U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2013–5015

Prepared in cooperation with (in alphabetical order) Antero Resources, Bureau of Land Management, Bureau 

of Reclamation, Chevron Corporation, City of Grand Junction and City of Rifle, Colo., Colorado Department of 

Agriculture, Colorado Department of Natural Resources, Colorado Department of Public Health and Environment, 

Colorado Division of Wildlife–River Watch, Colorado Oil and Gas Conservation Commission, Colorado River 

Water Conservation District, Delta County, Colo., EnCana Oil & Gas (USA) Inc., Garfield County, Colo., Gunnison 

Energy Corp., National Park Service, Natural Soda, Inc., North Fork River Improvement Association, Oxy Petroleum 

Corporation, Petroleum Development Corp., Rio Blanco County, Shell Oil Company, Solvay Chemicals, Towns 

of Carbondale, De Beque, Palisade, Parachute, Rangely, and Silt, Colo., U.S. Forest Service, West Divide Water 

Conservancy District, and Williams Companies, Inc.

Characterization and Data-Gap Analysis of Surface-Water 

Quality in the Piceance Study Area, Western Colorado, 

1959–2009
Characterization and Data-Gap 

Analysis of Surface-Water Quality in the 

Piceance Study Area, Western Colorado, 

1959–2009

By Judith C. Thomas, Jennifer L. Moore, Keelin R. Schaffrath, Jean A. Dupree, 

Cory A. Williams, and Kenneth J. Leib

Prepared in cooperation with (in alphabetical order) Antero Resources, Bureau of Land 

Management, Bureau of Reclamation, Chevron Corporation, City of Grand Junction and 

City of Rifle, Colo., Colorado Department of Agriculture, Colorado Department of Natural 

Resources, Colorado Department of Public Health and Environment, Colorado Division 

of Wildlife–River Watch, Colorado Oil and Gas Conservation Commission, Colorado 

River Water Conservation District, Delta County, Colo., EnCana Oil & Gas (USA) Inc., 

Garfield County, Colo., Gunnison Energy Corp., National Park Service, Natural Soda, 

Inc., North Fork River Improvement Association, Oxy Petroleum Corporation, Petroleum 

Development Corp., Rio Blanco County, Shell Oil Company, Solvay Chemicals, Towns of 

Carbondale, De Beque, Palisade, Parachute, Rangely, and Silt, Colo., U.S. Forest Service, 

West Divide Water Conservancy District, and Williams Companies, Inc.

Scientific Investigations Report 2013–5015

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod

To order this and other USGS information products, visit http://store.usgs.gov

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Thomas, J.C., Moore, J.L., Schaffrath, K.R., Dupree, J.A., Williams, C.A., and Leib, K.J., 2013, Characterization and 

data-gap analysis of surface-water quality data in the Piceance study area, western Colorado, 1959–2009: U.S. Geological Survey Scientific Investigations Report 2013–5015, 74 p.
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................2

Purpose and Scope ..............................................................................................................................2

Description of the Study Basin Areas ...............................................................................................2

White River Basin ........................................................................................................................4

Colorado River Basin...................................................................................................................4

Lower Gunnison River Basin......................................................................................................4

Geology...................................................................................................................................................4

Hydrology ...............................................................................................................................................7

Land Use and Land Cover....................................................................................................................7

White River Basin ........................................................................................................................7

Colorado River Basin...................................................................................................................9

Lower Gunnison River Basin....................................................................................................12

Land-Use Impacts......................................................................................................................12

Previous Studies .................................................................................................................................12

Methods.........................................................................................................................................................14

Compilation of Data ............................................................................................................................14

Analysis of Data ..................................................................................................................................14

Summary Statistics....................................................................................................................16

Comparison to Standards.........................................................................................................16

Trend Analysis and Load Calculation .....................................................................................21

Seasonal Kendall Test......................................................................................................21

Regression Model.............................................................................................................22

Characterization and Data-Gap Analysis of Surface-Water Quality...................................................23

Summary Statistics and Comparison to Standards ......................................................................23

Temporal Trends and Loads ..............................................................................................................25

White River Basin ......................................................................................................................26

Field Properties .................................................................................................................26

Nutrients.............................................................................................................................26

Dissolved Solids and Major Ions....................................................................................36

Trace Elements..................................................................................................................39

Suspended Sediment .......................................................................................................40

Colorado River Basin.................................................................................................................41

Field Properties .................................................................................................................42

Nutrients.............................................................................................................................42

Dissolved Solids and Major Ions....................................................................................43

Trace Elements..................................................................................................................44

Suspended Sediment .......................................................................................................45
iv

Lower Gunnison River Basin....................................................................................................45

Field Properties .................................................................................................................45

Nutrients.............................................................................................................................45

Dissolved Solids and Major Ions....................................................................................45

Trace Elements..................................................................................................................46

Suspended Sediment .......................................................................................................48

Data Gaps.............................................................................................................................................48

White River Basin ......................................................................................................................48

Colorado River Basin.................................................................................................................48

Lower Gunnison River Basin....................................................................................................48

Summary........................................................................................................................................................52

Acknowledgments.......................................................................................................................................54

References Cited..........................................................................................................................................54

Appendix 1. Summary of Surface-Water-Quality Data by Site, by Constituent, Piceance 

Study Area, Western Colorado ................................................................................................ Link

Appendix 2. Model Coefficients and Statistical Diagnostics from Regression Models 

Used for Trend Analysis in the Piceance Study Area, Colorado........................................ Link

Appendix 3. Schematic Diagrams of the Model Line without Streamflow or Seasonality 

Terms To Facilitate the Determination of Zero-Slope Year, Net Trend Direction, 

and Direction of the Trend Before and After the Zero-Slope Year.........................................62

Plates (located at back of report)

1. Map showing water-quality sites with downstream order number from 

appendix 1 in the Piceance study area, western Colorado.................................................64

2. Map showing exceedances of water-quality standards for temperature, pH, and 

dissolved oxygen from appendix 1 in the Piceance study area, western Colorado............66

3. Map showing exceedances of water-quality standards for nitrate and phosphorus 

from appendix 1 in the Piceance study area, western Colorado ............................................68

4. Map showing exceedances of water-quality standards for chloride and sulfate 

from appendix 1 in the Piceance study area, western Colorado ............................................70

5. Map showing exceedances of water-quality standards for copper, iron (total and 

dissolved), lead, zinc, and selenium from appendix 1 in the Piceance study area, 

western Colorado..............................................................................................................................72

Figures

1. Location of the Piceance study area, western Colorado.......................................................3

2. Generalized geologic structures of the Piceance study area, western Colorado.............5

3. Generalized geologic map of the Piceance study area, western Colorado .......................6

4. The hydrology of the Piceance study area, western Colorado.............................................8
v

5. Annual-mean streamflows for selected U.S. Geological Survey streamflow-gaging 

stations in the Piceance study area for 1990 through 2009, western Colorado ...................10

6. Land cover of the Piceance study area, western Colorado................................................11

7. Location of the sites where trend analysis was completed, western Colorado..............27

8. Loading profile for nitrate and orthophosphate in the White River Basin, 

western Colorado .......................................................................................................................28

9. Loading profile for dissolved solids, iron, and selenium in the White River Basin, 

western Colorado .......................................................................................................................29

10. Loading profile for nitrate and orthophosphate in the Colorado River 

Basin, western Colorado ...........................................................................................................30

11. Loading profile for dissolved solids, iron, and selenium in the Colorado 

River Basin, western Colorado.......................................................................................................31

12. Loading profile for dissolved solids and selenium in the Lower Gunnison 

River Basin, western Colorado.................................................................................................32

13. Locations of continuous streamflow, physical parameter data trend, 

concentration data trend, and summary statistic sites in the White River 

Basin, western Colorado ...........................................................................................................49

14. Locations of continuous streamflow, physical parameter data trend, 

concentration data trend, and summary statistic sites in the Colorado River 

Basin, western Colorado ...........................................................................................................50

15. Locations of continuous streamflow, physical parameter data trend, 

concentration data trend, and summary statistic sites in the Lower Gunnison 

River Basin, western Colorado.................................................................................................51

Tables

1. Annual-mean streamflow, in cubic feet per second, for selected U.S. Geological 

Survey streamflow-gaging stations in the Piceance study area for the period 

1990 through 2009, western Colorado .......................................................................................9

2. Colorado Department of Public Health and Environment section 303(d) list of 

impaired waters and monitoring and evaluation list for the Piceance study area, 

western Colorado, 2011 .............................................................................................................15

3. Selected Colorado Department of Public Health and Environment instream 

water-quality standards for stream segments in the Piceance study area, 

western Colorado .......................................................................................................................17

4. Summary of the seasonal Kendall test trend analysis results for field properties,

Piceance study area, western Colorado, 1990–2009 ............................................................33

5. Summary of regression model trend analysis results for nutrients and 

Escherichia coli, Piceance study area, western Colorado, 1990–2009 .............................34

6. Summary of regression model trend analysis results for dissolved solids and 

major ions, Piceance study area, western Colorado, 1990–2009 .......................................36

7. Summary of regression model trend analysis results for trace elements and 

suspended sediment, Piceance study area, western Colorado, 1990–2009.....................40
vi

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2) 

acre 0.004047 square kilometer (km2)

square foot (ft2) 929.0 square centimeter (cm2)

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2) 

Volume

cubic foot (ft3) 28.32 cubic decimeter (dm3) 

cubic foot (ft3) 0.02832 cubic meter (m3) 

acre-foot (acre-ft) 1,233 cubic meter (m3)

acre-foot (acre-ft) 0.001233 cubic hectometer (hm3) 

Flow rate

foot per second (ft/s) 0.3048 meter per second (m/s)

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

cubic foot per day (ft3/d) 0.02832 cubic meter per day (m3/d)

gallon per minute (gal/min) 0.06309 liter per second (L/s)

Mass

tons per day 0.9072 metric ton per day

tons per year (ton/yr) 0.9072 metric ton per day

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Elevation, as used in this report, refers to distance above the vertical datum.

