EPA/600/R-15/040 | March 2015 www.epa.gov/research
United States
Environmental Protection
Agency
An Ecological Characterization
and Landscape Assessment of the
Muddy-Virgin River Project Area
RESEARCH AND DEVELOPMENT
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An Ecological Characterization
and Landscape Assessment of
the Muddy-Virgin River Project Area
Prepared by
Leah Hare1, Daniel Heggem1, Robert Hall2, Peter Husby3
1U.S. Environmental Protection Agency
Office of Research and Development
National Exposure Research Laboratory
Environmental Sciences Division
Las Vegas, NV89119
2U.S. Environmental Protection Agency
Region 9 WTR2
San Francisco, CA 94105
3U.S. Environmental Protection Agency
Region 9 Laboratory
Richmond, CA 94804
Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official
Agency policy. Mention of trade names and commercial products does not constitute endorsement or
recommendation for use.
U.S. Environmental Protection Agency
Office of Research and Development
Washington, DC 20460
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11
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Table of Contents
List of Tables v
List of Figures vii
List of Appendices ix
List of Acronyms and Abbreviations xi
Acknowledgements xiii
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 9
2.3. Watershed 11
3.0 Methodology 13
3.1. Regional Classification 13
3.2. USEPA-Delineated Sub-Watersheds 13
3.3. Landscape Metrics 14
3.4. Soil and Landform Metrics 15
3.5. EMAP Measurements 16
3.6. Data Sources 16
3.7. Data Analysis 16
3.8. Quality Assurance Summary 17
4.0 Land Cover/Use 19
4.1. Forests 19
4.2. Shrubland 20
4.3. Grasslands 20
4.4 Agriculture 21
4.5. Grazing 22
4.6. Population Growth and Urban Development 23
4.7. Roads 25
4.8. Mining 25
4.9. Riparian Land Cover/Use 26
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Table of Contents
5.0 Land Cover Comparison 29
6.0 Soil Cover 31
6. l.R Factor 31
6.2. C Factor 32
6.3. K Factor 33
6.4. P factor 34
6.5. LS Factor 35
6.6. A Value 35
7.0 Ecological Indicators 37
7.1. Dissolved Oxygen 37
7.2. pH 38
7.3. Total Phosphorus 38
7.4. Total Nitrogen 38
7.5. Chloride 39
7.6. IBI 39
8.0 Landscape and Water Relationships 41
8.1. Regression Models 41
8.2. Model Application 41
9.0 Conclusion 43
References 47
Data 51
Programs 53
IV
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List of Tables
Table 1. Regional HUC Numbers and Corresponding Names 12
Table 2. 2001 National Land Cover Data Regional Land Cover Classes 13
Table 3. Major Population Areas in the Muddy-Virgin River Project Area from 1980-2000 24
Table 4. General Distribution of K Factor Values 33
Table 5. Water Quality Standards for Nevada 37
Table 6. Indicator Exceedances 40
Table 7. Multiple Regression Models "*" Denotes Log-Transformation 41
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VI
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List of Figures
Figure 1. Location of the Muddy-Virgin River Project Area 3
Figure!. 2001 NLCD (MRLC, 2008) 4
Figure 3. National Map of Roads (USGS, 1995) 5
Figure 4. Jurisdictional Boundaries for the Muddy-Virgin Project Area 6
Figure 5. National Elevation Data for the Muddy-Virgin River Project Area 7
Figure 6. Ecoregions in the Muddy-Virgin River Project Area 8
Figure 7. Land Cover/Use in the Muddy-Virgin River Project Area 9
Figure 8. Streams and Water Bodies in the Muddy-Virgin River Project Area 10
Figure 9. National Map of 8-DigitHUCs. 2-DigitHUCs are Illustrated in Color 11
Figure 10. Watershed Boundaries for the Muddy-Virgin River Project Area 12
Figure 11. Las Vegas Valley Vegetation Shown in Red 13
Figure 12. Muddy-Virgin River Project Area Watersheds and GIS-Delineated Sub-Watersheds 14
Figure 13. Example of the Maps that Appear in this Report. The Maps are Color
Coded to Show Land Cover/Use Percentages 15
Figure 14. Percent of Forest Cover in the Muddy-Virgin Project Area 19
Figure 15. Percent Shrub/Scrubland in the Muddy-Virgin River Project Area 20
Figure 16. Percent Natural Grasslands in the Muddy-Virgin River Project Area 21
Figure 17. Percent Total Agriculture in the Muddy-Virgin River Proj ect Area 21
Figure 18. Herd Management Areas in the Muddy-Virgin River Project Area 23
Figure 19. Percent Urban Areas in Muddy-Virgin River Project Area 23
Figure 20. Population Change in Major Cities in the Muddy-Virgin River Project Area 24
Figure 21. Road Density in the Muddy-Virgin River Project Area 25
Figure 22. Muddy-Virgin River Project Area Land Cover Including Mines
with 1km Buffer 25
Figure 23. Percentage of Riparian Buffer in Forest, Wetland, Shrubland, Grassland, Barren,
Total Agriculture and Urban Calculated within a 30m Buffer 26
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List of Figures (com.)
Figure 24. Meadow Valley Wash and Las Vegas Valley Land Cover Change 29
Figure 25. Rainfall Erosivity in the Muddy-Virgin Project Area 31
Figure 26. Average Rainfall Erosivity for the Continental United States (Troeh, 2005) 32
Figure 27. C Factor Values for the Muddy-Virgin River Project Area 32
Figure 28. K Factor Values in the Muddy-Virgin River Project Area 33
Figure 29. Map of Surface Layers in the Muddy-Virgin River Project Area 34
Figure 30. LS Factor for the Virgin Valley Area 35
Figure 31. A Values Throughout the West (USEPA, 2010) 35
Figure 32. Dissolve Oxygen in the Muddy-Virgin River Study Area 37
Figure 33. ph in the Muddy-Virgin River Study Area 38
Figure 34. Total Phosphorus in the Muddy-Virgin River Study Area 38
Figure 35. Total Nitrogen in the Muddy-Virgin River Study Area 39
Figure 36. Chloride in the Muddy-Virgin River Study Area 39
Figure 37. IBI in the Muddy-Virgin River Study Area 40
Figure 38. Land Cover/RUSLE 2 Extreme Values for 12-Digit HUCs 44
Figure 39. Predicted Water Quality Indicators Extreme Values 45
Figure 40. Muddy-Virgin River Project Area Subwatersheds Having Landscape Metrics
Associated with Water Quality Degradation 46
Figure 41. Predicted Total Phosphorus Value 68
Figure 42. Predicted Total Nitrogen Values 69
Figure 43. Predicted IBI Values 70
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Appendices
Appendix 1. List of Sites 55
Appendix 2. Ecoregions and Relating Physiography and Vegetation (USEPA, 2007) 56
Appendix 3. Muddy-Virgin Project Area Delineated Sub-Watershed Names with
Numbers Corresponding to Figure 12 57
Appendix 4. Descriptive Statistics for HUCs and Delineated Sub-Watersheds 58
Appendix 5. Land Cover/Use for the Muddy-Virgin Project Area Delineated
Sub-Watersheds 59
Appendix 6. Land Cover/Use for the Muddy-Virgin Project Area Delineated
Sub-Watersheds 60
Appendix 7. Land Cover/Use for the Muddy-Virgin Project Area Delineated
Sub-Watershed Riparian Buffers 61
Appendix 8. Land Cover/Use for the Muddy-Virgin Project Area Delineated Sub-Watershed
Riparian Buffers 62
Appendix 9. RUSLE 2 Variables 63
Appendix 10. Descriptive Water Quality and IBI Statistics in the Muddy-Virgin Project Area 64
Appendix 11. Indicators Summary Statistics 65
Appendix 12. User-Defined Summary of Surface Layers in the Muddy-Virgin Project Area 65
Appendix 13. Predicted Models 67
IX
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Acronyms and Abbreviations
A Value
AML
ATtlLA
ARS
AUM
BLM
BOR
C Factor
DEM
EMAP
ESRI
CIS
HUC
IBI
K Factor
LS Factor
MRLC
MVPA
NAC
NASA
NBA
NLC
NLCD
NNHP
NRCS
NFS
NDWP
P Factor
pH
QAPP
R Factor
Gross Soil Erosion Rate
Arc Macro Language
Analytical Tools Interface for Landscape Assessment
Agricultural Research Service
Animal-Unit-Months
Bureau of Land Management
U.S. Bureau of Reclamation
Surface Cover Effect
Digital Elevation Model
Environmental Monitoring and Assessment Program
Environmental Systems Research Institute
Geographical Information System
Hydrologic Unit Code
Index of Biotic Integrity
Surface Erodibility
Slope Length/Steepness
Multi-Resolution Land Characteristics Consortium
Muddy-Virgin Project Area
Nevada Administrative Code
National Aeronautics and Space Administration
Nevada Department of Agriculture
Nevada Legislative Counsel
National Land Cover Database
Nevada National Heritage Program
Natural Resources Conservation Service
National Park Service
Nevada Division of Water Planning
Conservation Practices
Hydrogen Ion Concentration
Quality Assurance Project Plan
Rainfall Erosivity
XI
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Acronyms and Abbreviations (com.)
RF3 River Reach File Version 3
RUSLE 2 Revised Universal Soil Loss Equation
SEDMOD Spatially Explicit Delivery Model
STATSGO State Soil Geographic Database
SNWA Southern Nevada Water Authority
TM Thematic Mapping
TMDL Total Maximum Daily Load
TN Total Nitrogen
TP Total Phosphorus
USEPA U.S. Environmental Protection Agency
USFWS U.S. Fish and Wildlife Service
USFS U.S. Forest Service
USGS U.S. Geological Survey
USDA U.S. Department of Agriculture
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Acknowledgements
The authors would like to recognize the good people that helped us with this report; Sherman Swanson,
Tad Harris, Pam Grossmann, May Fong, 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 Muddy-Virgin River Project Area. 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, Richard E. Lizotte,
and Donald Ebert.
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 of Nevada, Reno, Biological Resources Research Center. It has
been subjected to the Agency's peer and administrative review and has been approved for publication as
an USEPA document.
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XIV
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Executive Summary
The Muddy-Virgin River Project Area covers a large part of southern Nevada. Very little is known about
the water quality of the entire Basin. The Muddy and Virgin Rivers drain into Lake Mead which provides
drinking water for communities located in the Las Vegas Valley. The area covers some of the most
densely populated and fastest growing communities in the United States and yet this area also covers
some of the most remote lands in Nevada. The people living in this area depend on clean water. Not
knowing about water quality or ecological condition is a concern because people will need to manage the
negative impacts of mining, agriculture, livestock grazing, land development, water use (dewatering) and
recreation. These activities may adversely affect water quality for human use and for any unique aquatic
biota found in the rivers and streams. Having more ecological knowledge of this Project Area will help
community leaders and decisions makers balance water quality protection with economic growth and
social concerns. This will require a great deal of thought, coordination and cooperation. 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., 2013).
Three water quality parameters were chosen to analyze the association between water quality parameters
and landscape and soil metrics. Total nitrogen (TN), total phosphorus (TP), and benthic macroinvertebrate
structure index of biological integrity (IBI). High levels of TN 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 delivery metrics to
stream water quality parameters in watershed support areas in the Muddy-Virgin River Project Area.
Seven landscape metrics were used, road length, stream density, soil erodibility, gross soil erosion,
percent natural grassland, percent urban and percent forest all had relationships to the water quality
parameters. Percent forest and soil erodibility are important factors for the Index of Biotic Integrity (IBI).
The final regression models were used to predict the water quality parameters (TN, 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.
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1.0 Introduction
1.1 Objectives
This study is presented to give the results of an
ecological assessment using landscape ecology and
water quality methods in the Muddy-Virgin River
Project Area located in Environmental Protection
Agency (USEPA) Region 9. Landscape ecology focuses
on the relationships of spatial arrangements and the
ecological processes of the landscape. To ecologists and
environmental scientists, a landscape is more than a
vista, but comprises the features of the physical
environment and their influence on environmental
resources. Landscape ecology integrates biophysical
approaches with human perspectives and activities to
study spatial patterns at the landscape level, as well as
the functioning of the region. There are many
applications of this approach. (Heggem et al, 1999
Mehaffey et al., 2001). For example, areas most
disturbed by anthropogenic sources can be identified by
combining information on population density, roads and
land cover. Vulnerability of areas can also be identified
by looking at the surrounding conditions. Potential
erosion control issues can be evaluated as well by
considering variables such as precipitation and the
steepness of slopes. Ecological processes connect the
physical features of the landscape linking seemingly
separate watersheds.
