&EPA
EPA/600/R-13/006 | January 2013 | www.epa.gov/research
United States
Environmental Protection
Agency
An Ecological Characterization
id Landscape Assessment of
the Humboldt River Basin
RESEARCH AND DEVELOPMENT
-------
-------
An Ecological Characterization
and Landscape Assessment of
the Humboldt River Basin
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, CA94105
3U.S. Environmental Protection Agency
Region 9 Laboratory
Richmond, CA 94804
Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official
Agency policy. Mention of trade names and commercial products does not constitute endorsement or
recommendation for use.
U.S. Environmental Protection Agency
Office of Research and Development
Washington, DC 20460
-------
11
-------
Table of Contents
List of Tables v
List of Figures vii
List of Appendices xi
List of Acronyms and Abbreviations xiii
Acknowledgements xiv
Executive Summary 1
1.0 Introduction 3
1.1. Objectives 3
1.2. Broad-Scale Environmental Condition 4
1.3. Overview 6
2.0 The Biophysical Setting 7
2.1. Land Cover and Topography 7
2.2. Streams 10
2.3. Watershed 11
3.0 Methodology 13
3.1. Regional Classification 13
3.2. EPA-Delineated Sub-watersheds 14
3.3. Landscape Metrics 16
3.4. Soil and Landform Metrics 17
3.5. EMAP Measurements 17
3.6. Data Sources 18
3.7. Data Analysis 18
4.0 Land Cover/Use 19
4.1. Forests 19
4.2. Shrubland/Grasslands 20
4.3. Agriculture 21
4.4. Grazing 22
4.5. Population Growth and Urban Development 25
4.6. Roads 26
4.7. Mining 27
4.8. Riparian Land Cover/Use 31
iii
-------
5.0 Land Cover Comparison 33
6.0 Soil Cover 35
6. l.R Factor 35
6.2. C Factor 36
6.3. K Factor 37
6.4. P factor 38
6.5. LS Factor 38
6.6. A Value 39
7.0 Ecological Indicators 41
7.1. Dissolved Oxygen 41
7.2. pH 42
7.3. Total Kjeldahl Nitrogen 42
7.4. Total Phosphorus 42
7.5. IBI 43
7.6. TDS 43
8.0 Landscape and Water Relationships 45
8.1. Regression Models 45
8.2. Model Application 45
9.0 Conclusion 47
References 51
Data 55
Programs 57
Appendix 1. Humboldt Ecoregions (USEPA, 2007) 59
Appendix 2. Regional HUC Numbers and Corresponding Names 61
Appendix 3. List of Sampling Sites 62
Appendix 4. Descriptive Statistics for 12-DigitHUCs and Delineated Watersheds 64
Appendix 5. RILSE Variables 65
Appendix 6. User Defined Summary of Surface Layers in the Humboldt River Basin 66
Appendix 7. Ecological Indicators 67
Appendix 8. Predicted Models 69
iv
-------
List of Tables
Table 1. 2001 National Land Cover Data Regional Land Cover Classes 13
Table 2. Major Population Areas in the Humboldt Basin from 1980-2000 25
Table 3. Water Quality and Metal Data for Nested Sites within the Reese River Area 29
Table 4. R Values of Significant Correlations (P<0.05) Between Past and Present Gold
Mines and Ecological Indicators 30
Table 5. General Distribution of K Factor Values 37
Table 6. Water Quality Standards for Nevada 41
Table 7. Indicator Exceedances 44
Table 8. Multiple Regression Models 45
-------
VI
-------
List of Figures
Figure 1. Location of the Humboldt River Basin 3
Figure 2. 2001 NLCD (MRLC, 2008) 4
Figure 3. National Map of Roads (USGS, 1995) 5
Figure 4. Jurisdictional Boundaries for Nevada (BLM, 2010) 6
Figure 5. National Elevation Data for the Humboldt River Basin 7
Figure 6. Ecoregions in the Humboldt River Basin 8
Figure 7. Land Cover/Use in the Humboldt River Basin 9
Figure 8. Streams and Water Bodies in the Humboldt River Basin 10
Figure 9. National Map of 8-digit HUCs. 2-digitHUCs are Illustrated in Color 11
Figure 10. 12-Digit Watershed Boundaries for the Humboldt River Basin 12
Figure 11. Lovelock, Rye Patch Reservoir Vegetation Shown in Red 14
Figure 12. Humboldt Watersheds and GIS-Delineated Sub-Watersheds 15
Figure 13. Example of the Maps that Appear in this Report. The Maps are Color
Coded to Show Land Cover/Use Percentages 17
Figure 14. Percentage of Forested Land in the HUCs 19
Figure 15. Percent Shrub/Scrubland in the Humboldt River Basin 20
Figure 16. Percent Natural Grasslands in the Humboldt River Basin 20
Figure 17. Percent Total Agriculture in the Humboldt River Basin 21
Figure 18. Evidence of Soil Trampling 22
Figure 19. AUM Values Per Square Kilometer in the Humboldt River Basin 24
Figure 20. Percent Urban Areas in Humboldt River Basin 25
Figure 21. Population Change in the Humboldt River Basin 26
Figure 22. Road Density in the Humboldt River Basin 26
Figure 23. Number of Road/Stream Crossings Per Kilometer of Stream 27
vn
-------
Figure 24. Humboldt Land Cover Including Mine with 1km Buffer 28
Figure 25. Nested Sites in the Reese River with Past and Present Gold Mines
and Processing Plants 29
Figure 26. Percentage of Riparian Buffer in Forest, Shrubland, Grassland, Agriculture
and Wetland Calculated within a 30m Buffer 31
Figure 27. Retrofit Land Cover Change 33
Figure 28. National Land Cover Dataset for 1992 and 2001 Showing the Burn Locations
for the 1999 Fire Season 34
Figure 29. Rainfall Erosivity in the Humboldt River Basin 35
Figure 30. Average Rainfall Erosivity (R Factor) for the Continental United States
(Troeh, 2005) 36
Figure 31. C Factor Values for the Humboldt River Basin 36
Figure 32. K Factor Values in the Humboldt River Basin 37
Figure 33. Map of Surface Layers in the Humboldt River Basin 38
Figure 34. LS Values for the North Fork Humboldt Area 39
Figure 35. A Values Throughout the Western United States (USEPA, 2010) 39
Figure 36. Dissolved Oxygen in the Humboldt River Basin 41
Figure 37. pH in the Humboldt River Basin 42
Figure 38. Total Kjeldahl Nitrogen in the Humboldt River Basin 42
Figure 39. Total Phosphorus in the Humboldt River Basin 42
Figure 40. Index of Biological Integrity in the Humboldt River Basin 43
Figure 41. Total Dissolved Solids in the Humboldt River Basin 43
Figure 42. Land Cover/RUSLE Extreme Values for 12-digitHUCs 48
Figure 43. Predicted Water Quality Indicators Extreme Values for 12-digitHUCs 49
Figure 44. Humboldt Basin Subwatersheds Having Landscape Metrics Associated with
Water Quality Degradation 49
Figure 45. Humboldt Basin Subwatersheds Having Landscape Metrics Associated with
Water Quality Degradation 69
Vlll
-------
Figure 46. Predicted Total Kjeldahl Nitrogen Values for the Humboldt River Basin 69
Figure 47. Predicted Total Phosphorus Values for the Humboldt River Basin 70
Figure 48. Predicted IBI for the Humboldt River Basin 71
IX
-------
-------
Appendices
Appendix 1. Humboldt Ecoregions (USEPA, 2007) 59
Appendix 2. Regional HUC Numbers and Corresponding Names 61
Appendix 3. List of Sites 62
Appendix 4. Descriptive Statistics forHUCs and Delineated Watersheds 64
Appendix 5. RULSE Variables 65
Appendix 6. User Defined Summary of Surface Layers in the Humboldt River Basin 66
Appendix?. Ecological Indicators 67
Appendix 8. Predicted Models 69
XI
-------
Xll
-------
Acronyms and Abbreviations
A Value Gross Soil Erosion Rate
AML Arc Macro Language
ATtlLA Analytical Tools Interface for Landscape Assessment
ARS Agricultural Research Service
AUM Animal-unit-months
BLM Bureau of Land Management
BOR U.S. Bureau of Reclamation
C Factor Surface Cover Effect
DEM Digital Elevation Model
EMAP Environmental Monitoring and Assessment Program
GIS Geographical Information System
HUC Hydrologic Accounting Unit
IBI Index of Biotic Integrity
K Factor Surface Erodibility
LS Factor Slope Length/Steepness
MRLC Multi-Resolution Land Characteristics Consortium
NASA National Aeronautics and Space Administration
NDA Nevada Department of Agriculture
NLC Nevada Legislative Counsel
NLCD National Land Cover Database
NNHP Nevada National Heritage Program
NFS National Park Service
NDWP Nevada Division of Water Planning
P Factor Conservation Practices
R Factor Rainfall Erosivity
RF3 River Reach File Version 3
RUSLE Revised Universal Soil Loss Equation
SEDMOD Spatially Explicit Delivery Model
STATSGO State Soil Geographic Database
TM Thematic Mapping
USEPA U.S. Environmental Protection Agency
USFS U.S. Forest Service
USGS U.S. Geological Survey
USDA U.S. Department of Agriculture
Xlll
-------
Acknowledgements
The authors would like to recognize the good people that helped us with this report; Sherman Swanson,
Tad Harris, Pam Grossman, Kuen Huang-Farmer, Maria Gregorio, Angela Hammond, Richard Snell and
Heather Powell. We feel that this ecological landscape analysis will be of value as a starting point to
assess the condition of the Humboldt River System. We strongly believe that reporting this analysis 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 review this report in their time and effort including, David Goodrich,
Steve Gardner, and Maliha Nash.
Notice
The information in this document has been funded in part by the United States Environmental Protection
Agency under Student Services Contract number EP10D000282 to Leah Hare and Cooperative
Agreement CR-826293-01 University if 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.
xiv
-------
Executive Summary
The Humboldt River Basin covers a large part of northern Nevada. Very little is known about the water
quality of the entire Basin. The people living in this area depend on clean water. Not knowing about
water quality is a concern because people will need to manage the negative impacts of mining,
agriculture, livestock grazing, land development, water use, and timber harvest. This area has had some of
the most intense mining in Nevada history. It is also experiencing accelerated groundwater depletion and
acid mine drainage from older abandoned mines. These activities may adversely effect water quality for
human use and for the unique aquatic biota found there, including four threatened or endangered fishes
and one amphibian candidate for listing as endangered or threatened. Landscape characterization and
analysis are cost-effective tools which can be used to characterize the quality and condition of ecological
resources. This information can be used by local resource managers and local stakeholders to make
decisions that will help sustain the economic growth, ecological health and social benefits. This study
will provide a data set and demonstration of analyses that can serve as a basis for a landscape ecological
assessment. It can substantially increase our knowledge of conditions in this area using data collected
from an earlier water quality study (Hare, et al., 2012).
Four water quality parameters were chosen to analyze the association between water quality parameters
and landscape and soil metrics. Dissolved oxygen (DO), total kjeldahl nitrogen (TKN), total phosphorus
(TP), and benthic macroinvertebrate structure index of biological integrity (IB I). DO levels vary
depending on temperature change and sedimentation which can be related to land use practices. High
levels of TKN and TP can indicate excess nutrient input from agriculture and manure deposition from
cattle which can lead to increased algal growth and disturb the ecological balance of streams. The IBI
combines metrics sensitive to stressors representing diverse aspects of the biota. Benthic
macroinvertebrate structure can be effected through many land use practices which change channel shape
and form, thus decreasing stream bank stability, leading to erosion and change in vegetation and habitat.
Multiple regressions were used to associate land cover/use metrics and sediment transport metrics to
stream water quality parameters in watershed support areas in the Humboldt River Basin. Six landscape
metrics were used; road density, stream density, soil erodibility, gross soil erosion (strong relation with
the water quality metrics) percent natural grassland and road length (to a lesser degree) which all had
relationships to the water quality parameters. Road length and road density are important factors in and
around the populated areas of Lovelock, Battle Mountain, Winnemucca and Elko. The Index of Biotic
Integrity (IBI) and total phosphorus remained low around all urban areas, total kjeldahl nitrogen and
dissolved oxygen had high values primarily around the more populated areas.
The final regression models were used to predict the water quality parameters (DO, TKN, TP, and IBI) in
areas were measurements do not exist. The predicted water quality values were ranked in group classes
and mapped to examine their magnitude with that of land use activities like mining and cattle grazing.
-------
-------
1.0 Introduction
1.1 Objectives
The Humboldt River Basin is located in northern Nevada
and is a part of the Environmental Protection Agency
(EPA) Region 9. To ecologists and environmental
scientists, a landscape is more than a vista; it comprises
the features of the physical environment and their
influence on environmental resources. Landscape
ecology focuses on the relationships between spatial
arrangements and the ecological processes of the
landscape. Landscape ecology also integrates
biophysical approaches with human perspectives and
activities to study spatial patterns at the landscape level,
as well as the ecological functionality of the region.
There are many applications of this approach (Heggem,
et al., Mehaffey, et al.). For example, areas most
disturbed by anthropological sources can be identified by
combining information on population density, roads and
land cover. Vulnerability of areas can also be identified
by inspecting and assessing the surrounding conditions.
Potential erosion control issues can be evaluated as well
by considering variables such as precipitation and the
steepness of slopes. Ecological processes connect the
physical features of the landscape linking seemingly
separate watersheds.