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).
vii

Abbreviations Used in This Report

BLM Bureau of Land Management

BTEX benzene, toluene, ethylbenzene, and xylene

CDPHE Colorado Department of Public Health and Environment

CFU colony forming units

DS dissolved solids

ESTREND Estimate Trend computer program

GMUG Grand Mesa Uncompahgre and Gunnison (National Forests)

LOADEST Load Estimation computer program

MCL maximum contaminant level 

μg/L micrograms per liter

mg/L milligrams per liter

NIWQP National Irrigation Water Quality Program

NWIS National Water Information System

PRESS prediction sum of squares

TMDL total maximum daily loads

TPH total petroleum hydrocarbons

TVS table-value standards

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

Characterization and Data-Gap Analysis of Surface-Water 

Quality in the Piceance Study Area, Western Colorado, 

1959–2009

By Judith C. Thomas, Jennifer L. Moore, Keelin R. Schaffrath, Jean A. Dupree, Cory A. Williams, 

and Kenneth J. Leib

Nutrients within the study area were not well represented 

in each basin and were often not being sampled currently. 

For the entire study area, 62 sites had nitrate data collected 

between 1958 and 2009, and median nitrate concentrations 

ranged from less than detection to 3.72 mg/L as nitrogen. The 

maximum contaminant level for domestic water supply for 

nitrate is 10 mg/L and was exceeded once in 3,736 samples. 

Total phosphorus was collected at 113 sites between 1974 

and 2009, and median total phosphorus concentrations ranged 

from less than detection to 5.04 mg/L. The U.S. Environmental Protection Agency recommendation for phosphorus is 

less than 0.1 mg/L, and 1,469 of 4,842 samples exceeded this 

recommended standard. An upward trend in both nitrate and 

total phosphorus was detected in the White River above Coal 

Creek near Meeker, Colo.

Standards for major ions exist only for chloride and 

sulfate. For the entire study area, 118 sites had both chloride 

and sulfate concentration data collected between 1958 and 

2009. Median chloride concentrations ranged from 0.085 mg/L 

to 280 mg/L. Median sulfate concentrations ranged from 

4.57 mg/L to 15,000 mg/L. Both chloride and sulfate domestic 

water-supply standards are 250 mg/L. There were 120 chloride 

concentrations and 1,111 sulfate concentration samples that 

exceeded these standards. A downward trend in dissolved solids was detected at the Colorado River near the Colorado-Utah 

state border and could be a result of salinity control work near 

Grand Junction, Colo.

Trace elements were relatively well represented both 

temporally and spatially in the study area though the number 

of trace element samples per site was not typically enough 

to compute trends or loads except for selenium. There were 

127 sites that had dissolved iron concentration data collected 

between 1961 and 2009, and median iron concentrations 

ranged from less than detection to 1,100 micrograms per 

liter (μg/L). The 30-day drinking-water standard for iron is 

300 μg/L, and 203 samples exceeded the standard. Selenium 

was the best represented trace element with selenium concentration data collected at 197 sites between 1973 and 2009, 

and median selenium concentrations range from less than 

detection to 181 μg/L. The chronic standard of 4.6 μg/L for 

Abstract

The U.S. Geological Survey, in cooperation with Federal, 

State, county, and industry partners, developed a Webaccessible common data repository to provide access to historical and current (as of August 2009) water-quality information 

(available on the Internet at http://rmgsc.cr.usgs.gov/cwqdr/

Piceance/index.shtml). Surface-water-quality data from public 

and private sources were compiled for the period 1931 to 2009 

and loaded into the common data repository for the Piceance 

Basin. A subset of surface-water-quality data for 1959 to 2009 

from the repository were compiled, reviewed, and checked 

for quality assurance for this report. This report contains data 

summaries, comparisons to water-quality standards, trend 

analyses, a generalized spatial analysis, and a data-gap analysis for select water-quality properties and constituents.

Summary statistics and a comparison to standards were 

provided for 347 sites for 33 constituents including field properties, nutrients, major ions, trace elements, suspended sediment, 

Escherichia coli, and BTEX (benzene, toluene, ethylbenzene, 

and xylene). When sufficient data were available, trends over 

time were analyzed and loads were calculated for those sites 

where there were also continuous streamflow data.

The majority of sites had information on field properties. 

Water temperature data was available for 316 sites where data 

were collected between 1959 and 2009. The only trend that was 

detected in temperature was an upward trend at the Gunnison 

River near Grand Junction, Colorado. There were 326 values 

out of a total of 32,006 values in the study area that exceeded 

the aquatic-life standard for daily maximum water temperature. 

For the entire study area, 196 sites had dissolved-oxygen data 

collected between 1970 and 2009, and median dissolved-oxygen 

concentrations ranged from 6.8 to 11.2 milligrams per liter 

(mg/L). There were 185 concentrations that exceeded the dissolved oxygen aquatic-life standard out of a total of 11,248 values. The pH data were available for 276 sites, and median 

pH values ranged from 7.5 to 9.0. There were 241 values that 

exceeded the high pH standard and 13 values that were less than 

the low pH standard of the 16,790 values in the study area.
2 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

selenium concentrations was exceeded in 899 samples, and 

the acute aquatic-life standard of 18.4 μg/L for selenium was 

exceeded in 629 samples. High concentrations of selenium are 

of concern in the Lower Gunnison River Basin because of the 

combination of geologic formations and land use. There were 

significant downward trends in selenium at both main-stem 

sites on the Gunnison River at Delta, Colo., and the Gunnison 

River near Grand Junction, Colo. High selenium concentrations correlate with high salinity concentrations; thus, when 

salinity control efforts are conducted in selenium-rich areas in 

the Lower Gunnison River Basin, both salinity and selenium 

have the potential to decrease.

Spatial, temporal, and analytical data gaps were identified in the study area. The spatial coverage of sampling 

sites could be expanded in the White River Basin by adding 

more tributary sites. No water-quality data exist for tributary 

streams in the area north of Rangely, Colo., where extensive 

energy development has occurred in a complex geologic setting. Douglas Creek has a drainage area of 425 square miles 

and has limited historic water-quality and water-quantity data. 

Limited data were available for field properties, major ions, 

nutrients, and trace elements on the main stem of the Colorado 

River between Glenwood Springs and Cameo, Colo. Nutrient 

data were minimally collected upstream from Colorado River 

at the Colorado-Utah state border and on the Gunnison River 

(major tributary in the reach). Approximately 30 percent of 

the samples for total phosphorus in the Lower Gunnison River 

Basin exceeded the recommended standard, yet there were 

insufficient data to do trends analysis in the Lower Gunnison 

River Basin except at the Gunnison near Grand Junction site. 

There is limited trace element data except for selenium in the 

Lower Gunnison River Basin. Additional sampling is necessary to understand the occurrence, concentrations, and loads of 

these constituents.

Introduction

Water resources can be affected by natural and human 

factors. Human factors can include activities such as urbanization, agriculture, and multiple types of development and 

changes in land use, including energy development and 

infrastructure. Northwestern Colorado is experiencing many 

of these types of changes in land use, which can result in 

short- and long-term changes in the water resources in the 

study area. Ongoing monitoring and assessment are required 

to periodically reestablish our understanding of baseline conditions and to detect changes. Substantial water-resource datasets, publications, and other materials have been developed in 

past years and can be used to assess baseline conditions and 

to evaluate land-use effects. However, these data are generally 

stored in disparate formats among numerous agencies, energy 

companies, private consulting firms, universities, and stakeholder groups. A publically accessible common data repository was needed to compile water-quality data collected by 

various entities. Compilation and quality assurance of existing 

water-quality data from the currently disparate sources and 

formats provides a useful contribution to public and private 

entities tasked with planning, oversight, conservation, and 

management of water resources. The U.S. Geological Survey 

(USGS), in cooperation with Federal, State, county, and industry partners, developed a Web-accessible common data repository to provide energy operators, researchers, consultants, 

agencies, and interested stakeholders equal access to historical 

and current (as of August 2009) water-quality information 

(available on the Internet at http://rmgsc.cr.usgs.gov/cwqdr/

Piceance/index.shtml). The following is an alphabetical list of 

cooperators involved in this study: Antero Resources, Bureau 

of Land Management, Bureau of Reclamation, Chevron 

Corporation, City of Grand Junction and City of Rifle, Colo., 

Colorado Department of Agriculture, Colorado Department 

of Natural Resources, Colorado Department of Public Health 

and Environment, Colorado Division of Wildlife–River 

Watch, Colorado Oil and Gas Conservation Commission, 

Colorado River Water Conservation District, Delta County, 

Colo., EnCana Oil & Gas (USA) Inc., Garfield County, Colo., 

Gunnison Energy Corp., National Park Service, Natural 

Soda, Inc., North Fork River Improvement Association, 

Oxy Petroleum Corporation, Petroleum Development Corp., 

Rio Blanco County, Shell Oil Company, Solvay Chemicals, 

Towns of Carbondale, De Beque, Palisade, Parachute, 

Rangely, and Silt, Colo., U.S. Forest Service, West Divide 

Water Conservancy District, and Williams Companies, Inc.

