese River
Longitute
-117.34278
-116.88611
-115.25972
-117.21389
-115.16639
-115.57556
-117.48250
-116.62500
-116.96250
-116.34083
-116.13528
-117.78028
-117.06167
-115.24222
-115.68278
-117.08917
-117.10361
-117.35778
-115.30639
-116.16694
-116.50056
-116.20639
-115.05722
-115.95389
-115.72667
-115.59361
-116.22389
-115.76694
-117.11861
-117.36222
-115.85611
-117.42583
Latitude
39.04167
41.39278
40.98333
41.62778
41.59000
40.55944
41.64194
41.20694
39.79833
41.34250
40.37111
40.50167
41.17028
41.41278
41.50528
41.27306
39.86556
41.62500
41.46278
39.93139
41.34667
39.83278
41.39222
40.99972
40.94944
41.39667
40.99278
41.24083
41.22972
41.76750
40.63750
38.80917
76
-------
Appendix 2. Summary Statistics for Water Chemistry Indicators for the Humboldt Basin.
Indicator
Temperature
Conductivity
Dissolved
Oxygen
PH
Ammonia
Chloride
Nitrate
Sulfate
Total
Dissolved
Solids
Total
Kjeldahl
Nitrogen
Total
Phosphorus
Total
Suspended
Solids
Units
°c
ps/cm
mg/L
pH units
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
Mean
17.72
328.40
8.07
8.27
0.039
17.58
0.050
26.74
221.33
0.22
0.066
12.16
Lower
95%
Conf.
16.60
256.28
7.61
8.10
0.036
10.68
0.030
17.06
178.71
0.18
0.055
7.53
Upper
95%
Conf.
18.84
400.52
8.52
8.45
0.043
24.47
0.080
36.41
263.95
0.26
0.076
16.80
Median
18.45
236.00
7.95
8.30
0.040
10.82
0.020
9.56
179.00
0.17
0.055
10.00
Min
8.20
53.00
2.40
6.60
0.010
0.20
0.020
0.20
17.20
0.061
0.014
0.00
Max
27.65
1.51E+03
15.50
11.70
0.08
204.20
0.65
259.00
1.01E+03
1.20
0.20
140.00
Range
19.45
1.46E+03
13.10
5.10
0.070
204.00
0.63
258.80
992.80
1.14
0.18
140.00
Variance
21.32
8.80E+04
3.48
0.48
0.000
828.45
0.011
1.63E+03
3.24E+04
0.027
0.002
374.96
Standard
Deviation
4.62
296.64
1.86
0.70
0.015
28.78
0.106
40.40
178.00
0.17
0.043
19.36
Standard
Error
0.57
36.79
0.23
0.088
0.002
3.52
0.013
4.94
21.75
0.020
0.005
2.37
77
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics.
Type
channel
cover
Indicator
undercut dist
bankfull
width
bankfull
height
channel
slope
channel
incision
height
bank angle
wetted width
width*depth
width/depth
depth
reach length
sinuosity
percent fast
percent slow
percent
pools
percent
dry/sub
median bank
anglef
area covered
by all types
but algae
Units
m
m
m
%
m
degree
m
m2
m/m
cm
m
unitless
%
%
%
%
degree
areal
prop.
Indicator
Abbrv.
XUN
XBKF_W
XBKF_H
XSLOPE
XINCJH
XBKA
XWIDTH
XWXD
XWD_RAT
XDEPTH
REACHLEN
SINU
PCT_FAST
PCT_SLOW
PCT_POOL
PCT_DRS
MEDBK_A
XFC_ALL
Mean
0.013
5.68
0.42
3.17
1.01
36.76
3.03
1.08
15.86
23.79
164.73
1.28
33.30
59.82
6.46
6.88
27.46
0.42
Lower
95%
Conf.
0.009
4.42
0.36
2.55
0.77
33.28
2.34
0.68
13.48
19.23
152.04
1.21
25.46
51.58
3.58
1.29
23.23
0.31
Upper
95%
Conf.
0.017
6.93
0.48
3.79
1.26
40.23
3.71
1.48
18.24
28.35
177.42
1.36
41.13
68.07
9.34
12.47
31.69
0.52
Median
0.006
4.01
0.31
2.54
0.66
33.64
2.31
0.46
12.99
18.74
150.00
1.22
24.00
68.67
0.91
0.00
25.50
0.22
Min
0.00
0.87
0.16
0.30
0.00
10.36
0.00
0.00
0.00
0.00
100.00
1.01
0.00
0.00
0.00
0.00
9.00
0.00
Max
0.10
29.57
1.35
12.23
6.44
86.36
16.68
10.76
57.39
110.49
380.00
2.47
100.00
100.00
68.00
100.00
79.00
2.02
Range
0.10
28.69
1.19
11.93
6.44
76.00
16.68
10.76
57.39
110.49
280.00
1.46
100.00
100.00
68.00
100.00
70.00
2.02
Variance
0.00
27.98
0.062
6.74
1.06
216.94
8.22
2.84
100.25
368.63
2.39E+03
0.082
1.10E+03
1.22E+03
149.03
560.76
172.46
0.18
Standard
Deviation
0.019
5.29
0.25
2.60
1.03
14.73
2.87
1.68
10.01
19.20
48.88
0.29
33.21
34.94
12.21
23.68
13.13
0.43
Standard
Error
0.00
0.64
0.030
0.31
0.13
1.77
0.35
0.20
1.21
2.33
6.47
0.038
4.00
4.21
1.47
2.85
2.16
0.052
78
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics (cont.).
Type
Indicator
area
covered by
natural
objects
area
covered by
large objects
filamentous
algae cover
aquatic
macrophyte
cover
area
covered by
natural
objects
area
covered by
large objects
filamentous
algae cover
aquatic
macrophyte
cover
large woody
debris cover
brush and
small woody
debris cover
overhanging
vegetation
cover
Units
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
Indicator
Abbrv.
XFC_NAT
XFC_BIG
XFC_ALG
XFC_AQM
XFC_NAT
XFC_BIG
XFC_ALG
XFC_AQM
XFC_LWD
XFC_BRS
XFCJDHV
Mean
0.41
0.16
0.13
0.13
0.41
0.16
0.13
0.13
0.010
0.074
0.19
Lower
95%
Conf.
0.31
0.10
0.092
0.085
0.31
0.10
0.092
0.085
0.001
0.051
0.14
Upper
95%
Conf.
0.51
0.21
0.18
0.18
0.51
0.21
0.18
0.18
0.019
0.097
0.23
Median
0.22
0.059
0.075
0.043
0.22
0.059
0.075
0.043
0.00
0.049
0.094
Min
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Max
2.02
0.96
0.88
0.88
2.02
0.96
0.88
0.88
0.27
0.63
0.79
Range
2.02
0.96
0.88
0.88
2.02
0.96
0.88
0.88
0.27
0.63
0.79
Variance
0.18
0.050
0.032
0.043
0.18
0.050
0.032
0.043
0.00
0.009
0.042
Standard
Deviation
0.43
0.22
0.18
0.21
0.43
0.22
0.18
0.21
0.037
0.096
0.21
Standard
Error
0.052
0.027
0.022
0.025
0.052
0.027
0.022
0.025
0.005
0.012
0.025
79
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics (cont.).