Mesquite
Lake Mead
Figure 1. Location of the Muddy-Virgin River Project Area.
The Muddy-Virgin River Project Area (Figure 1) drainage is of interest to water quality managers due to
potential human impacts including livestock grazing, agriculture, mining practices, commercial and
industrial waste and urban runoff (Clark County Nevada, 2000). This report presents an environmental
assessment of the project area, studying the relationships between water quality and landscape,
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 implemented to improve environmental quality. Currently, large
areas of southern Nevada are undergoing intensive land management changes ridding the landscape of the
exotic, invasive species tamarisk (Tamaricaceae: Tamarix ramosissima Deneb). Tamarisk is a brushy,
woody shrub that out competes native vegetation for large quantities of water while excreting salt through
shed leaves and can overtake the riparian corridor. A concentration of tamarisks can result in changes in
stream flow, increase dissolved solids in nearby streams, increase wildfire hazards while decreasing
wildlife habitat (Washington County Water Conservation District, 2006). Landcover analysis could be
used to assess the changes in water quality before and after restoration.
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 a visualization
of the conditions across the basin and within each delineated sub-watershed.
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1.2 Broad-Scale Environmental Condition
Taking a broader view, the landscape perspective changes allows 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 south western United States, rivers
are the flowing arteries in the midst of huge, arid, and often desolate western landscape (Homer et al.,
2007). There are also significantly fewer roads in the west compared to the east, thus greater amounts of
open areas (Figure 3).
NLCD2001
^B Water
^B Urban
| | Barren
| Forest
^\ Shrubland
^] Grassland
~^\ Agriculture
| Wetlands
~1 No Data
Figure 2. 2001 NLCD (MRLC, 2008).
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Roads
Figure 3. National Map of Roads (USGS, 1995).
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1.3 Overview
The Muddy-Virgin River Project Area, located in Nevada, with portions of southwest Utah and northwest
Arizona included to incorporate the lower Virgin River Basin, holds rivers which are resources for both
humans and wildlife, and are of primary importance in both the economy and ecology of the region. The
Las Vegas area originally was a stopover on the Spanish Trail because of its natural springs. With the
discovery of minerals in the 1850s, a community arose to mine the mineral commodities. The upper half
of the project area had its history as a stop on the Mormon Trail alternate route until silver and gold ore
was discovered. Natural springs abound throughout the project area feeding the streams (Clark County
Nevada, 2000). These streams provide water for agricultural irrigation and ranching, as well as feeding
into the Colorado River, proving additional water for urban areas downstream. Today, much of Nevada
State is managed by the Bureau
of Land Management (BLM),
originally known as the Grazing
Service, due to excessive
habitat degradation from
overgrazing (Figure 4).
Another prospective
anthropologenic impact is the
effects of mining. Nevada State
is the third largest gold
producer globally. Although
today, mining in the project
area consists mostly of
nonmetallic minerals such as
gypsum, limestone and gravel,
potential anthropologenic
effects can occur such as
increasing instream sediment
load and dissolved minerals in
nearby washes and floodplains.
In this study, relationships
between landscape and water
quality indicators in the
watersheds are investigated
using a snapshot in time to
establish the influence of the
landscape.
Project Area
Land Ownership
^^ Tribal Lands
Bureau of Land Management
Bureau of Reclamation
Department of Defense
| | Fish and Wildlife Service
| | Forest Service
| | National Park Sen/ice
|] State
^H Private
Figure 4. Jurisdictional Boundaries for the Muddy-Virgin Project Area.
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2.0 The Biophysical Setting
2.1 Land Cover and Topography
The Muddy-Virgin River Project Area covers 85,100 square kilometers (32,850 square miles) in Nevada,
14,000 square kilometers (5,400 square miles) in Arizona and 6200 square kilometers (2,400 square
miles) in Utah. Located in the semi-arid Great Basin and Mojave Desert, precipitation is low. In the
Mojave Desert, precipitation is less than 15 cm (6 in) per year, and around 30 cm (11.8 in) per year in the
Great Basin. The low annual precipitation for this subecoregion is both a function of distance from the
Pacific Ocean and the rain-shadow effects of the Sierra Nevada mountain range. Elevation ranges from
367 m (1204 ft) in the valley floors, located in the central areas to the south, up to 3626 m (11900 ft) in
the surrounding mountain ranges. Butte, Egan, White Pine and Egan Ranges border the area to the north,
while the Spring and Sheep Ranges rise to the south (Figure 5). The mountains are steep and deeply
incised with alluvial/colluvial deposits in the canyons with fine sediments becoming the dominant
substrate in the broad valleys. Fan deposits in the south are predominantly composed of debris flows.
Butte
Mountains
White
Pine
Range
Egan
Range
Spring
Mountains
Wilson
Creek
Range
20 0 20 40 Kilometers
| | Project Area
Elevation (m)
| | 367 - 729
| | 730 - 967
| | 968 - 1214
| | 1215 - 1465
| | 1466 - 1684
| | 1685 - 1879
^B 1880 - 2111
H 2112 - 2445
^H 2446 - 3626
| | No Data
Figure 5. National Elevation Data for the Muddy-Virgin Project Area.
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Surface water resources in the drainage basin are primarily spring fed, generally draining north to south,
with the Virgin River receiving drainage from seasonal snowmelt in central and eastern Utah. Hydrology
within the Great Basin is internal, depositing in underground aquifers. Most high elevation streams are
dry throughout most of the year, with flow alternating between the surface and the hyporheic zone, and
returning to valley streams.
The project area is split between subecoregions 13 (Central Basin and Range) and 14 (Mojave Basin and
Range) with a small portion of Arizona and Nevada in subecoregion 22 (Arizona/New Mexico Plateau).
The portion of the lower Central Basin and Range and upper Mojave Basin is comprised of north-south
trending fault-bounded horst and graben geomorphology. The Mojave Basin and Range physiography is a
creosote bush-dominated shrub community (Figure 6) which is distinct from the saltbush-greasewood and
sagebrush-grass associations that occur to the north in the Central Basin and Range. Major vegetation
communities include montane, pinyon-juniper, western juniper, sagebrush/grassland, shadscale, and
Mojavean (Mac et al., 1998).
40 Kilometers
Location Map
Ecoregion III
22
Ecoregions III (AZ) &IV(NV,UT)
| | Mojave Basin and Range
| | Arizona/New Mexico Plateau
| | Shadscale-Dominated Saline Basin
| | Sagebrush Basin and Slopes
| | Woodland and Shrub Covered Low Mountains
| | High Elevation Carbonate Mountains
I | Wetlands
^B Carbonate Sagebrush Valleys
|||; , Carbonate Woodland Zone
I | To no pah Basin
| | Tonopah Sagebrush Foothills
^^| Tonopah Uplands
Creosote Bush- Dominated Basins
Arid Footslopes
Mojave Mountain Wood- and Shrubland
| | Mojave High Elevation Mountains
| | Arid Valleys and Canyonlands
| | Mojave Playas
I I Middle Elevation Mountains
Figure 6. Ecoregions in the Muddy-Virgin River Project Area.
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The land cover in the basin is made up primarily of shrub/scrublands, predominantly big sagebrush
(Artemisia tridentata Nutt.), black sagebrush (Artemisia nova), rabbitbrush ((Chrysothamnus spp.
and Ericameria spp.), and shadscale (Atriplex confertifolid) (Figure 7). Grasslands consist of Indian rice
grass (Achnatherum hymenoides) and the invasive cheatgrass (Bromus tectorum). Forests are generally
dominated by single-needle pinyon pine (Pinus monophylla) and juniper (Juniperus sp). In higher
altitudes, bristlecone (Pinus aristata), and white firs (Abies concolof) can be found (USEPA, 2007; Benke
and Gushing, 2005). Riparian vegetation along rivers mainly includes rushes, cattails, inland salt grass,
stands of mesquite (Prosopis L.) and willows (Salix sp.) with the invasive tamarisk (Tamarix sp.)
(Tamarix ramosissima Deneb) becoming more common. Creosote bush (Larrea tridentata), cacti, and
yuccas exist in the lower Mojave Basin.
Urban areas are minimal throughout the Project Area, with the largest population, Las Vegas, located in
the southwest corner with a large military instillation bordering to the northwest. Other sizable
populations are Mesquite, located on the border of Arizona, and Hiko, located in the center of the project
area, north of Pahranagat Valley. A substantial
percentage of the basin's agricultural crops
provide alfalfa hay for the cattle and sheep
farms that graze throughout. Agricultural
areas are prevalent around the main rivers.
2.2 Streams
Streams and rivers not only direct the
flow of water, but also provide
necessary resources, such as essential
habitat for plants and 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 while
designated a primary resource for
human use. The stream network
used for this assessment is the USEPA
River Reach File (RF3), derived , v. 1SN#WW^- - "P^HPir CH Project Area
from the U.S. Geological Survey ] '/ M 2001 NLCD Landcover
(USGS) Digital Line Graph i : '1'* ^ open water
AT o\ '
(figure 8), : m^_ Barren Rock/Sand/Clay
Deciduous Forest
Evergreen Forest
Mixed Forest
Shrub/Scrub
Grassland/Herbaceous
Pasture/Hay
Cultivated Crops
Woody Wetlands
Emergent Herbaceous Wetlands
No Data
20 0 20 40 Kilometers
a
a
a
Figure 7. Land Cover/use in the Muddy-Virgin River Project Area.
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Meadow Valley
Wash
Beaver Dam
Wash
| | Project Area
/\/ Major Rivers
' River Reach File
Waterbodies
Las Vegas
Wash
Figure 8. Streams and Water Bodies in the Muddy-Virgin River Project Area.
The Virgin River originates east of Rockville, UT where the confluence of the East and North Forks
converge in Washington County. It then disappears into the riverbed through the Beaver Dam mountains
and resurfaces above Littlefield, AZ, flowing northeast to southwest. During low-flow periods, most of
the flow in the Virgin River originates from a highly saline, major spring system in Littlefield, Arizona,
located approx 16 km (10 miles) upstream of Mesquite (ADWR, 2009). The Virgin River also drains
numerous springs and washes as well; the Beaver Dam Wash being its largest tributary. It is the largest
contributor to the Colorado River in Nevada accounting for 1.4% of water resources in Lake Mead, a
reservoir created by the Hoover Dam (Las Vegas Wash Coordination Committee, 2010). The Meadow
Valley Wash, an intermittent stream system flowing from its northern headwaters in the Wilson Creek
Range emptying into the Muddy River, is the principal drainage channel in the range with flow
originating from precipitation in the mountains (Resource Concepts, 2001). The Muddy River originates
from thermal springs in the Moapa Valley and flows 51.5 km (32 miles) into Lake Mead. Currently an
urban drainage system with few naturally flowing springs, the Las Vegas Valley Wash contains urban
runoff and treated waste water flowing through the local wetlands and into Lake Mead and receives
10
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spring or autumnal monsoon rainfall. To the north, the Pahranagat and White Rivers are highly
manipulated waterways with large portions in straight ditches rather than natural channels. About 90% of
Pahranagat Creek is in irrigation ditches or are dewatered during the irrigation season. Only during the
winter months do the four water impoundments in the Pahranagat Valley (North Marsh, Middle Marsh
and Upper and Lower Pahranagat Lakes) receive water from the Hiko, Crystal and Ash Spring sources
(USFWS, 1998).
2.3 Watersheds
A watershed is an area of land into which all forms of precipitation permeate into the ground or drain into
streams. 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.
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The Muddy-Virgin River Project Area is located within region 15, which represents the Lower Colorado
Basin. The USGS's national 12-Digit hydrologic unit code is used in this report to summarize landscape
metrics. Figure 10 displays all 12-Digit HUCs in the project area within the larger 8-Digit cataloging
units, illustrated in color. For 8-Digit HUC numbers and total area, see Table 1.
Table 1. Regional HUC Numbers and Corresponding Names.
8-Digit HUC
15010010
15010011
15010012
15010013
15010015
Name
Lower Virgin, Arizona, Nevada, Utah
White, Nevada
Muddy, Nevada
Meadow Valley Wash, Nevada, Utah
Las Vegas Wash, Nevada
Area Square Kilometers
5361
7356
4533
6579
4817
Area Square Miles
2070
2840
1750
2540
1860
Meadow Valley
Wash, NV, UT
Las Vegas
Wash, NV
Lower Virgin
AZ, NV, UT
Muddy, NV
Figure 10. Watershed Boundaries for the Muddy-Virgin River Project Area.