Purpose and Scope

This report provides an analysis of select surface-water 

data for 1959–2009 from the common data repository for 

the Piceance study area. Data were summarized to identify 

available data and evaluate temporal and spatial patterns in 

the study area. These data were analyzed to provide a baseline assessment of available water-resource data and aid in 

the development of regional monitoring strategies. The report 

contains data summaries, comparisons to standards, trend 

analyses, and a generalized spatial analysis for selected waterquality properties and constituents. Gaps in available data 

were identified from these analyses.

Description of the Study Basin Areas

The Piceance study area refers to an area of approximately 9,500 square miles (mi2

) in western Colorado extending from north of Rangely to south of Delta and east to west 

from Glenwood Springs, Colorado (Colo.) to the ColoradoUtah state border (fig. 1). The study area was delineated 

based on hydrology, geology, and political boundaries. The 

Piceance study area is subdivided into three study basin 

areas: the White River Basin, the Colorado River Basin, and 

the Lower Gunnison River Basin (fig. 1). The climate of the 

Piceance study area is arid to semiarid with the exception of 

higher elevations of the Grand Mesa and the Roan Plateau, 

which are considered subalpine zones (fig. 1). The majority 
Introduction 3

Figure 1. Location of the Piceance study area, western Colorado.

N:\Jeff\den12_cmre00_0081_sir_thomas\figures\figure_01.ai

White River

Roan Creek

Big

Salt Wash

Piceance Creek

Wolf Creek

Smith Fork

Plateau Creek

Kannah Creek

East Salt Creek

Flag Creek

Clear Creek

West Salt Creek

East Creek

Red Wash

Surface

Creek

Ryan Gulch

Coal Creek

Yellow Creek

Big Creek

Cottonwood Creek

Carr Creek

Jerry Creek

Douglas Creek

Kelso Creek

North Fork White River

Dry Fork

Leon Creek

Hubbar

Anthracite 

Creek

Strawberry 

Creek

Fawn Creek

Dry Creek

Willow Creek

Kimball Creek

Criswell Creek

Missouri Creek

Sulphur Creek

Rifle 

Creek

Corral Gulch

Parachute Creek

Clear Fork

Salt 

Creek

Coal Creek

Sunflower

Drain

Minnesota

Creek

Gunnison 

Tunnel Uncompahgre River

Cathedral

Bluffs

West Elk 

Mountains

Douglas 

Pass

Colorado River

d

Silt

Rifle

Delta

Meeker

Olathe

Fruita

Paonia

Rangely

Montrose

Palisade

De Beque

Collbran

Parachute

Cedaredge

New

Castle Glenwood Springs

MESA 

COUNTY

COLORADO

UTAH

COLORADO

UTAH

MOFFAT 

COUNTY

GUNNISON

COUNTY

GARFIELD

COUNTY

RIO BLANCO

COUNTY

MONTROSE

COUNTY

DELTA 

COUNTY

PITKIN 

COUNTY

Wayne N. Aspinall 

Federal Storage Unit

Vega 

Reservoir

Taylor Draw 

Reservoir

Lewis

Wash

Alkali Flats

Roan 

Plateau

Grand Mesa

109° 108°30' 108° 107°30' 107°

40°

39°30'

39°

38°30'

Base from Environmental Research Systems Institute 

(ESRI) digital data, 2009, 1:24,000 and 

U.S. Geological Survey digital data, 2010, 1:100,000

Universal Transverse Mercator, Zone 13 North

0 10 20 30 MILES

0 10 20 30 KILOMETERS

EXPLANATION

White River Basin

Colorado River Basin

Lower Gunnison River Basin

Study area boundary

Creek

40

40

40

50

50

6

6

50

Dinosaur

64

65

13

13

139

West Rifle

Creek

East Rifle Creek

Mamm

Creek

Divide Creek

Buzzard Creek

70

70

Juniata 

G

Reservoir unnison River

Grand

Junction

Highline

Lake

Roaring Fork

550

North Fork

Gunnison River

Hotchkiss

Roubideau Creek

Loutsenhizer

Arroyo

Crawford

ROUTT

COUNTY

133

149

141

82

92

90

COLORADO

DENVER

INDEX MAP

Piceance 

study area
4 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

of precipitation in the lower elevations falls as rain during the 

late summer and early fall. The majority of precipitation in the 

higher elevations falls as snow and accumulates in a seasonal 

snowpack (Western Regional Climate Center, 2012).

White River Basin

The White River Basin is partially defined by the 

Piceance Structural Basin boundary and begins near the mouth 

of Coal Creek and extends downstream to the White River at 

the Colorado-Utah state border. Elevations range from more 

than 8,675 feet (ft) at Cathedral Bluffs to about 5,200 ft on the 

White River near the Colorado-Utah state border. The basin is 

located in Rio Blanco, Garfield, and Moffat Counties (fig. 1). 

The towns of Meeker and Rangely are the two largest population centers in the basin (fig. 1). Meeker had a population of 

2,475 in 2010, and Rangely had a population of 2,365 in 2010 

(U.S. Census Bureau, 2011).

Colorado River Basin

The Colorado River Basin includes the drainage area from 

Glenwood Springs, Colo., to the Colorado-Utah state border 

(fig. 1). Elevations range from more than 11,000 ft on the Grand 

Mesa (fig. 1) down to about 4,300 ft on the Colorado River at 

the Colorado-Utah border. The basin is located in Garfield and 

Mesa Counties (fig. 1). The primary population centers in this 

basin (from east to west) are Glenwood Springs, New Castle, 

Silt, Rifle, Parachute, Collbran, De Beque, Palisade, Grand 

Junction, and Fruita, Colo. (fig. 1). The largest population center 

in the basin is Grand Junction, which had a population of 58,566 

in 2010 (U.S. Census Bureau, 2011). In comparison, Collbran 

had a population of 708 in 2010 (U.S. Census Bureau, 2011).

Lower Gunnison River Basin

The Lower Gunnison River Basin is the southernmost 

section of the Piceance study area (fig. 1). The Lower Gunnison River Basin is only a part of the entire Gunnison River 

Basin; the Gunnison River is the largest tributary to the Colorado River in Colorado. The Lower Gunnison River Basin, 

for this study, included the entire drainage area of the North 

Fork of the Gunnison River and the drainage area beginning 

slightly downstream from the Gunnison Tunnel on both the 

Gunnison River and the Uncompahgre River. The Gunnison 

Tunnel diverts irrigation water from the Gunnison River to the 

Uncompahgre River. Elevations in the Lower Gunnison River 

Basin range from about 13,000 ft in the West Elk Mountains 

(fig. 1) located in the southeast corner of the basin to 4,600 

ft near the confluence of the Gunnison River and Colorado 

River. The basin is located in Delta, Mesa, Gunnison, and 

Montrose Counties (fig. 1). The largest population center in 

the basin is Delta which had a population of 8,915 in 2010 

(U.S. Census Bureau, 2011). The smallest population center in 

the basin is Hotchkiss, which had a population of 944 in 2010 

(U.S. Census Bureau, 2011).

Geology

The Piceance study area lies within the Piceance 

Structural Basin, which is a downwarped region surrounded 

by uplifted regions including the Axial Basin Arch to the 

north, the Grand Hogback to the east, the Gunnison Uplift to 

the southeast, the Uncompahgre Uplift to the southwest, and 

the Douglas Creek Arch to the west (fig. 2). Outcropping bedrock units in the center of the downwarped region are Tertiary 

sedimentary rocks (fig. 3). Uplifted regions at the boundaries 

of the structural basin are primarily Cretaceous sedimentary 

rocks (figs. 2 and 3).

The surface geology of the study area ranges from 

Quaternary to Jurassic age (Tweto, 1979; Green, 1992) (fig. 3). 

Alluvial, terrace, and valley-fill deposits of Quaternary age 

form the unconsolidated materials in the valleys. The Green 

River Formation, of early Tertiary age, rests conformably on 

the Wasatch Formation (older Tertiary rock). The Green River 

Formation is well known for rich oil-shale deposits. The Green 

River Formation also contains natural resources of economic 

interest including nacholite, dawsonite, potable groundwater, 

natural gas, and crude oil, depending on location in the basin. 