The Humboldt River drainage (Figure 1) is of interest to
water quality managers due to potential human impacts
from livestock grazing, mine dewatering and runoff. This
report presents an environmental assessment of the basin
by studying the relationships between water quality and the landscape, while considering the potential
human impacts. This assessment can be used as a tool to estimate the impact of human land use practices
that are being currently implemented to improve environmental quality. Currently, the Argenta Marsh, a
wetlands located in the center of the basin directly below the Humboldt River, is the subject of much
discussion. What used to be an extensive riparian and wetland area of between 12,000 and 15,000 acres
which connected Humboldt's main river with south channels through an expanse of swamps, tules and
dense vegetation, was drained when the Humboldt River was channelized in the 1950's. Recently, effort
has been made to begin a marsh restoration project to convert the area back to wetlands. Although
controversy exists over the ownership of this area, converting this community pasture to a wetlands has
been proposed to increase habitat for many native species (Horton, 2000). Land cover analysis could be
used to assess the changes in water quality before and after restoration. The objective of this report is to
provide a data set and demonstration of characterizing the Humboldt River Basin to determine the
ecological status by relating known water quality to landscape metrics by way or multiple regression
analyses.
Rye/Patch Winnemucca
Reservoir
Figure 1. Location of the Humboldt River Basin.
This assessment can also be used for ecosystem targeting and help people make decisions on the best
locations for restoration sites. The information presented in the following pages provides characterization
of the area by the visualization of the conditions across the basin and within each sub-watershed.
-------
1.2 Broad-Scale Environmental Condition
Taking a broader view, the landscape perspective changes allowing an easier understanding of land cover
interactions and helps to make predictions of future anthropogenic problems. At a small-scale level,
perspectives and concerns are based locally. Looking at the national setting can help place the basin in
context and interpret individual conditions, as well as help determine land cover similarities elsewhere in
the country which is important because local environmental issues can have regional impacts. As seen in
Figure 2, the southwest is unique in that shrublands and barren land dominate the landscape, whereas
forests are prominent in the east and agriculture in the mid-west. In the Nevada Great Basin, rivers are the
flowing arteries in the midst of huge, arid, and often desolate western landscape. There are also
significantly fewer roads in the west compared to the east, thus greater amounts of open areas (Figure 3).
NLCD2001
^B Water
i j Urban
| | Barren
m Forest
[ | Shrubland
| | Grassland
| | Agriculture
| | Wetlands
~| No Data
Figure 2. 2001 NLCD (MRLC, 2008).
-------
Roads
Figure 3. National Map of Roads (USGS, 1995).
-------
1.3 Overview
The Humboldt River Basin, located in the Nevada Great Basin, holds the Humboldt River, a main artery
which has been a key resource for both humans and wildlife, and is of primary importance in both the
economy and ecology of the region (Figure 1). The basin's land use history began in the mid 1800's when
miners traveled across Nevada's Humboldt Basin in search of California's gold. Silver, and later gold,
was soon discovered in Humboldt's Carlin area, and subsequently, agricultural and livestock ranches
were established to service the miners (True, 1913). In the late 1800s, heavy grazing led ranchers to
supplement with hay crops, creating water conflicts. It was soon realized that sufficient water in the
Lovelock Valley was going to be in short supply and a consistent water source was necessary to continue
with their land use practices (Bard et al., 1981). Rye Patch Dam, located just upstream of the Humboldt
sink (an intermittent lake bed with
no natural outlet), was built in
1936, and is the basin's chief
reservoir with most of the water
diverted for irrigation for farming
and mining. By the 1900s, there
was grazing induced vegetation
destruction and subsequent erosion.
This led to many upland watersheds
being managed by the United States
Forest Service (USFS). Much of
Nevada State is currently managed
by the Bureau of Land
Management (BLM), due to
excessive habitat degradation from
overgrazing (Figure 4). To date,
livestock grazing has continued
throughout the basin, drastically
changing the ecological balance of
the basin through the invasion of
annual exotic species and
introduction of more hearty, yet
toxic, plants (Horton, 2000).
Another prospective
anthropological impact to the
Humboldt Basin are the effects of
mining. Nevada State is one of the
largest gold producers globally,
with the greatest number of mining
operations in the Humboldt Basin.
Early mining efforts led to
deforestation in the lower basin.
Currently, concerns include mine
dewatering, which creates the
potential for changes in water
quality from chemical pollution
(Horton, 2000).
Agency
Bureau of Indian Affairs
Bureau of Land Management
^f Bureau of Reclamation
| | Department of Defense
Department of Energy
Forest Service
Fish and Wildlife
National Park Service
_ Nevada State
| | Private
_ Water
| | Not Alloted or No Data
0
100 Kilometers
3
Figure 4. Jurisdictional Boundaries for Nevada (BLM, 2010).
-------
2.0 The Biophysical Setting
2.1 Land Cover and Topography
The Humboldt River drainage covers an area of approximately 44,000 km2 (-17,000 mi2) between
Latitude 41ฐ50' in the north and 38ฐ 45' in the south. The geography of the area, with the Sierra Nevada
Mountains to Nevada's western border, stops the access of easterly storms from the Pacific Ocean,
resulting in the 'rain shadow' effect. This has created an overall arid landscape in the bowl-shaped Great
Basin.
Surface water flows enter the system almost entirely through melting snow from the mountain ranges. In
the Humboldt River Basin, the snowmelt from the Jarbidge, Independence and Ruby Mountain ranges are
the primary source of water in the basin, which generally drains northeast to southwest. These mountains
are steep and deeply incised with alluvial/colluvial deposits in the canyons with fine sediment becoming
the dominant substrate in the broad valleys. The topography of the basin ranges from 1175 m (3855 ft) in
the valleys to over 3500 m (11,483 ft) in the mountain ranges. Existing mountain ranges border the basin
to the south (Toiyabe National Forest), east (Ruby Mountains) and north (Independence, Jarbidge and
Santa Rosa Mountains) (Figure 5).
Santa Rosa
Range
Jarbidge
Mountains
Independence
Mountains
Ruby
Mountains
I I Boundary
Elevation (m)
^| 1183-1392
1393-1544
1545- 1689
| 1 1690- 1821
| | 1822-1964
| 1 1965-2137
| ]2133-2366
^| 2367-2692
^f 2693 - 3548
| | No Data
Figure 5. National Elevation Data for the Humboldt River Basin.
-------
The Humboldt Basin is located almost entirely within subecoregion 13 (Central Basin and Range), which
is generally characterized by a wide variety of habitats ranging from salt flats and sage (Artemesia spp)
dominated basins to subalpine zones in montane environments (Figure 6). The lower elevation basin areas
of subecoregion 13 receive low amounts of rainfall but are characterized as semi-desert, which are
systems that typically receive between 250-500 mm of precipitation per year. A small portion to the north
of the basin is within subecoregion 80 (Northern Basin and Range) consisting of sagebrush and juniper
(Juniperus sp) woodlands. For a full description of ecoregions, see Appendix 1.
40
Location Map
Ecoregion
IV Ecoregions
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
Semiarid Uplands
Partly Forested Mountains
Figure 6. Ecoregions in the Humboldt River Basin.
-------
The land cover in the basin is made up primarily of shrub/scrublands, predominantly four-winged
saltbrush (Atriplex canescens), shadscale (Atriplex confertifolid), rabbitbrush (Chrysothamnus Nutt.), and
big sagebrush (Artemisia tridentata Nutt.), and grasslands. Examples of grassland species include Indian
rice grass (Achnatherum hymenoides) and invasive cheatgrass (Bromus tectorum). Willows (Salix spp.)
and cottonwoods (Populus L.) subsist in the low elevation riparian portions of the basin. Forests are
generally dominated by single-needle pinyon pine (Pinus monophylla) and juniper (Juniperus sp). In
higher altitudes, bristlecone (Pinus aristata), whitebark pine (Pinus albicaulis) and white firs (Abies
concolor) can be found (USEPA, 2007). A substantial percentage of the basin's agricultural crops provide
alfalfa hay for the cattle and sheep farms that graze throughout the basin. Urban areas are minimal with
sizable populations in the city of Elko in the eastern portion of the basin, Winnemuccato the west and
Battle Mountain located mid-basin; all three are situated on the Humboldt River.
Winnemucca
fvf %:*ฃ./ JLiJyy^M&f;, ^j**! rM: r w
,-fV ซM .ft'
.-&! '*&ง* .
Boundary
Land Cover
^B Open Water
| | Urban
| | Barren Rock/Sand/Clay
| | Deciduous Forest
^^ Evergreen Forest
^B Mixed Forest
| | Shrub/Scrub
| | Grassland/Herbaceous
^EJ Pasture/Hay
| | Cultivated Crops
| | Woody Wetlands
| | Emergent Herbaceous Wetlands
I I No Data
Figure 7. Land Cover/Use in the Humboldt River Basin.
-------
2.2 Streams
Streams and rivers not only direct the flow of water but also provide necessary resources such as essential
habitat for animals, the filtering of pollutants, processing of litter and debris, distribution of nutrients, and
recreation. The landscape surrounding a stream provides a diverse and productive system for plants and
animals. The stream network used for this assessment is the EPA River Reach File (RF3), derived from
the U.S. Geological Survey (USGS) Digital Line Graph.
The main tributaries to the Humboldt River are the Reese River, Mary's River, the South, North, and East
Fork of the Humboldt, and the Little Humboldt Rivers (Figure 8). Mary's River originates in the Jarbidge
Mountain range and is considered to be the headwaters of the Humboldt River. Stream flow is at a
maximum at Palisade. Because of this, environmental conditions within and between lotic systems in this
drainage are highly variable. The mainstem of the Humboldt River is one of the longest rivers in the Great
Basin having an aerial extent of 483 km (300 mi), or 1610 meandering kilometers (1000 mi) from the
headwaters to its terminus within the Humboldt Lake, at an elevation of 1185 meters (3888 ft). Humboldt
Lake is a body of water located in the Humboldt Sink, an 18 km (11 mi) by 6 km (4 mi) area which has
no outlet.
Ruby Mountains
20 0 20 40 Kilometers
Location Map
Figure 8. Streams and Water Bodies in the Humboldt River Basin.
10
-------
2.3 Watershed
A watershed is an area of land in which all forms of precipitation drain into streams or permeate into the
ground water at the same place. Watersheds can provide a way of evaluating landscape and water
relations based on the water flow through the system. A hydrologic unit code (HUC) is an area which
represents all or part of a surface drainage area, a combination of drainage areas, or a distinct hydrological
feature (USGS, 2009). The United States is divided into different levels of hydrological units: regions (2-
digit areas), sub-regions, accounting units, and cataloging units (Figure 9).
Watersheds
Figure 9. National Map of 8-digit HUCs. 2-digit HUCs are Illustrated in Color.
The Humboldt River Basin is located within Region 16, (Figure 9) which represents the Great Basin. The
USGS's national 12-digit hydrologic units are used in this report to summarize landscape metrics. Figure
10 displays all 12-digic HUCs in the Humboldt River Basin within the larger 8-digit cataloging units,
illustrated in color. For 8-digit HUC numbers and total area, see Appendix 2.
11
-------
Little
Humboldt
North Fork
Humboldt
Lower
Humboldt
Upper
Humboldt
South Fork
Humboldt
Figure 10.12-Digit Hydrologic Unit Boundaries for the Humboldt River Basin.
12
-------
3.0 Methodology
3.1 Regional Classification
The land cover used for this report is from the 2001 National Land Cover Database (NLCD) completed by
the Multi-Resolution Land Characteristics Consortium (MRLC) (Homer et al, 2007). The 2001 land cover
was used due to availability of datasets and the proximity to the sampling period. The MRLC is a federal
consortium created to use Landsat 5 and Landsat 7 thematic mapping (TM) imagery to provide consistent
land cover for the entire United States. Every surface reflects a unique electromagnetic radiation that can
be detected to classify land cover. An example of a Landsat remote sensing image can be seen in Figure
11, with vegetation shown in red. NLCD 2001 data uses 30m Digital Elevation Model (DEM) to
distinguish 29 land cover classes. In the Humboldt River Basin, there are fifteen individual NLCD
classifications which, for this study, have been assembled into eight dominant categories (Table 1).
Table 1. 2001 National Land Cover Data Regional Land Cover Classes.
Open Water Water
Developed, Open Space
Developed, Low Intensity
Developed, Medium Intensity
Developed, High Intensity Urban
Barren Land Barren
Deciduous Forest
Evergreen Forest
Mixed Forest Forest
Shrub/Scrubland Shrubland
Grassland/Herbaceous Grassland
Pasture/Hay
Cultivated Crops Agriculture
Woody Wetlands
Emergent Herbaceous Wetlands Wetlands
13
-------
Figure 11. Lovelock, Rye Patch Reservoir . Vegetation Shown in Red.
3.2 EPA-Delineated Sub-watersheds
A separate set of geographical information system (GIS) delineated watersheds was used for the
Humboldt watersheds based on sampling points. These watersheds were delineated using DEM data to
calculate flow direction and flow accumulation. This process determines boundaries and ridge tops, which
divide water flow to drainage, or outlet points. A number of the original 68 watersheds were nested,
which are sampling site sub-watersheds within a larger sampling sub-watershed. Final sites were chosen
for analysis according to the greatest number of non-nested watersheds available, while mainly including
the delineated watershed furthest downstream. A total of 41 sites were chosen for analysis (Figure 12).
Corresponding site names and locations are listed in Appendix 3.
14
-------
040
Boundary
Sampling Sites
I | Delineated Watersheds
12-digit HUCs
Figure 12. Humboldt Watersheds and GIS-Delineated Sub-Watersheds.