Type
riparian
Indicator
undercut bank
cover
boulder and
rock ledge
cover
artificial
structure
cover
canopy
present
midlayer
present
groundlayer
present
canopy+
midlayer
present
3 layers
present
veg canopy
cover
veg midlayer
cover
veg ground
cover
veg canopy+
midlayer
veg canopy+
mid woody
canopy+ mid+
ground
Units
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
Indicator
Abbrv.
XFC_UCB
XFC_RCK
XFCJHUM
XPCAN
XPMID
XPGVEG
XPCM
XPCMG
XC
XM
XG
XCM
XCMW
XCMG
Mean
0.038
0.10
0.003
0.18
0.85
0.98
0.18
0.18
0.069
0.33
0.53
0.39
0.29
0.93
Lower
95%
Conf.
0.021
0.060
0.001
0.11
0.79
0.97
0.11
0.11
0.028
0.28
0.48
0.32
0.23
0.82
Upper
95%
Conf.
0.054
0.15
0.006
0.26
0.91
1.00
0.25
0.25
0.11
0.37
0.59
0.47
0.35
1.04
Median
0.014
0.018
0.00
0.00
1.00
1.00
0.00
0.00
0.00
0.33
0.54
0.35
0.23
0.90
Min
0.00
0.00
0.00
0.00
0.00
0.59
0.00
0.00
0.00
0.00
0.030
0.00
0.00
0.055
Max
0.38
0.88
0.057
1.00
1.00
1.00
1.00
1.00
0.92
0.90
1.02
1.71
1.33
2.74
Range
0.38
0.88
0.057
1.00
1.00
0.41
1.00
1.00
0.92
0.90
0.99
1.71
1.33
2.68
Variance
0.005
0.034
0.00
0.094
0.071
0.003
0.089
0.088
0.030
0.042
0.050
0.10
0.069
0.22
Standard
Deviation
0.069
0.19
0.010
0.31
0.27
0.058
0.30
0.30
0.17
0.20
0.22
0.32
0.26
0.47
Standard
Error
0.008
0.023
0.001
0.037
0.032
0.007
0.036
0.036
0.021
0.025
0.027
0.039
0.032
0.056
80
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics (cont.).
Type
Indicator
canopy+ mid+
ground woody
canopy
coniferous
canopy
deciduous
canopy mixed
(conif+ decid)
canopy absent
midlayer
coniferous
midlayer
deciduous
midlayer mixed
conif+ decid
midlayer absent
midlayer woody
midlayer
herbaceous
ground woody
ground
herbaceous
ground barren
riparian canopy
cover >0.3mt
Units
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
areal
prop.
Indicator
Abbrv.
XCMGW
PCAN_C
PCAN_D
PCAN_M
PCAN_N
PMID_C
PMID_D
PMID_M
PMID_N
XMW
XMH
XGW
XGH
XGB
XCS
Mean
0.48
0.011
0.17
0.004
0.81
0.00
0.28
0.48
0.21
0.22
0.10
0.19
0.35
0.22
0.086
Lower
95%
Conf.
0.39
-0.005
0.10
-0.002
0.74
0.19
0.38
0.13
0.18
0.08
0.15
0.30
0.17
0.025
Upper
95%
Conf.
0.57
0.026
0.24
0.010
0.89
0.36
0.58
0.28
0.26
0.13
0.22
0.39
0.27
0.15
Median
0.40
0.00
0.00
0.00
1.00
0.00
0.00
0.50
0.045
0.21
0.062
0.15
0.33
0.17
0.00
Min
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.030
0.00
0.00
Max
1.86
0.55
1.00
0.20
1.00
0.00
1.00
1.00
1.00
0.61
0.62
0.70
0.85
0.88
0.88
Range
1.86
0.55
1.00
0.20
1.00
0.00
1.00
1.00
1.00
0.61
0.62
0.70
0.82
0.88
0.88
Variance
0.14
0.005
0.093
0.00
0.094
0.00
0.14
0.17
0.11
0.026
0.014
0.023
0.033
0.039
0.036
Standard
Deviation
0.37
0.068
0.30
0.026
0.31
0.00
0.38
0.42
0.33
0.16
0.12
0.15
0.18
0.20
0.19
Standard
Error
0.045
0.008
0.037
0.003
0.037
0.000
0.046
0.050
0.040
0.019
0.014
0.018
0.022
0.024
0.031
81
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics (cont.).
Type
human
Indicator
canopy density
mid channel
canopy density
all human dist
non agric.
human
agric human
dist
building
wall
pavement
road/railroad
pipes
trash/landfill
lawn/park
row crop
pasture/hayfield
logging activity
Units
%
%
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
prox.wtd
. index
Indicator
Abbrv.
XCDENBK
XCDENMID
W1JHALL
W1JHNOAG
W1_HAG
W1 H_BLDG
W1 H_WALL
W1 H_PVMT
W1 H_ROAD
W1H_PIPE
W1H_LDFL
W1 H_PARK
W1 H_CROP
W1 H_PSTR
W1 H_LOG
Mean
45.63
18.82
1.47
0.27
1.20
0.021
0.017
0.002
0.19
0.00
0.018
0.00
0.001
1.20
0.002
Lower
95%
Conf.
39.06
13.06
1.31
0.20
1.08
0.001
-0.004
-0.001
0.14
0.00
0.005
0.00
0.00
1.08
-0.001
Upper
95%
Conf.
52.20
24.59
1.62
0.34
1.32
0.041
0.038
0.004
0.25
0.00
0.030
0.00
0.002
1.32
0.005
Median
41.58
7.62
1.53
0.17
1.50
0.00
0.00
0.00
0.030
0.00
0.00
0.00
0.00
1.50
0.00
Min
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
Max
100.00
100.00
2.50
1.16
1.53
0.42
0.64
0.068
0.77
0.00
0.32
0.00
0.030
1.50
0.068
Range
100.00
100.00
2.50
1.16
1.53
0.42
0.64
0.068
0.77
0.00
0.32
0.00
0.030
1.50
0.068
Variance
775.44
596.83
0.44
0.094
0.27
0.007
0.008
0.00
0.053
0.00
0.003
0.00
0.00
0.27
0.000
Standard
Deviation
27.85
24.43
0.66
0.31
0.52
0.084
0.089
0.009
0.23
0.00
0.052
0.00
0.005
0.52
0.012
Standard
Error
3.35
2.94
0.080
0.037
0.062
0.010
0.011
0.001
0.028
0.00
0.006
0.000
0.001
0.062
0.001
82
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics (cont.).
Type
Iwd
pools
Indicator
mining activity
volume class 1
volume class 2*
count class 1* n
count class 2*
number of
residual pools in
reach
number of pools
>50cm
number of pools
>75cm
channel length
that forms
residual pools1"
channel length
with sediment
present*
presence of
thalweg small
sediment % of
residual pool
length1
pool tail length
with sediment*
pool head
length with
sediment*
Units
prox.wtd.
index
m3/m2
3/m2
i #/100m
#/100m
count
count
count
%
%
%
%
%
Indicator
Abbrv.
WW1H_MINE
V1W_MSQ
V2W_MSQ
C1WM100
C2WM100
NRP
RPGT50
RPGT75
PCTCHARP
PCTCHASD
PCTPSED
PCTDSED
PCTUSED
Mean
0.014
0.00
0.00
1.19
0.25
15.31
0.48
0.11
55.67
7.68
12.56
13.62
12.74
Lower
95%
Conf.
-0.002
0.00
0.00
-0.854
-0.245
12.53
0.25
0.027
43.46
-1.89
-1.11
-0.11
-0.92
Upper
95%
Conf.