The Wasatch Formation consists of a varied colored mudstone 

with sandstone lenses (Johnson and Flores, 2003). Some of 

the sandstone lenses, such as the Wasatch “G” interval of the 

Wasatch Formation, are appreciable reservoirs of natural gas 

in or near Parachute and Rulison, Colo. (Nelson and Santus, 

2010). The Wasatch Formation is also a source of potable water.

Cretaceous sedimentary rocks of primary interest in the 

study area were the Mesaverde Group, the Mancos Shale, 

and the Dakota Sandstone (fig. 3). The Mesaverde Group 

was formed by a series of marine transgressions and regressions with later periods of fluvial deposition (Johnson, 1989) 

resulting in a sequence of marine shales, siltstones, and 

sandstones capped by a thick sequence of terrestrial fluvial deposits. The fluvial deposits of the Mesaverde Group 

consist almost entirely of lenticular channel sandstones and 

fine-grained flood-plain deposits. The channel sandstones 

are the primary reservoirs for natural gas and require a dense 

pattern of drilling to recover the gas from these sandstones 

(Nelson and Santus, 2010). The Mesaverde Group consists 

of the Iles Formation and the Williams Fork Formation. The 

Iles Formation contains the Corcoran, Cozzette, and Rollins 

Members (Reinecke and others, 1991). The Williams Fork 

Formation is an important natural gas producing unit within 

the study area. The Mancos Shale is of Late Cretaceous age 

and is composed of massive, fossiliferous marine shale with 

interbedded sandstone, siltstone, and devitrified volcanic ash 

layers. The Mancos Shale is a major source of dissolved solids 

and selenium in the study area. The Mancos Shale is the lateral 

equivalent to the Niobrara Shale, Cody Shale, and Pierre Shale 

in Colorado, Montana, Nebraska, South Dakota, and Wyoming 

(Tweto, 1979; Green, 1992; Wright and Butler, 1993). The 

Dakota Sandstone, of Early Cretaceous age, is composed of 

interbedded, hard sandstone, conglomerates, shale, and coal 

(Brune, 1953); it is a potential source of potable water as well 

as a source of dissolved solids in the study area.
Introduction 5

Figure 2. Generalized geologic structures of the Piceance study area, western Colorado.

Base from Environmental Research Systems Institute 

(ESRI) digital data, 2009, 1:24,000 and 

U.S. Geological Survey digital data, 2010, 1:100,000

Universal Transverse Mercator, Zone 13 North

0 10 20 30 MILES

0 10 20 30 KILOMETERS

Silt

Rifle

Delta

Meeker

Olathe

Fruita

Paonia

Rangely

Montrose

Dinosaur

Palisade

De Beque

Collbran

Crawford

Parachute

Hotchkiss

Cedaredge

New Castle

Grand 

Junction

Glenwood Springs

Rulison

White River

Gunnison River

Roan Creek

Piceance Creek

Plateau Creek

East Salt Creek

Yellow Creek

MESA 

COUNTY

MOFFAT 

COUNTY

ROUTT 

COUNTY

GUNNISON

COUNTY

GARFIELD

COUNTY

RIO BLANCO

COUNTY

MONTROSE

COUNTY

DELTA 

COUNTY

PITKIN 

COUNTY

Axial Basin Arch

White River 

Uplift

Piceance 

Structural 

Basin

Gunnison 

Uplift

Grand

Hogback

Douglas Creek Arch

Uncompahgre Uplift

109° 108°30' 108° 107°30' 107°

40°

39°30'

39°

38°30'

Geology from Green, 1992. Geologic structure

modified from Johnson and Flores, 2003

Piceance Structural Basin from U.S. Geological Survey

Oil Shale Assessment team, 2010

40

40

40

64

139

13

13

70

70

Colorado River

50

50

65

550

EXPLANATION

Mesaverde Group outcrop

Piceance Structural Basin boundary

Study area boundary

Uncompahgre River

N:\Jeff\den12_cmre00_0081_sir_thomas\figures\figure_02.ai COLORADO UTAH COLORADO UTAH

50

6

6

133

82

149

141

92

90
6 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Figure 3. Generalized geologic map of the Piceance study area, western Colorado.

N:\Jeff\den12_cmre00_0081_sir_thomas\figures\figure_03.ai

Silt

Rifle

Delta

Meeker

Olathe

Fruita

Paonia

Rangely

Montrose

Dinosaur

Palisade

De Beque

Collbran

Crawford

Parachute

Hotchkiss

Cedaredge

New

Castle

Grand 

Junction

Glenwood Springs

MESA 

COUNTY

MOFFAT 

COUNTY

ROUTT 

COUNTY

GUNNISON

COUNTY

GARFIELD

COUNTY

RIO BLANCO

COUNTY

MONTROSE

COUNTY

DELTA 

COUNTY

PITKIN 

COUNTY

109° 108°30' 108° 107°30' 107°

40°

39°30'

39°

38°30'

Geology modified from Tweto, 1979

Rulison

Base from Environmental Research Systems Institute 

(ESRI) digital data, 2009, 1:24,000 and 

U.S. Geological Survey digital data, 2010, 1:100,000

Universal Transverse Mercator, Zone 13 North

0 10 20 30 MILES

0 10 20 30 KILOMETERS

COLORADO

UTAH

COLORADO

UTAH

40

40

40

64

139

13

13

70

70

50

65

50

550

50

6

6

133

149

141

82

92

90
Introduction 7

Hydrology

The Piceance study area has three study basin areas: 

the White River, Colorado River, and the Lower Gunnison 

River (fig. 4). The annual streamflow cycle in the study 

area is marked by spring snowmelt, which causes water 

levels in the river to rapidly rise. Low-flow conditions are 

characteristic of the late summer through winter seasons. 

Annual-mean streamflows at 10 USGS streamflow-gaging 

stations were calculated (1990 through 2009) to represent 

effects such as the construction of major diversions or storage 

facilities and climatic effects such as wet and dry hydrologic 

cycles (table 1, fig. 5). Streamflow data were obtained from 

the National Water Information System (NWIS) website 

(http://waterdata.usgs.gov). Generally, the annual-mean 

streamflows were variable based on basin area. Annual-mean 

streamflows in the Piceance study area demonstrated a wet 

period from approximately 1997 through 1999 followed by a 

dry period from approximately 2002 through 2004.

Land Use and Land Cover

Land use and land cover in the Piceance study area are 

varied, including forested land, rangeland/shrubland, agricultural land, barren land, and developed/urban land, which 

includes ski resorts and energy development (fig. 6). The 

total study area is almost 9,500 mi2 and includes 4,600 mi2

(about 50 percent) of forested land and 3,800 mi2 (about 

40 percent) of rangeland (Homer and others, 2004). Natural 

gas development has increased in the study area since 2000, 

in part because of advancements in the application of hydraulic fracturing, which has allowed successful extraction of 

natural gas from previously inaccessible sources (Nelson and 

Santus, 2010).

White River Basin

The area of the White River Basin is 3,160 mi2. The 

Bureau of Land Management (BLM) owns 2,176 mi2 (69 percent), and private entities own 837 mi2

 (26 percent) (Bureau 

of Land Management, 2009). The dominant land cover in the 

basin in 2001 was rangeland/shrubland (48 percent) (Homer 

and others, 2004). Much of the BLM land serves multiple 

uses, including ranching of sheep and cattle, natural gas development, and oil shale research development and demonstration 

leases (Bureau of Land Management, 2009). Part of the BLM 

land is managed for wild horse and burro herds (Bureau of 

Land Management, 2011a). Natural gas development on public lands in Rio Blanco County has increased from 58 permits 

in 2001 to 200 permits in 2006, and a total of 2,556 multiple 

well pads are projected during the next 20 years (Bureau of 

Land Management, 2011b).

The White River Basin is located primarily in Rio Blanco 

County (fig. 1) and is a tributary to the Green River, which 

then flows into the Colorado River in Utah. The White River 

Basin includes the White River and other major tributaries 

such as Piceance Creek, Yellow Creek, and Douglas Creek 

(fig. 1). Sedimentary rocks of Tertiary age including the 

Uinta Formation and the Green River Formation outcrop in 

the eastern and central part of the White River Basin (fig. 3). 