15
-------
3.3 Landscape Metrics
Understanding watershed characteristics will help in the identification and interpretation of
biogeographical patterns in biological communities. To characterize a watershed or a stream, it is
necessary to identify the geology, geomorphology, hydrology, land cover vegetation and distribution and
land use. The first step is to identify a set of landscape indicators with which to conduct a comparative
landscape assessment on the sub-regional study areas. The landscape monitoring and assessment
approach involves the analysis of spatially explicit patterns of, and associations between, ecological
characteristics such as soils, topography, climate, vegetation, land use, and drainage pathways, and
interprets the resulting information relative to ecological conditions on areas ranging in size from small
watersheds (a few hundred hectares) to entire basins (several million hectares).
A combination of the NLCD and a reporting unit, either HUCs or delineated sub-watersheds, were used to
generate a new dataset (ie. the amount of forest cover in each HUC). Both the HUCs and delineated
watersheds, used as reporting units, were overlaid on the NLCD 2001 image. Using Analytical Tools
Interface for Landscape Assessments (ATtlLA), four different categories of metrics were calculated:
landscape characteristics, riparian characteristics, human stressors and physical characteristics of ATtlLA
(Ebert, eta!2004).
Landscape characteristics include basic summary calculations, such as the percent of natural land use,
forests, shrublands, as well as forest patch data. The riparian characteristics calculate the percentage of
stream length adjacent to a specified component. Human stressors compute population density (and/or
change) and stream/road density. Physical characteristics calculate general statistics of element as
elevation slope.
Maps showing the relative ranking of each metric in the reporting unit were also produced. Figure 13 uses
the 12-digit HUCs as reporting units in calculating the percent shrubland in the basin. The map is color-
coded to show relative conditions among watersheds. The dark green areas have the greatest amount of
shrubland, while the maroon areas have the least. The natural breaks classification method was used to
display results finds groups and patterns using a statistical formula, to minimize variance within each
class.
16
-------
% Shrubland
^B 9-56
\^\ 56 - 72
| | 72 - 84
| 84 - 93
93-100
Figure 13. Example of the Maps that Appear in this Report. The Maps are Color Coded to Show Land
Cover/Use Percentages.
3.4 Soil and Landform Metrics
Soil erosion metrics were calculated using the watershed analysis tool for RUSLE/SEDMOD (Van
Remortel, et al 2004) soil erosion and sedimentation modeling. The revised universal soil loss equation
(RUSLE) model and the spatially explicit delivery model (SEDMOD) were the primary framework for
this tool. The soil and landform metrics use Arclnfo as the platform for the four AML scripts and two
ANSI C++ executable programs. STATSGO soil data, NLCD 2001, boundary area, delineated
watersheds, ArcHydro generated filled DEM, flow direction, flow accumulation and stream network grid
were used to run the model. This tool is important because it quantifies the amount of soil coming through
the system by looking at factors which influence this. The RUSLE/SEDMOD model generates master soil
and landform geodatasets that are used to calculate the LS (slope length/steepness), R (rainfall erosivity),
K (surface erodibility), C (surface cover effect), and P (conservation practices) factors, as well as,
STATSGO derived soil parameters. These factors are used together to achieve the gross soil erosion rate
(A value).
3.5 EMAP Measurements
Through the Environmental Monitoring and Assessment Program (EMAP), water column and benthic
macroinvertebrate data were collected in the summers of 1998 and 1999. Sites were selected using a
probability-based, or random design to represent the wadeable streams within the Humboldt River Basin
using the EPA RF3. Thirty-five were sampled in 1998, while the remaining thirty-four sites were sampled
in 1999. Any sites that were resampled in 1999 were not used in this report.
17
-------
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 waters 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 EPA.
Benthic macroinvertebrate assemblages reflect overall biological integrity of the stream, and monitoring
these assemblages is useful in assessing the current status of the water body, as well as monitoring long-
term changes. In this report, an Index of Biotic Integrity (IB I) is used to represent the overall health of the
assemblages. This method evaluates biological variables using a number of criteria, and a subset of the
five best performing metrics is then combined into a single, unitless index. These final variables, or
metrics, should be sensitive to stressors, represent diverse aspects of the biota and be able to discriminate
between reference and stressed conditions. Values range from 1 to 100 with higher numbers
corresponding to healthier biotic assemblages.
3.6 Data Sources
Data sources include (1) EPA delineated watersheds, RF3 files, and Environmental Monitoring and
Assessment Program (EMAP) data; (2) Natural Resource Conservation Service (NRCS) State Soil
Geographic Data Base (STATSGO) soil data; (3) United States Geologic Survey (USGS) digital elevation
model (DEM) and hydrologic units (HUC); (4) Multi-resolution Land Characteristics Consortium
(MRLC) 2001 national land cover data (NLCD); and (5) NASA satellite thematic mapping (TM)
imagery. Using this data, statistical analyses were conducted.
3.7 Data Analysis
To study the relationship between landscape and water quality, stepwise multiple regression was used to
associate stream indicators with ATtlLA landscape and RUSLE sediment transport metrics in each
delineated sub-watershed. Prior to regression, pairwise correlations were examined between predictors
(landscape and RUSLE metrics). When two predictors were found to be highly correlated (R>|0.75|), one
was excluded from further analysis to prevent the presence of collinearity. Soil variables were
standardized to achieve comparable data. A natural log transformation was performed, if necessary, to
linearize relationships. Outliers were also tested for, and removed to achieve normal distribution for
residuals. The amount of variability explained by the regression model was assessed using the regression
coefficient of determination R2. The multiple regression model is:
y=(3o+(3lXi+(32X2...+(3nXn+ฃ
where y is the response predicted value, PO is the constant, Pi...Pn are the coefficients of the predictors
(x's), and ฃ are the residuals. Residuals were all tested for normality, using a Shapiro-Wilk's test (p >
0.30). Table 8 presents the final regression models. We used R version 2.13.1 (2011-07-08) software for
our statistical analyses.
18
-------
4.0 Land Cover/Use
Humans have been altering land cover throughout history through fire, clearance of forests for agriculture,
and livestock grazing through animal domestication, and activities have only increased with the passing
of time. Thus, today's land cover can be seen as the product of past land uses. Yet, land use and land
cover are inexplicably linked. Humans structure the landscape, but the landscape determines the activity.
For example, soil type and topography decide the feasibility of agriculture in an area. The relationship
between humans and the landscape is important in understanding changes and quantifying linkages.
4.1 Forests
Trees are an important element for
humans and wildlife. Clearly, forests are
an economical natural resource. Historic
use in the Humboldt River Basin has
included the use of pinyon-juniper trees
from the surrounding mountain ranges
to supply the charcoal industry in
Eureka, as well as using them for
building corrals and roofs in the
neighboring towns. Mining companies
have been the largest consumer of
lumber, accounting for most of the
lumber camps and sawmills in the
region (Bowers & Muessig, 1982). Yet,
forest ecosystems are also of great
importance to water quality and
quantity, habitat and climate. Trees
regulate hydrologic flow by capturing
rainfall and reducing the intensity of
rainfall that reaches the ground. This
can increase absorption and water
storage capacity while decreasing surface flow and erosion. Trees are essential for erosion control by
stabilizing soil with roots systems, thus decreasing sedimentation, and improving water quality. Trees
also provide habitat through food supply and shelter, and through forest litter, large woody debris which
is a natural habitat for aquatic species. Air and water temperatures are also regulated by shade proved by a
forest canopy (Center for Watershed Protection & USFS, 2008). In the Great Basin, forests within
mountain ranges and riparian areas act as important refugia and corridors for macrofauna.
In the Humboldt River Basin, tree cover is a minor land cover type (Figure 14).. The greatest percentage
of forest is in the Ruby Mountains and Toiyabe National Forest, which line the edges of the east and
south portions of the basin. Average overall forest cover is 6.1% in the basin, with the majority of HUCs
having less than 3% cover. In the individual sub-watersheds, forest cover averages higher (13%), due to
many of the delineated sub-watersheds are located in the mountain ranges.
% Forest
^B 0- 3
I13-11
11-24
24-41
41 -73
Figure 14. Percentage of Forested Land in the HUCs.
19
-------
4.2 Shrubland/Grasslands
Desert shrubs are the foremost land cover component in the Humboldt River Basin. Vegetative shrubland
cover in the lower volcanic ranges consists of widespread greasewood (Sarcobatus sp.) and shadscale. In
areas with greater moisture, cover comprises of sagebrush, horsebrush (Tetradymia sp.) and rabbitbrush
species (Horton, 2000). Shrub/scrub type
vegetation is distributed throughout the
basin with the largest continuous areas in
the north. Cover averaged 80% within the
HUCs and delineated sub-watersheds
(Figure 15).
4- 12
| 1 12-22
m22 -36
36 - 91
Figure 16. Percent Natural Grasslands in the Humboldt River Basin.
20
% Shrubland
^| 9-56
| | 56 - 72
72-84
84-93
93-100
Figure 15. Percent Shrub/Scrubland in the Humboldt River Basin.
Grasslands are an important land cover
type in the Humboldt Basin because
they provide forage for the wildlife and
livestock in the area. Native grasslands
include saltgrass, a low palatable forage
for livestock found in marshy areas,
such as the Humboldt Lake area. This
plant may reduce salinity of streams
and can be vital to soil erosion control.
Other foraging grasses are bluegrass
(Poa sp.), needlegrass (Achnatherus
sp.), Indian ricegrass (Nevada's state
grass), Idaho fescue (Festuca
idahoensis) and the Great Basin wildrye
(Leymus cinereus) (USDA, 2010).
Grasslands are located in the lowland
valleys adjacent to the mainstem of the
Humboldt River. Values averaged 11%
throughout the basin and 6% in the
delineated sub-watersheds (Figure 16).
-------
The changing of native grasses to exotic species is a serious problem in Nevada. Halogeton, an
herbaceous, toxic annual, arrived in the basin in the early 1900s and is able to survive high salt
conditions, out-competing native forage. Cheatgrass, an annual grass which is used for forage, quickly
turns the landscape into monocultures, forcing out other more desirable grasses. Cheatgrass is highly
flammable, susceptible to the recurrence of wildfires, does not provide adequate habitat for wildlife and
threatens sensitive species in the area. Once a fire has burned an area, re-growth is dominated by the early
germinating and rapidly growing cheatgrass. This trend has caused many problems in the lowland areas,
increasing the severity and frequency of wildfires (Horton, 2000).
4.3 Agriculture
Agriculture in Nevada's semiarid climate
is heavily directed to range livestock.
Nevada's agriculture is primarily cattle
production, and to a lesser degree, sheep
ranches. Yet, a variety of other crops can
be harvested where the landscape can be
irrigated. Beginning with the mining
boom, agriculture in Nevada started in
Rye Patch Meadow and Lovelock Valley
because they were the first and last
places with potable water and available
forage for many miles. Commodities
initially consisted largely of vegetables
and grains, but later evolved into range
livestock production (Bard et al., 1981).
By 1913, there were 2,689 farms
accounting for over 2 million acres, with
livestock grazing reaching most lowland
meadows in the Humboldt Basin (True,
1913). But by the beginning of the
1900's water scarcity was already
proving to be an issue. Even with the
construction of the Rye Patch Dam in the
1930s, water continued to be a restricting
factor. With a limited number of water storage facilities, water users, predominantly irrigators, which in
1990 were estimated to be responsible for 75% of the water use in the basin, are dependant on surface
water flow.
% Total Agriculture
HO- i
I |4-8
HI8-15
15-34
Figure 17. Percent Total Agriculture in the Humboldt River Basin.
With irrigated land comes a myriad of potential negative environmental impacts. In 2000, it was reported
that agricultural nonpoint source pollution was the leading cause of water quality impacts on surveyed
lakes and rivers in the United States. Irrigated runoff water may contain fertilizers and pesticides, which
can contaminate water bodies, poison fish, and cause algal blooms, which deplete oxygen. Irrigation
water also can erode stream banks, washing soil off fields and into water, increasing turbidity, and
decreasing critical sunlight for aquatic plants. A problem endemic to arid regions is the increase of soil
salinity from evaporation due to the inability of the soil to filter minerals (USEPA, 2005).
The Humboldt River Basin is located in 8 counties: Churchill, Elko, Eureka, Humboldt, Lander, Nye,
Pershing and White Pine counties. Forage and pastures (native grasses), grains (wheat, oats and barley),
and alfalfa (hay) are the largest commodities in the region (NBA, 2009). Alfalfa is the leading crop in the
21
-------
basin, much sold to dairy ranches. Other crops may consist of root crops or vegetables, such as potatoes
and onions (NBA, 2009). Higher elevation pastures consist of cultivated grasses such as June grass
(Koeleria sp), while in the lowlands, wild grasses reign. June grass is not planted, but instead sprouts up
where alfalfa fields have been over-watered. The dry climate and soil type affect the type of agricultural
commodities available to be harvested.
Total agriculture (includes row crops and pastures) averages 1.7% across the entire basin with less than
1% in the individual watersheds (Figure 17). This relatively low percent could be, in part, due to the large
amount of area used for open range grazing, thus represented by grasslands/shrublands. The largest
agricultural areas are located in the lowland valleys in the southeast portion of the basin near the Rye
Patch Reservoir, the areas surrounding the town of Wells in the east, and in Humboldt County in the
northwest.