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3.0 Methodology
3.1 Regional Classification
The land cover used in 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 mapping1--1 imagery, as seen in Figure 11, to
provide consistent land cover for the entire United States. By analyzing the different wavelengths
reflected by different surface types, land cover is able to be classified from reflected light. NLCD 2001
data uses 30m Digital Elevation Model (DEM) to distinguish 29 land cover classes. In the Muddy-Virgin
River Project Area, there are fifteen individual NLCD classifications which, for this study, have been
assembled into eight dominant categories (Table 2).
Table 2. 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 Grasslands
Pasture/Hay
Cultivated Crops
. Agriculture
Woody Wetlands
Emergent Herbaceous Wetlands.
.. ..Wetlands
Figure 11. Las Vegas Valley. Vegetation Shown in Red.
3.2 USEPA- Delineated Sub-Watersheds
The sample locations were determined by using a spatially distributed, randomized site selection process
(Herlihy et al., 1998, Herlihy et al., 2000). This sampling design may not be appropriate in an area with
so little water. In this arid basin the design called out 35,000 stream kilometers but only 706 km were
usable wet streams. Nested sites, which are sampling site sub-watersheds within a larger sampling
watershed, were unavoidable, thus all sites were kept for analysis, although they may skew results. A
separate set of GIS-delineated sub-watersheds (Jones et al., 2001) was used for the assessing relationships
between landscape and water quality in the Muddy-Virgin Project Area based on 37 sampling points
13
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(Figure 12). These watersheds were delineated using DEM data to calculate flow direction and flow
accumulation. This process determines boundaries and ridge tops that divide water flow to drainage or
outlet points. These delineated sub-watersheds ranged in size from less than 7 square kilometers (2.7
square miles) to over 18,000 square kilometers (6950 square miles). Corresponding site names are listed
in Appendix 1.
0 20 40 Kilometers
Sampling Sites
| | Project Area
I | Delineated Watersheds
12-digitHUCs
Figure 12. Muddy-Virgin River Project Area HUCs and GIS-Delineated Sub-Watersheds.
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 geologic, geomorphologic, hydrologic, 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,
14
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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 (e.g., 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 are calculated:
landscape characteristics, riparian characteristics,
human stressors and physical characteristics.
Landscape characteristics include basic summary
calculations such, as the percent of natural land use,
forests, or shrublands. Riparian characteristics
calculate the percentage of stream length adjacent to a
specified component. Human stressors compute
population density (and/or change), phosphorous and
nitrogen loading and stream/road density. Physical
characteristics are calculations of general statistics
such as elevation, slope and stream density.
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 forest in the basin. The map is color-coded to
show relative conditions among watersheds. The dark
green areas have the most amount of forest, while the
brown areas have the least. The natural breaks
classification method was used which displays results
by finding groups and patterns using a statistical
formula to minimize variance within each class.
Figure 13. Example of the Maps that Appear in
this Report. The Maps are Color
Coded to Show Land Cover/use
3.4 Soil and Landform Metrics
Soil erosion metrics were calculated using the watershed analysis tool for RUSLE 2/SEDMOD soil
erosion and sedimentation modeling. The Revised Universal Soil Loss Equation (RUSLE 2) model and
the spatially explicit delivery model (SEDMOD) were the primary framework for this tool. The soil and
landform metrics use GIS Arclnfo as the platform for the four arc macro language (AML) scripts and two
ANSI C++ executable programs. State Soil Geographic (STATSGO) database soil data, NLCD 2001,
boundary area, delineated sub-watersheds, ArcHydro generated filled DEM, flow direction, flow
accumulation and stream network grid were used to run the model. The RUSLE 2/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).
15
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3. 5 EMAP Measurements
Through the Environmental Monitoring and Assessment Program EMAP, planktonic and benthic
macroinvertebrate data were collected between May and June, 2000. Peck et al., 2006, describes field
procedures that were used during the EMAP Western Pilot Study, conducted from 1999 through 2004
which were the same methods use for this study. Sites were selected using a probability-based or random
design to represent the wadeable streams within the Muddy-Virgin area using the USEPA RF3.
In general terms, a water quality standard defines the goals for a body of water by designating the use or
uses to be made of the water, setting criteria necessary to protect those uses, and preventing degradation
of water quality through anti -degradation provisions. Water quality standards apply to surface water of
the United States, including rivers, streams, lakes, oceans, estuaries and wetlands. Under the Clean Water
Act, each state establishes water quality standards which are approved by the USEPA.
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) USEPA delineated sub-watersheds, RF3 files, and 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 unit code (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 2 sediment transport metrics in each
delineated sub-watershed. Prior to regression, pairwise correlations were examined between predictors
(landscape and RUSLE 2 metrics). When two predictors were found to be highly autocorrelated (R>
0.75), one was arbitrarily 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=(30+ PiXi+ (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.
16
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3.8 Quality Assurance Summary
A Quality Assurance Project Plan (QAPP) was prepared for this work entitled, Northeastern Nevada
Landscape and Aquatic Resource Characterization on Federal Lands: A Landscape Assessment of the
Humboldt River Basin, which was approved on April 29, 2009. A Technical Systems Audit was
performed on all landscape ecology projects in the Environmental Sciences Division from February to
March of 2011 and this project was given three minor revisions. Laboratory Notebooks were reviewed by
the Environmental Sciences Division Director and Quality Assurance Manager annually. There were no
findings requiring corrective actions. The audit and review conclusions did not impact the quality of the
environmental data. The QAPP title caused a deviation in that the title stated the study was done in the
Humboldt River Basin and not the Muddy-Virgin Project Area. The QAPP does state in the Abstract and
Research Work Plan Summary that, "future research areas will coincide with the State of Nevada Total
Maximum Daily Load (TMDL) priority watersheds", which is the case for sections of both Rivers and the
Las Vegas Bay area of Lake Mead. This deviation did not have any impact on the environmental data
quality. Environmental measurement data included locational data (e.g. National Land Cover Data,
Satellite Data, and Geographic Information System Data) which all met performance and acceptance
criteria stated in the QAPP. There were no deviations to methods or general or specific limitation on the
use of the results.
17
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18
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4.0 Land Cover/Use
Humans are seen as a force behind environmental
changes. Humans have been altering land cover
throughout history through fire, clearance of forests
for agriculture and livestock grazing through
animal domestication. Human 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 linked.
Humans structure the landscape, but the landscape
determines the activity. For example, soil type,
geology 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.
For example, changes in land cover affect climate
which in turn alters vegetation transpiration and
surface hydrology.
4.1 Forests
Trees are an important element for humans and
wildlife alike, playing numerous significant roles in
a watershed. Clearly, forests are an economical,
natural resource. 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 and
decreases 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 present in stream beds
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.
Historic use of wood in the Spring and Sheep Mountains Ranges north of Las Vegas was for charcoal
production, construction and firewood. Today, the only permitted use is for non-commercial firewood
from dead trees. In the northern portion of the area, forests, consisting of pine and mountain mahogany,
also have historically been used for lumber mills, charcoal and fuel (Thompson & West, 1958). In the
Muddy-Virgin Project Area, forest cover averaged 20% within the HUCs and 28% in the individual
delineated sub-watersheds. The highest forest cover was found in the Meadow Valley in the Wilson Creek
Range, and in the White Pine and Butte Mountain Ranges (Figure 14).
Figure 14. Percent Forest Cover in the Muddy-Virgin
Project Area.
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4.2 Shrubland
Shrubland (Figure 15) is the dominate land cover type with an average of 75% cover in the HUCs and
68% in the delineated sub-watersheds. Sagebrush (Artemisia tridentate spp.) is the leading vegetation,
usually in association with other shrubs such as Bitterbrush (Purshia tridentate), ephedra (Ephedra sp.),
and rabbitbrush (Chrysothmanus nauseosus).
The height of these shrublands range from
0.3 (1.0 ft) to 2.0 m (6.6 ft) tall and may have
pure stands of sagebrush or associated with other
vegetation such as other types of shrubland or
grasslands (Washington County Water
Conservation District, 2006). Riparian
shrubland, areas that are adjacent to waterways,
consist of willows (Salix sp.), acacia (Acacia
sp.) and arrowweed (Pluchea sericea).
The exotic, invasive species tamarisk (Tamarix
sp.), also referred to as salt cedar, is a brushy
vegetation that has invaded river corridors
within the Muddy-Virgin Project Area by
displacing native trees. Tamarisks excrete salts
through their leaves as they grow making it
increasingly difficult for native plants to survive.
Because they use large quantities of
groundwater, at which they are more efficient at
capturing, they out compete the native
vegetation. This results in higher salinity level
and reduced flows. Dense stands create a
monoculture offering little to wildlife and have
become a fire hazard to communities. Finally,
tamarisks are difficult to eliminate because of
their longevity, large quantities of seeds and
tolerance of environmental conditions.
% Shrubland
^B 6-28
28-51
51 -73
73-90
90 - 100
4.3 Grasslands
Grasslands are a minimal land use type with
only an average of 1.5% cover in the HUCs and
delineated sub-watersheds (Figure 16). The
largest overall areas with grasslands are in the
White Pine area to the north and the Beaver Dam Wash to the southeast. Grasses include squirreltail
(Sitanion hystrix) and Great Basin wildrye (Elymus cinereus) with cheatgrass (Bromus tectorum), an
invasive species, present in upland areas and rangelands.
Figure 15. Percent Shrubland Cover in the Muddy-Virgin
Project Area.
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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, displacing native grasses, is also 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 of wildfires (Horton, 2000).
Natural Grassland
_
02-5
HI 5-10
10-19
Figure 16. Percent Grassland in the Project Area.
4.4 Agriculture Land Use
Agriculture in Nevada's semiarid climate is
heavily directed to range livestock, primarily
cattle production. Yet, a variety of other crops can
be harvested where the landscape can be irrigated.
This economic industry began to develop in
Nevada from the mining boom in the mid 1800's.
With the influx of settlers, agriculture and
ranching erupted to provide for the miners.
Commodities consist largely of alfalfa hay for
cattle feed, but other crops such as onions,
potatoes, nuts and vegetables are also harvested to
a lesser extent.
% Total Agriculture
HB 0-0.5
| | 0.5- 1.6
| | 1.6-3.2
BB 3.2-6.6
6.6-12.4
Figure 17. Percent Total Agriculture in the Project Area.
The natural ground-water springs in the project
area supply water for irrigation. With irrigated
land comes a myriad of potential negative environmental effects. In 2000, it was reported that agricultural
nonpoint source pollution was the leading cause of water quality impacts on surveyed lakes and rivers.
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 streams and water bodies, increasing turbidity, and decreasing critical sunlight for
aquatic plants. A problem endemic to arid regions is increased soil salinity from evaporation due to the
inability of the soil to filter minerals (USEPA, 2005).
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The Muddy-Virgin project area is located in 6 counties: White Pine, NV, Nye, NV, Lincoln, NV, Clark,
NV, Washington, UT and Mojave, AZ. Forage, alfalfa (hay), and grains (wheat, oats, and barley) are the
largest commodities in the region followed by livestock and row crops (NBA, 2009). Total agriculture
(includes row crops and pastures) is minimal with an average of less than 1% in the HUCs and delineated
sub-watersheds (Figure 17). Agricultural areas are found along the riparian areas of all the major rivers.
Moapa Valley, encompassing the lower part of the Muddy River, has 2016 hectares (4,982 acres) of
irrigated, agricultural lands while the Virgin Valley, in the lower portion surrounding the Virgin River,
had 1242 hectares (3,068 acres), as of 2000 (Clark County, Nevada, 2000).
4.5 Grazing
Historically, agriculture was largely directed toward livestock, and overgrazing had become problematic.
The Virgin River specifically was used for grazing in the mid 1800's by Mexican livestock along the
Spanish Trail and then was later settled by Europeans. Open range livestock grazing has since spread
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. Total phosphorus and nitrogen, as well as heavy metals, can also
be transported, especially in dense cattle areas such as feedlots and dairies. Soil quality is changed by
severe trampling and compaction, causing increased erosion and limiting sustainability of plants. This can
make streams wider and shallower, and can increase suspended sediment concentrations (Bengeyfield,
2007). High shrubland cover may also be attributed to overgrazing. For example, the big sagebrush, was
not foraged because of its high oil content, and the overgrazing of grasses did not allow for seed
production and re-growth. As grasses decreased, shrubland cover expanded (Young & Sparks, 2002).