Cretaceous Mesaverde Group rocks outcrop in the western 

part of the White River Basin (fig. 3), specifically within the 

Douglas Creek drainage area (figs. 1 and 3). The White River 

has no major transbasin diversions or diversions for agricultural use. Oil shale and natural gas development have been 

and continue to be one of the most important land uses in the 

White River Basin. Conventional and unconventional natural 

gas extraction and the associated infrastructure are becoming 

increasingly prevalent in the basin. Rio Blanco County is one 

Figure 3. Generalized geologic map of the Piceance study area, 

western Colorado.—Continued

Study area

Geologic unit

Quaternary sedimentary units, undifferentiated

Quaternary-Tertiary ancient alluvium

Tertiary volcanic and plutonic units

Tertiary Browns Park Formation

Tertiary Uinta Formation

Oligocene sedimentary rocks

Tertiary Green River Formation

Tertiary Lower Green River and Wasatch Formation 

Tertiary Wasatch Formation

Tertiary Fort Union Formation

Mesozoic rocks, undifferentiated

Cretaceous-Jurassic Dakota, Burro Canyon, Morrison, Wanakah, 

 and Entrada Formations 

Cretaceous Dakota Sandstone and Burro Canyon Formation

Cretaceous Mesaverde Group

Cretaceous Mount Garfied Formation and Sego Sandstone

Cretaceous Sego Sandstone, Buck Tongue of Mancos Shale, 

 and Castlegate Sandstone 

Cretaceous Mancos Shale

Jurassic units, undifferentiated

Triassic Kayenta Formation

Triassic Wingate Sandstone and Chinle Formations

Triassic-Permian Chinle, Moenkopi, Park City, and State Bridge Formations

Triassic Chinle Formation

Pennsylvanian Maroon Formation and Weber Sandsone 

Pennsylvanian Minturn

Pennsylvanian Belden Formation

Pennsylvanian evaporitic facies

Pennsylvanian Morgan Valley Formation and Round Valley Limestone

Mississippian-Cambrian units, undifferentiated

Precambrian, undifferentiated

Geologic fault line

EXPLANATION
8 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Figure 4. The hydrology of the Piceance study area, western Colorado.

N:\Jeff\den12_cmre00_0081_sir_thomas\figures\figure_04.ai

White River

Roan Creek

Big

Salt Wash

Piceance Creek

Wolf Creek

Smith Fork

Kannah Creek

East Salt Creek

Flag Creek

Clear Creek

West Salt Creek

East Creek

Red Wash

Surface

Creek

Ryan Gulch

Coal Creek

Yellow Creek

Big Creek

Cottonwood Creek

Carr Creek

Jerry Creek

Douglas Creek

Kelso Creek

North Fork White River

Dry Fork

Leon Creek

Hubbar

Anthracite 

Creek

Strawberry 

Creek

Fawn Creek

Dry Creek

Willow Creek

Kimball Creek

Criswell Creek

Missouri Creek

Sulphur Creek

Rifle 

Creek

Corral Gulch

Parachute Creek

Clear Fork

Salt 

Creek

Coal Creek

Minnesota

Creek

Gunnison 

Tunnel Uncompahgre River

Colorado River

d

Silt

Rifle

Delta

Meeker

Olathe

Fruita

Paonia

Rangely

Montrose

Palisade

De Beque

Collbran

Parachute

Cedaredge

New

Castle

Glenwood Springs

MESA 

COUNTY

COLORADO

UTAH

COLORADO

UTAH

MOFFAT 

COUNTY

GUNNISON

COUNTY

GARFIELD

COUNTY

RIO BLANCO

COUNTY

MONTROSE

COUNTY

DELTA 

COUNTY

PITKIN 

COUNTY

Taylor Draw 

Reservoir

109° 108°30' 108° 107°30' 107°

40°

39°30'

39°

38°30'

Base from Environmental Research Systems Institute 

(ESRI) digital data, 2009, 1:24,000 and 

U.S. Geological Survey digital data, 2010, 1:100,000

Universal Transverse Mercator, Zone 13 North

0 10 20 30 MILES

0 10 20 30 KILOMETERS

EXPLANATION

White River Basin

Colorado River Basin

Lower Gunnison River Basin

Study area boundary

U.S. Geological Survey streamflow-gaging

 station and identifier

40

40

40

50

50

Dinosaur

64

65

13

13

139

West Rifle

Creek

East Rifle Creek

Mamm

Creek

Divide Creek

Buzzard Creek

Creek

70

70

Gunnison River

Grand

Junction

Highline

Lake

Roaring Fork

550

North Fork

Gunnison River

Hotchkiss

Roubideau Creek

Loutsenhizer

Arroyo

Crawford

Plateau Creek

Sunflower

Drain

50

6

6

133

149

141

82

92

90

09306290

09306222

09304800

09163500

09152500

09149500

09149500

09105000

09095500

09144250

09085100

ROUTT

COUNTY
Introduction 9

of the six counties in Colorado that have the greatest number 

of actively operating gas wells; there were 2,906 active gas 

wells in Rio Blanco County as of October 2011 (Colorado Oil 

and Conservation Commission, 2011).

Colorado River Basin

The area of the Colorado River Basin (study area) is 

3,560 mi2, and the area of the drainage area of the Colorado 

River upstream from the site at the Colorado-Utah state border 

is 17,843 mi2. About 1,600 mi2 (45 percent) of the study area 

are managed by the Bureau of Land Management (Bureau 

of Land Management, 2009). About 1,400 mi2 (39 percent) 

of the basin were privately owned and 500 mi2 (14 percent) 

were managed by the U.S. Forest Service (Bureau of Land 

Management, 2009). The dominant land cover (48 percent) 

in the basin during 2001 was deciduous and evergreen forest. 

More than 230 mi2 (6.5 percent) had an agricultural land cover 

in 2001 (Homer and others, 2004) and 220 mi2 were irrigated 

(Techni Graphics Systems, Inc., 2004).

The Colorado River drains watersheds from seven states, 

and the headwaters originate in Colorado. Large diversions 

of water from the Colorado River are used for agricultural 

irrigation and by municipalities for drinking water. There 

are thermal hot springs adjacent to the Colorado River in 

Glenwood Springs. The water chemistry of the springs 

comprises up to 22,200 milligrams per liter (mg/L) dissolved 

solids, 7,600 mg/L of sodium, 11,000 mg/L of chloride, and 

2,450 mg/L of sulfate (Lund and Hunter, 2009). The springs 

also contain significant quantities of fluoride, silica, barium, 

iron, lithium, and boron. Water temperatures from the springs 

flowing to the river are approximately 32–49 °C (Lund and 

Hunter, 2009). Uranium and vanadium mining and milling 

operations took place in Rifle, Colo., in the 1920s and again 

from 1947 to 1957 (U.S. Energy Information Administration, 

2011). During the latter time period, the mill processed ore at 

about 200 tons/day. A second mill was built in 1958 with an 

ore processing capacity of 400 tons/day. Both mill locations 

were remediated by the U.S. Department of Energy starting in 

1989 (U.S. Energy Information Administration, 2011).

The economy of the basin is dominated by agriculture, 

energy development, industry, real estate development, tourism, and recreation (Leib and Bauch, 2008). The Colorado 

River is home to 14 native species of fish, of which four 

are endemic and endangered: the Colorado pikeminnow, 

razorback sucker, bonytail chub, and humpback chub 

(U.S.Fish and Wildlife Services, 2011). The Roan Plateau 

(fig. 1) provides habitat to a native, genetically diverse population of cutthroat trout (Bureau of Land Management, 2002). 

The Grand Mesa has more than 200 lakes and reservoirs. The 

Grand Mesa, as part of the Grand Mesa Uncompahgre and 

Gunnison National Forests (GMUG), has unique natural peatforming wetlands called fens that are considered an aquatic 

resource of national importance by the U.S. Environmental 

Protection Agency (USEPA) (U.S. Forest Service, 2011). The 

Roan Plateau is leased for the drilling of natural gas. Based 

on estimates from the BLM management plan for the Roan 

Plateau Planning area, Federal lands on the Roan Plateau 

could provide 3,630 billion cubic feet (ft3) of natural gas during the next 20 years (Bureau of Land Management, 2002). 

The estimated technically recoverable gas resource within 

the Roan Plateau Planning Area of Federal lands is approximately 8,900 billion ft3

. Colorado Oil and Gas Conservation 

Commission issued 13,775 application permits to develop 

natural gas since 2004 in Garfield County (fig. 6) (Colorado 

Oil and Gas Conservation Commission, 2011). The Roan 

Plateau area also is a potential region for the development of 

oil shale. The Parachute Creek Member of the Green River 

Formation is about 900 to 1,200 ft thick in the Roan Plateau 

area and is generally considered the primary oil shale unit of 

interest (Bureau of Land Management, 2002).

Table 1. Annual-mean streamflow, in cubic feet per second, for selected U.S. Geological Survey 

streamflow-gaging stations in the Piceance study area for the period 1990 through 2009, western Colorado.

[Mean annual streamflow caclulated using data from 1990 through 2009]

Site 

identification

number

(fig. 4)

Station name

Mean annual 

streamflow,

in cubic feet

per second

Drainage area,

in square miles

White River Basin

09304800 White River below Meeker, Colo. 614 1,024

09306222 Piceance Creek at White River, Colo. 38 652

09306290 White River below Boise Creek, near Rangely, Colo. 723 2,530

Colorado River Basin

09085100 Colorado River below Glenwood Springs, Colo. 3,344 6,014

09095500 Colorado River near Cameo, Colo. 3,854 7,986

09105000 Plateau Creek near Cameo, Colo. 194 592

09163500 Colorado River near Colorado-Utah State Line 6,465 17,849

Lower Gunnison River Basin

09149500 Uncompahgre River at Delta, Colo. 335 1,114

09144250 Gunnison River at Delta, Colo. 1,964 5,636

09152500 Gunnison River near Grand Junction, Colo. 2,600 7,923
10 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Figure 5. Annual-mean streamflows for selected U.S. Geological Survey streamflow-gaging stations in the Piceance study area for 

1990 through 2009, western Colorado.