4.4 Grazing
With agriculture directed primarily toward livestock, overgrazing has become problematic. Open range
livestock grazing has spread since the 1800s throughout Nevada State reaching virtually every lowland
meadow and upland watershed. Livestock grazing can affect many aspects of riparian areas through
erosion, sedimentation, and water quality, in turn affecting aquatic life downstream. Soil quality is
changed by severe trampling and compaction, causing increased erosion and limiting sustainability of
plants (Figure 18). This can make streams wider and more shallow, and can increase suspended sediment
concentrations
(Bengeyfield, 2007).
Grazing can also change
vegetative structure with
the potential to introduce
exotic species (USDA et
al., 2009). As mentioned
previously, halogeton, a
toxic annual, has become
a problem in the basin in
that it out competes
native grasses. Programs
have been established to
convert acres of
halogeton species to
other wheatgrass
seedling, but it has been
found that most
rangeland improvements
have resulted from
reducing the amount of
grazing and changing the
timing of foraging
(Young & Clements, 2006, USDA et al., 2009). High shrubland cover may also be attributed to
overgrazing. For example, the big sagebrush, was not foraged because of its high oil content, and
overgrazing of grasses did not allow for seed production and re-growth. As grasses decreased, and
shrubland cover expanded (Young & Sparks, 2002).
Figure 18. Evidence of Soil Trampling.
22
-------
Grazing allotments in the Humboldt River Basin are managed by the BLM, US Fish and Wildlife
(USFWS), National Park Service (NFS) and USFS. Animal-unit-months (AUM) can illustrate the amount
of use of a particular allotment. An AUM is the amount of forage needed by an animal unit (AU) for a
month. This is calculated by dividing the number of days livestock are on an allotment by 30. That
number is then multiplied by the number of livestock (sheep, cattle or horse). Then, that number is
multiplied by the AUs. The AUs listed below were decided upon by the BLM jointly with the USFS
while consolidating Nevada State's allotment database (Resource Concepts, 2001).
Animal Units:
Mature Cow = 1
Cow/Calf = 1.32
Ewe w/Lamb = 0.3
Dry Ewe = 0.2
Horse = 1.2
Bull =1.5
Yearling Bovine = 0.7
From the BLM's GIS shapefile and the United States Department of Agriculture's (USDA) allotment
database, the allotment numbers were matched and AUMs inserted to achieve the following map. The
USFS, private and non-BLM allotments did not have identifying numbers or AUMs thus were not
transferred to the shapefile, and were classified as no data. Only one third of all Federal lands have been
compiled for grazing statistics for Nevada with most BLM land and selected USFS lands completed.
Allotments with multiple sections were merged together so AUMs were distributed to all. The allotments
with the greatest AUM densities were in the north and eastern portions of the basin, while the allotments
with the smallest number of AUMs were in the agricultural areas near Lovelock Valley and Winnemucca
in the west (Figure 19).
Areas with higher densities are more susceptible to loss of ecosystem function (Figure 18). This could be
especially true if ecosystem stresses are combined during the same time period such as fire, climate
change, or increases in agriculture. The determination of how many animals the land will support is very
important to a properly functioning condition. Currently it is determined by knowing the particular
animal's forage requirement and how much forage the land has available. Knowing the types,
combinations, and locations of ecosystem stress can help land managers and producers adapt management
practices to best suite the needs of the ecosystem and the animal. In the future, landscape indicators for
grazing such as presented here can be used with the other traditional methods to determine stocking rates
for best production and to consider ecosystem function.
23
-------
I Boundary
AUM/km2
^| No Data
H 0-10.7
| 10.7-19.7
19.7-34.6
^B 34.6-114.2
Figure 19. AUM Values Per Square Kilometer in the Humboldt River Basin.
24
-------
4.5 Population Growth and
Urban Development
According to the U.S. Census
Bureau, in 2000, the population of
the Humboldt River Basin was
about 65,000 people covering an
area of 43,000 km2 (17,000 mi2)
resulting in an average population
density of about 1.5 people per
square kilometer (ESRI, 2010).
Urban development which consists
mostly of agriculture (row crops and
pasture) and to a lesser extent, urban
areas (towns and roads) averages
0.6% throughout the HUCs and
minimal presence in the delineated
sub-watersheds (Figure 20). Higher
concentrations are located in the
residential areas around Lovelock
Valley, Winnemucca and Battle
Mountain in the west, and Wells,
Elko and Carlin (located due east of
Elko) in the eastern portion of the
basin.
Winnemucca &
/\/ Major Roads
% Urban Area
| | 0-0.4
0.4-1.4
1.4-3.5
3.5-7.3
7.3- 19.1
Figure 20. Percent Urban Areas in Humboldt River Basin.
From 1980 to 2000, populations in the major cities more than doubled (Table 2). The greatest increases
revolved around the cities of Elko, Winnemucca, and Spring Creek, a community of the nearby city of
Elko (Figure 21). The greatest factor in population increases is the gold mining opportunities in the
surrounding areas. Although gold prices have fluctuated greatly, the areas in and around Elko have
remained economically stable even when the rest of the country have faced recession. Along with mining
jobs, come other small companies associated with mining such as metal fabrication and steel recycling, as
well as community based employment.
Table 2. Major Population Areas in the Humboldt Basin from 1980-2000.
Place
Battle Mountain
Carlin city
Elko city
Lovelock city
Spring Creek CDP
Wells city
Winnemucca city
Sum
County
Lander
Elko
Elko
Pershing
Elko
Elko
Humboldt
1980
2,749
1,232
8,758
1,680
~
1,218
4,140
19,777
1990
3,542
2,220
14,736
2,069
5,866
1,256
6,134
37,813
2000
2,871
2,161
16,708
2,003
10,548
1,346
7,174
44,811
25
-------
2000
1990
Year
Figure 21. Population Change in the Humboldt River Basin.
4.6 Roads
Roads are necessary to join people with
each other, recreational sites and other
necessities. Yet, the network of roads with
the associated traffic can result in
environmental degradation. Roadways can
change the adjacent natural habitat by
impairment of species migration, be a
source of pollution from runoff of vehicle-
related chemicals, facilitate spread of
exotic species, alter streams by sediment
deposition from erosion, and change the
stream hydrology by changing timing and
routing of runoff (Transportation Research
Board, 2002). Road density and the number
of roads crossing streams are important
landscape indicators to include in
environmental assessments. This study
calculated road metrics from 1:100,000
USGS Digital Land Graph data (U.S.
Census Bureau, 2009).
Road Density (km/km2)
HO-0.3
| [0.3-0.6
| 10.6-0.9
^ 0.9-1.3
1.3-2.5
According to the road map used in this
study, which includes all types of roads
Figure 22. Road Density in the Humboldt River Basin.
26
-------
(highways, country roads and city
streets) there is a total of
31,100 km of roads in the
Humboldt River Basin averaging
0.5 km per person. Road density is
minimal with the highest road
density in the basin located in the
residential areas of Elko
(Figure 22). In the individual
delineated sub-watersheds, road
density had less of a presence with
the highest density (1.3 km/km2) in
Spaulding (site 35), south of the
town of Winnemucca. Interstate
Highway 80 is the primary
connector, traveling east-west
through the basin following the
contours of the Humboldt River.
# of Road/Stream Crossings
^H 0- 0.22
| [0.22-0.38
^] 0.38 - 0.55
| | 0.55- 0.76
^BfO.76- 1.18
'per kilometer of stream
Figure 23. Number of Road/stream Crossings Per Kilometer of Stream.
The density of roads crossing
streams is relatively low with a
range between 0.0 and 1.2
crossings per kilometer of stream
and an average of 0.4. Only five
HUCs have stream crossing densities greater than one, including three watersheds located around the
town of Elko (Figure 23). Only one watershed, located in the center of the basin directly above the
Humboldt River, has a road/stream crossing density of zero, having no roads within its border. In the
delineated sub-watersheds, road/stream crossing density values ranged between 0.0 and 1.9 crossings per
kilometer (site 37) with an average of 0.4.
4.7 Mining
Mining is a valuable human land use that began in Nevada with silver in the late 1800s. In the early
1900s, gold had been discovered and continues today making Nevada one of the largest gold producer
globally. The Carlin Trend, an 80-by-8 km (50-by-5 mi) belt within the Humboldt Basin, accounts for
much of the mined gold. As of 2006, there were 74 hardrock mines of which 69 were gold or gold and
silver mines of which all used cyanide leaching and are primarily open pit.
Open pit mines, which can be a two-thousand feet deep, may be below the water table. Mine dewatering
is then necessary to remove groundwater in order to facilitate mining activities. Pumped waters are often
discharged to surface receiving water creating the potential for chemical and/or thermal pollution which is
monitored by state and federal agencies. Additionally, the groundwater resources being depleted are
drawing down the water table creating a temporary increase in flow, currently being used for irrigation,
but with the possibility of reducing baseflow in streams and springs. The potential for the creation of
contaminated pit lakes in the empty areas the groundwater once occupied, and the ecosystems that the
high water flow once supported have caused concern (Solnit, 2001). Research about acid mine drainage
from abandoned mines has also been conducted. Runoff may contain elevated concentrations of inorganic
contaminants which would then result in discharge of acidic metal-laden waters. Selenium drainage into
the sink has already occurred, changing conditions for the Lahontan cutthroat trout (Glennon, 2002; Gray,
2003). Cyanide plumes have been detected from tailings seepage and contaminations of groundwater have
27
-------
been observed for toxic materials such as arsenic, mercury, and manganese. Increased sedimentation due
to surface disturbance can cause increases in dissolved solids (Kuipers et al, 2006).
Although most potential mine runoff would not directly flow to mainstream waters, specifically because
of the lack of rain in the region, the presence of mines and mine waste can still affect the surrounding
area. (Gray, 2003, Barman and Hershey, 2004). In the case of the Rain Gold Mine near Elko, acid mine
drainage has been a problem since 1990 from waste rock piles, contaminating 2 miles of Dixie Creek
(Site 69) with elevated levels of mercury and arsenic (Earthworks, 2004). When gold ore is mined, sulfur
is typically contained, which when exposed to air or water forms sulfuric acid. This acid draws out other
metals such as arsenic, antimony, lead and mercury. (Solnit, 2001, Barman and Hershey, 2004). A more
likely interaction of mine activities to surface waters is historic mill tailings, or spent ore. Since most
tailings were placed in
lowlands, rain activities can
carry acids and metals a short
distance before being stopped
by the natural geology and
soils. Through evaporation,
small ephemeral ponds can be
created which can hold high
concentrations of metals (Nash,
2003).
Using 2005 mine data created
by USGS, a one kilometer
diameter buffer was created
around each mine to represent
the relative affect of each mine.
One kilometer was determined
by comparing satellite imagery
to land cover data to determine
the extent of the mine's
anthropological influence. Past
producing gold mines, currently
producing gold mines and
processing plants have been
included (Figure 24).
I | Boundary
^H Gold Mines
Land Cover
^B Open Water
^B Urban
^^ Barren Rock/Sand/Clay
| | Deciduous Forest
^| Evergreen Forest
^B Mixed Forest
| | Shrub/Scrub
| | Grassland/Herbaceous
^H Pasture/Hay
| | Cultivated Crops
| | Woody Wetlands
| | Emergent Herbaceous Wetlands
| | No Data
Figure 24. Humboldt Land Cover Including Mine with 1km Buffer.
Trends related to mining and
water quality can be observed in
the nested sites of the Reese
River. Site 280 is the most
upstream watershed that is
nested within watershed 4
which is then within watershed
3 and so on up to watershed 196 (Figure 25). As seen in Table 3, pH, chloride (Cl) and sulfate (SO4)
increased downstream while IBI decreased. Many other variables had overall increases, but had their
highest values at site 6 and 96, with a drastic decrease at 196, such as for Total Dissolved Solids (TDS),
Total Kjeldahl Nitrogen (TKN), lead in sediment (Pb-S), mercury in sediment (Hg-S), arsenic in
sediment (As-S), nickel in sediment (Ni-S) and arsenic in water (As-W). Dissolved Oxygen (DO)
decreased slowly until site 6, which had the lowest sampled value in the basin at 2.4 mg/L.
28
-------
196
Gold Mines
Sampling Sites
Nested Delineated Watersheds
Figure 25. Nested Sites in the Reese River with Past and Present Gold Mines and Processing Plants.
Table 3. Water Quality and Metal Data for Nested Sites within the Reese River Area.
Site
280
4
o
3
6
96
196
Au
Mines
0
0
6
32
33
33
DO
8.4
6.9
5.6
2.4
11.3
10.5
pH
7.4
7.7
8.1
8.1
8.4
8.9
TDS
61
80
212
708
1010
549
TK
N
0.12
0.12
0.40
0.66
1.20
0.27
Cl
-
1.4
5.9
58.3
114
-
SO4
-
2.3
13.4
128
259
-
IBI
92
68
38
10
28
18
As-W
0
1.8
7.8
-
75
37.6
As-S
11.3
2.2
4.1
27.6
13.0
9.3
Hg-S
-
0.16
0.14
1.40
0.08
-
Ni-S
12.7
4.1
1.3
15.2
20.0
16.8
Pb-S
3.1
5.2
8.8
52.7
12.0
1.0
*S= Sediment. W=Water. Hg only sampled in 1998.
The pH, which measures of acididity or basicity of water, does not appear to be affected by mine drainage
which typically decreases with an increase of mining discharge. Acidic compounds such as ferric iron
runoff affects the alkalinity of water, producing more acidity and lowering the pH. In the case of the
Reese River, pH increases slightly as water flows downstream.