0.031
0.001
0.001
3.24
0.75
18.08
0.71
0.20
67.88
17.26
26.24
27.34
26.39
Median
0.00
0.00
0.00
0.00
0.00
16.00
0.00
0.00
56.00
1.33
2.97
6.17
4.85
Min
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
Max
0.33
0.016
0.011
35.33
8.67
39.50
3.00
1.00
83.64
74.67
100.00
100.00
100.00
Range
0.33
0.016
0.011
35.33
8.67
39.50
3.00
1.00
83.64
74.67
100.00
100.00
100.00
Variance
0.005
0.00
0.00
37.12
2.21
138.37
0.74
0.10
582.43
358.31
681.62
686.47
679.41
Standard
Deviation
0.068
0.002
0.002
6.09
1.49
11.76
0.86
0.32
24.13
18.93
26.11
26.20
26.07
Standard
Error
0.008
0.00
0.00
1.04
0.25
1.42
0.12
0.044
6.23
4.89
6.98
7.00
6.97
83
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics (cont.).
Type
substrate
Indicator
residual
volume per
1 00 m of
reach1"
mean residual
area per
1 00 m of
channel
number of
pools
>100cm
mean res.
depth
mean res.
pool width
mean res.
pool depth
mean pool
length
mean res.
pool volume
mean res.
pool area
percent
cobble
percent fine
Units
mVlOOm
m2/100m
count
cm
m
cm
m
m3
m2
%
%
Indicator
Abbrv.
RPV100R
RP100C
PRGT100
RP100
RPXWID
RPXDEP
PRXLEN
RPXVOL
RPXAREA
PCT_CB
PCT_FN
Mean
6.12
5.75
0.00
6.36
0.87
8.79
5.99
0.71
0.70
18.39
31.83
Lower
95%
Conf.
1.84
3.22
5.04
0.66
7.29
4.73
0.35
0.49
13.94
25.00
Upper
95%
Conf.
10.39
8.28
7.68
1.08
10.28
7.25
1.07
0.92
22.84
38.67
Median
2.61
4.23
0.00
4.89
0.69
7.12
5.23
0.21
0.37
10.91
26.42
Min
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.009
0.00
0.00
Max
28.20
15.91
0.00
20.34
4.51
25.01
21.92
8.24
3.33
69.09
100.00
Range
28.20
15.91
0.00
20.34
4.51
25.01
21.92
8.24
3.33
69.09
100.00
Variance
71.24
24.95
0.00
24.53
0.60
31.35
22.22
1.74
0.65
355.39
840.05
Standard
Deviation
8.44
5.00
0.00
4.95
0.78
5.60
4.71
1.32
0.81
18.85
28.98
Standard
Error
2.18
1.29
0.00
0.67
0.11
0.76
0.64
0.18
0.11
2.27
3.49
84
-------
Appendix 3. Summary Statistics for Physical Habitat Metrics (cont.).
Type
Indicator
percent coarse
gravel
percent fine
gravel
percent boulder
percent sand
percent
hardpan
percent wood
percent
bedrock
mean size
classf
mean
embeddedness
(channel only)f
mean
embeddedness
(mid-channel
and margin)
streambed
stability
Units
%
%
%
%
%
%
%
class 0-6
%
%
unitless
Indicator
Abbrv.
PCT_GC
PCT_GF
PCT_BL
PCT_SA
PCT_HP
PCT_WD
PCT_BR
SUB_X
XCEMBED
XEMBED
LRBS_NOR
Mean
20.55
14.77
5.30
8.15
0.42
0.38
0.20
2.71
58.83
72.44
-0.35
Lower
95%
Conf.
16.42
12.19
2.65
5.24
-0.021
0.12
-0.094
2.37
49.21
67.57
-0.63
Upper
95%
Conf.
24.67
17.35
7.96
11.06
0.86
0.64
0.49
3.05
68.46
77.31
-0.062
Median
16.36
12.73
0.00
1.89
0.00
0.00
0.00
2.92
65.30
76.27
-0.30
Min
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
1.21
10.73
-5.61
Max
69.09
47.27
64.00
61.82
12.73
7.27
10.00
4.73
100.00
100.00
1.32
Range
69.09
47.27
64.00
61.82
12.73
7.27
10.00
3.73
98.79
89.27
6.93
Variance
305.80
119.76
126.93
151.82
3.51
1.23
1.53
1.10
892.08
425.65
1.24
Standard
Deviation
17.49
10.94
11.27
12.32
1.87
1.11
1.24
1.05
29.87
20.63
1.11
Standard
Error
2.11
1.32
1.36
1.48
0.23
0.13
0.15
0.17
4.91
2.48
0.15
•fSamples taken only in the 1998 sampling season.
85
-------
Appendix 4. Streambed Stability.
Variable Name
XSLOPE
S
RP100
SDDEPTH
XBKF_H
XDEPTH
V1W_MSQ
Rbf
Rb3
R*bf
Ct rpwd
Cp3_mill
LSub_Dmm_NOR
Cp3Ctrpwd_Rat
Reyp3
Shld_Px3
Dcbf_NOR
LRBS NOR
g
V
rho
rhosed
Variable Description
(%) Channel Slope
Slope (cm)
Residual mean depth of reach (cm)
Standard deviation of Thalweg depth profile (cm)
Bankfull height mean (m)
Depth (cm)
Large woody debris volume in active channel (m3/m2)
Bankfull hydraulic radius, also Dbf th (m)
Bankfull hydraulic radius, accounting for channel geometry (m)
Bankfull hydraulic radius corrected for roughness (m)
Reach scale hydraulic resistance of residual pool woody debris
Particle resistance to submergence
Sum of weighted substrate proportions, excluding bedrock and hardpan
Resistance Ratio (resistance to submergence/residual pool reach
scale hydraulic resistance)
Reynolds number
Shields parameter for incipient motion
Streambed shear stress of bankfull flows, excluding bedrock and
hardpan
Relative Streambed stability, excluding bedrock and hardpan
Gravity (9.807 m/s2)
Kinematic viscosity of water at 20°C (1.02xlO**-6m2/s)
Density of fresh water at 20°C (998 kg/m2)
Density of silica (2650 kg m3)
86
-------
Appendix 4. Streambed Stability (cont).