N:\Jeff\den12_cmre00_0081_sir_thomas\figures\figure_05.ai

500

Annual-mean streamflow, in cubic feet per second

Year

09306222

09304800

09306290

1990 1992

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

0

200

400

600

800

1,000

1994 1996 1998 2000 2002 2004 2006 2008

EXPLANATION

09095500

09085100

09163500

09304800

EXPLANATION

09152500

09144250

09149500

EXPLANATION

Lower Gunnison River Basin

Colorado River Basin

White River Basin
Introduction 11

Figure 6. Land cover of the Piceance study area, western Colorado.

N:\Jeff\den12_cmre00_0081_sir_thomas\figures\figure_06.ai COLORADO UTAH COLORADO UTAH

40

40

40

64

139

0 10 20 30 MILES

0 10 20 30 KILOMETERS

Land use from U.S. Geological Survey 2001

National Land Cover Dataset

(Homer and others, 2001), 1:100,000

Oil and gas wells from the Colorado Oil and

Gas Conservation Commission, 2010

Base from Environmental Research Systems Institute 

(ESRI) digital data, 2009, 1:24,000 and 

U.S. Geological Survey digital data, 2010, 1:100,000

Universal Transverse Mercator, Zone 13 North

13

13

50

65

70

70

50

550

EXPLANATION

Water/riparian

Developed/urban land

Barren land

Forested

Rangeland/shrubland

Agricultural land

Study area boundary

Oil/gas well

Land use/land cover

50

6

6

133

149

141

82

92

90

White River

Uncompahgre River

Roan Creek

Piceance Creek

Plateau Creek

East Salt Creek

Yellow Creek

Gunnison River

Colorado River

Silt

Rifle

Delta

Meeker

Olathe

Fruita

Paonia

Rangely

Montrose

Dinosaur

Palisade

De Beque

Collbran

Crawford

Parachute

Hotchkiss

Cedaredge

Grand

Junction

Glenwood Springs

New Castle

GUNNISON

COUNTY

GARFIELD

COUNTY

MOFFAT 

COUNTY

RIO BLANCO

COUNTY

MESA 

COUNTY

MONTROSE

COUNTY

ROUTT 

COUNTY

DELTA 

COUNTY

PITKIN 

COUNTY

109° 108°30' 108° 107°30' 107°

40°

39°30'

39°

38°30'
12 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Lower Gunnison River Basin

The area of the Lower Gunnison River Basin is 

2,700 mi2, and the entire drainage area (measured from where 

the Gunnison River enters the Colorado River) is 7,900 mi2. 

The U.S. Forest Service manages the GMUG National Forests, 

which comprise 1,100 mi2 (about 41 percent) within the basin. 

The BLM manages public lands with an area of about 790 mi2 

(29 percent) of public land; private ownership accounts for 

about 780 mi2 (29 percent) (Bureau of Land Management, 

2009). The land cover in the Lower Gunnison River Basin is 

dominated by forest (48 percent), rangeland (33 percent), and 

agriculture (8 percent) (Homer and others, 2004). Throughout 

the lower elevations in the Lower Gunnison River Basin, about 

6 percent (173 mi2) of the land is irrigated agriculture (Techni 

Graphic Systems, Inc., 2004). Coal mining occurs within 

the national forest in the North Fork of the Gunnison River. 

The GMUG has approximately 25 mi2 of Federal coal leases 

(U.S. Forest Service, 2011).

The Gunnison River is the largest tributary to the Colorado 

River in Colorado. Major storage facilities such as the Wayne 

N. Aspinall Federal Storage Unit (fig. 1; outside the study area) 

are situated in line with the main channel of the Gunnison River 

(Bureau of Reclamation, 2011). There are multiple beneficial 

uses of Aspinall Project water, including irrigation and domestic 

supplies, hydropower generation, and essential environmental 

and recreational uses in Colorado. The Gunnison Tunnel (fig. 1) 

delivers about 320,000 acre-ft per year from the Gunnison River 

to the Uncompahgre River during the irrigation season (April 

through October) (Colorado Department of Public Health and 

Environment, 2010). Nearly 173 mi2 of land are irrigated in 

the Lower Gunnison River Basin (Techni Graphic Systems, 

2004). The complex geology, combined with various landuse types such as irrigation and residential development, can 

greatly impact water-quality conditions in the Lower Gunnison 

River Basin.

The source water for the City of Grand Junction comes 

from Juniata Reservoir and Kannah Creek (fig. 1), which 

drain the western slopes of the Grand Mesa into the Lower 

Gunnison River Basin. Energy development (gas drilling) is 

increasing in scale on the slopes of the Grand Mesa (Bureau of 

Land Management, 2004). This type of development has the 

potential to affect groundwater and surface-water quality running off the Grand Mesa.

Land-Use Impacts

Agricultural land use in the study area is largely irrigated where 440 mi2

 of the 540 mi2 of agricultural land cover 

was irrigated in 2001 (Techni Graphic Systems, Inc., 2004; 

Homer and others, 2004). Irrigated agriculture is a main 

concern to water managers because of the additional dissolved solids (DS) that enter the watershed. Natural sources 

of DS include seeps or springs that originate from geological 

formations with high salt content. Salts are mobilized through 

dissolution, surface runoff, and deep percolation into the 

groundwater system that discharges to the river system as base 

flow (Kanzer and Merritt, 2008). The application of irrigation 

water to these agricultural lands increases the rate at which 

salts in the bedrock are dissolved and transported to streams 

(Prairie and others, 2005; Kenney and others, 2009). The history of salinity control efforts in the Gunnison and Colorado 

River Basins dates back to the 1970s when the Salinity 

Control Act, Public Law 93–320, prompted the creation of the 

Colorado River Basin Salinity Control Forum to investigate, 

plan, and construct projects to reduce salinity loading to the 

Colorado River (Bureau of Reclamation, 2009). Investigations and projects completed by the Colorado River Basin 

Salinity Control Forum refer to the entire drainage area of the 

Gunnison River or Colorado River, rather than the parts of the 

basins presented in this report. The Bureau of Reclamation 

(2011a) estimated that 47 percent of the salinity load in the 

entire Colorado River Basin is derived from natural sources, 

including geological formations, saline springs, and surface 

runoff; 37 percent results from irrigation; and the remaining 

16 percent results from reservoir-storage effects and municipal 

and industrial activities.

Selenium is another concern in the Lower Gunnison and 

Colorado River Basins. The National Irrigation Water Quality 

Program (NIWQP) is a multiagency program within the 

Department of the Interior that has performed investigations of 

various irrigation projects in the Western United States to determine whether irrigation drainage was having adverse effects 

on water quality and on fish and wildlife (Butler and Leib, 

2002). NIWQP studies were initiated in the Lower Gunnison 

River Basin in 1988. In 1997 the Colorado State Water Quality 

Control Commission revised the chronic aquatic-life criterion 

for dissolved selenium from 17 micrograms per liter (μg/L) 

to 4.6 μg/L. In response to this action and in cooperation with 

NIWQP, the Gunnison Basin Selenium Task Force was established in 1998 as a group of private, local, State, and Federal 

interests to develop ideas and projects for reducing selenium in 

the Lower Gunnison River Basin.

Previous Studies

The Piceance study area in western Colorado contains 

energy, mineral, and other natural resources that have been the 

subject of numerous studies and publications. Selected publications that relate to water resources within the study area are 

summarized herein.

The relationship between groundwater and surface water 

in the White River Basin has been evaluated in several studies. A study of simulated effects of oil shale development 

used digital models to evaluate the hydrologic system (Weeks 

and others, 1975). The study, specifically in the Piceance 

and Yellow Creek drainage areas, concluded that proposed 

oil shale development would have significant effects on the 

surface-water and groundwater systems. A study from 1977 

to 1981 of Piceance and Yellow Creeks collected physical and chemical data at perennial and intermittent streams 
Introduction 13

(Tobin and others, 1985). The study indicated that groundwater contributions to streams during medium and low 

flow result in increases in fluoride, sulfate, dissolved solids, 

arsenic, boron, lithium, and strontium. A study conducted 

during December 2000 used tracer-dilution techniques and 

synoptic-water-quality sampling to evaluate mass loading in 

Piceance Creek (Ortiz, 2002). Groundwater upwelling in the 

Alkali Flats area (fig. 1) contributed substantially to observed 

increases in constituent concentrations; however, losses in 

streamflow resulted in small increases in loads downstream on 

the study reach.

Trends and loads of DS, suspended sediment, and other 

constituents in the White River Basin have been conducted. A 

study from 1975 to 1988 of sediment transport, water-quality 

characteristics, and loads on the White River determined that 

snowmelt runoff from the headwaters of the White River 

dilutes and transports large concentrations of suspended 

sediment and dissolved solids in the central part of the basin 

(Tobin, 1993). A study of characteristics and trends of streamflow and dissolved solids in the White River Basin reported 

a decrease in annual-median-flow-adjusted concentrations of 

dissolved solids in the White River below Meeker from 1974 

through 1983 (Liebermann and others, 1989).