29
-------
Site 6 appears to be the most affected by all variables. With the lowest IBI and DO and some of the
highest values for TKN, SO4, Arsenic, mercury and lead, this watershed is being disturbed. Twenty six
mines are directly in this watershed, with most nearby the sampling site.
Examining the relationships between past and present gold mines and water quality and metal indicators
in the basin, a number of correlations were found. Although correlations do not imply cause and effect
relationships, they can provide insight into the ecological processes at work. Significant correlations are
termed weak, moderate, or strong where r <0.50, 0.50< r <0.75, and r >0.75, respectively.
Overall, there were positive correlations for all relationships, with the exception of a weak negative
correlation between past gold mines and IBI (Table 4). There was only one moderate correlation which
was between present gold mines and mercury (1998 sampling season only).
Table 4. R Values of Significant Correlations (P<0.05)
Between Past and Present Gold Mines and Ecological Indicators.
Aluminum (sediment)
Arsenic (sediment)
Mg (sediment)
Mercury (sediment)*
DO
TKN
TDS
IBI
Past Gold Mines
0.34
0.43
0.39
0.42
-0.32
Present Gold Mines
0.30
0.39
0.63
0.32
0.32
*1998 sampling season only
30
-------
4.8 Riparian Land Cover/Use
Riparian buffers, areas connected to or adjacent to a stream bank or other body of water, are complex
ecosystems connecting the landscape to the stream system. These zones act as traps, filtering sediments
and nutrients, slowing water flow and providing stable stream banks, and improving water quality.
Riparian buffers along stream banks can affect water quality through amount and type of cover, which
can determine soil loss and sediment movement. Characterization of these conditions can identify areas in
need of improvements. Vegetation moderates temperature and provides habitat and is a source of
nutrients for wildlife. Buffers are most effective when they constitute native grasses and deep rooted trees
and shrubs. Lack of necessary vegetation can result in increased erosion, reduction of water storage
capacity, and a decrease in water quality (Snyder et al., 2003).
Buffer distances of 30 and 90 meters on both sides of the streams are used to calculate land cover metrics.
The relative amount of land cover/use in a 30 meter riparian buffer (each side of streams) within the
Humboldt River Basin can be seen in Figure 26. Looking at the entire basin, riparian land cover/use is
similar to the total watershed assessment. Percent wetlands, natural grasslands and agriculture have a
slightly higher proportion in the riparian buffer area. Shrublands and forests were slightly lower. The
range of human use, not including mines, within the 30 meter buffer is between 0.0% and 41.6% and an
average of 3.5%, with agriculture land use accounting for close to 97% of that amount. The descriptive
statistics for total watershed assessment, as well as 30 m and 90 m riparian buffer are displayed in
Appendix 4.
Riparian Buffer (30m)
| J Forest
| | Shrubland
| | Grassland
QB Agriculture
1 Wetland
Figure 26. Percentage of Riparian Buffer in Forest, Shrubland, Grassland, Agriculture and Wetland
Calculated within a 30m Buffer.
31
-------
32
-------
5.0 Land Cover Comparison
Over time, the landscape is
changed from one cover type to
another by natural changes, such as
fires and flooding, and
anthropogenic mechanisms,
including urbanization, logging
and farming.
The MRLC's NLCD 1992/2001
Retrofit Land Cover Change
Product was developed to be an
accurate analysis between the 1992
and 2001 land cover years.
Because of new mapping
technologies, new input data and
mapping legend changes, direct
pixel comparison between the two
years would not exact. This retrofit
product was used to analyze
changes in the landscape in the
Humboldt River Basin (Figure 27).
Increases in agriculture in
Lovelock and Winnemucca are
apparent as well as increases in
wetlands along the mainstem of the
Humboldt River, due primarily to
restoration efforts. Other changes
include increases in forest, specifically in the Pine watershed. This area includes the Wilderness Study
Area in Robert's Mountains, created in 1980 and encompassing 15,000 acres of land under the Federal
Land Policy and Management Act, which states that study areas must be managed to maintain wilderness
suitability or not cause undue degradation. In addition to changes in land use, there may be another
contributing factor for the increase in forest cover. Vegetation in this region requires high moisture for
seed establishment. In the mid 1980s, there were months with above average precipitation, which would
help re-vegetate.
I | 8-digitHUCs
1992 to 2001 Land Cover Change
|^| Change to Water
^H Change to Urban
I | Change to Barren
^| Change to Forest
Change to Grass/Shrubland
Change to Agriculture
Change to Wetlands
No Data
Figure 27. Retro Fit Land Cover Change.
Since the Retrofit NLCD combines grass and shrubland, a visual comparison was made between the 1992
and 2001 NLCDs in the Humboldt Basin to observe changes. In five of the 8-digit HUCs, there was a
decrease in shrubland and forest cover, while large grassland increases evident. According to the Desert
Research Institute (DRI), wildfires devastated Nevada in 1999, with the majority occurring in the
Humboldt Basin. The 1999 wildfire season ranked first in regard to acres burned and second in the
number of total fires (Brown & Hall, 2000). With the invasion of cheatgrass, natural re-vegetation of
burned areas is being overtaken by this exotic species. Looking at the land cover overlaid with the fire
boundaries as seen in Figure 28, grassland increases have occurred in all burned areas.
33
-------
I I 1999 Humboldt Fires
1992 Land Cover
^B Open Water
^| Urban
| | Barren
^| Forest
| | Shrub/Scrub
~~ Grassland
_ Agriculture
| | Wetlands
| | No Data
| | 1999 Humboldt Fires
2001 Land Cover
^H Open Water
^B Urban
[ | Barren
S Forest
Shrub/Scrub
| | Grassland
^B Agriculture
| | Wetlands
| | No Data
Figure 28. National Land Cover Dataset for 1992 and 2001 Showing the Burn Locations for the 1999 Fire Season.
34
-------
6.0 Soil Cover
The automated GIS Watershed Analysis Tool was used for soil erosion modeling. This program computes
soil erosion and sediment delivery metrics based on the Revised Universal Soil Loss Equation (RUSLE)
soil erosion framework and the Spatially Explicit Delivery Model (SEDMOD) sedimentation framework.
Rainfall derived erosivity (R), soil surface cover characteristics (C), soil surface erodibility (K), slope
length and steepness (LS), and soil management practices (P) are multiplied to reach the gross erosion
rate (A) for each of the Humboldt's 45 delineated watersheds. Complete data can be found in Appendix 5.
6.1 R Factor
The R factor, which represents
rainfall-runoff erosivity, is a
measure of the erosion force of a
rainfall event at particular locations
with the final value quantifying the
amount of runoff, as well as the
intensity of the raindrops' effect. A
cumulative summation of a normal
year's rain is used to determine this
index. Greater R factors can identify
areas with greater potential for
erosion.
In the entire Humboldt Basin, R
factors ranged from 3 to 62 with the
majority of values less than ten,
while in the individual delineated
watersheds, R factor values ranged
between 6 and 30. The areas with
the greatest potential for rainfall
erosion are located in the Ruby,
Independence, Jarbidge and Santa
Rosa mountain ranges (Figure 29).
For comparison, average R factors
throughout the continental United
States vary from less than one hundred in the arid Great Basin to a couple hundred along the pacific coast,
and up to 700 in the gulf coast (Troeh, 2005) (Figure 30).
I Boundary
| | Delineated Watersheds
R Factor
| 13-6
| |7-9
| 1 10- 13
| |14 - 18
M 19 - 24
H 25 - 31
^B 32 - 39
H 40 - 48
^B 49 - 62
I No Data
Figure 29. Rainfall Erosivity in the Humboldt River Basin.
35
-------
200
100
600
Figure 30. Average Rainfall Erosivity (R Factor) for the Continental United States (Troeh, 2005).
6.2 C Factor
The C factor, or cover management
factor, reflects the effect of cropping and
management practices on erosion rates
(Figure 31). Simply, the C Factor
indicates how conservation plans, such as
changes in plant and soil cover and
biomass will affect soil loss. For
example, for most of the basin, values are
less than 0.16. This signifies that erosion
will be reduced up to 16% compared to
the amount that would have occurred
naturally (ARS, 2010). This is an
important variable because it represents
how conservation changes can reduce
erosion. To calculate this factor, RUSLE
uses sub-factors canopy, surface cover,
surface roughness and prior land use to
compute a soil loss ratio. The C factor is
an averaged soil loss ratio weighted by R
factor distribution. In the delineated
watersheds, values were very low
ranging from 0.06 to 0.20 with an
average of 0.09.
Boundary
C Factor
H 0-0.01
H0.01 - 0.03
0.03-0.06
^B 0.06 - 0.42
0.42 - 0.98
Figure 31. C Factor Values for the Humboldt River Basin.
36
-------
6.3 K Factor
Soil erosion is an environmental
variable that can have profound
effects on and off site. With grazing a
key factor of erosion through the
trampling of stream banks, increased
sedimentation can be an affect.
Mining operations may dump large
amounts of sediment directly into
streams. An excess of sediment can
change the quality of the water
affecting aquatic life and beneficial
uses downstream. Large amounts of
sediment reduce capacity and
increases flood damage (Julien,
1998).
I Boundary
K Factor
BB 0-0.17
| | 0.17-0.23
| 1 0.23-0.35
BB 0.35-0.45
BB 0.45-0.53
| | No Data
Surface soil erosion can also affect
soil productivity and ecosystem
function. Since nutrients and organic
matter are typically most
dense in the surface soil layer, erosion
washes away the most productive
layer. Soil erodibility, expressed here
as the K factor, evaluates the potential
for erosion using the Natural Resources Conservation Service (NRCS) State Soil Geographic
(STATSGO) database soil data. The K factor represents the combination of soil type and detachability, as
well as transportability of the eroded sediment. Table 5 describes the general relative distribution of K
Factor values.
Figure 32. K Factor Values in the Humboldt River Basin.
Table 5. General Distribution of K Factor values.
K Factor
0-0.15
0.05-0.2
0.25-0.4
>0.4
Definition
Fine textured soils high in clay, resistant to detachment
Coarse textured soils which may be high in sand, low runoff
Moderately susceptible to detachment, moderate runoff
High silt content, susceptible to detachment, high runoff rates, hi|
jher erodibility
In the Humboldt Basin, potential soil erodibility ranged from 0.00-0.56, and an average of 0.29 while the
delineated sub-watersheds have values between 0.12 and 0.35 (Figure 32). The areas with the highest
erodibility are in the valley floors near streams, coinciding with areas that are traditionally used for
grazing and agriculture. Figure 33 displays the surface soil types for the basin summarized by user
defined classes. For the list of defined classes, see Appendix 6.
37
-------
Surface Summary Soils
^H Gravelly Loam
| | Sandy Loam
j^f Silty Loam
| | Cobbly Loam
| | Clay Loam
| | Channery Loam
I | Loam
| | Sand
| | Clay
Unknown
Figure 33. Map of Surface Layers in the Humboldt River Basin.
6.4 P Factor
The P factor, computed as the ratio of soil loss, represents how management practices on surface
conditions connected with upslope and downslope tillage affect erosion by modifying flow factors.
Practices may include vegetation erosion management, contour farming, terracing, subsurface drainage or
strip cropping. These practices affect erosion by directing runoff and increasing or decreasing erosivity.
Factors included in the P factor involve runoff rate, management practices, and transport capacity affected
by slope and roughness of the surface. Practices that do little to reduce soil erosion have numbers nearing
1.0 (Renard et al., 1997). In the Humboldt River Basin, the P Factor for all delineated watersheds is 1.0.
6.5 LS Factor
The LS factor consists of slope length, which is the distance of flow along its path, and steepness, which
represents the effect of the slope gradient of erosion (Van Remortel et al., 2005). The LS factor examines
the steepness of the slope, the susceptibility of soil to erode and the relationship between slope and length.
As slope length increases, runoff accumulates and detachment potential and transport capacities increase,
thus a considerable increase in soil loss. An LS value of 1.0 is equal to a 9% slope steepness for a 72.6 ft
(22.1 m) unit plot. The values are also determined by erosion susceptibility. Examples of the tables used
to determine the LS factor, based on land use practices and land type, can be found in Renard et al, 1997.
38
-------
Overall values were relatively low with values
ranging from 2.3 to 17.5 in the delineated
watersheds. Because of the detailed resolution of the
data, an entire basin map is not appropriate. Figure
34 displays the North Fork Humboldt area for LS
values.
6.6 A Value
The A value computes the gross soil erosion per unit
area using the formula: A=R*C*K*LS*P. Values
range depending on rainfall, soil type, slope, and
conservation practices in the specific locations. As
seen in Figure 35, overall values in the west are
lowest in Nevada and North Dakota and highest
along the coast of California, Oregon and
Washington. In the Humboldt Basin, values averaged
from 476 to 15,818 kg/ha/y in the delineated sub-
watersheds with the highest value located in North
Fork Little Humboldt River (site 269).
LS Factor
| 1 0.01 - 2.47
| 1 2.48-6.34
^6.35-11.99
| 1 12.00-21.18
^B 21.19 -73.45
| | No Data
Figure 34. LS Values for the North Fork Humboldt Area.
Legend
82 1817
1818- 3191
3192 - 6446
6447 - 17374
17375 - 310519
O Hป JOO KIIOMUFRI
Quantile
Gross soil erosion, A value
(kg/ha/yr)
Figure 35. A Values Throughout the Western United States (USEPA, 2010).
39
-------
40
-------
7.0 Ecological Indicators
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
6).
Table 6. Water Quality Standards for Nevada.