Such land cover changes can result in habitat loss for endangered species such as the now endangered
southwest willow flycatcher (Empidomax trailii extimis). Cattle eat or trample young riparian plants,
preventing deciduous cottonwoods and willows from establishing. Although these flycatchers have been
found to nest in tamarisk, mature cottonwoods and willows are preferred for nesting. Without the
understory to replace the older trees, prime habitat is lost (Suckling et al, 1992).
As of 2000, northeast Clark County, much under the authority of the BLM, has nineteen grazing
allotments, seven of which are now controlled by Clark County and are no longer in use. There have also
been strict restrictions on livestock grazing by the USFWS due to potential impacts on desert tortoise
habitat (Clark County Nevada, 2000). In the project area, grazing occurs primarily in the Lincoln and
White Pine counties. Animals such as feral horses and burros are the main users of the rangelands. In
1971, the BLM was charged to manage wild horses and burros in specific areas in 10 states. Only areas
that were found to have significant populations in 1971 are designated as management areas. This does
not mean that the areas are designated for horses only, but areas where the BLM evaluates to determine if
there is adequate food, water, cover and space to sustain healthy and diverse wild horse and burro
populations over the long term. Currently, there are an estimated 38,000 wild horses and burros in the
managed rangelands in the ten western states. In Nevada State there are an estimated 17,700 horses and
1,200 burros. With horse size doubling about every four years, removal of wild horses and burros occurs
to ensure rangeland health, in accordance with land-use plans that are developed in an open, public
process.
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Rangeland health is also dependant on the proper
management of the wild horse and burro population.
Decisions are made when applying to establish
livestock grazing regarding appropriate management
levels for wild horse and burros. In the Muddy-Virgin
project area, there are large sections designated as
herd management areas located within the Meadow
Valley Wash and around the White Pine River area
(Figure 18). Wild horses and burros can quickly
| | Project Area
| | Delineated Watersheds
| | Herd Management Areas
Figure 18. Herd Management Areas in the Project Area.
overpopulate an area, exceeding the capacity of
the land. Degradation can include impacts on
vegetation communities and effects on water
quality. A typical result is the changing of the
land cover from grasses to unpalatable shrubs
(Smith, 1986). The BLM is responsible for
keeping wild horse and burro populations
within appropriate numbers to avoid these
potential impacts.
Las Vegas. NV
Caliente, NV
St. George. UT
Mesquite, NV
Valley, NV
Henderson. NV
Figure 19. Percent Urban Areas in the Project Area.
4.6 Population Growth and Urban
Development
Residential areas exist predominately in the
southern portion of the project area. Las Vegas
Valley is the largest urban area present with an
estimated population of 1.3 million, located to the southwest. Other smaller communities are Mesquite,
on the border of Nevada and Arizona, Hiko, along the Pahranagat, St. George in Utah and communities
along the Muddy and Virgin River. Overall percent urban areas are minimal with most values less than
1% (Figure 19). Values range up to 84.5% for the densely populated Las Vegas Valley. According to the
U.S. Census Bureau, in 2000 the population in the Muddy-River Project Area was about just under 2
million people covering an area of 40,656 km2 (15,700 mi2), with the majority located in the Las Vegas
Valley (ESRI, 2010). The Las Vegas Valley is one of the fastest growing metropolitan areas in the US
(U.S. Census Bureau, 2009) whose population doubled from 1980 to 1994 and then again from 1994 to
2007 in addition to the yearly tourist population of 36.4 million. Between 1980 and 2000, the city of Las
Vegas itself grew from 165,000 to 478,000 people (Table 3). Mesquite has grown from a little more than
/\/ Major Roads
% Urban Area
^B 0-0.9
| | 0.9 - 4
| [4-10.3
| | 10.3-34
34-34.5
23
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500 people to almost 10,000, while Henderson, a suburb of Las Vegas has grown from a population of
12,500 to 175,000 (Figure 20).
Table 3. Major Population Areas in the Muddy-Virgin Project Area.
Place
Las Vegas, NV
Henderson, NV
N. Las Vegas, NV
St. George, UT
Mesquite, NV
Moapa Valley, NV
Caliente, NV
County
Clark
Clark
Clark
Washington
Clark
Clark
Lincoln
1980
164,674
24,363
42,739
11,350
992
702
982
1990
258,295
64,942
47,707
28,502
1,871
3,444
1,111
2000
478,434
175,381
115,488
49,663
9,389
5,784
1,123
^\"
Figure 20. Population Change in Major Cities in the Muddy-Virgin Project Area.
In this arid landscape, increases in population can have major affects to water supply and the landscape.
Currently, the Southern Nevada Water Authority (SNWA) is planning a pipeline to groundwater
resources in valleys just outside the project area boundaries around Pahranagat and Meadow Valley areas.
An Environmental Impact Statement is being prepared to assess the affects such a proposal would have to
the land cover and current use of it by the resident population and native biota. High ground-water levels
produce meadows and cover the desert floor with phreatophytes, which are groundwater dependent
plants, that arrest erosion (Schlyer, 2007). A reduction of the water table could have adverse affects on the
surrounding desert wildlife. Although the valleys are outside the Muddy-Virgin Project area, the
24
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Road Density (km/km2)
^B 0- 0.5
I 10.5-1.1
I M.1-2.5
^B 2.5-6
6-9.4
Figure 21. Road Density in the Project Area.
carbonate-rock aquifer system, extends beneath numerous
surface-water drainage basins, or hydrographic areas including
a large portion of the MV Project Area. Long term effects of
groundwater pumping could be significant drops in the water
table and a loss of dependant plant life and the associated
wildlife (Schlyer, 2007; Deacon et al., 2007).
4.7 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 of the National
Academies, 2002). Road density and 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). According to the road map used in this study,
which includes all types of roads (highways, country roads and
city streets) road density was minimal with the highest density in the basin (9.4 km/km2) in the Las
Vegas Valley (Figure 21). The main road through the
project area is Highway 93 traveling north-south down
through Las Vegas. Other main roads are Highway 95
running NW-SE and 1-15 running SW-NE, both
intersecting Las Vegas. The density of roads crossing
streams is relatively low with a range between 0.0 and 4.6
crossings per kilometer of stream with an average of 0.4.
The only areas with densities greater than 1.0 are located
in and around the Las Vegas Valley, to the north around
White Pine River and to the east in Utah.
4.8 Mining
The Las Vegas area, originally a stop on the Spanish
Trail, was known for its natural springs. Minerals were
discovered in the 1850s, and mining began for metals
such as gold, silver and lead, and nonmetallic minerals, as
gypsum, limestone, silica sand and gravel (Clark County
Nevada, 2000). The upper half of the project area has its
history as a stopover on the Mormon Trail alternate route
until ore was also discovered, primarily gold and silver.
Yet, because the mining centers were remote, population
influxes did not occur as they did further north in the
Humboldt Basin.
| | prn | fici Area
Hd fl'' n^ -
Land Cover
|^| Open Water
H '-lrt'3-
B^| Darren Rock/Sand/Clay
[ [ terHiuoLis f-dresl
^B Evergreen Forest
^^ Mixed Forest
[ yhrlib/Scrub
Currently, there are many active mining areas in the
czr>
"~| rm^rqent I Isrbai
_l Nft Dflta
Figure 22. Muddy-Virgin River Project Area Land Cover
Including Mines with 1km Buffer.
25
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Muddy-Virgin River Project Area (MV PA) with nonmetallic mineral production exceeding metallic.
Minerals include gypsum throughout the V and M mountains, limestone at Apex, NE of LV and others
such as marble, mica, salt, borates and fluorspar (Clark County Nevada, 2000). Sand and gravel mining is
one of the major mining operations in the project area. All industrial silica sand and gravel mines in the
PA are now past producers. Today, sand and gravel mining is utilized for construction, providing
necessary building supplies. Erosion, sediment deposition and air pollution through fugitive dust are the
main concerns in this types of mining. Removing the vegetation cover and exposing the soil increases
erosion rates and velocity of water runoff while releasing dust into the air.
Geothermal mines are increasing in number in Nevada. In the MV PA, wells and hot springs are being
used to produce geothermal energy along the Muddy and Virgin River systems, to the north in Meadow
Valley and in the Pahranagat Valley. Geothermal mines use the naturally heated water and steam for
generation of electric power, direct heating or geothermal pumps. There are minimal amounts of emitted
gases, spent water is pumped back into the wells and most mines are known to blend well with other land
uses (University of Utah, 2001).
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 22).
4.9 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. Thus, the surrounding land
cover is related to stream productivity.
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
Riparian Buffer (30m)
| | Forest
^\ Wetland
| | Shrubland
^m Grassland
| | Barren
| | Total Agriculture
^m Urban
Figure 23. Percentage of Riparian Buffer in Forest, Wetland,
Shrubland, Grassland, Barren, Total Agriculture and
Urban Calculated within a 30m Buffer.
26
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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
project area can be seen in Figure 23. Looking at the entire basin, riparian land cover/use is similar to the
total watershed assessment. Percent wetlands, agriculture and urban areas had a slightly higher proportion
in the riparian buffer area. Percent natural grasslands and forests were slightly lower. The descriptive
statistics for total watershed assessment, as well as 30 m and 90 m riparian buffers are displayed in
Appendix 2.
27
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28
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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 be exact.
This retrofit product was used to analyze changes in the landscape in the Muddy-Virgin Project Area.
Two subset images are shown in Figures 24a-b. Average land cover/use change in the project area was
very slight. Significant changes included decreases in forest cover in the Meadow Valley Wash area
because of clear cutting which changed the land cover to shrubland. Other changes occurred changing
from shrub/grassland to barren and urban land in the Las Vegas area because of increased development.
Shrub/grasslands and agricultural patches were interchanged as well throughout all HUCs because of
changes in farming and grazing. Wetlands increased slightly along the Las Vegas Wash and Lower Virgin
and Muddy Rivers.
a.
1992/2001 Land Cover Change
BOpen Water
Urban
^^ Barren
^H Forest
S Grassland/Shrub
Agriculture
I | Wetlands
I | Change to Water
I | Change to Urban
I | Change to Barren
^B Change to Forest
^] Change to Grass/Shrubland
| | Change to Agriculture
^^ Change to Wetlands
| | No Data
1992/2001 Land Cover Chanjs
Op*n Water
Urban
Barren
^m Forosl
Change to water
_ . Change to urban
I '"M.-I-MJ- ro M,,r~n
^g Changs to Forest
B Change to Orass/Shfubland
_ Change to Agriculture
^B Change to Wellancts
I No Dala
Figure 24a-b. Meadow Valley Wash and Las Vegas Valley Land Cover Change.
29
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30
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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 in the Revised Universal Soil Loss Equation (RUSLE 2)
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 Project Area's 40 delineated sub-watersheds.
6.1 R Factor
The R factor, which represents the rainfall-
runoff erosivity factor, 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 project area, R factors ranged
from 6 to 42, while in the individual
delineated sub-watersheds, average R factor
values ranged between 9 and 28 with the
majority of values less than or equal to 14. The
areas with the greatest potential for rainfall
erosion are located in the surrounding
mountain ranges and the Meadow Valley and
Beaver Dam areas (Figure 25). 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 and Thompson,
2005) (Figure 26).
| | Project Area
R Factor
| 6- 10
1 11 -13
| 14- 16
| | 17- 19
BB 20 - 23
BB 24 - 27
BB 28 - 30
BB 31 - 35
BB 36 - 42
~~| No Data
Figure 25. Rainfall ErosMty in the Muddy-Virgin Project Area.
31
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200
600
Figure 26. Average Rainfall Erosivity for the Continental United States (Troeh, 2005).
6.2 C Factor
The C factor, or cover management factor, reflects
the effect of cropping and land management
practices on erosion rates. 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 0.09. This signifies that erosion will be
reduced up to 9% 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 2 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 sub-watersheds,
averaged values were very low ranging from 0.04 to
0.15 with an overall average of 0.09 (Figure 27).
High individual values of up to 0.98 can be found in
the southern areas around the Muddy and Virgin
Rivers, locations to the north of Las Vegas and
other places with heavy agriculture.