Water quality has been studied in springs and surface 

water in the Colorado River Basin. A study in the Colorado 

River Basin from 1981 to 1983 of discharge, water-quality, 

and radiochemical data collected at springs in the oil shale 

regions of the Roan and Parachute Creek Basins reported that 

springs were mixed-cation bicarbonate water types (Butler, 

1985). The study also concluded that springs located near oil 

shale mines or processing plants could be used for monitoring groundwater quality and quantity. In 2008, the USGS 

published a report of DS trends (1986–2003) in the Upper 

Colorado River Basin upstream from the Grand Valley Salinity 

Control Unit (Leib and Bauch, 2008). The report details results 

for trends in concentrations and loads of DS and selected 

major ions near the Grand Valley Salinity Control Unit. The 

largest decrease in salinity load was 6,590 tons per year 

(ton/yr) and occurred in the area between the Colorado River 

at Cameo, Colo., and the Colorado River above Glenwood 

Springs, Colo. Downward trends in DS load (11,200 ton/yr) 

were detected at the Gunnison River near Grand Junction, 

Colo., streamflow-gaging station. A USGS study from 2004 

to 2006 analyzed DS and selenium trends (concentrations and 

loads) in the Upper Colorado River Basin, specifically, in three 

tributaries to the Colorado River in the Grand Valley (Leib, 

2008). The report states that the reduction in annual DS load 

at Lewis Wash (fig. 1) could be the result of either salinitycontrol work or land-use change, particularly the conversion 

of agricultural land to residential development. A USGS study 

from 2000 to 2004 collected and analyzed water-quality data 

for the Government Highline Canal and Highline Lake, which 

are located in the Grand Valley area (Ortiz, 2005). Data were 

used to characterize the seasonal stratification patterns, waterquality chemistry, bacteria populations, and phytoplankton 

community structure in the lake. Highline Lake was reported 

as having strong thermal and dissolved-oxygen stratification 

patterns during the summer months, which likely released 

ammonia from the bottom sediments. Generally, the seasonal 

succession of phytoplankton was similar to that of other lakes 

in similar climates.

The importance and complexity of DS and selenium in 

the Gunnison River is reflected in the abundance of studies and 

publications on the topics. These efforts have included quantifying the natural component of the DS load as well as identifying 

trends over time in DS and selenium concentrations and loads. 

Salt loading from natural sources in the Gunnison River Basin 

was 542,000 ton/yr for water years 1914–1957 (a water year is 

from October 1 through the following September 30 and is designated by the year in which it ends), assuming the 1957 level of 

water-resources development (Iorns and others, 1965). Another 

study for the same period used a mass balance approach and 

reported that 431,000–463,000 tons of DS load were caused by 

natural sources (Mueller and Osen, 1988). The DS concentration and load results were reported in both studies for the site 

Gunnison River near Grand Junction, Colo. (streamflow-gaging 

station 09152500).

Studies that quantified DS trends over time relative to 

land-use changes have reported downward trends in DS at the 

Gunnison River near Grand Junction, Colo. (09152500) for 

different study periods. Liebermann and others (1989) quantified the DS trends at the Gunnison River near Grand Junction 

(streamflow-gaging station 09152500) based on the completion of the Blue Mesa Dam in 1965, the uppermost of the 

three dams that make up the Aspinall Unit. The Aspinall Unit 

is located outside of the study area upstream from the Lower 

Gunnison River Basin (fig. 1). The pre-reservoir period was 

1934–1965 and the post-reservoir period was 1966–1983, and 

they performed a step trend test to determine whether there 

were significant differences between the pre- and post-dam 

periods as well as trend tests within each of the two periods. 

A downward step trend of 119,000 tons (pre- and post-dam 

comparison) was reported at the Gunnison River near Grand 

Junction, Colo., site as a result of the construction and operation of Blue Mesa reservoir, but there were no significant 

trends within each of the two periods (Liebermann and others, 

1989). Streamflow and DS concentrations in the Gunnison 

River decreased during high flow (May–June) and increased 

during the low-flow period (August–March) as a result of 

Blue Mesa Reservoir. Butler and others (1996) reported a net 

downward trend of 146,000 tons of DS at Gunnison River 

near Grand Junction (streamflow-gaging station 09152500) 

from 1970 to 1993. Butler and others (1996) concluded that 

the measured decreases were not the result of DS control 

projects implemented by the Bureau of Reclamation and the 

Natural Resources Conservation Service. Leib and Bauch 

(2008) showed a downward trend of 201,600 tons in the 

Gunnison River near Grand Junction, Colo., for water years 

1986–2003. Schaffrath (2012) quantified trends at 15 sites in 

the Gunnison River Basin. Results indicated a downward trend 

of 247,000 tons from 1989 to 2004. The downward trend was 

smaller at 190,000 tons from 1989 to 2007, potentially indicating that DS concentration and load are leveling off.
14 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

The effect of converting previously irrigated agricultural 

land to urban land use was investigated during two recent 

studies (Mayo, 2008; Moore, 2011) in western Colorado. The 

Grand Valley study measured irrigation-water application 

and deep percolation on urban sites in Grand Junction, Colo., 

where deep percolation was defined as infiltration of water 

below the top 12 inches of soil (Mayo, 2008). The measurements were compared to water application and deep percolation data from agricultural sites provided by the Natural 

Resources Conservation Service. The study results indicated 

that conversion of land from agricultural use to urban residential use can result in a decrease in salt loading of 90 percent 

per developed acre. The second study compared DS concentrations and load between two sites on the Montrose Arroyo 

near Montrose, Colo. (Moore, 2011). One site was upstream 

and the other was downstream from increased urbanization. 

The previous land use was dominated by irrigated agriculture 

but included other land-use categories. There were no significant differences between DS at the two sites, which implies 

that urbanization had no effect on DS concentration or load at 

that scale.

A study in 2007 analyzed selenium load from 1978 to 2005 

in the Lower Gunnison River Basin in support of the development of total maximum daily loads (TMDLs) for selenium 

(Thomas and others, 2008). Results for the Uncompahgre River 

indicated that a reduction of 69 percent of the mean annual load 

of selenium for water years 2001–2005 was necessary to meet 

the water-quality standard for the Uncompahgre River at Delta, 

Colo., streamflow-gaging station.

Methods

The data compiled in the Web-accessible common data 

repository were analyzed to provide a baseline assessment of 

available water-resource data and aid in the development of 

regional monitoring strategies. Selected water-quality properties and constituents were compared to Federal and State standards or previous studies where applicable. When sufficient 

data were available, trends over time were analyzed and loads 

were calculated for those sites where there were also continuous streamflow data.

Compilation of Data

A repository of available water-quality data was compiled from local, State, and Federal agencies and private 

entities (consulting firms, energy, and mining companies). The data repository is accessible on the Internet at 

http://rmgsc.cr.usgs.gov/cwqdr/Piceance/index.shtml. Not all 

known data sources were loaded into the data repository for a 

variety of reasons, such as non-participation, non-electronic 

format, insufficient metadata, and late data submission. 

However, the repository represents the most comprehensive 

set of surface-water-quality data for the study area available as 

of August 2009. Data were evaluated for duplication (the same 

site, sample, or result submitted to the repository under two 

or more source agencies) and removed prior to analysis. Sites 

and water-quality data were evaluated to determine if it was 

appropriate to aggregate data if sites were within a 50-ft buffer 

of one another. The USGS NWIS Water-Quality User Manual 

was consulted for evaluating properties and constituents 

that can be recensored (assigned the value of “less than the 

censoring level”) if the stored value is zero and for properties 

and constituents that allow negative values (U.S. Geological 

Survey, 2011).

The data repository contained 1,433 surface-water sites, 

45,008 samples, and 1,144,808 water-quality results for the 

period from 1931 to 2009. A subset of data from the repository 

was extracted and checked for quality assurance for this report 

using the following criteria. Only water-quality data from the 

most recent 50 water years (1959 to 2009) were included, so 

data had to be collected after September 30, 1958. Sites were 

required to have five or more samples, collected over at least 

13 months so that seasonality would be represented. USEPA 

water-quality standards and guidelines were used to analyze 

a subset of the available constituents. Additionally, specific 

constituents of interest were analyzed based on stakeholder 

input, land-use factors, recommendations from the Colorado 

Department of Public Health and Environment (CDPHE) 

303d (table 2), and monitoring and evaluation lists (Colorado 

Department of Public Health and Environment, 2010). Lake 

sites were not included because of the lack of depth information associated with samples. When multiple samples were 

collected in a single day, such as stormwater sampling, the first 

sample was included and the remaining data were removed 

from the analysis. The final dataset used in this report included 

347 surface-water sites, 35,970 samples, and 228,242 waterquality results (app. 1). Limited metadata were available for 

much of the data, which limited the ability to evaluate the 

quality of the water-quality data. No distinctions between 

water-quality data collection methods or laboratory-analytical 

techniques were made owing to this limited metadata. Disparities between data from various sources resulting from these 

differences may bias the statistical results. Robust statistical 

methods were employed to limit these sources of bias on the 

statistical results.