Indicator
Dissolved Oxygen
pH
Total Phosphorous
Standards for Nevada
>5 mg/L (non-trout waters) >6 mg/L (trout waters)
6.5-9.0
<0.1mg/L
Considering that a large portion of the water flowing through the Basin is supplied by surface water
runoff, the topography and land cover within the basin can affect the water entering the system, which in
turn affects the biology of the stream. These ecological indicators are measurable characteristics of the
environment and can provide information on ecological resources. In this chapter, variations of these
ecological indicators are examined. For a complete data set, see Appendix 7.
7.1 Dissolved Oxygen
Dissolved oxygen (DO) is the
amount of gaseous oxygen
dissolved in water and available
for organismsal respiration.
(Figure 36). Decreases in DO
can be associated with inputs of
organic matter, increased
temperature, a reduction in
stream flow, and increased
sedimentation. DO values
ranged from 5.5 to 11.2 mg/L
with a mean of 8.0 mg/L among
samples. Two sites had DO
values that went below 6 mg/L,
which represents the lower limit
determined suitable for trout by
Nevada State standards, located
in the Reese River to the south
and at the top left area of the
basin.
Dissolved Oxygen (mg/L)
5.5-6.5
o 6.5-7.6
o 7.6-8.5
8.5-9.5
9.5-11.2
Figure 36. Dissolved Oxygen in the Humboldt River Basin.
41
-------
7.2 pH
Hydrogen ion activity (pH), is a numerical
measure of the concentration of the constituents
that determine water acidity, specifically
hydrogen ion concentration (Figure 37). pH is
measured on a logarithmic scale of 1.0 (acidic)
to 14.0 (basic) with 7.0 signifying neutral. The
pH of the Humboldt Basin watersheds ranges
from 6.6 to 11.7 with a mean of 8.4. Three
samples, all located in the upper portion of the
basin, were greater than 9.0, representing the
upper limit set for Nevada. No sites were below
the lower limit of 6.5.
PH
6.6-7.3
o 7.3 - 8
o 8-8.5
8.5-9.3
9.3-11.7
TKN (mg/L)
0.06-0.1
o 0.1-0.14
o 0.14-0.19
0.19-0.27
0.27-0.41
Figure 38. Total Kjeldahl Nitrogen
in the Humboldt River Basin.
for grazing in the Humboldt River Basin,
manure deposition from cattle can add
nutrients, such as TKN, from the manure to
the streams. Similarly, loss of nutrients from
human activities can also reduce stream
productivity. Values for TKN range from
0.06 to 0.41 mg/L with and average of 0.18.
The highest value (0.41 mg/L) is located at
site 247 in the North Fork Humboldt area.
7.4 Total Phosphorus
Phosphorus is often a limiting factor in
growth of aquatic vegetation as it is an
essential nutrient for plant and bacterial
activity (Figure 39) . Yet, an excess of
Figure 37. pH in the Humboldt River Basin.
7.3 Total Kjeldahl Nitrogen
Nutrient inputs to streams are important, as
substantial inputs (eutrophication) from
anthropogenic sources can result in increased
algal growth which can upset the ecological
balance of the stream (Figure 38). Total
Kjeldahl Nitrogen (TKN), which is the
combination of organic nitrogen and ammonia,
comes mainly from agricultural processes, such
as pesticides and fertilizers, and sewage. Total
nitrogen was not used, because of lack of nitrite
data for 1999. With the high proportion of land
used
42
TP (mg/L)
0.01 - 0.03
o 0.03-0.06
o 0.06-0.09
0.09-0.13
0.13-0.2
Figure 39. Total Phosphorus
in the Humboldt River Basin.
-------
phosphorus may reduce habitat, disrupt ecological cycles and affect macroinvertebrate communities. An
increase in phosphorus, which could be the result of nutrient input from agriculture, is reflected in
increased growth of algae. Samples for total phosphorous (TP) in the Humboldt River Basin ranged from
0.01 to 0.20 mg/L with a mean of 0.06 mg/L. Six sites had TP levels above the Nevada water quality
standard of 0.1 mg/L all located in the upper reaches of the basin.
7.5 IB I
The Index of Biological Integrity (IBI)
combines metrics sensitive to stressors
representing diverse aspects of the biota in
order to differentiate between stressed and
unstressed conditions (Figure 40). An IBI score
is representative of the health of a stream.
Changes in aquatic species can occur from a
number of actions. Breakdown of stream banks
change channel shape, structure and form, and
decrease stream bank stability. This can lower
the groundwater table, increase water turbidity,
and change type of vegetation and aquatic
habitat, thus changing habitat diversity
(Bellows, 2003). Values ranged from 16 to 96
with an average of 50. Although there is no
standard, higher values are indicative of
healthier systems. Five sites had values below
20.
7.6 TDS
Total dissolved solids (TDS) include calcium, carbonate, chloride, sulfate, phosphate, nitrate, organic ions
and other ions that can pass through a filter (Figure 41). Although a certain level of TDS are necessary for
aquatic life, excessive levels can be harmful. Increased levels of dissolved solids can result in reducing
water clarity, thus limiting photosynthesis of aquatic plants. High concentrations of dissolved solids can
be attributed to the surrounding geology,
runoff from streets and agriculture, soil
erosion and the organic particles of decayed
of plants and animals. With the
recommended standard for TDS in drinking
water is 500 mg/L, four sites were in
exceedance in the Humboldt Basin. Values
ranged from 17 to 692 mg/L with a mean of
202 mg/L. Exceedances for each indicator
are summarized in Table 7. Only those sites
that had such exceedances are listed.
Figure 40. Index of Biological Integrity
in the Humboldt River Basin.
TDS (mg/L)
17.2-35
o 35 - 141.4
o 141.4-214
214-317.4
317.4-692
Figure 41. Total Dissolved Solids
in the Humboldt River Basin.
43
-------
Table 7. Indicator Exceedances.
Site
5
11
25
35
103
129
140
164
196
245
247
250
259
269
DO
(mg/L)
5.5
5.5
pH
9.2
11.7
9.3
TKN
(mg/L)
0.41
TP (mg/L)
0.16
0.20
0.13
0.11
0.12
0.20
TDS
(mg/L)
516
692
549
505
IBI
18.0
16.0
18.0
18.0
16.0
44
-------
8.0 Landscape and Water Relationships
8.1 Regression Models
Riparian metrics were highly correlated to whole watershed metrics and were thus eliminated. Percent
shrub/scrubland was also eliminated, since the percent of shrub/scrubland in the delineated sub-
watersheds is simply the inverse of the percentage of forest, grassland and other land uses that make up
the area. Using shrub/scrubland would not further elucidate the relationships between the land cover and
water quality indicators. RUSLE R and C Factors were eliminated for strong correlation with other
independent variables. Of the remaining landscape metrics six variables (A Value, K Factor, percent
natural grassland, stream density, road length and road density) were used in the stepwise multiple
regression. Different predictors were significantly related to each of the water quality metrics (Table 8).
The amount of variability explained by models ranged from 24% to 54% (R2, Table 8). Road length and
road density are important factors in and around the populated areas of Lovelock, Battle Mountain,
Winnemucca and Elko. The Index of Biotic Integrity (IBI) and total phosphorus remained low around all
urban areas, Total kjeldahl nitrogen and dissolved oxygen had high values primarily around the more
populated areas.
While all of predictors (png, strmdens, rdlen and rddens) enhanced TKN in streams. Soil factors (A Value
and K Factor) decreased IBI and DO in streams.
Table 8. Multiple Regression Models "*" Denotes Log-Transformation
Dependent
Variable
DO
TKN*
TP*
IBI
R2
0.384
0.544
0.257
0.241
Formula
6.949-0.028*AValue+0.0304*KFactor
-3.097+0.00902*png+0.012*strmdens+0.00801*rdlen+0.00897*iddens
-4.75+0.0208*strmdens+0.00921*rddens
68.97+0.341*AValue-0.467*KFactor
8.2 Model Application
Using the 2001 NLCD and averaged RUSLE grids, predictions were made of potential IBI and water
quality indicators in the Humboldt Basin within each 12 digit HUC. Predicted dissolved oxygen had
higher values around the major urban areas with the lowest values located to the north and in the lower
reaches of the Reese River. High predicted TKN values were spread throughout the basin with the higher
values in the urban areas of Lovelock, Winnemucca, and Elko, while low values were congregated around
the southern portions. Total phosphorus had overall low predicted values throughout the basin with the
highest values located around the main stem of the Humboldt through the center. Surrounding the more
populated areas, IBI remained relatively low with the lowest values around Battle Mountain and Elko and
the highest values in the upper reaches of the basin and the southern tip of the Reese River. See Appendix
8 for the predicted model averages in each hydrologic unit.
45
-------
46
-------
9.0 Conclusion
Nevada has a basin and range physiography. A repeating pattern of fault block mountains and intervening
valleys. Most of the state is internally drained and lies within the Great Basin ecoregion. Valley
ecoregions are predominantly shrub or shrub- and grass-covered. Mountains may be brush-, woodland-,
or pinion-juniper forested systems. The Humboldt River Basin is in the northern portion of Nevada, and
encompasses approximately 17,000 square miles. The Humboldt River is the largest river system in the
lower 48 states that begins and ends on the North American continent. The Humboldt River is a terminal
system ending in the Humboldt Sink. The Humboldt River Basin is sparsely populated with two major
land use types mining and agriculture (hay and cattle).
The Humboldt River, hydrologically, is fairly unique. The river trends east-west, and gains most of its
water from snowmelt in the alpine regions of the Basin and Range ecosystem (Ruby Mountains, Jarbidge
Mountains, and Independence Mountains in the eastern part of the watershed, and Toiyabe Mountains in
the south-central portion). Agricultural activity in the valleys increases water withdrawals for irrigation.
Water into the river comes from snowmelt, and open pit mining discharge. Flow is highly variable from
season to season and year to year (depending on the amount of snow every winter). These unique features
and the high desert environment contribute to the formation of a very large number of ephemeral and
intermittent streams.
The objective of this study is to provide an additional supportive methodology tool using remote sensing
and geographic information systems (GIS) to derive and connect land cover and human land use patterns
in relationship to ecological features to support decision making. Physically, ecosystems are always in
motion reacting to natural climatic and anthropogenic conditions. These changes, in environmental
condition, will affect the chemical and biological community structure, which cause further alterations to
the environment. Water quality issues in the Humboldt River Basin are nutrients (nitrogen, phosphorus
and sediment), temperature, total suspended solids and metals. Traditional water quality measures give
some information but are very limited in time and space. A landscape metric analysis explains more
about ecologic condition and function, because landscape metrics tend to integrate time and space.
Landscape metric analysis and water quality measures used together provides a very powerful
environmental condition and risk analysis tool. This report provides a full set of landscape metrics to
analyze. This report demonstrates how to take those metrics and derive basin-wide water quality
predictions, and make those predictions in places where there are no water quality measurements.
Finding environmental problems is sometimes easier than finding solutions. This study found that past
grazing practices has impacted stream flood plain vegetation, which holds together the stream channel
and stream banks during flood events, and holds the water on the landscape. Adding more knowledge
through landscape analyses will help land managers find troubled areas and help to choose the correct
adaptive management practices to mitigate problems. Through further study more relationships can be
discovered and additional predictive models mapped.
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 most of the biodiversity in this state is associated with riparian or
aquatic habitats, makes the management of these systems a matter of particular importance. The authors
recommend that decision makers, stakeholders, ranchers, Federal, State, Tribes and local officials
consider our approach and use this information to begin adaptive management practices.
Water quality in the Humboldt Basin had few cases of water quality standard exceedances. Road density
and length, in addition to gross soil erosion and soil erodibility are main contributors to potential water
quality degradation, along with stream density and percent natural grassland. Other contributors may
47
-------
include grazing density and gold mines. Mining can deplete groundwater resource while creating the
potential for chemical pollution. Trends seen in nested watersheds show that as water flows from
upstream watersheds downstream in a system with an expanding number of mines, increases in TDS, Hg,
Cl and SO4 occur while decreasing values of IBI. Sites 6 and 96, where most past and present gold mines
occur, seem to have the most extreme values for many indicators such as mercury, TKN, lead and arsenic.
Regression models demonstrate the watersheds that have a high potential for water quality impacts
affected by one or more land cover use and/or erosion potential.
For the following maps, final metrics included in the prediction models are shown displaying their
extreme values. For this, ten natural breaks were found for each variable, as defined by ATtlLA, and the
highest (or lowest) class was selected. Each variable was overlaid to show the HUCs that are affected
(Figure 42, 43). For the final joined map, all affected watersheds were joined and then overlaid (Figure
44). This shows the watersheds that have the most potential to be affected by the land cover/use and
sedimentation. Significant watersheds lie mainly along the mainstem of the Humboldt.
K Factor
_ HIGH VALUES
AValue
HIGH VALUES
Stream Density
^| LOW Values
Road Length
BB HIGH VALUES
% Natural Grassland
I"/"; HIGH VALUES
Road Density
mt HIGH VALUES
Figure 42. Land Cover/RUSLE Extreme Values for 12-digit HUCs.
48
-------
pJBI
^B LOW VALUES
p_TP
HIGH VALUES
p_QO
Ml LOW VALUES
p_TKN
1H HIGH VALUES
Figure 43. Predicted Water Quality Indicators Extreme Values for 12-digit HUCs.
Water Quality Indicators
IIIIIIIIH Significant Values
Predictive Variables
i ; Significant Values
Figure 44. Humboldt Basin Subwatersheds Having Landscape Metrics Associated with Water Quality Degradation.