Project Area
C Factor
0 - 0.02
0.02-0.03
| 10.03-0.06
| [0.06-0.42
0.42-0.98
Figure 27. C Factor Values for the Muddy-Virgin Project Area.
32
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6.3 K Factor
Soil erosion is an important environmental variable
that can have profound effects on and off site. In the
Muddy-Virgin River Project Area, grazing is a factor
in erosion. Trampling of streambanks by livestock
compress the soil, decreasing the vegetation and the
soil's ability to absorb and hold water. This erodes
the bank, adding sediment into the stream. Erosion
of streambanks can result in the straightening of the
river bed, increasing slope and flow velocity. Mining
operations may dump large amounts of sediment
directly into streams. Increased sedimentation 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). Surface soil erosion can also
affect soil productivity and ecosystem function.
Since most nutrients and organic matter are most
dense in the surface soil layer, erosion washes away
the most productive layer. Soil erodibility, expresses
here as the K factor, evaluates the potential for
erosion using the NRCS STATSGO database soil
data. The K factor represents the combination of soil
type and detachability, as well as transportability of
the eroded sediment. Table 3 describes the general
relative distribution of K Factor values.
I | Project Area
K Factor
^H 0-0.1
| | 0.1 -0.14
| [0.14-0.2
| ] 0.2-0.3
0.3-0.47
Figure 28. K Factor Values for the Muddy-Virgin
Project Area.
Table 4. 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, higher erodibility
In the project area, potential soil erodibility ranged from 0.00-0.47, while the delineated sub-watersheds
have values between 0.13 and 0.23 (Figure 28). The areas with the highest erodibility are along the
Pahranagat and White Pine Rivers and around the Las Vegas Valley. The predominant soil types are
sandy loam with sand prevalent surrounding the Muddy and Virgin Rivers (Figure 29). For a list of the
user-defined classes, see Appendix 3.
33
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Surface Summary Soils
^^ Cobbly Clay Loam
| | Cobbly Sandy Loam
| | Cobbly Loam
| | Gravelly Loam
| | Gravelly Sandy Loam
| Sandy Loam
| | Silt Loam
| | Sand
^B Unweathered Bedrock
Variable
Figure 29. Map of Surface Layers in the Muddy-Virgin River Project Area.
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 Muddy-Virgin River Project Area, the P Factor for all delineated sub-
watersheds is 1.0.
34
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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 on 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,
which can result in a considerable increase in soil loss.
An LS value of 1.0 is equal to a 9% slope steepness for
a 22.1m (72.6 ft) 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. Values averages ranged from 0.94 to 6.49 in
the delineated sub-watersheds. Because of the detailed
resolution of the data, an entire basin map is not
appropriate. Figure 30 displays the Virgin Valley area
for LS values.
LS Factor
I 1 1 - 3.3
\ 3.3 -8.6
^| 3.6-15.9
M 15.9-27.6
n27.6- 140.2
No Data
Legend
82 - 1817
ISIS - 3191
3192 - 6446
6447 - 17374
17375 -310519
Quantile
Gross soil erosion, A value
(kg/ha/yr)
Figure 30. LS Factor for the Virgin Valley Area.
6.6 A Value
The A value computes the gross
soil erosion per unit area using
the formula: R*K*LS*C*P.
Values range depending on
rainfall, soil type, slope, and
conservation practices in the
specific locations. As seen in
Figure 31, overall values in the
west are lowest in Nevada and
North Dakota and highest along
the coast of California, Oregon
and Washington. In the Muddy-
Virgin Area, individual values
ranged from 281 kg/ha/y in the
Virgin River, (site 1190) to
2621 kg/ha/y (site 19).
Figure 31. A Values Throughout the West (EPA, 2010).
35
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36
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7.0 Ecological Indicators
The State of Nevada has established water quality standards for water quality criteria citing the 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. The State of Nevada water
quality standards are given in the Nevada Administrative Code (NAC) 445A. 11704 through 445A.2234.
(TableS).
Table 5. Water Quality Standards for Nevada.
Indicator
Dissolved Oxygen
pH
Total Phosphorous
Standards for Nevada
>5ฐ mg/L (non-trout waters)
>6ฐ 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.
7.1 Dissolved Oxygen
Dissolved oxygen (DO) is simply the amount of gaseous
oxygen dissolved in water and available for organisms'
respiration. Decreases in DO can be associated with inputs
of nitrogen and phosphorus (eutrophication), organic matter,
increased temperature, and a reduction in stream flow. DO
values ranged from 5.1 to 12.8 mg/L with a mean of
8.3 mg/L among samples as shown in Figure 32. Two sites,
in Meadow Valley Wash (285) and Paharanagat Creek
(875), had DO values that went below 6 mg/L, which
represents the lower limit determined suitable for trout by
Nevada State standards.
5.1 -6.4
6.4-7.5
7.5-8.4
8.4-10.1
10.1 -12.i
Figure 32. Dissolved Oxygen in the Muddy-
Virgin River Study Area.
37
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7.2pH
Another important water column variable, hydrogen ion
concentration (pH), is a numerical measure of the
concentration of the constituents that determine water acidity,
specifically hydrogen ion concentration. It is measured on a
logarithmic scale of 1.0 (acidic) to 14.0 (basic) with 7.0
signifying neutral. The pH of the MV Basin watersheds ranges
from 7.2 to 8.6 with a mean of 8.0 as indicated in Figure 33.
All samples were within the standards set for Nevada.
7.3 Total Phosphorus
Phosphorus (Figure 34) is often a limiting factor in growth
of aquatic vegetation as it is an essential nutrient for plant
and bacterial activity. Yet, an excess of phosphorus may
reduce habitat, disrupting ecological cycles and affecting
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 MV River Basin ranged from 0.01
to 0.43 mg/L with a mean of 0.06 mg/L. Three sites had TP
levels above the Nevada water quality standard of <0.1
mg/L. Two sites (669 and 1009) are located along the
agricultural corridor along the Muddy River adjacent to
Lake Mead. The other site (289) is located on the Virgin
River in Washington County, UT.
Figure 33. ph in the Muddy-Virgin River Study Area.
7.4 Total Nitrogen
Total Nitrogen, the sum of total kjeldahl nitrogen, nitrate and
nitrite, is an important nutrient input to streams as an essential
nutrient for plants and animals. Figure 35 shows the total
nitrogen in the Muddy-Virgin River Study Area. However,
substantial inputs (eutrophication) from anthropogenic sources
can result in increased algal growth which can upset the
ecological balance of the stream. Similarly, loss of nutrients from
human activities can also reduce stream productivity. Sources of
nitrogen can include agricultural processes, such as pesticides
and fertilizers, runoff from animal manure, and sewage. With the
proportion of land used for grazing and agriculture in the Muddy-
Virgin Project Area, manure deposition from cattle and fertilizer
runoff can add nutrients, to the streams. Values ranged from 0.09
to 4.02 mg/L with an average of 0.68 mg/L. Four sites had values
greater than 1.0. Two sites (19 and 289) were located in the
Virgin River, both in Washington County, UT. The Las Vegas
Wash, site 232, had the highest value of 4.0 mg/L. The last site is
located in the Meadow Valley Wash (site 215).
Figure 34. Total Phosphorus in the Muddy-Virgin River Study Area.
38
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7.5 Chloride
Chloride, present in all natural waters at low levels (Hem,
1985), is considered a good tracer because it is involved in few
reactions relative to other ions (Feth, 1981). Herlihy et al.
(1998) found chloride to be an indicator of human disturbance
in the Mid-Atlantic region of the United States. The worldwide
chloride mean concentration in rivers is 7.8 mg/L, with a range
from 1 to 280,000 mg/L (Hem, 1985). The national secondary
drinking water regulation standard for chloride is 250 mg/L.
While the variation in chloride concentrations in Nevada
streams appears large, with a range of 1 to 675 mg/L, care
should be taken to account for solute input from spring
sources. Eleven sites were greater than 250 mg/L, all located
on the Virgin River.
TN (mg/L)
0.09-0.37
8 0.37-0.67
o 0.67 -1.04
1.04-1.92
1.92-4.02
Figure 35. Total Nitrogen
in the Muddy-Virgin River
Study Area.
7.6 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. (Peck et
al., 2006). 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). In the delineated sub-watersheds values ranged
from 4 to 84 with an average of 47.8 (Figure 37). Although there is
no standard, higher values are indicative of more healthy systems.
Two sites, 669 and 720, had scores below 30. Exceedances for each
indicator are summarized in Table 5.
Figure 36. Chloride in the Muddy-Virgin River Study Area.
39
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Table 6. Indicator Exceedances.
Site
19
110
119
215
232
285
289
310
319
660
669
720
790
875
1009
1100
1190
DO (mg/L)
5.9
5.1
TP (mg/L)
0.43
0.20
0.16
TN (mg/L)
1 .0
1.9
4.0
3.3
Chloride (mg/L)
543
522
512
378
415
422
675
358
437
480
368
IBI
24
4
Figure 37. IBI in the Muddy-Virgin River
Study Area.
40
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8.0 Landscape and Water Relationships
8.1 Regression Models
In this highly modified, arid system, the inclusion of nested sites for analysis was unavoidable. Although
it is preferable to not include them, this area is unique and must be treated that way. For regression
models, we looked at the entire basin with all watersheds. Because virtually all sites were nested, analysis
was not able to be performed only on non-nested sites.
Riparian metrics were highly correlated to whole watershed metrics and were thus eliminated, except for
percent natural grassland (30m) and percent human use (30m) in the Muddy and Virgin River assessment.
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 2 R factor was eliminated also for its strong correlation with A value. Of
the remaining landscape metrics six variables (A Value, K Factor, percent natural grassland, (strmdens)
stream density, (rdlen) road length, (purb) percent urban and (pfor) percent forest) were used in the
stepwise multiple regression. Different predictors were significantly related to each of the water quality
metrics (Table 6). The amount of variability explained by models ranged from 36% to 62% (r2, Table 6).
Road length and road density are important factors in and around the populated areas of Las Vegas and
Mesquite, Nevada and St. George Utah. The Index of Biotic Integrity (IBI) and total phosphorus
remained low around all urban areas, Total nitrogen and total phosphorus had high values primarily
around the more populated and agricultural areas. The formula metric abbreviations can be found in Ebert
and Wade 2004.
Table 7. Multiple Regression Models "*" Denotes Log-Transformation.
Dependent
Variable
TN
TP
IBI
R2
0.623
0.367
0.378
Model
p-value
0.0000
0.0046
0.0005
Formula
p_lnTN=-5.315-0.0378*pfor-0.631*png+0.02*stmdens+0.0349*avalue+0.0381*k
factor
p_lnTP=0.235-0.362*png-0.162*purb-0.0454*strmdens+0.0176*rdlen
p_IBI=62.42+0.477*pfor-0.431 *a value
8.2 Model Application
Using the 2001 NLCD and averaged RUSLE 2 grids, estimates were made of potential IBI and water
quality indicators in the Muddy-Virgin River Project Area within each 12-Digit HUC. Predicted total
phosphorus had the higher values around the main Muddy and Virgin Rivers with the lowest values in the
upper reaches of the White River, the Las Vegas area and Meadow Valley Wash. Predicted total nitrogen
had very low values throughout the White River and Meadow Valley Wash systems as well as along the
Muddy and Virgin Rivers and Las Vegas Valley. Higher values were along the Pahranagat area and the
central portion of the project area. IBI values were highest in the Meadow Valley White and upper
reaches of the White River. Low values existed sporadically around the Las Vegas Valley and the Virgin
River. See Appendix 5 for the predicted model averages in each hydrologic unit.
41
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42
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9.0 Conclusion
Nevada has a basin and range physiography with a repeating pattern of fault block mountains and
intervening valleys. Valley ecoregions are predominantly shrub or shrub- and grass-covered. Mountains
may be brush-, woodland-, or pinion-juniper forested systems. The Muddy-Virgin River Project Area is in
the southern portion of Nevada, and encompasses approximately 32,000 square miles. The Muddy-Virgin
River Project Area is a part of the Colorado River system one of the largest and most important systems
in the lower 48 states. The Colorado River system is used by well over 40 million people in the western
United States and supplies much needed fresh water to the Las Vegas, Nevada area and highly populated
southern California. A large portion of the Muddy-Virgin River Project Area is sparsely populated with
two major land use types mining and agriculture (hay and cattle).