Equations
1 Geometric Diameter Mean
General Equation: ((x1)(x2)(x3)...)(1/n)
gm~
((Substrate upper limit)
(Substrate lower limit))A(1/2)
2 Weighted Proportion
j)(Log10 (Dgm))(PCT_substrate/100)
2LSub_Dmm NOR
= X Site Weighted Proportions
2 Slope
SLOPE (S) = XSLOPE /100
If XSLOPE = 0, replace value with
0.01 (personal communication)
2 Bankfull Hydraulic Radius
(Rbf or Dbf_th)
Rbf = XBKF_H + XDEPTH/100
2 Bankfull hydraulic radius, accounting
for channel geometry (Rb3)
Rb3 = (0.65)(Dbf_th)
1 Reach scale hydraulic resistance of
residual pool woody debris (Ct_rpwd)
Ct_rpwd =
08
)((RP 100/1 00) +
VlW_msq)0638) /Dbfjh3 32
1 2Keulegan equation, particle resistance
to submergence (Cp3_mill)
Cp3_mill = (1/8) [2.03 Log10(12.2 (Rb3 /
//-i Q(LSub_Dmm_NOR/ 1000)\-i-2
*If Cp3_mill<0.002 then set value =
0.002
**If Cp3_mill>Ct_rpwd THEN
Ct_rpwd=Cp3_mill=Ct_rpwd_cl
2 Ratio of resistance to submergence
(Cp3_mill) to residual pool reach scale
hydraulic resistance (Ct_rpwd or
Ct_rpwd_cl) (Cp3Ctrpwd_Rat)
Cp3Ctrpwd_Rat = Cp3_mill / Ct_rpwd or
Ct_rpwd_cl
*If Cp3Ctrpwd_rat>l .000000 then
Cp3Ctrpwd_rat = 1.00
12 Roughness corrected bankfull
hydraulic radius (R*bf)
R*bf = Rb3 (Cp3Ctrpwd_Rat)1/3
12 Reynolds Number, used in calculating
Shields Parameter (Reyp3)
Reyp3 = (gR*bf(S/100))(
i r>(LSub_Dmm_NOR/1000) ;
g = 9.807 m/s2
0.5
v= 1.02xlO-6m2/s
1 2 Shields Parameter for incipient motion
(Shld_Px3)
IfReyp3>26then
Shld_Px3= 0.5{0.22Reyp3-°6 +
0.06 (10 -77Rew3-06)}
IfReyp3<26then
Shld_Px3 = 0.04Reyp3-°24
2 Streambed sheer stress of bankfull flows
(Dcbf_NOR)
Dcbf_NOR= 1000*((rho g R*bf(S/100)) /
(Shld_px3(rhosed - rho)g))
2 Stream Bed stability excluding bedrock
and hardpan (LRBS_NOR)
LRBS NOR = LSUB dmm NOR -
Log10Dcbf_NOR
87
-------
Appendix 4. Streambed Stability (cont).
Final Streambed Stability Values
Site ID
3
4
5
6
7
11
12
14
15
22
25
29
34
35
37
49
52
53
55
66
69
70
71
82
87
92
96
101
103
108
109
114
116
118
120
127
129
130
133
134
139
140
158
161
LRBS_NOR
0.525
-
-
-
-0.045
-5.615
-
1.164
-
-
0.336
0.388
-0.312
-1.328
0.203
0.092
0.622
0.156
0.004
-1.200
-0.536
-
-0.380
-0.551
-0.450
0.815
-1.838
-
-1.649
-1.702
-
-
1.264
0.553
0.577
-0.190
0.860
0.652
-0.751
1.171
-0.089
-1.661
1.320
0.282
88
-------
Appendix 4. Streambed Stability (cont).
Final Streambed Stability Values (cont.)
Site ID
164
166
170
176
181
183
184
190
193
196
199
204
215
230
235
244
245
247
250
257
259
263
269
278
280
LRBS_NOR
-1.281
0.442
0.578
-0.960
-0.480
-1.152
-0.906
-0.989
-0.598
-1.737
0.325
-0.714
-0.157
0.334
-0.597
0.041
-0.485
-0.774
-0.415
0.975
-2.202
-1.246
-0.577
-0.287
0.989
89
-------
Appendix 5. Summary Statistics for Macroinvertebrate Metrics.
Indicator
Taxa Richness
HBI
Shannon H
% EPT
EPT Taxa
% Ephemeroptera Taxa
Ephemeroptera Taxa
% Plecoptera Taxa
Plecoptera Taxa
% Trichoptera Taxa
Trichoptera Taxa
% Collectors
% Filterers
% Predators
% Scrapers
% Stredders
%lntolerant(<4)
% Tolerant Taxa (>7)
Dominant Taxa
Mean
24.56
4.73
1.99
42.86
10.92
25.54
4.34
5.32
2.31
11.99
4.27
46.90
24.52
14.23
12.07
2.28
16.26
10.02
37.55
Lower
95%
Conf.
22.67
4.47
1.88
37.42
9.37
20.90
3.79
3.31
1.79
8.24
3.56
42.10
20.04
11.34
8.72
1.15
12.21
5.88
33.65
Upper
95%
Conf.
26.46
5.00
2.10
48.29
12.47
30.19
4.90
7.34
2.83
15.75
4.97
51.71
29.01
17.12
15.41
3.41
20.30
14.16
41.45
Median
23.50
4.62
2.10
43.00
10.00
22.38
4.00
1.74
2.00
5.42
4.00
45.48
21.16
10.44
7.24
0.45
11.78
3.01
35.11
Min
9.00
2.29
0.75
1.82
2.00
0.91
1.00
0.00
0.00
0.00
0.00
7.28
0.44
1.89
0.22
0.00
0.00
0.00
13.90
Max
40.00
7.83
2.74
86.53
24.00
81.56
10.00
33.49
7.00
62.78
13.00
87.22
69.76
58.11
56.42
27.59
57.21
73.19
81.56
Range
31.00
5.54
1.99
84.71
22.00
80.65
9.00
33.49
7.00
62.78
13.00
79.94
69.32
56.22
56.20
27.59
57.21
73.19
67.66
Variance
59.90
1.20
0.20
491.60
40.04
359.50
5.18
67.55
4.54
234.83
8.23
384.70
335.40
139.20
186.50
21.35
272.60
285.53
253.54
Standard
Deviation
7.74
1.09
0.45
22.17
6.33
18.96
2.28
8.22
2.13
15.32
2.87
19.61
18.31
11.80
13.66
4.62
16.51
16.90
15.92
Standard
Error
0.97
0.14
0.06
2.77
0.79
2.37
0.28
1.03
0.27
1.92
0.36
2.45
2.29
1.47
1.71
0.58
2.06
2.11
1.99
90
-------
Appendix 6. 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
(W1_HALL)
<1.5
>3.0
%Fines
<50%
>90%
Canopy
Density
(XCDENBK)
>50%
<10%
Criteria used by John Stoddard to Identify Least- and Most-Disturbed Sites
Stoddar
d
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
91
-------
Appendix 7. Candidate Macroinvertebrate Metrics and Results of Range Test.
Metric ID
Shan_e
AmphPct
BivalPct
ChiroPct
ColeoPct
CorbPct
CrCh2ChiPct
CrMolPct
DipPct
EphemPct
EPTPct
GastrPct
IsoPct
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
EphemTax
Metric Class
Composition
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
Richness
Metric Description
Shannon's Evenness Index base e
% 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
FiltererTaxa 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
Ephemeroptera Taxa Richness
Range Test
Pass
Fail
Pass
Pass
Pass
Fail
Fail
Pass
Pass
Pass
Pass
Pass
Fail
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Fail
Pass
Pass
Pass
Pass
Fail
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Pass
92
-------
Appendix 7. Candidate Macroinvertebrate Metrics and Results of Range Test (cont.).
Mertric ID
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
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Tolerance
Metric Description
EPT Taxa Richness
Oligochaeta Taxa Richness
Orthocladiinae Taxa Richness
Plecoptera Taxa Richness
Pteronarcys Taxa Richness
Tanytarsini Taxa Richness
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
Fail
Fail
Pass
Fail
Fail
Pass
Pass
Pass
Pass
Fail
Pass
Pass
Pass
Pass
Pass
Pass
Pass
Fail
Pass
93
-------
Appendix 8. F-Test Results for Candidate Microinvertebrate Metrics.