49
-------
50
-------
References
Bard, J. C., Busby, C. I., & Findlay, J. M. (1981). A cultural resources overview of the Carson and
Humboldt sinks, Nevada Cultural Resource Series No. 2. Bureau of Land Management.
Bellows, B. C. (2003). Managed grazing in riparian areas: Livestock systems guide. Fayetteville, AK:
ATTRA, NCAT.
Bengeyfield, P. (2007). Quantifying the effects of livestock grazing on suspended sediment and stream
morphology. In M. Furniss, C. Clifton & K. Ronnenberg (Eds.), Advancing the fundamental
sciences: Proceedings of the forest service national earth sciences conference. San Diego, CA: U.S.
Forest Service.
Benke, A. C., & Gushing, C. E. (Eds.). (2005). Rivers of North America: The natural history. Burlington,
MA: Elsevier Academic Press.
Bowers, M. H., & Muessig, H. (1981). History of central Nevada: An overview of the battle mountain
district Cultural Resources Series No. 4. Bureau of Land Management.
Brown, T.J., & Hall, B.L. (2000). Nevada 1999 Wildfire and Climate Season Assessment. CEFA Report
00-04. Desert Research Institute.
Center for Watershed Protection & USFS. (2008). Watershed forestry resource guide.2QW, from
http://www.forestsforwatersheds.org/urban-watershed-forestry/
Earle, J., & Callaghan, T. (1998). Impacts of mine drainage on aquatic life, water uses, and man-made
structures. In K. B. C. Brady, M. W. Smith & J. Schueck (Eds.), Coal mine drainage prediction and
pollution prevention in Pennsylvania. The Pennsylvania Department of Environmental Protection.
Earman, S., & Hershey, R. L. (2004). Water quality impacts from waste rock at a Carlin-type gold mine,
Elko county, NV. Environmental Geology, 45(8), 1043.
Ebert, D. W., & Wade, T. G. (2004). Analytical tools interface for landscape assessments (ATtlLA) user
manual EPA/600/R-04/083.
Glennon, R. (2002). Water follies: Groundwater pumping and the fate of America's fresh waters.
Washington: Island Press.
Gray, J. E. (2003). Leaching, transport, and methylation of mercury in and around abandoned mercury
mines in the Humboldt River Basin and surrounding areas, Nevada U.S. Geological Survey
Bulletin 2210-C.
Heggem, D. T., Neale, A. C., Edmonds, C. M., Bice, L. A., Van Remortel, R. D., & Bruce Jones, K.
(1999). An ecological assessment of the Louisiana Tensas River basin EPA/600/R-99/016.
51
-------
Homer, C., Dewitz, J., Coan, M., Hossain, N., Larson, C., Herold, N., McKerrow, A., VanDriel, J.N., and
Wickham, J. (2007). Completion of the 2001 National Land Cover Database for the Conterminous
Unnited States. Photogrammetric Engineering and Remote Sensing, Vol. 73, No. 4, pp 337-341.
Horton, G. A. (2000). Humboldt River chronology: An overview and chronological history of the
Humboldt River and related water issues. Nevada Division of Water Planning, Department of
Conservation and Natural Resources.
Humboldt River Basin Water Authority. (2007). Forecasting water demand in the Humboldt River Basin:
Capabilities and constraints. Carson City, NV.
Julien, P. Y. (1998). Erosion and sedimentation. Cambridge, United Kingdom: Cambridge University
Press.
Kuipers, J. R., Maest, A. S., MacHardy, K. A., & Lawson, G. (2006). Comparison of predicted and actual
water quality at hardrock mines: The reliability of predictions in environmental impact statements.
Maxey, G. B., & Shamberger, H. A. (1961). The Humboldt River research project, Nevada. International
Association of Scientific Hydrology, Publication Number 57, 437.
Mehaffey, M. H., Nash, M. S., Wade, T. G., Edmonds, C. M., Ebert, D. W., Jones, K. B., et al. (2001). A
landscape assessment of the Catskill/Delaware watersheds 1975-1998; New York City's water
supply watersheds. EPA/600/R-01/075.
Nash, J. T. (2003). Historic mills and mill tailings as potential sources of contamination in and near the
Humboldt River Basin, northern Nevada No. USGS Bulletin 2210-D. U.S. Geological Survey.
Nash, J. T. (2005). Hydrogeochemical studies of historical mining areas in the Humboldt River Basin and
adjacent areas, northern Nevada. Scientific Investigations Report 2004-5236. U.S. Geological
Survey.
Nevada Department of Agriculture. (2009). Nevada and its agriculture. 2010, from
http://agri.nv.gov/AgInNevada.htm
Nevada Legislative Counsel. (2010). Chapter 445A- water controls.20 W, from
http://www.leg.state.nv.us/nac/NAC-445A.html
Nevada National Heritage Program. (2008). Nevada priority wetlands inventory 2007. Carson City, NV:
Prepared for Nevada Division of State Parks.
Renard, K. G., Foster, G. R, Weesies, G. A., McCool, D. K., & Yoder, D. C. (1997). Predicting soil
erosion by water: A guide to conservation planning with the revised universal soil loss equation
(RUSLE) Agriculture Handbook no. 703. U.S. Department of Agriculture, Agricultural Research
Service.
Resource Concepts, I. (2001). Nevada grazing statistics report and economic analysis for federal lands in
Nevada. State of Nevada Department of Agriculture and Nevada Association of Counties.
52
-------
Snyder, C. D., Young, J. A., Villella, R., & Lemarie, D. P. (2003). Influences of upland and riparian land
use patterns of stream biotic integrity. Landscape Ecology, 18, 647.
Soil Science Society of America. (2010). Glossary of soil science terms 2010, from
https://www. soils.org/publications/soils-glossary/
Solnit, R. (2000). The new gold rush. Sierra, 85(4), 50.
Stone, M., McGraw, D., Stone, A., & Ohren, M. (2007). Humboldt River Basin water authority data gap
analysis. Desert Research Institute, Division of Hydrologic Sciences.
Transportation Research Board of the National Academies. (2002). Interaction between roadways and
wildlife ecology: A synthesis of highway practice. NCHRP Synthesis 305. National Cooperative
highway research program.
Troeh, F. R., & Thompson, L. M. (2005). Soils and soil fertility 6th edition. Ames, Iowa: Blackwell
Publishing Professional.
True, G. H. (1913). Agriculture. In S. P. Davis (Ed.), The history of Nevada (pp. 640). Los Angeles, CA:
Elms Publishing Company.
U.S. Bureau of Reclamation, Technical Service Center. (2001). Turbidity and total suspended solids fact
sheet. Denver, CO: Water Treatment and Engineering and Research Group.
U.S. Department of Agriculture, Natural Resources Conservation Service. (2010). Plants database. 2010,
from http://plants.usda.gov/
U.S. Department of Agriculture, U.S. Forest Service, Intermountain Region, Humboldt-Toiyabe National
Forest, & Santa Rosa Ranger District. (2009). Martin Basin Range land Project final environmental
impact statement.
U.S. Department of the Interior. (2006). Grazing management processes and strategies for riparian-
wetland areas. TR 1737-20. BLM/ST/ST-06/002+1737. Denver, CO: Bureau of Land Management,
National Science and Technology Center.
U.S. Environmental Protection Agency. (2005). Protecting water quality from agricultural runoff. EPA
841-F-05-001.
U.S. Environmental Protection Agency. (2010). Wetlands fact sheets. 2010, from
http://www.epa.gov/owow/wetlands/facts/
U.S. Fish and Wildlife. (2010). 'National wetlands inventory.2010, from
http: //www. fws. gov/wetlands/Data/WetlandCodes .html
Vale, T. R. (1975). Presettlement vegetation in the sagebrush-grass area of the intermountain west.
Journal of Range Management, 28(1), 32.
53
-------
Van Remortel, R. D. (2010). Manning's n roughness coefficient.
Van Remortel, R. D., Maichle, R. W., Heggem, D. T., & Pitchford, A. M. (2005). Automated GIS
watershed analysis tools for RUSLE/SEDMOD soil erosion and sedimentation modeling.
EPA/600/X-05/007.
Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion losses: A guide to conservation
planning Agriculture Handbook Number 537. U.S. Department of Agriculture.
Young, J. A., & Clements, C. D. (2006). Nevada rangelands. Rangelands, 28(5), 10.
Young, J. A., & Sparks, A. (2002). Cattle in the cold desert. Reno, Nevada: University of Nevada Press.
54
-------
Data
Bureau of Land Management. (2009). Download Geospatial Data: Nevada., 2010, from
http://www.blm.gov/nv/st/en/prog/more_programs/geographic_sciences/gis/geospatial_data.html
ESRI. (2010). Census 2000 TIGER/Line Data., 2010, from
http://www.esri.com/data/download/census2000-tigerline/index.html
Multi-Resolution Land Characteristics Consortium. (2008). National Land Cover Database (NLCD 2001)
multi-zone download site.2QW, from http://www.mrlc.gov/nlcd_multizone_map.php
National Atlas of the United States. (2009). Raw Atlas Data Download, 2010, from
http://www.nationalatlas.gov/atlasftp.htmltfhucsOOm
Natural Resources Conservation Service. (2010). Soil Data Mart., 2010, from
http://soildatamart.nrcs.usda.gov/USDGSM.aspx
Nevada Department of Agriculture. (2009). Grazing Database., 2010, from
http://agri.nv.gov/Index GrazingDB.htm
U.S. Census Bureau. (2009). 2008 TIGER/Lineฎ Shapefiles., 2010, from http://www2.census.gov/cgi-
bin/shapefiles/national-files
U.S. Environmental Protection Agency. (2007). EcoregionMaps and GISResources. 2010, from
http://www.epa.gov/wed/pages/ecoregions.htm
U.S. Geological Survey. (2009). Water Resources of the United States: Hydrologic Unit Maps. 2010,
from http://water.usgs.gov/GIS/huc.html
55
-------
56
-------
Programs
U.S. Department of Agriculture, Agricultural Research Service. (2010). Revised Universal Soil Loss
Equation (RUSLE). http://www.ars.usda.gov/Research/docs.htm?docid=5971
U.S. Environmental Protection Agency. (2007). Analytical Tools Interface for Landscape Assessments
(ATtlLA). http://www.epa.gov/nerlesdl/land-sci/attila/index.htm
57
-------
58
-------
Appendix 1. Humboldt Ecoregions (USEPA, 2007).
Level IV Ecoregions
13e
13g
13h
13j
13k
131
13m
13n
13o
13p
13q
13r
13s
13t
13z
80a
High Elevation
Carbonate
Mountains
Wetlands
Lahontan and
Tonopah 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
Physiography
High rugged mountains. Cold water streams
fed by snow melt.
Flat terrain with saline or freshwater wetlands.
Broad alkali flats, playas, sand dunes and
plains. Saline lakes and marshes occur. Water
more alkaline.
Rolling plains, scattered hills and sand sheets.
Surface water more alkaline.
Hills, upper alluvial fans and low mountain
slopes.
Low fault block mountains. Streams fed by
springs and snow melt.
Rolling plains, alluvial fans, foothills and few
hot springs.
Mid-elevation mountains. Snow-melt and cold
springs feed lakes and streams.
High elevation mountains containing glacial
features. Small cold lakes fed by snow melt.
Flat to gently sloping basins, floodplains and
hill slopes. Scattered ridges. Stream flow
variable.
Mid-elevation sloping mountains.
Underground drainage common with many
springs.
Rolling to hilly, high elevation valleys.
Alluvial fans. Substrates are of fine sediments.
Mid-elevation slopes and summits. Streams
fed by snow melt and cold springs.
High-elevation mountains with moderate to
high gradient headwater streams fed by
snowmelt and cold springs.
Flat to rolling valleys with plains, hills and
eroded gullies. Some hot springs.
Rolling volcanic plateaus dissected by shear-
walled canyons. Variable flow.
Vegetation
Spruce-fir forest. Understory of brush
species and grasses. Limited areas of alpine
meadows or tundra.
Tule marshes. Non-native tamarisk becoming
common.
Mostly barren. Does contain saltbrush and
other extremely salt-tolerant plants.
Saltbrush. Riparian woodland.
Great Basin sagebrush community and
sagebrush steppe.
Juniper steppe woodland. Riparian
vegetation can be lacking.
Great Basin sagebrush community and
sagebrush steppe.
Juniper-pinyon woodland and mountain-
mahogany.
Great Basin pine forest community. Aspen
groves. Alpine tundra. Rocky mountain flora
is dominant.
Great Basin sagebrush community.
Understory composed of grasses.
Juniper-pinyon woodland and some Great
Basin sagebrush community.
Mostly Great Basin sagebrush community.
Riparian habitat lacking.
Juniper-pinyon woodland and mountain-
mahogany.
Mostly mountain-mahogany. Only Great
Basin tree communities occur.
Mostly saltbrush-greasewood and Great
Basin sagebrush community.
Mostly sagebrush steppe. Overgrazed areas.
59
-------
Level IV Ecoregions
80b
80g
80j
80k
Semiarid Hills and
Low Mountains
High Lava Plains
Semiarid Uplands
Partly Forested
Mountains
Physiography
Hills, low mountains and alluvial fans.
Flat to hilly volcanic plateau. Lakes and
ephemeral pools levels are variable.
Hills, low to mid elevation mountain slopes
and volcanic cones.
Partially glaciated. High, rugged mountains
containing glacial features.
Vegetation
Mostly sagebrush steppe and juniper-pinyon
woodland.
Sagebrush steppe.