The Muddy-Virgin River Project Area, hydrologically, is fairly unique. The river trends north-south, and
gains most of its water from snowmelt in the alpine regions of the Basin and Range ecosystem (Spring,
Sheep, White Pine and Butte Mountains in the western part of the watershed, and Wilson Creek and Egan
Mountains in the east). Proposals have been made to pipe water from this area to the southern Nevada
area to supplement drinking water supplies. Agricultural activity in the valleys increases water
withdrawals for irrigation. Water into the river comes from seasonal snowmelt. 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 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 Muddy-Virgin River Project Area 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.
43
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Water quality in the Muddy-Virgin River Project Area had few cases of water quality standard
exceedances. Percent forest and natural grasslands, in addition to stream density and gross soil erosion are
the main contributors to potential water quality degradation, along with percent urban, road length and
soil erodibility. 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 38 and 39). For the final joined map, all affected watersheds were joined and then overlaid
(Figure 40). This shows the watersheds that have the most potential to be affected by the land cover/use
and sedimentation. Significant watersheds lie in the lower portion in the basin specifically around the Las
Vegas Valley and the Muddy and Virgin River head waters.
Road Length
F^ High Values
% Forest
[g
-------
Predicted IBI
| | Low Values
Predicted TN
giigil High Values
Predicted TP
| | High Values
Figure 39. Predicted Water Quality Indicators Extreme Values.
45
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Water Quality Indicators
fl^ Significant Values
Predictive Variables
| | Significant Values
Figure 40. Muddy-Virgin River Project Area Subwatersheds Having Landscape Metrics Associated with Water Quality
Degradation.
46
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References
Arizona Department of Water Resources (ADWR). (2009). Virgin River Basin.., 2009, from
http://www.azwater.gov/azdwr/StatewidePlanningAVaterAtlas/documents/Vol_6_VRG.pdf
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.
Center for Watershed Protection & USFS. (2008). Watershed forestry resource guide.
http://www.forestsforwatersheds.org/urban-watershed-forestry/
Clark County Nevada. (2000). Northeast Clark County 208 water quality management plan.
http://www.accessclarkcountv.com/depts/comprehensive_planning/compplanelements/Page
s/208water_chapter_l .aspx
Deacon, J. E., Williams, A. E., Williams, C. D., & Williams, J. E. (2007). Fueling population
growth in Las Vegas: How large-scale groundwater withdrawal could burn regional
biodiversity. BioScience, 57(8), 688.
Ebert, D. W., & Wade, T. G. (2004). Analytical tools interface for landscape assessments
(ATtlLA) user mawwa/USEPA/600/R-04/083.
Feth, L. H. (1981). Chloride in natural continental water-a review. Water Supply Paper 2176.
Washington, D.C.: U.S. Geological Survey.
Hare, L., Heggem D., Hall R., and Husby P. Ecological Condition of Streams in Northern
Nevada USEPA R-MAP Humboldt Basin Project. U.S. Environmental Protection Agency,
Washington, DC, USEPA/600/R-12/605, August, 2012.
Hare, L., Heggem D., Hall R., and Husby P. An Ecological Characterization and Landscape
Assessment of the Humboldt River Basin. U.S. Environmental Protection Agency,
Washington, DC, USEPA/600/R-13/006, January, 2013.
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 USEPA/600/R-
99/016.
47
-------
Herlihy, A. T., Stoddard, J. L., & Johnson, C. B. (1998). The relationship between stream
chemistry and watershed land cover data in the mid-Atlantic region. U.S. Water, Air and
Soil Pollution, 105, 377.
Herlihy, A.T., D.P. Larsen, S.G. Paulsen, N.S. Urquhart, and BJ. Rosenbaum. (2000) Designing
a spatially balanced, randomized site selection process for regional stream surveys: the
EMAP mid-Atlantic pilot study. Environ. Monit. Assess. 63:95-113
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 United 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.
Jones, K. B., A. C. Neale, M. S. Nash, R. D. Van Remortel, J. D. Wickham, K. H. Riitters, and
R. V. O'Neill. 2001. Predicting nutrient and sediment loadings to streams from landscape
metrics: a multiple watershed study from the United States Mid-Atlantic
Region. Landscape Ecology, 16:301-312.
Julien, P. Y. (1998). Erosion and sedimentation. Cambridge, United Kingdom: Cambridge
University Press.
Las Vegas Wash Coordination Committee. (2010). Las Vegas Wash., 2010, from
http ://www.lvwash. org/html/index.html
Mac, M. J., Opler, P. A., Puckett Haecker, C. E., & Doran, P. D. (1998). Status and trends of the
nation's biological resources. Reston, VA: U.S. Department of the Interior, U.S. Geological
Survey.
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 USEPA/600/R-01/075.
Nevada Department of Agriculture. (2009). Nevada and its agriculture.
http: //agri. nv. gov/AglnNevada. htm
Nevada Legislative Counsel. (2010). Chapter 445A- water controls.
http://www.leg.state.nv.us/nac/NAC-445A.html
Peck, D.V., Herlihy, A.T., Hill, B.H., Hughes, R.M., Kaufmann, P.R., Klemm, D.J., Lazorchak,
J.M., McCormick, F.H., Peterson, S.A., Ringold, P.L., Magee, T., and Cappaert, M.,. 2006.
Environmental Monitoring and Assessment Program-Surf ace Waters Western Pilot Study:
48
-------
Field Operations Manual for Wadeable Streams. EPA/620/R-06/003. U.S. Environmental
Protection Agency, Office of Research and Development, Washington, D.C.
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 2) 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.
Schlyer, K. (2007). Gambling on the water table: The high-stakes implications of the Las Vegas
pipeline for plants, animals, places and people. Washington D.C.: Defenders of Wildlife;
Great Basin Water Network.
Suckling, K., Hogan, D., & Silver, R. D. (1992). In Biodiversity Legal Foundation, Friends of
the Owls and Forest Guardians(Eds.), Petition to list the southwest willow flycatcher
empidonax trailii extimus as a federally endangered species
Smith, M.A. (1986). Impacts of feral horses grazing on rangelands: an overview. Journal of
Equine Veterinary Science, 6 (5) 236.
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.
Thompson, & West. (1958). History of Nevada 1881. Berkley, CA: Howell-North.
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.
University of Utah. (2001). Geothermal energy: Clean sustainable energy for the benefit of
humanity and the environment.., 2011, from http://www.geothermal.org/GeoEnergy.pdf
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. Bureau of Land Management. (2009). Nevada wild horses & burros herd management
areas (HMAs).http://www.blm.gov/nv/st/en/prog/wh_b/herd_management_areas.html
U.S. Department of Agriculture. Agricultural Research Service. (2010). Revised universal soil
loss equation 2:overview of RUSLE 2.
49
-------
http://www.ars.usda.gov/Research/docs. htm? docid=6010
U.S. Department of Agriculture, U.S. Forest Service, Intermountain Region, Humboldt-Toiyabe
National Forest, & Santa Rosa Ranger District. (2009). Martin basin rangelandproject
final environmental impact statement
U.S. Department of Agriculture, Natural Resources Conservation Service. (2010). Plants
database. 2010, from http://plants.usda.gov/
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. USEPA 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. (1998). Recovery plan for the aquatic and riparian species of the
pahranagat valley. Portland, OR:
U.S. Fish and Wildlife. (2010). National wetlands inventory.2010, from
http://www.fws.gov/wetlands/Data/WetlandCodes.html
Van Remortel, R. D., Maichle, R. W., Heggem, D. T., & Pitchford, A. M. (2005). Automated
GIS watershed analysis tools for RUSLE 2/SEDMOD soil erosion and sedimentation
modeling. USEPA/600/X-05/007.
Washington County Water Conservation District. (2006). Virgin River water shed management
plan.
Young, J. A., & Sparks, A. (2002). Cattle in the cold desert. Reno, Nevada: University of
Nevada Press.
50
-------
Data
Bureau of Land Management. (2009). DownloadGeospatial Data: Nevada.., 2010,
http://www.blm.gov/nv/st/en/prog/more_programs/geographic sciences/gis/geospatial dat
a.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.2010, 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 Shape/ties., 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, Mineral Resource Data System, 2005.
http://mrdata.usgs.gov/
U.S. Geological Survey. (2009). Water Resources of the United States: Hydrologic Unit Maps.
2010, from http://water.usgs.gov/GIS/huc.html
51
-------
52
-------
Programs
U.S. Department of Agriculture, Agricultural Research Service. (2010). Revised Universal Soil
Loss Equation (RUSLE 2). 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/nerlesd 1/land-sci/attila/index.htm
53
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54
-------
Appendices
Appendix 1. List of Sites.
Site
8
10
19
95
110
119
128
144
170
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
Stream Order
3
4
5
5
5
5
3
1
5
3
3
5
5
4
3
3
5
5
3
5
5
3
4
3
4
5
4
5
5
3
4
3
5
5
5
3
3
Stream Name
Meadow Valley Wash
White River
Virgin River
Meadow Valley Wash
Virgin River
Virgin River
Flatnose Wash
Unnamed
Muddy River
Las Vegas Wash
Pahranagat River
Meadow Valley Wash
Meadow Valley Wash
Las Vegas Wash
Beaver Dam Wash
Muddy River
Meadow Valley Wash
Virgin River
Meadow Valley Wash
Virgin River
Virgin River
Meadow Valley Wash
Muddy River
Muddy River
Muddy River
Virgin River
Muddy River
Virgin River
Virgin River
Pahranagat River
Muddy River
Muddy River
Virgin River
Virgin River
Muddy River
Muddy River
Muddy River
Longitude
-114.3552778
-115.1608333
-113.9191667
-114.5672222
-114.2283333
-114.2675
-114.102778
-115.144444
-114.52881
-115.041944
-115.191944
-114.664444
-114.510278
-115.036111
-114.058056
-114.666944
-114.57416
-113.681944
-114.346667
-114.033889
-113.928056
-114.332778
-114.496389
-114.687222
-114.551389
-114.073611
-114.417222
-114.171667
-114.219444
-115.134444
-114.468333
-114.708889
-114.129722
-114.084167
-114.566944
114.598056
-114.626111
Latitude
37.834167
38.9325
36.919167
37.436944
36.723889
36.689444
37.919167
38.379444
36.641667
36.148333
37.439444
36.869444
37.086944
36.134137
37.49222
36.673889
37.551389
37.013056
37.841667
36.801667
36.883056
37.853333
36.620556
36.704444
36.650833
36.795556
36.526389
36.756111
36.734167
37.314722
36.582222
36.714444
36.782778
36.791667
36.661944
36.655556
36.654167
55
-------
Appendix 2. Ecoregions and Relating Physiography and Vegetation (USEPA, 2007).
Level III Ecoregion
14
22
Mojave Basin and
Range
Arizona/New Mexico
Plateau
Level IV Ecoregion
13b
13c
13d
13e
13g
13p
13q
13u
13v
13w
14a
14b
14c
14d
14e
14f
22d
Shadscale-Dominated
Saline Basin
Sagebrush Basins and
Slopes
Woodland- and Shrub-
Covered Low
Mountains
High Elevation
Carbonate Mountains
Wetlands
Carbonate Sagebrush
Valleys
Carbonate Woodland
Zone
Tonopah Basin
Tonopah Sagebrush
Foothills
Tonopah Uplands
Creosote Bush-
Dominated Basins
Arid Footslopes
Mojave Mountain
Wood- and Shrubland
Mojave High Elevation
Mountains
Arid Valleys and
Canyonlands
Mojave Playas
Middle Elevation
Mountains
Physiography and Vegetation
Composed of broad basins and scattered mountains that generally low, warm and dry. It has a creosote
bush-dominated shrub community.
High plateau cut by canyons and punctuated by mountains, mesas and buttes. It's transitional between
higher, forested, mountainous ecoregions and arid shrublands.
Physiography
Mostly gently sloping to nearly flat valleys and
scattered sand dunes. Drained by a few small
streams.
Valleys and low hills drained by a few streams.
Low mountain ranges, foothills, and alluvial fans.
Streams are fed by snow-melt and springs.
Partially glaciated, high, mountains. Headwaters
for several streams fed by snow-melt and cold
springs.
Flat terrain with saline or freshwater wetlands.
Nearly flat to gently sloping basins.
Moderate sloping mountains and ridges with
many springs occurring.
Rolling valleys containing scattered hills, sand
dunes, and hot springs.
Foothills and low mountains. Ephemeral washes
are common. Surface water comes from springs.
Mountains and hills drained by ephemeral
washes.