Diversity
Composition
Feeding
Habit
Richness
Metric ID
Shan e
Shan_2
Shan_10
Orth2ChiPct
Tanyt2ChiPct
ChiroPct
GastrPct
EPTPct
TanytPct
EphemPct
TrichPct
PlecoPct
DipPct
CrMolPct
OdonPct
OligoPct
ColeoPct
NonlnPct
BivalPct
ScrapPct
FltrTax
ShredTax
Scrap! ax
PredTax
ShredPct
CllctTax
FiltrPct
PredPct
CllctPct
ClngrTax
ClngPct
SwmmrPct
SprwIPct
SwmmrTax
BrrwPct
SprwITax
BrrwTax
ChiroTax
TrichTax
PlecoTax
EPTTax
CrMolTax
EphemTax
TotalTax
DipTax
F
1.346
1.346
1.346
226.342
13.089
12.944
9.713
9.318
6.753
5.485
3.337
2.496
2.260
1.948
1.244
1.030
0.897
0.611
0.410
5.824
4.623
2.580
1.856
1.734
1.646
0.167
0.809
0.356
0.003
9.375
6.866
2.493
1.561
1.471
1.431
0.357
0.000
15.625
12.755
10.168
9.579
7.857
2.748
2.296
1.522
P-value
0.273
0.273
0.273
0.000
0.005
0.005
0.011
0.012
0.027
0.041
0.098
0.145
0.164
0.193
0.291
0.334
0.366
0.453
0.536
0.036
0.057
0.139
0.203
0.217
0.228
0.692
0.390
0.564
0.959
0.012
0.026
0.145
0.240
0.253
0.259
0.563
1.000
0.003
0.005
0.010
0.011
0.019
0.128
0.161
0.246
94
-------
Appendix 8. F-Test Results for Candidate Microinvertebrate Metrics (cont).
Tolerance
Metric ID
ColeoTax
TolerTax
IntolTax
HBI
BeckBI
IntolPct
TolPct
DomOIPct
Hyd2EPTPct
Hyd2TriPct
Baet2EptPct
F
0.220
15.943
14.246
14.172
12.414
9.982
6.750
1.671
0.575
0.154
0.103
P-value
0.649
0.003
0.004
0.004
0.006
0.010
0.027
0.225
0.466
0.703
0.755
95
-------
Appendix 9. R2 Values for Redundancy Test.
Shan_e
Orth2ChiPct
Tnyt2ChiPct
ChiroPct
GastrPct
EPTPct
TanytPct
EphemPct
FiltrTax
ScrapPct
ClngrTax
ClngrPct
ChiroTax
TrichTax
PlecoTax
EPTTax
CrMolTax
TolerTax
IntolTax
HBI
BeckBI
IntolPct
TolerPct
Shan_e
1
0.11
0.30
0.33
0.00
0.51
0.48
0.47
0.46
0.37
0.34
0.41
0.01
0.39
0.44
0.54
0.03
0.00
0.48
0.27
0.48
0.33
0.03
Orth2ChiPct
0.11
1
0.59
0.66
0.47
0.49
0.47
0.37
0.29
0.30
0.38
0.34
0.64
0.48
0.45
0.41
0.32
0.49
0.51
0.49
0.46
0.45
0.30
Tnyt2ChiPct
0.30
0.59
1
0.59
0.34
0.24
0.77
0.14
0.24
0.14
0.22
0.17
0.30
0.45
0.25
0.43
0.11
0.22
0.45
0.29
0.42
0.28
0.12
ChiroPct
0.33
0.66
0.59
1
0.28
0.52
0.84
0.50
0.24
0.18
0.27
0.24
0.29
0.35
0.28
0.34
0.02
0.10
0.39
0.21
0.37
0.30
0.01
GastrPct
0.00
0.47
0.34
0.28
1
0.10
0.17
0.03
0.00
0.15
0.22
0.19
0.54
0.26
0.22
0.22
0.56
0.61
0.29
0.14
0.25
0.27
0.02
EPTPct
0.51
0.49
0.24
0.52
0.10
1
0.35
0.91
0.50
0.72
0.57
0.72
0.14
0.67
0.73
0.70
0.02
0.18
0.73
0.68
0.69
0.71
0.22
TanytPct
0.48
0.47
0.77
0.84
0.17
0.35
1
0.30
0.21
0.12
0.19
0.16
0.11
0.31
0.21
0.34
0.00
0.03
0.36
0.15
0.34
0.22
0.01
EphemPct
0.47
0.37
0.14
0.50
0.03
0.91
0.30
1
0.53
0.65
0.46
0.61
0.07
0.50
0.51
0.48
0.00
0.07
0.55
0.48
0.54
0.44
0.14
FiltrTax
0.46
0.29
0.24
0.24
0.00
0.50
0.21
0.53
1
0.31
0.25
0.27
0.10
0.33
0.31
0.33
0.00
0.07
0.35
0.46
0.35
0.22
0.36
ScrapPct
0.37
0.30
0.14
0.18
0.15
0.72
0.12
0.65
0.31
1
0.73
0.93
0.06
0.78
0.73
0.75
0.11
0.27
0.82
0.70
0.80
0.63
0.33
ClngrTax
0.34
0.38
0.22
0.27
0.22
0.57
0.19
0.46
0.25
0.73
1
0.88
0.09
0.77
0.77
0.79
0.20
0.28
0.86
0.67
0.90
0.68
0.29
ClngrPct
0.41
0.34
0.17
0.24
0.19
0.72
0.16
0.61
0.27
0.93
0.88
1
0.06
0.79
0.86
0.82
0.13
0.24
0.89
0.70
0.88
0.73
0.27
96
-------
Appendix 9. R2 Values for Redundancy Test (cont).
Shan_e
Orth2ChiPct
Tnyt2ChiPct
ChiroPct
GastrPct
EPTPct
TanytPct
EphemPct
FiltrTax
ScrapPct
ClngrTax
ClngrPct
ChiroTax
TrichTax
PlecoTax
EPTTax
CrMolTax
TolerTax
IntolTax
HBI
BeckBI
IntolPct
TolerPct
ChiroTax
0.01
0.64
0.30
0.29
0.54
0.14
0.11
0.07
0.10
0.06
0.09
0.06
1
0.18
0.13
0.11
0.37
0.61
0.15
0.23
0.12
0.20
0.15
TrichTax
0.39
0.48
0.45
0.35
0.26
0.67
0.31
0.50
0.33
0.78
0.77
0.79
0.18
1
0.72
0.94
0.18
0.38
0.94
0.82
0.95
0.75
0.40
PlecoTax
0.44
0.45
0.25
0.28
0.22
0.73
0.21
0.51
0.31
0.73
0.77
0.86
0.13
0.72
1
0.85
0.20
0.30
0.86
0.77
0.81
0.91
0.29
EPTTax
0.54
0.41
0.43
0.34
0.22
0.70
0.34
0.48
0.33
0.75
0.79
0.82
0.11
0.94
0.85
1
0.15
0.30
0.96
0.80
0.95
0.86
0.31
CrMolTax
0.03
0.32
0.11
0.02
0.56
0.02
0.00
0.00
0.00
0.11
0.20
0.13
0.37
0.18
0.20
0.15
1
0.76
0.18
0.23
0.16
0.22
0.27
TolerTax
0.00
0.49
0.22
0.10
0.61
0.18
0.03
0.07
0.07
0.27
0.28
0.24
0.61
0.38
0.30
0.30
0.76
1
0.35
0.49
0.32
0.40
0.41
IntolTax
0.48
0.51
0.45
0.39
0.29
0.73
0.36
0.55
0.35
0.82
0.86
0.89
0.15
0.94
0.86
0.96
0.18
0.35
1
0.80
0.99
0.82
0.33
HBI
0.27
0.49
0.29
0.21
0.14
0.68
0.15
0.48
0.46
0.70
0.67
0.70
0.23
0.82
0.77
0.80
0.23
0.49
0.80
1
0.79
0.81
0.67
BeckBI
0.48
0.46
0.42
0.37
0.25
0.69
0.34
0.54
0.35
0.80
0.90
0.88
0.12
0.95
0.81
0.95
0.16
0.32
0.99
0.79
1
0.78
0.34
IntolPct
0.33
0.45
0.28
0.30
0.27
0.71
0.22
0.44
0.22
0.63
0.68
0.73
0.20
0.75
0.91
0.86
0.22
0.40
0.82
0.81
0.78
1
0.28
TolerPct
0.03
0.30
0.12
0.01
0.02
0.22
0.01
0.14
0.36
0.33
0.29
0.27
0.15
0.40
0.29
0.31
0.27
0.41
0.33
0.67
0.34
0.28
1
97
-------
Appendix 10. Final IBI Scores.