Mostly juniper steppe woodland and
sagebrush steppe.
Great Basin pine forest community.
60
-------
Appendix 2. Regional HUC Numbers and Corresponding Names.
8-digit HUC
16040101
16040102
16040103
16040104
16040105
16040106
16040107
16040108
16040109
Name
Upper Humboldt
North Fork Humboldt
South Fork Humboldt
Pine
Middle Humboldt
Rock
Reese
Lower Humboldt
Little Humboldt
Area sq. km
7045
2559
3289
2551
8236
2300
5983
6708
4507
Area sq. miles
2720
988
1270
985
3180
888
2310
2590
1740
61
-------
Appendix 3. List of Sampling Sites.
Site
4
5
7
11
14
22
25
34
35
37
53
66
69
71
92
103
108
127
129
130
133
134
140
158
161
164
166
176
181
183
184
196
Stream Name
Upper Reese River
Brewer Canyon
Mullinix
Evans (lower) Creek
Boulder Creek
Thomas Creek
Elbow Canyon
Kelly
Spaulding
Panther
Dorsey Creek
Smith Creek
Dixie Creek
Talbot Creek
Trout Creek
Huntington Creek
Chimney Creek
Welsh Canyon
Beaver Creek
Marysville Creek
Little Humboldt River
Boulder Creek
Hot Creek
South Fork Humboldt River
Round Corral Creek
Willow Creek
Iowa Canyon
Pine Creek
Table Mountain
Jake Creek
Mary's River
Reese River
Longitude
-117.47055560
-117.23138890
-117.53888890
-117.00388890
-116.33722220
-117.73333330
-117.67833330
-117.15722200
-117.79666670
-117.50361110
-115.74972220
-115.70250000
-115.85027780
-115.44750000
-116.94638890
-115.76138890
-115.38555560
-116.29777780
-116.22527780
-117.34277780
-116.88611110
-115.25972220
-115.16638890
-115.57555560
-117.48250000
-116.62500000
-116.96250000
-116.13527780
-117.78027780
-117.06166670
-115.24222220
-117.10361110
Latitude
38.85000000
39.23861111
41.56138889
41.11083333
41.10361111
40.89861111
40.75638889
41.13611111
40.53972222
40.55666667
41.05805558
40.46055556
40.66750000
40.73861111
40.38472222
40.14000000
41.56416667
40.79027778
41.11194444
39.04166667
41.39277778
40.98333333
41.59000000
40.55944444
41.64194444
41.20694444
39.79833333
40.37111111
40.50166667
41.17027778
41.41277778
39.86555556
62
-------
Site
199
204
230
244
245
247
250
259
269
Stream Name
Martin Creek
Hank's Creek
Rock Creek
Pole Creek
Susie Creek
Sherman Creek
Beaver Creek
Gance Creek
Upper Little Humboldt River
Longitude
-117.35777780
-115.30638890
-116.50055560
-115.05722220
-115.95388890
-115.72666670
-115.59361110
-115.76694440
-117.36222220
Latitude
41.62500000
41.46277778
41.34666667
41.39222222
40.99972222
40.94944444
41.39666667
41.24083333
41.76750000
63
-------
Appendix 4. Descriptive Statistics for
12-Digit HUCs and Delineated Watersheds
% Forest
% Agriculture
% Shrubland
% Natural Grassland
% Urban
% Wetlands
% Barren
Stream Density (km of streams/area in km2)
Road Density (km of roads/area in km2)
# Road/stream crossings per km of stream in
HUCs
Total # of road/stream crossings in HUCs
% stream length adjacent to forest 30m
% stream length adjacent to agriculture 30m
% stream length adjacent to shrubland 30m
% stream length adjacent to natural grasslands
30m
% stream length adjacent to all human use 30m
(land cover)
% stream length adjacent to wetlands 30m
% stream length adjacent to barren 30 m
% stream length adjacent to forest 90m
% stream length adjacent to agriculture 90m
% stream length adjacent to shrubland 90m
% stream length adjacent to natural grasslands
90m
% stream length adjacent to all human use 90m
(land cover)
% stream length adjacent to wetlands 90m
% stream length adjacent to barren 90 m
HUCs
Mean
6.1
1.7
79.5
10.5
0.6
1.1
0.4
0.9
0.7
0.4
43.0
5.5
2.9
75.2
11.9
3.5
3.3
0.5
5.7
2.7
76.4
11.4
o o
J.J
2.7
0.5
Min
0.0
0.0
9.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
3.0
0.0
0.0
0.0
0.0
0.0
0.0
4.2
0.0
0.0
0.0
0.0
Max
72.6
34.0
100.0
91.0
19.1
21.9
30.9
1.9
2.5
1.2
526.0
56.7
40.3
100.0
97.0
41.6
38.6
32.5
62.0
36.5
100.0
95.8
37.7
35.9
37.7
Delineated Watersheds
Mean
12.9
0.6
79.6
5.9
0.1
0.5
0.3
0.9
0.5
0.4
67.0
13.8
1.2
76.0
5.8
1.4
2.7
0.3
14.0
1.0
77.0
5.6
1.2
1.9
0.3
Min
0.0
0.0
27.1
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
26.1
0.0
0.0
0.0
0.0
0.0
0.0
26.9
0.0
0.0
0.0
0.0
Max
69.6
11.3
100.0
72.9
0.7
3.4
11.8
1.3
1.1
1.9
859.0
67.1
18.6
100.0
73.9
18.6
15.0
11.9
69.8
16.5
100.0
73.1
16.5
9.9
11.8
64
-------
Appendix 5. RULSE Variables.
Site ID
4
5
7
11
14
22
25
34
35
37
53
66
69
71
92
103
108
127
129
130
133
134
140
158
161
164
166
176
181
183
184
196
199
204
230
244
245
247
250
259
269
A Value
(kg/ha/yr)
6948
14785
11409
1762
3436
6715
5332
2234
2230
5560
723
4233
1102
5005
4153
1923
2897
1236
4193
7150
3085
15818
2647
8757
6438
1848
3873
1086
3109
3540
476
2503
9409
922
3741
3473
1283
1532
2204
2751
10829
R Factor
20
20
22
7
11
12
9
9
9
10
8
13
6
15
10
10
14
6
13
12
12
30
12
18
21
9
16
9
10
10
6
12
25
7
13
15
7
7
14
11
29
K Factor
0.16
0.29
0.25
0.33
0.16
0.22
0.22
0.32
0.23
0.25
0.12
0.25
0.30
0.18
0.15
0.35
0.15
0.20
0.16
0.24
0.20
0.19
0.13
0.17
0.22
0.21
0.16
0.26
0.19
0.20
0.20
0.25
0.24
0.13
0.16
0.13
0.22
0.15
0.18
0.25
0.29
LS Factor
12.05
17.54
9.32
5.47
8.56
14.56
12.03
3.28
6.02
12.07
3.44
8.07
3.55
12.29
15.90
3.47
6.24
8.48
10.59
13.32
5.98
15.94
7.57
16.84
6.44
4.62
9.41
3.22
7.34
7.82
2.38
5.41
7.50
4.60
8.23
8.22
4.38
6.97
4.29
5.74
5.65
C Factor
0.081
0.063
0.098
0.071
0.098
0.089
0.093
0.196
0.090
0.093
0.099
0.080
0.088
0.065
0.078
0.091
0.100
0.056
0.090
0.070
0.097
0.079
0.100
0.073
0.097
0.099
0.069
0.083
0.098
0.094
0.100
0.084
0.098
0.099
0.094
0.100
0.098
0.099
0.100
0.098
0.100
P Factor
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
65
-------
Appendix 6. User Defined Summary of Surface Layers
in the Humboldt River Basin.
Summary Soils
Sandy Loam
Clay
Loam
Soil Groups
Fine Sandy Loam
Gravelly Sandy Loam
Gravelly Fine Sandy Loam
Gravelly Coarse Sandy Loam
Gravelly Very Fine Sandy Loam
Sandy Loam
Cobbly Fine Sandy Loam
Fine Sandy Loam
Gravel Coarse Sandy Loam
Gravelly Sandy Loam
Gravelly Very Fine Sandy Loam
Very Fine Sandy Loam
Silty Clay
Clay
Loam
Summary Soils
Gravelly Loam
Silt Loam
Cobbly Loam
Sand
Clay Loam
Channery Loam
Soil Groups
Extremely Gravelly Loam
Gravelly Loam
Very Gravelly Loam
Gravelly Silt Loam
Silt Loam
Very Cobbly Silt Loam
Cobbly Loam
Very Cobbly Loam
Fine Sand
(Gravelly) Loamy Sand
Sand
Very Gravelly Coarse Sand
Silty Clay Loam
Very Channery Loam
66
-------
Appendix 7. Ecological Indicators.
Site
4
5
7
11
14
22
25
34
35
37
53
66
69
71
92
103
108
127
129
130
133
134
140
158
161
164
166
176
181
183
184
196
199
204
230
244
245
247
250
DO
(mg/L)
6.9
5.5
7.6
8.8
7.1
8.5
9.1
9.5
7.6
7.5
8.2
7.9
10.0
8.4
8.8
11.2
6.4
9.1
7.6
7.9
8.0
7.5
8.2
6.7
7.0
8.2
7.8
8.5
8.3
6.8
7.5
10.5
7.5
6.5
-
7.0
7.2
8.2
9.9
PH
(unitless)
7.7
8.5
8.1
9.2
8.6
8.7
8.3
9.0
8.7
8.7
8.7
7.8
8.6
8.4
8.6
8.6
7.0
8.1
8.5
8.5
8.1
7.3
8.6
6.6
7.8
-
8.8
7.6
8.0
-
8.3
8.9
8.8
8.1
-
8.3
11.7
7.6
9.3
TKN
(mg/L)
0.12
0.09
0.22
0.22
0.24
0.14
0.11
0.24
0.27
0.17
0.35
0.24
0.22
0.11
0.12
0.26
0.24
0.37
0.07
0.12
0.13
0.15
0.14
0.11
0.15
0.18
0.10
0.32
0.09
0.11
0.06
0.27
0.15
0.15
0.09
0.16
0.17
0.41
0.26
TP
(mg/L)
0.05
0.02
0.05
0.08
0.09
0.03
0.04
0.05
0.05
0.04
0.06
0.08
0.04
0.03
0.05
0.02
0.04
0.10
0.16
0.03
0.06
0.03
0.20
0.02
0.06
0.13
0.03
0.05
0.01
0.09
0.04
0.05
0.04
0.08
0.01
0.06
0.11
0.12
0.07
IDS
(mg/L)
80
424
92
115
114
182
516
202
692
299
161
117
286
99
199
214
93
35
278
183
103
107
317
85
98
17
249
165
185
117
150
549
138
141
185
238
505
34
104
IBI
(unitless)
68.0
44.0
48.0
28.0
34.0
68.0
44.0
46.0
58.0
38.0
58.0
38.0
40.0
76.0
62.0
18.0
48.0
30.0
96.0
68.0
80.0
70.0
16.0
66.0
56.0
48.0
70.0
34.0
-
86.0
72.0
18.0
82.0
50.0
-
-
18.0
32.0
24.0
67
-------
Appendix 7. Ecological Indicators (cont).
Site
259
269
Mean
Upper 95%
Conf.
Lower 95%
Conf.
Median
Minimum
Maximum
Standard
Deviation
DO
(mg/L)
9.8
5.5
8.0
8.4
7.6
7.9
5.5
11.2
1.25
PH
(unitless)
8.4
7.1
8.4
8.6
8.1
8.5
6.6
11.7
0.82
TKN
(mg/L)
0.25
0.19
0.18
0.21
0.16
0.16
0.06
0.41
0.08
TP
(mg/L)
0.07
0.20
0.06
0.08
0.05
0.05
0.01
0.20
0.05
IDS
(mg/L)
237
159
202
247
156
161
17
692
148.3
IBI
(unitless)
16.0
52.0
50
56.8
43.2
22
16
96
21.5
68
-------
Appendix 8. Predicted Models
Predicted DO
^7-8
| 18-8.5
HH3.5-9
BB 9- 10
Figure 45. Predicted Dissolved Oxygen Values for the Humboldt River Basin.
Predicted TKN
^H 0.07-0.1
| | 0.1 - 0.12
| | 0.12-0.15
BB 0.15-0.2
0.2-0.27
Figure 46. Predicted Total Kjeldahl Nitrogen Values for the Humboldt River Basin.
69
-------
Predicted TP mg/l
Hi 0.016-0.022
H 0.022 - 0.027
0.027 - 0.032
^B 0.032 - 0.04
0.04-0.093
Figure 47. Predicted Total Phosphorus Values for the Humboldt River Basin.
70
-------
Predicted IBI
^| 22 - 36
36-43
43-51
51 -63
63-88
Figure 48. Predicted IBI for the Humboldt River Basin.
71
-------
72
-------
-------
&EPA
United States
Environmental Protection
Agency
Office of Research
and Development (8101R)
Washington, DC 20460
Official Business
Penalty for Private Use
$300
EPA/600/R-13/XXX
January 2013
www.epa.gov
Please make all necessary changes on the below label, detach
or copy and return to the address in the upper left hand corner.
If you do not wish to receive these reports CHECK HERE fj;
detach, or copy this cover, and return to the address in the
upper left hand corner.
PRESORTED STANDARD
POSTAGE & FEES PAID
EPA PERMIT No, G-35
Recycled/Recyclable
Printed with vegetable-based ink on
paper that contains a minimum of
50% post-consumer fiber content
processed chlorine free
------- |