Valleys containing floodplains, isolated hills, and
eroded washes. Alkaline warm streams and rivers
occur.
Alluvial fans and low mountains drained by
ephemeral streams.
Mid-elevation mountain slopes drained by
ephemeral streams, springs, and washes.
Unglaciated, rugged, isolated, high elevation
mountains. Water is primarily from snow-melt.
Arid canyons, terraces, and floodplains in the
Colorado River corridor.
Alluvial flats, muddy lake plains, and sand dunes.
Saline lakes occur.
Rugged mountains, steep ridges, mesas, buttes,
and canyons.
Vegetation
Mostly saltbrush-greasewood and Great Basin
sagebrush community with stands of juniper.
Great Basin sagebrush community along with
scattered, invading Utah juniper.
Mostly juniper-pinyon woodland with Joshua trees.
Sagebrush dominates the understory.
Spruce-fir pine forest communities with Mountain
brush species and grasses. Areas of alpine meadows
or tundra.
Tule marshes Non-native tamarisk tree becoming
common.
Great Basin sagebrush community. Understory is
composed of grasses.
Mostly juniper-pinyon woodland and some Great
Basin sagebrush community.
Great Basin sagebrush community with Mojave
Desert plants becoming common.
Great Basin sagebrush community with Mojave
Desert plants becoming common and include yucca
species
Juniper-pinyon woodland, sagebrush and chaparral.
Mostly creosote bush. Some areas are barren of
vegetation.
Mix of Mojavean shrubs and succulents as well as
cacti.
Juniper-pinyon woodland.
Great Basin pine forest. Small aspen groves occur.
Creosote bush and occasional Sonoran species with
native riparian plants.
Mostly barren with scattered creosote bush and other
salt-tolerant plants.
Chaparral and juniper-pinyon woodland. Sagebrush
in understory.
56
-------
Appendix 3. Muddy-Virgin Project Area Delineated Sub-watershed Names
with Numbers Corresponding to Figure 12.
8 Meadow Valley
10 White River
19 Virgin River
95 Meadow Valley Wash
11 Virgin River
11 Virgin River
12 Flatnose Wash
14 Kirch WM A
17 Muddy River
17 Las Vegas Wash
18 Pahranagat Creek
20 Meadow Valley
21 Meadow Valley
23 Las Vegas Wash
25 Beaver Dam
27 Muddy River
28 Meadow Valley Wash
28 Virgin River
298 Meadow Valley
310 Virgin River
319 Virgin River
368 Meadow Valley
469 Muddy River
519 Muddy River
530 Muddy River
660 Virgin River
669 Virgin River
720 Virgin River
790 Virgin River
875 Pahranagat Valley
1009 Muddy River
1069 Muddy River
1100 Virgin River
1190 Virgin River
1260 Muddy River
1300 Muddy River
1310 Muddy River
57
-------
Appendix 4. Descriptive Statistics for HUCs and Delineated Sub-Watersheds.
% Forest
% Agriculture
% Shrubland
% Natural Grassland
% Urban Areas
% 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
% Stream Length Adjacent to Urban 30m
% Stream Length Adjacent to Wetlands 30m
% Stream Length Adjacent to Barren 30m
% 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
% Stream Length Adjacent to Urban 30m
% Stream Length Adjacent to Wetlands 90m
% Stream Length Adjacent to Barren 90m
HUCs
Mean
19.5
0.4
75.0
1.5
2.0
0.3
1.2
1.0
0.7
0.4
44.3
16.6
0.8
76.6
1.5
2.9
2.1
1.2
1.3
16.8
0.7
76.6
1.5
2.9
2.1
0.9
1.3
Min.
0.0
0.0
6.1
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
11.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
9.4
0.0
0.0
0.0
0.0
0.0
Max.
88.4
12.4
99.9
19.3
84.5
6.4
73.2
2.1
9.4
4.6
652.0
87.0
17.0
100.0
19.6
79.5
79.5
40.4
69.9
87.1
15.6
100.0
21.6
78.9
78.9
36.5
70.9
Delineated Sub-Watersheds
Mean
28.3
1.0
67.5
1.5
0.8
0.3
0.7
1.0
0.6
0.4
2554.2
24.0
0.9
70.6
1.4
2.2
1.3
1.1
0.8
24.5
0.8
70.5
1.5
2.1
1.3
0.7
0.8
Min.
0.0
0.0
1.4
0.1
0.0
0.0
0.0
0.6
0.3
0.0
5.0
0.3
0.0
1.3
0.0
0.0
0.0
0.0
0.0
0.1
0.0
1.5
0.0
0.0
0.0
0.0
0.0
Max.
97.8
1.7
97.4
5.0
11.2
0.7
7.3
1.3
1.7
0.9
6681.0
98.7
2.5
95.0
4.7
11.1
11.1
4.0
8.3
99.0
2.2
96.1
4.8
11.2
11.2
2.1
8.3
58
-------
Appendix 5. Land Cover/Use for the Muddy-Virgin Project Area Delineated Sub-Watersheds.
SITE
8
10
19
95
110
119
128
144
170
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
8HUC
Meadow Valley
White River
Lower Virgin
Meadow Valley
Lower Virgin
Lower Virgin
Meadow Valley
White River
Muddy River
Las Vegas Wash
White River
Meadow Valley
Meadow Valley
Las Vegas Wash
Lower Virgin
Muddy River
Meadow Valley
Lower Virgin
Meadow Valley
Lower Virgin
Lower Virgin
Meadow Valley
Muddy River
Muddy River
Muddy River
Lower Virgin
Muddy River
Lower Virgin
Lower Virgin
White River
Muddy River
Muddy River
Lower Virgin
Lower Virgin
Muddy River
Muddy River
Muddy River
PFOR
49.93
58.06
16.17
45.92
17.25
17.03
97.76
29.09
20.88
9.57
18.86
37.83
42.92
9.57
81.96
14.62
45.22
3.62
59.19
22.81
26.01
59.40
20.86
14.69
21.06
22.20
20.40
21.47
17.15
18.24
20.55
14.74
21.92
0.03
21.07
12.81
14.56
PWETL
0.09
0.18
0.30
0.11
0.37
0.39
0.00
0.48
0.22
0.01
0.37
0.13
0.13
0.01
0.72
0.30
0.10
0.67
0.16
0.35
0.29
0.16
0.22
0.30
0.22
0.40
0.22
0.46
0.37
0.39
0.22
0.30
0.43
0.22
0.22
0.26
0.30
PSHRB
48.26
39.60
80.48
51.66
79.16
79.35
1.43
63.62
75.72
69.53
76.25
60.17
54.89
69.53
16.85
81.30
52.36
90.28
38.62
74.35
71.16
38.43
75.74
81.29
75.53
74.73
76.06
75.08
79.25
76.87
75.97
81.27
74.73
97.38
75.52
83.05
81.29
PNG
0.53
1.19
1.37
0.73
1.92
1.90
0.81
5.02
1.53
0.70
3.16
0.64
0.68
0.70
0.23
2.35
0.72
2.15
0.79
1.40
1.49
0.79
1.53
2.36
1.54
1.37
1.52
1.36
1.94
3.05
1.52
2.36
1.36
0.08
1.54
2.08
2.35
PNBAR
0.01
0.04
0.44
0.11
0.32
0.33
0.00
0.17
0.55
7.27
0.12
0.11
0.10
7.27
0.04
0.35
0.09
0.91
0.01
0.30
0.29
0.01
0.55
0.30
0.55
0.33
0.63
0.37
0.32
0.12
0.61
0.27
0.37
1.03
0.55
0.71
0.41
U_INDEX
1.17
0.93
1.24
1.49
0.99
1.00
0.00
1.61
1.10
12.92
1.24
1.13
1.28
12.92
0.19
1.08
1.50
2.37
1.22
0.79
0.76
1.22
1.10
1.07
1.10
0.97
1.17
1.26
0.98
1.33
1.13
1.07
1.19
1.26
1.10
1.09
1.10
PURE
0.04
0.37
0.39
0.06
0.28
0.27
0.00
0.07
0.14
11.20
0.09
0.05
0.05
11.20
0.00
0.17
0.06
1.10
0.00
0.19
0.22
0.00
0.14
0.17
0.14
0.29
0.16
0.37
0.28
0.14
0.14
0.17
0.37
0.00
0.14
0.18
0.17
PACT
1.13
0.56
0.85
1.43
0.72
0.73
0.00
1.54
0.96
1.72
1.14
1.08
1.22
1.72
0.19
0.91
1.44
1.27
1.22
0.60
0.55
1.22
0.96
0.90
0.97
0.69
1.01
0.89
0.70
1.19
0.98
0.90
0.82
1.26
0.96
0.91
0.92
59
-------
Appendix 6. Land Cover/Use for the Muddy-Virgin Project Area Delineated Sub-Watersheds.
SITE
8
10
19
95
110
119
128
144
170
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
8HUC
Meadow Valley
White River
Lower Virgin
Meadow Valley
Lower Virgin
Lower Virgin
Meadow Valley
White River
Muddy River
Las Vegas Wash
White River
Meadow Valley
Meadow Valley
Las Vegas Wash
Lower Virgin
Muddy River
Meadow Valley
Lower Virgin
Meadow Valley
Lower Virgin
Lower Virgin
Meadow Valley
Muddy River
Muddy River
Muddy River
Lower Virgin
Muddy River
Lower Virgin
Lower Virgin
White River
Muddy River
Muddy River
Lower Virgin
Lower Virgin
Muddy River
Muddy River
Muddy River
STRMLEN
2423582.45
154254.26
963092.24
5467628.76
5078681.81
5108970.88
19012.80
2875639.82
19945181.29
2804311.55
6451375.61
7708335.44
6669238.81
2804311.55
181845.06
10550809.85
5259143.31
325265.53
1371029.21
3338545.70
2944031.44
1365764.74
19961936.98
10517029.17
19770074.23
3410490.52
20236558.31
3548231.35
5041513.52
6730211.43
20169052.84
10489332.67
3491383.50
6126.66
19764997.25
11535511.97
10580534.40
STRMDENS
1.05
0.63
0.80
1.22
1.04
1.03
1.19
0.88
1.09
0.76
0.99
1.25
1.24
0.76
1.33
1.05
1.23
0.69
1.12
1.02
1.07
1.12
1.09
1.05
1.09
1.01
1.08
0.99
1.04
0.99
1.09
1.05
1.00
0.89
1.09
1.01
1.05
RDLEN
1436426.08
141920.55
811744.44
2788137.74
2879902.69
2903409.33
4778.43
2426968.04
8905463.28
6352202.27
4018447.83
3082822.70
2994234.90
6352202.27
66983.22
5008062.92
2753535.75
376314.41
513583.03
1947207.50
1659301.98
511837.66
8916381.06
4969386.48
8869144.96
2058240.76
9239756.83
2281478.88
2845065.70
4197681.15
9085934.73
4963822.39
2214627.97
10166.14
8864217.07
5629347.18
5033252.21
RDDENS
0.62
0.58
0.67
0.62
0.59
0.59
0.30
0.74
0.49
1.73
0.62
0.50
0.56
1.73
0.49
0.50
0.64
0.79
0.42
0.59
0.60
0.42
0.49
0.50
0.49
0.61
0.49
0.64
0.59
0.62
0.49
0.50
0.63
1.48
0.49
0.49
0.50
STXRD
0.38
0.36
0.47
0.40
0.38
0.38
0.26
0.54
0.33
0.88
0.43
0.33
0.36
0.88
0.38
0.35
0.40
0.64
0.26
0.39
0.40
0.26
0.33
0.35
0.33
0.40
0.33
0.41
0.38
0.43
0.33
0.35
0.41
0.82
0.33
0.34
0.35
STXRD CNT
921
55
449
2169
1913
1917
5
1560
6567
2476
2759
2523
2432
2476
70
3675
2113
207
361
1318
1186
361
6574
3668
6539
1358
6681
1446
1904
2904
6647
3664
1432
5
6537
3953
3682
60
-------
Appendix 7. Land Cover/Use for the
Delineated Sub-Watershed
Muddy-Virgin Project Area
Riparian Buffers.