Site ID
3
4
5
6
7
11
12
14
15
22
25
29
34
35
37
49
52
53
55
66
69
70
71
82
87
92
96
101
103
108
109
114
116
118
120
127
129
130
133
134
140
158
161
164
166
170
IBI
38.0
68.0
44.0
10.0
48.0
28.0
44.0
34.0
36.0
68.0
44.0
82.0
46.0
58.0
38.0
52.0
86.0
58.0
56.0
38.0
40.0
82.0
76.0
32.0
76.0
62.0
28.0
48.0
18.0
48.0
58.0
74.0
48.0
76.0
82.0
30.0
96.0
68.0
80.0
70.0
16.0
66.0
56.0
48.0
70.0
78.0
98
-------
Appendix 10. Final IBI Scores (cont.).
Site ID
176
183
184
190
193
196
199
20
215
235
245
247
250
259
263
269
278
280
IBI
34.0
86.0
72.0
38.0
58.0
18.0
82.0
50.0
44.0
38.0
18.0
32.0
24.0
16.0
52.0
52.0
28.0
92.0
99
-------
Appendix 11. Sediment Respiration.
Site
Number
3
4
5
6
7
11
12
14
15
22
25
29
34
35
37
49
52
53
55
66
69
71
82
87
92
96
101
103
108
109
114
116
118
120
127
Temperature
(°C)
19.8
17.2
12.9
20.5
22.0
21.7
16.1
26.6
26.8
22.5
13.5
18.0
22.8
28.8
17.9
18.0
16.6
21.9
20.0
16.5
25.7
14.5
18.4
18.7
11.6
21.7
12.0
19.1
14.0
21.4
13.9
22.3
17.0
17.4
12.5
DO/AFDM/TIME
(mg/g/h)
2.89
0.90
0.57
1.31
5.98
4.52
4.49
4.43
8.23
4.89
4.34
3.89
13.43
2.99
5.76
6.43
-0.59
5.31
6.61
6.94
5.57
3.23
9.72
5.80
3.29
4.45
0.97
8.07
4.85
1.60
4.93
10.03
5.11
4.06
4.06
100
-------
Appendix 11. Sediment Respiration (cont).
Site
Number
129
130
133
134
140
158
161
164
166
170
176
181
183
184
190
193
196
199
204
215
235
244
245
247
250
259
263
269
278
280
Temperature
(°C)
16.7
9.7
18.4
18.7
11.5
18.5
16.7
26.6
18.5
16.2
20.7
31.2
22.8
25.0
13.5
20.2
25.9
20.3
16.0
23.1
8.2
23.8
24.4
14.4
23.2
15.2
23.0
12.0
23.0
8.7
DO/AFDM/TIME
(mg/g/h)
2.92
1.51
4.96
5.80
2.08
0.70
3.24
8.75
5.03
1.78
2.96
9.02
5.22
7.89
2.18
2.69
6.56
4.22
5.26
4.81
3.38
1.63
4.80
6.17
9.01
7.70
2.99
3.29
3.04
1.73
101
-------
Appendix 12. Water Metals (H9/L).
Metal
Aluminum
Antimony
Arsenic
Barium
Beryllium
Boron
Cadmium
Calcium
Chromium
Cobalt
Copper
Iron
Lead
Magnesium
Manganese
Mercury1^
Molybdenum*
Nickel
Phosphate*
Potassium
Selenium
Silicon*
Silver
Sodium
Strontium*
Sulfur*
Thallium*
Tin*
Titanium*
Vanadium
Zinc
Hardness
Mean
76.86
19.08
7.47
79.79
0.15
90.23
1.18
3.10E+04
1.77
2.62
2.33
77.07
4.33
1.15E+04
27.90
0.10
2.56
10.28
70.93
3.62E+03
8.29
1.46E+04
1.86
2.19E+04
176.58
1.23E+04
9.20
8.65
3.55
3.67
7.43
126.56
Lower
95% Conf.
38.34
16.31
4.75
67.37
0.14
60.70
1.14
2.66E+04
1.71
2.47
2.14
35.95
3.64
8.95E+03
-1.73
1.91
9.21
58.86
2.67E+03
6.72
1.27E+04
1.62
1.51E+04
140.99
6.66E+03
8.93
8.19
2.99
3.04
5.72
106.42
Upper 95%
Conf.
115.39
21.85
10.19
92.22
0.17
119.76
1.23
3.53E+04
1.84
2.78
2.52
118.19
5.01
1.40E+04
57.53
3.22
11.36
82.99
4.58E+03
9.86
1.65E+04
2.10
2.87E+04
212.16
1.80E+04
9.47
9.11
4.11
4.31
9.14
146.69
Median
30.50
8.00
2.90
69.50
0.20
49.10
1.00
2.80E+04
1.50
2.00
2.00
23.70
7.00
6.75E+03
4.30
0.10
2.00
6.00
51.00
2.32E+03
14.00
1.49E+04
1.20
1.29E+04
145.70
4.06E+03
9.00
8.00
3.00
3.00
5.30
100.68
Min
3.70
8.00
0.00
7.30
0.10
8.30
1.00
4.34E+03
1.50
2.00
1.80
1.30
0.90
834.00
0.30
0.10
1.10
6.00
37.00
459.00
0.50
5.01 E+03
0.80
1.91 E+03
44.20
1.30E+02
9.00
8.00
3.00
0.30
1.00
15.24
Max
1.280E+03
35.90
75.00
269.70
0.20
817.00
1.60
7.63E+04
2.30
4.20
5.40
1.200E+03
7.30
4.15E+04
1.11 E+03
0.10
13.50
17.10
187.35
3.08E+04
23.15
2.79E+04
3.30
2.21E+05
515.50
7.49E+04
13.30
13.90
12.70
12.60
39.10
322.17
Range
1.276E+03
27.90
75.00
262.40
0.10
808.70
0.60
7.20E+04
0.80
2.20
3.60
1.199E+03
6.40
4.07E+04
1.11 E+03
0.00
12.40
11.10
150.35
3.03E+04
22.65
2.29E+04
2.50
2.19E+05
471.30
7.48E+04
4.30
5.90
9.70
12.30
38.10
306.93
Variance
2.90E+04
149.47
140.50
3.01 E+03
0.002
1.70E+04
0.042
3.69E+08
0.093
0.46
0.72
3.30E+04
9.28
1.26E+08
1.71E+04
0.00
4.59
22.47
1.55E+03
1.79E+07
48.15
3.78E+07
1.13
9.06E+08
1.35E+04
3.45E+08
0.78
2.26
3.32
7.89
57.20
7.92E+03
Standard
Deviation
170.22
12.23
11.85
54.90
0.050
130.48
0.20
1.92E+04
0.30
0.68
0.85
181.69
3.05
1.12E+04
130.93
0.00
2.14
4.74
39.41
4.24E+03
6.94
6.15E+03
1.06
3.01 E+04
116.25
1.86E+04
0.89
1.50
1.82
2.81
7.56
88.97
Standard
Error
19.66
1.41
1.39
6.34
0.006
15.07
0.024
2.22E+03
0.035
0.079
0.098
20.98
0.35
1.30E+03
15.12
0.00
0.33
0.55
6.16
489.20
0.80
960.14
0.12
3.48E+03
18.16
2.90E+03
0.14
0.23
0.28
0.32
0.87
10.27
"fSamples taken only
*Samples taken only
in the 1998 sampl
in the 1999 sampl
mg season.
ing season.