SITE
8
10
19
95
110
119
128
144
170
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
RFOR30
42.04
44.10
13.69
37.71
15.74
15.64
98.75
21.17
17.34
8.47
13.37
30.97
35.60
8.47
72.28
10.24
36.87
2.65
50.32
20.82
23.29
50.52
17.33
10.28
17.50
20.44
17.09
19.93
15.64
12.92
17.15
10.31
20.23
0.26
17.50
9.40
10.22
RWETL30
0.25
1.40
1.63
0.34
1.62
1.69
0.00
1.82
0.74
0.02
1.25
0.45
0.45
0.02
4.03
0.98
0.32
2.79
0.42
1.61
1.36
0.42
0.76
0.98
0.74
1.83
0.76
2.15
1.61
1.31
0.75
0.98
2.01
2.11
0.74
0.91
0.99
RSHRB30
55.21
53.66
81.09
58.66
78.55
78.56
1.25
69.47
78.52
71.43
80.89
66.01
61.08
71.43
22.65
84.83
59.53
88.81
46.12
74.65
72.45
45.92
78.51
84.83
78.35
74.64
78.67
74.33
78.65
81.15
78.65
84.87
74.33
94.99
78.35
85.70
84.79
RNG30
0.32
0.08
1.16
0.63
2.72
2.72
0.00
4.66
1.22
0.75
2.48
0.58
0.58
0.75
0.35
1.83
0.63
1.92
0.37
1.66
1.70
0.37
1.22
1.81
1.23
1.65
1.23
1.81
2.74
2.39
1.22
1.81
1.75
0.00
1.23
1.69
1.82
RNBAR30
0.00
0.00
0.34
0.03
0.31
0.31
0.00
0.24
0.45
8.27
0.12
0.03
0.03
8.27
0.01
0.44
0.03
0.74
0.01
0.29
0.23
0.01
0.45
0.43
0.45
0.32
0.49
0.36
0.31
0.13
0.49
0.39
0.34
2.64
0.45
0.66
0.49
RHUM30
2.18
0.76
2.08
2.62
1.06
1.08
0.00
2.63
1.73
11.06
1.89
1.96
2.26
11.06
0.68
1.69
2.62
3.09
2.76
0.96
0.96
2.76
1.73
1.67
1.74
1.13
1.75
1.41
1.05
2.10
1.74
1.65
1.34
0.00
1.74
1.65
1.70
RURB30
0.45
0.54
2.05
0.72
0.72
0.72
0.00
0.66
0.63
11.06
0.62
0.56
0.65
11.06
0.00
0.67
0.68
2.98
0.23
0.71
0.71
0.23
0.63
0.67
0.63
0.87
0.64
0.97
0.72
0.70
0.64
0.66
0.97
0.00
0.63
0.70
0.67
RAGT30
1.73
0.21
0.04
1.90
0.34
0.36
0.00
1.97
1.10
0.00
1.28
1.40
1.61
0.00
0.68
1.02
1.93
0.11
2.53
0.25
0.25
2.53
1.10
1.01
1.11
0.26
1.11
0.45
0.33
1.40
1.10
0.99
0.36
0.00
1.11
0.95
1.03
61
-------
Appendix 8. Land Cover/Use for the
Delineated Sub-Watershed
Muddy-Virgin Project Area
Riparian Buffers.
SITE
8
10
19
95
110
119
128
144
170
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
RFOR90
43.51
45.48
13.77
39.08
15.84
15.74
99.00
21.77
17.72
8.26
13.58
31.87
36.66
8.26
74.70
10.40
38.29
2.90
52.34
20.92
23.41
52.54
17.71
10.43
17.88
20.54
17.46
20.06
15.74
13.12
17.52
10.46
20.35
0.12
17.88
9.52
10.37
RWETL90
0.18
0.86
1.02
0.22
1.07
1.13
0.00
1.33
0.52
0.01
0.92
0.28
0.28
0.01
2.05
0.72
0.20
1.95
0.30
1.04
0.83
0.30
0.53
0.72
0.52
1.18
0.54
1.41
1.07
0.97
0.53
0.72
1.30
0.96
0.52
0.67
0.72
RSHRB90
53.90
52.38
81.37
57.48
79.03
79.05
1.00
69.47
78.40
71.47
81.00
65.35
60.25
71.47
22.36
84.93
58.30
89.12
44.40
75.17
72.85
44.20
78.40
84.94
78.22
75.22
78.56
75.01
79.13
81.29
78.54
84.96
74.97
96.14
78.22
85.83
84.90
RNG90
0.40
0.20
1.30
0.70
2.71
2.70
0.00
4.76
1.29
0.79
2.64
0.61
0.64
0.79
0.43
1.94
0.69
2.16
0.53
1.66
1.71
0.53
1.29
1.93
1.30
1.65
1.29
1.77
2.73
2.55
1.29
1.93
1.72
0.12
1.30
1.79
1.94
RNBAR90
0.01
0.00
0.35
0.07
0.25
0.25
0.00
0.24
0.45
8.28
0.13
0.07
0.07
8.28
0.01
0.42
0.06
0.72
0.00
0.22
0.19
0.00
0.45
0.41
0.45
0.24
0.49
0.28
0.25
0.13
0.49
0.37
0.27
2.65
0.45
0.64
0.47
RHUM90
2.00
1.08
2.19
2.45
1.10
1.12
0.00
2.44
1.62
11.20
1.73
1.81
2.09
11.20
0.45
1.59
2.45
3.15
2.42
1.00
1.01
2.43
1.62
1.57
1.63
1.17
1.65
1.47
1.08
1.93
1.64
1.55
1.39
0.00
1.62
1.55
1.60
RURB90
0.46
0.59
2.15
0.73
0.73
0.73
0.00
0.66
0.62
11.20
0.60
0.55
0.64
11.20
0.00
0.66
0.70
3.03
0.19
0.74
0.77
0.19
0.62
0.66
0.62
0.88
0.64
1.00
0.73
0.67
0.63
0.66
1.00
0.00
0.62
0.69
0.66
RAGT90
1.54
0.49
0.04
1.72
0.36
0.39
0.00
1.78
1.00
0.00
1.14
1.26
1.45
0.00
0.45
0.92
1.75
0.12
2.23
0.26
0.25
2.24
1.00
0.91
1.01
0.28
1.02
0.47
0.35
1.26
1.00
0.90
0.39
0.00
1.00
0.86
0.93
62
-------
Appendix 9. RUSLE 2 Variables.
Site
8
10
19
95
110
119
128
144
170
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
A Value
1462
1927
2621
1502
1916
1901
2204
1463
1563
2032
1440
1657
1619
2032
2108
1555
1432
1834
1811
2160
2287
1807
1564
1548
1565
2110
1548
2048
1925
1425
1553
1561
2079
281
1565
1523
1526
R Factor
22
16
14
20
15
15
26
13
14
13
13
18
20
13
28
12
20
11
23
16
17
23
14
12
14
16
14
15
16
13
14
13
16
9
14
12
12
K Factor
0.18
0.19
0.15
0.17
0.13
0.14
0.14
0.23
0.17
0.15
0.21
0.16
0.16
0.15
0.16
0.19
0.17
0.21
0.17
0.13
0.13
0.17
0.17
0.19
0.17
0.14
0.17
0.14
0.13
0.19
0.17
0.19
0.14
0.14
0.17
0.18
0.19
LS Factor
3.20
4.22
6.28
3.41
4.66
4.64
6.49
3.50
3.87
4.20
3.34
4.02
3.90
4.20
4.83
3.96
3.14
3.59
3.91
5.39
5.63
3.91
3.87
3.96
3.88
5.28
3.83
5.21
4.72
3.28
3.84
3.98
5.24
0.94
3.88
3.84
3.93
C Factor
0.069
0.064
0.092
0.072
0.091
0.091
0.041
0.081
0.091
0.147
0.087
0.077
0.074
0.147
0.051
0.092
0.072
0.102
0.063
0.087
0.085
0.063
0.091
0.093
0.091
0.088
0.092
0.090
0.090
0.094
0.092
0.092
0.089
0.108
0.091
0.097
0.097
P Factor
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
63
-------
Appendix 10. Descriptive Water Quality and
IBI Statistics in the Muddy-Virgin Project Area.
Site
8
10
19
95
110
119
128
144
170
173
185
207
215
232
258
270
285
289
298
310
319
368
469
519
530
660
669
720
790
875
1009
1069
1100
1190
1260
1300
1310
DO
6.9
8.8
12.8
11.6
8.9
8.3
6.4
10.1
7.1
9.2
6.6
9.3
6.3
12.8
7.4
7.7
5.9
9.1
7.8
9.0
8.9
8.6
8.4
7.5
7.1
11.4
7.4
8.9
7.5
5.1
8.3
6.7
8.6
9.3
7.3
7.6
7.8
pH
8.21
8.05
7.35
8.62
8.05
8.03
7.82
8.15
8.22
8.00
8.08
8.26
7.84
8.23
7.75
8.25
7.72
8.49
8.30
8.04
7.82
8.19
8.44
8.03
8.21
7.73
7.57
8.02
7.90
7.63
7.18
7.94
7.90
7.93
8.44
8.20
8.34
TP
0.043
0.017
0.045
0.018
0.021
0.025
0.010
0.021
0.088
0.064
0.010
0.012
0.027
0.010
0.010
0.024
0.074
0.426
0.051
0.027
0.027
0.019
0.065
0.023
0.088
0.037
0.204
0.054
0.052
0.010
0.164
0.026
0.053
0.030
0.067
0.071
0.043
TN
0.191
0.142
1.041
0.358
0.487
0.441
0.203
0.089
0.630
0.723
0.238
0.858
1.916
4.024
0.251
0.530
0.257
3.280
0.238
0.446
0.704
0.258
0.636
0.576
0.674
0.563
0.708
0.374
0.503
0.303
0.897
0.461
0.364
0.250
0.531
0.538
0.337
Cl
1.0
6.9
543.0
18.9
522.0
512.0
5.7
6.7
87.3
41.4
4.8
61.8
36.2
151.6
8.9
46.7
53.5
378.0
1.0
415.0
422.0
1.0
54.2
48.2
82.4
675.0
228.6
358.0
437.0
8.7
162.3
58.3
480.0
368.0
72.7
90.7
65.9
IBI
74
74
22
66
32
46
84
62
62
46
30
52
24
54
52
58
34
64
38
36
44
38
68
42
40
24
4
56
40
34
64
58
48
58
46
64
-------
Appendix 11. Indicators Summary Statistics.
Indicator
Dissolved Oxygen
PH
Total Phosphorous
Total Nitrogen
Chloride
Sulfate
IBI
Units
mg/L
pH units
mg/L
mg/L
mg/L
mg/L
Unitless
Mean
8.33
8.03
0.06
0.68
173.08
498.56
48.69
Median
8.30
8.04
0.03
0.49
65.93
245.12
46.65
Min
5.10
7.18
0.01
0.09
1.00
1.00
6.66
Max
12.80
8.62
0.43
4.02
675.00
1854.00
86.63
Appendix 12. User-Defined Summary of Surface Layers in the Muddy-Virgin Project Area.
Summary Soils
Cobbly Sandy Loam
Cobbly Clay Loam
Cobbly Loam
Gravelly Loam
Gravelly Sandy Loam
Loam
Sand
Sandy Loam
Silt Loam
Unweathered Bedrock
Unknown
Variable
Soil Groups
Very Cobbly Sandy Loam
Very Cobbly Clay Loam
Extremely Cobbly Loam
Very Gravelly Loam
Gravelly Loam
Gravelly Fine Sandy Loam
Very Gravelly Fine Sandy Loam
Extremely Gravelly Fine Sandy Loam
Gravelly Sandy Loam
Very Gravelly Sandy Loam
Loam
Very Channery Loam
Very Gravelly Sandy Clay Loam
Fine Sand
Loamy Fine Sand
Loamy Sand
Very Gravelly Loamy Sand
Loamy Coarse Sand
Fine Sandy Loam
Extremely Stony Sandy Loam
Very Fine Sandy Loam
Silt Loam
Unweathered Bedrock
Unknown
Variable
65
-------
66
-------
Appendix 13. Predicted Models
67
-------
Predicted TP (mg/L)
0 - 0.05
0.05-0.12
0.12-0.22
0.22 - 0.35
0.35 - 0.57
Figure 41. Predicted Total Phosphorus Values.
68
-------
Predicted TN (mg/L)
0-0.04
0.04-0.11
0.11 -0.23
0.23 - 0.44
0.44-1.07
Figure 42. Predicted Total Nitrogen Values.
69
-------
Predicted IBI (mg/L)
35-48
48-57
57-64
64-76
76-98
Figure 43. Predicted IBI Values.
70
-------
-------
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