102
-------
Appendix 13. Sediment Metals (mg/kg).
Metal
Aluminum
Antimony
Arsenic
Barium
Beryllium
Boron*
Cadmium
Calcium
Chromium
Cobalt
Copper
Iron
Lead
Magnesium
Manganese
Mercury1
Molybdenum*
Nickel
Phosphate*
Potassium
Selenium
Silicon*
Silver
Sodium
Strontium*
Sulfur*
Thallium*
Tin*
Titanium*
Vanadium
Zinc
Mean
1.42E+04
6.59
5.50
313.60
0.69
23.94
0.61
1.12E+04
14.66
6.58
16.51
1.53E+04
8.50
4.29E+03
438.58
0.22
0.51
16.12
576.80
3.46E+03
11.00
2.68E+03
0.60
690.73
65.87
373.53
0.82
0.85
671.29
38.58
65.61
Lower
95% Conf.
1.30E+04
4.95
4.36
257.94
0.63
20.08
0.41
7.09E+03
12.50
5.86
13.95
1.39E+04
6.63
3.68E+03
354.86
0.11
0.26
13.12
494.82
3.02E+03
8.59
2.39E+03
0.44
556.20
51.23
282.04
0.69
-0.035
591.84
32.02
52.30
Upper 95%
Conf.
1.54E+04
8.23
6.64
369.26
0.76
27.81
0.81
1.53E+04
16.81
7.30
19.08
1.67E+04
10.36
4.91E+03
522.30
0.33
0.76
19.12
658.78
3.89E+03
13.42
2.97E+03
0.75
825.26
80.52
465.03
0.96
1.74
750.74
45.15
78.91
Median
1.43E+04
1.93
4.06
264.50
0.63
20.05
0.45
5.22E+03
12.32
5.98
13.12
1.41E+04
7.35
3.52E+03
358.62
0.13
0.09
13.04
525.75
2.87E+03
10.92
2.35E+03
0.069
462.50
56.14
239.67
0.60
0.40
655.92
30.15
52.84
Min
3.20E+03
0.50
0.40
26.51
0.15
2.31
0.00
637.22
1.35
0.92
0.57
2.81 E+03
0.97
485.88
116.77
0.07
0.09
1.28
118.17
571.22
0.17
1.44E+03
0.050
72.10
5.62
35.45
0.17
0.40
161.07
3.50
10.04
Max
2.54E+04
32.00
27.60
1.56E+03
1.80
51.76
7.74
1.23E+05
44.90
16.50
58.30
3.70E+04
52.70
1.47E+04
3.25E+03
1.50
4.39
98.82
1.19E+03
9.28E+03
40.04
5.43E+03
3.00
2.70E+03
301.48
1.29E+03
2.76
20.35
1.24E+03
170.98
509.42
Range
2.22E+04
31.50
27.20
1.54E+03
1.65
49.45
7.74
1.22E+05
43.55
15.58
57.73
3.42E+04
51.73
1.42E+04
3.13E+03
1.43
4.30
97.54
1.07E+03
8.71 E+03
39.87
3.99E+03
2.95
2.63E+03
295.86
1.25E+03
2.59
19.95
1.08E+03
167.48
499.38
Variance
2.86E+07
54.66
26.33
6.29E+04
0.091
170.82
0.81
3.43E+08
94.49
10.52
133.80
3.78E+07
69.78
7.63E+06
1.42E+05
0.10
0.72
182.73
7.70E+04
3.84E+06
118.46
9.70E+05
0.48
3.67E+05
2.46E+03
9.59E+04
0.20
9.05
7.23E+04
874.70
3.60E+03
Standard
Deviation
5.35E+03
7.39
5.13
250.82
0.30
13.07
0.90
1.85E+04
9.72
3.24
11.57
6.15E+03
8.35
2.76E+03
377.25
0.32
0.85
13.52
277.44
1.96E+03
10.88
984.71
0.69
606.19
49.58
309.65
0.45
3.01
268.87
29.58
59.96
Standard
Error
605.24
0.84
0.58
28.40
0.034
1.97
0.10
2.10E+03
1.10
0.37
1.31
696.00
0.95
312.86
42.72
0.056
0.13
1.53
41.83
221.81
1.23
148.45
0.079
68.64
7.47
46.68
0.068
0.45
40.53
3.35
6.79
"fSamples taken only in
*Samples taken only in
the 1998 sampling
the 1999 sampling
season.
season.
103
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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.
Benthic Invertebrate Indicators and Water Chemistry Stressors
Richness
EPT Taxa
% Intolerants
PH
-0.320
-0.420
SpC
-0.374
-0.484
-0.410
Chloride
-0.329
-0.376
Sulfate
-0.426
-0.430
-0.317
TKN
-0.356
-0.379
IDS
-0.442
-0.496
-0.387
NH3
-0.348
-0.332
Benthic Invertebrate Indicators and Physical Habitat Stressors
Richness
EPT Taxa
% Intolerants
All Fish
cover
types but
Algae
0.370
0.432
Fish
cover
areas by
Natural
Objects
0.371
0.435
Fish
cover
areas by
Large
Objects
0.393
Canopy
Present
0.426
0.553
0.389
Midlayer
Present
0.443
0.401
0.355
Canopy
Absent
-0.428
-0.556
-0.389
Mean
Canopy
Density
0.437
0.430
0.346
% Fine
-0.421
-0.402
% Boulder
0.376
Streambed
Stability
0.424
0.327
Benthic Invertebrate Indicators and Physical Habitat Stressors
EPT Taxa
% Intolerants
All
-0.383
-0.383
Pastures/Hayfields
-0.419
-0.341
104
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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 (cont.).
Macroinvertebrate IBI Indicator and Physical Habitat Stressors
IBI
Undercut
0.301
Bankfull
Height
0.323
% Fast
0.542
Canopy
Present
0.439
Midlayer
Present
0.313
Canopy
Absent
-0.442
Mean
Canopy
Density
0.463
%
Cobble
0.442
% Fine
-0.615
%
Coarse
Gravel
0.361
%
Boulder
0.462
Streambed
Stability
0.498
Macroinvertebrate IBI Indicator and Physical Habitat and Riparian Disturbance Stressors
IBI
All Fish cover types
but Algae
0.417
Fish cover areas
by Natural Objects
0.423
Fish cover areas by
Large Objects
0.401
Pasture/Hayfield
-0.350
Macroinvertebrate IBI indicator and Water Chemistry Stressors
IBI
pH
-0.319
SpC
-0.464
Sulfate
-0.319
TKN
-0.379
IDS
-0.407
105
-------
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 (cont.).
Water Chemistry indicators and Physical Habitat stressors
PH
Cond
DO
Temp
Chloride
Sulfate
TSS
TKN
TP
IDS
NH3
Slope
-0.289
%
Fast
-0.281
-0.314
-0.286
-0.299
All
Fish
Cover
types
but
Algae
-0.306
-0.338
-0.454
-0.314
-0.299
-0.361
Fish
Cover
areas by
Natural
Objects
-0.306
-0.339
-0.451
-0.316
-0.299
-0.277
-0.363
Fish
cover
areas
by
Large
Objects
-0.287
-0.287
-0.337
-0.338
-0.299
Vegetation
Canopy
Cover
-0.348
Vegetation
Midlayer
Cover
-0.289
-0.314
-0.410
-0.328
-0.399
-0.291
Vegetation
Ground
Cover
-0.304
0.312
Canopy
Absent
0.380
0.348
0.343
Mean
Canopy
Density
-0.384
-0.427
-0.405
-0.387
-0.385
-0.480
%
Fine
0.386
0.296
0.359
0.327
0.390
0.428
0.286
Riparian
Disturbance
Pastures
0.309
106
-------
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 (cont.).
Physical Habitat indicators and Riparian Disturbances
Undercut Distance
% Pools
All Fish Cover types but Algae
Fish Cover area by Natural Objects
Fish Cover Areas by Large Objects
Vegetation Midlayer Cover
Canopy Absent
Mean Canopy Density
% Fine Gravel
All
-0.261
-0.256
Buildings
-0.282
0.302
Roads
-0.284
Pastures
-0.252
-0.397
-0.393
-0.368
-0.356
0.388
-0.407
0.298
Sediment Metabolism Indicator and Physical Habitat Stressors
Sediment
Metabolism
% Fast
-0.326
All Fish
Cover types
but Algae
-0.371
Fish Cover
areas by
Natural Objects
-0.368
Fish cover areas
by Large
Objects
-0.272
Vegetation
Midlayer
Cover
-0.389
Vegetation
Ground
Cover
-0.371
Canopy
Absent
0.312
Midlayer
Absent
0.332
Mean
Canopy
Density
-0.381
Sediment Metabolism Indicator and Water Column Stressors
Sediment Metabolism
PH
0.259
Temperature
0.353
107
-------
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)].
Metric
%slow
density
RipDist All
Embed
SO4
TP
TN
Fish Cover
RipVeg
RP100
LRBS_NOR
Description
% Pools + Glides
Canopy Density
Riparian Disturbance All
Mean Embeddedness
Sulfate
Total Phosphorus
Total Nitrogen
Fish Cover from Natural Features
Riparian Vegetation
Mean Residual Depth
Streambed Stability
A(#of
sites)
17
19
7
16
14
10
9
8
18
21
4
B(#of
sites)
23
5
3
5
4
8
8
1
10
18
1
C(#of
sites)
5
3
15
6
11
5
3
17
2
1
4
D(#of
sites)
1
14
23
22
22
14
7
25
11
1
7
Relative
Risk
0.3
4.0
2.0
3.3
3.0
1.7
1.5
5.4
2.4
1.1
3.2
Most
Disturbed
Condition
17.4%
34.8%
72.5%
53.6%
34.3%
35.8%
37.1%
77.9%
24.6%
3.7%
25.4%
108
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Appendix 16 - USEPA Water Quality Criteria for Trace Metals
Aquatic Life Criteria Table
Pollutant
Alkalinity
Aluminum pH
6.5-9.0
Ammonia
Arsenic
Bacteria
Boron
Cadmium
Chloride
Chromium (III)
Chromium (VI)
Copper
Hardness
Iron
Lead
Mercury
Methylmercury
Nickel
Nutrients
Oxygen, Dissolved
Freshwater
pH
Phosphorus
Elemental
Selenium
Silver
Solids Suspended
and Turbidity
Sulfide-Hydrogen
Sulfide
Temperature
Zinc
CAS P/NP*
Number
— NP
7429905 NP
7664417 NP
7440382 P
— NP
— NP
7440439 P
16887006 NP
16065831 P
18540299 P
7440508 P
— NP
7439896 NP
7439921 P
7439976
P
22967926
7440020 P
— NP
7782447 NP
— NP
7723140 NP
7782492 P
7440224 P
— NP
7783064 NP
— NP
7440666 P
Freshwater Saltwater
CMC1 CCC1 CMC- CCC-
(acute) (chronic) (acute) (chronic)
(ug/L) (ug/L) (ug/L) (ug/L)
20000 C
750 I 87 I,S
FRESHWATER CRITERIA ARE pH, Temperature and Life-stage
DEPENDENT
SALTWATER CRITERIA ARE pH AND TEMPERATURE
DEPENDENT
340 A,D 150 A,D 69A,D 36A,D
FOR PRIMARY RECREATION AND SHELLFISH USES— SEE
DOCUMENT
NARRATIVE STATEMENT— SEE DOCUMENT
2.0 D,E 0.25 D,E 40 D 8.8 D
860000 230000
570 D,E 74 D,E
16D 11D 1,100D 50D
Freshwater criteria calculated using the . 0 „ , , „
„,, „ _ ^ 6 4.8D,cc 3.1D,cc
BLM mm - See Document
NARRATIVE STATEMENT— SEE DOCUMENT
1000C
65D,E 2.5 D,E 210D 8.1 D
1.4D,hh 0.77 D,hh L8D,ee,hh 0.94 D,ee,hh
470 D,E 52D,E 74 D 8.2 D
See USEPA's Ecoregional criteria for Total Phosphorus, Total
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
DOCUMENT
6.5 -9 C 6.5-8.5C,P
L 5.0 290D,dd 71D,dd
3.2D,E,G L9D,G
NARRATTVF ST A TFTV/TKMT SFF DPiPTTK/TRNT P
IN/nJVTvrt. 1 1 V JIj O 1 r\ 1 JJ/IVLUJIN 1 Ojjjjjj J_-*vJV^ UIVUJ/IN 1 V_.
2.0 C 2.0 C
SPECIES DEPENDENT CRITERIA— SEE DOCUMENT M
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).
109
-------
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 O
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).
110
-------
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
mA bA mc bc
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)] [(/«hardness)(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)
111
-------
112
-------
Appendix 17 - Calculation of Freshwater Ammonia Criterion
1. The one-hour average concentration of total ammonia nitrogen (in mg N/L) does not exceed,
more than once every three years on the average, the CMC (acute criterion) calculated using the
following equations:
o Where salmonid fish are present:
• CMC = (0.275/(1 + 107204-pH)) + (39.0/(1 + 10pH-7204))
o Or where salmonid fish are not present:
• CMC = (0.411/(1 + 107'204-pH)) + (58.4/(l + 10pH-7'204))
2.
A. The thirty-day average concentration of total ammonia nitrogen (in mg N/L) does not
exceed, more than once every three years on the average, the CCC (chronic criterion)
calculated using the following equations:
• When fish early life stages are present:
• CCC = ((0.05777(1 + 107688-pH)) + (2.487/(l + 10pH-7688))) x MIN (2.85, 1.45-100028<25-T))
• When fish early life stages are absent:
• CCC = ((0.05777(1 + 107688-pH)) + (2.487/(l + 10pH-7'688))) x iA5.iQ°-™-&-wv.T»
B. In addition, the highest four-day average within the 30-day period should not exceed 2.5
times the CCC.
113
-------
114
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-------
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