Analysis of Data

The final dataset that resulted from the compilation of the 

data contained 347 sites and 33 constituents. These data were 

summarized using summary statistics and compared to USEPA 

and CDPHE recommendations and standards. Additional 

criteria were applied to select data for analysis of time trends 

and load calculations.
Methods 15

Table 2. Colorado Department of Public Health and Environment section 303(d) list of impaired waters and monitoring and evaluation list for the Piceance study area, western Colorado, 2011.[CDPHE, Colorado Department of Public Health and Environment; WBID, water-body identifier; E. coli, Escherichia coli; Fe, iron; Se, selenium; Trec, total recoverable; USFS, U.S. Forest Service; USGS, U.S. Geological Survey. Data from Colorado Department of Public Health and Environment (2011b)]

Segment CDPHE WBID Segment description Segment portion Clean Water Act Section 303(d) impairment 303(d) priority

LGunn_2 COGULG02 Gunnison River, Uncompahgre River to Colorado River all Se high

LGunn_8 COGULG08 Tributaries to Gunnison River, Kannah Creek Kannah Creek below

USGS station 09152000

Se high

NFkGunn_3 COGUNF03 North Fork of the Gunnison from Black Bridge above Paonia to the confluence within 

the Gunnison

all Se high

NFkGunn_5 COGUNF05 Hubbard, Terror, Minnesota and Leroux Creeks from USFS boundary to N. Fork. main stem 

of Jay Creek and main stem and tributaries of Roatcap Creek to the N. Fork

Leroux Creek,

Jay Creek,

Se high

L_Gunn_8 COGUNF06a Tributaries to the North Fork of the Gunnison River not on USFS lands Short Draw Se highNFkGunn_6b COGUNF06b Bear Creek, Reynolds Creek, Bell Creek, McDonald Creek, Cottonwood Creek, Love 

Gulch, Cow Creek, Dever Creek, German Creek, Miller Creek, Stevens Gulch, Big Gulch, Stingley Gulch and Alum Gulch not on national forest lands from the source to the North Fork of the Gunnison River

Cottonwood Creek Se high

Uncom_4b COGUUN04b Uncompahgre River, La Salle Road to Confluence Park all Se highUncom_4c COGUUN04c Uncompahgre River, Confluence Park to Gunnison River all Se highUncom_12 COGUUN12 Tributaries to Uncompahgre River, South Canal to Gunnison River all Se highLCol_2b COLCLC02b Colorado River, Rapid Creek to Gunnison River Humphrey

Backwater area

Se medium

LCol_3 COLCLC03 Colorado River, Gunnison River to state line all Se mediumLCol_4a COLCLC04a Tributaries to Colorado River, Roaring Fork to Parachute Creek except for specific segments all Se mediumLCol_10 COLCLC10 East Rifle Creek, West Rifle Creek and Rifle Creek, including tributaries from Rifle Gap to 

the Colorado River

all Se low

LCol_13b COLCLC13b Tributaries to Colorado River from Government Highline Canal Diversion to Salt Creek Salt Creek sediment lowLCol_13b COLCLC13b Tributaries to Colorado River from Government Highline Canal Diversion to Salt Creek 

except specific segments

all Se medium

LCol_13b COLCLC13b Tributaries to Colorado River from Government Highline Canal Diversion to Salt Creek 

except specific segments

Adobe Creek E. coli, Fe(Trec) high

LCol_13c COLCLC13c Walker Wildlife Area Ponds all Se mediumLCol_14c COLCLC14c Main stem of Roan Creek including all tributaries from Kimball Creek to the Colorado River Dry Fork Se lowLCol_19 COLCLC19 Lakes and reservoirs tributary to the Colorado River, Parachute Creek to the Colorado/Utah 

border

West Pond Orchard

Mesa Wildlife Area

Se high

White_9d COLCWH09d Sulphur Creek and tributaries from source to White River. Flag Creek and tributaries from 

the East Fork of Flag Creek to the White River

all Se low

White_22 COLCWH22 Tributaries to White River, Douglas Creek to Colorado-Utah border West Evacuation Wash,

Douglas Creek

sediment low
16 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Summary Statistics

Summary statistics were computed for each of the 347 

sites and the selected constituents, including the period of 

record, the number of observations, the number of censored 

observations, and minimum, 25th percentile, median (50th 

percentile), 75th percentile, and maximum values (app. 1). 

Most of the 33 constituents are dissolved, meaning the sample 

was filtered, unless otherwise stated. Unfiltered samples will 

be referred to as total or total recoverable. In addition, certain 

constituents are never filtered and include field properties (pH, 

temperature, dissolved oxygen, specific conductance). Constituents like E. coli and suspended sediment are also unfiltered 

as these are particulates carried in water. The determination of 

the chemical properties of waters can result in left-censored 

data (nondetects) because of analytical limits of the laboratory analysis. In a dataset of this breadth, there can be multiple 

forms of bias in nondetect data including antiquated methods 

for storing nondetects (zero and negative values) and changes 

in the meaning of less-than values (Helsel, 2005a). In an effort 

to reduce these sources of bias, zero-values were changed to 

the appropriate reporting limit for select constituents. Where 

multiple censoring levels exist for a single constituent, data 

were not edited to a common censoring level in this report 

(Helsel, 2005b). Instead, data were re-censored using the longterm method detection limit where applicable. This resulted 

in an improvement to the overall dataset but did not remove 

all instances of these forms of bias; therefore, these results 

should be considered with this in mind. Summary statistics 

were computed using Kaplan-Meier methods when no more 

than 50 percent of the observations were censored (Helsel, 

2005b). Maximum likelihood estimations were computed for 

greater than 50 observations and where 50 to 80 percent of 

the observations were censored. Regression-on-order statistics were computed for less than 50 observations where 50 to 

80 percent of the observations were censored. The data range, 

censoring levels, and maximum observation were reported 

where more than 80 percent of the observations were censored 

(Helsel, 2005b).

Comparison to Standards

Instream water-quality standards for surface water in 

Colorado have been established by the Water Quality Control Commission of the CDPHE to protect the beneficial uses 

of surface water, which include aquatic life, domestic water 

supply, agriculture, and recreation (Colorado Department of 

Public Health and Environment, 2010). The CDPHE provides 

basic standards (Regulation 31) and separates Colorado into 

13 planning and management regions for regulatory purposes, 

each with standards tabulated by stream-reach segment. 

Stream-segment descriptions for this study were used to assign 

each surface-water measurement site to a segment to apply the 

appropriate standards. Surface-water sites in the study area are 

located in one of the following three management regions: the 

Upper Colorado River Basin and North Platte River (Region 

12, Regulation 33), the Lower Colorado River Basin (Region 

11, Regulation 37), or the Gunnison and Lower Dolores River 

Basins (Region 10, Regulation 35). Not all constituents are 

regulated by established water-quality standards. The CDPHE 

has not established a water-quality standard for the constituent 

total phosphorus; therefore, the standard of 0.1 mg/L recommended by USEPA was used (U.S. Environmental Protection 

Agency, 2000). Data from the study area were compared to 

the CDPHE and USEPA standards to guide interpretation of 

surface-water quality, look for spatial patterns of standard 

exceedances, and obtain a broad understanding of waterquality conditions across the study area. The objective of this 

comparison was not to assess stream impairment or compliance with standards.

Each stream segment has a different standard and can be 

regulated for multiple beneficial uses. For example, a given 

segment may have a different standard for iron concentrations 

for drinking-water supply than for aquatic life. Standards can 

vary by season, elevation, or fish species believed to be present in the segment (for example, water temperature). Several 

segments that were matched to sites in the study area have 

temporary standards for certain constituents, particularly for 

selenium concentrations. Table 3 lists constituents and the 

standards for individual segments that were used to assess 

water-quality measurement sites in the study area.

The CDPHE has established two types of numeric waterquality standards: (1) fixed-value standards and (2) table-value 

standards (TVSs) (Colorado Department of Public Health and 

Environment, 2011). Fixed-value standards can be aquaticlife standards; USEPA maximum contaminant levels (MCLs); 

standards for domestic water supply; or recreation-based 

standards (table 3). An MCL is a legally enforceable standard 

that applies to drinking water from public water systems only. 

The TVSs are usually calculated values that are established for 

aquatic-life protection and include acute and chronic classifications. An acute standard is not to be exceeded by the 

concentration in a single sample or by the average concentration of all samples collected during a one-day period. For 

water temperature, the acute standard is the daily maximum, 

which is the highest 2-hour average temperature measured 

in a 24-hour period. A chronic standard is a value not to be 

exceeded by the concentration for either a single representative sample or by the average of all samples collected during 

a 30-day period. The chronic standard for water temperature 

is based on the average of equally spaced measurements (a 

minimum of three per day) made for seven consecutive days. 

The chronic standard is implemented in combination with a 

selected duration and frequency of recurrence. The TVSs for 

water temperature are specified for Regulation 37, the Lower 

Colorado River region, and are based on water temperature, 

fish species, and season. Acute and chronic TVSs based on 

pH and temperature have been established for total ammonia 

for cold- and warm-water stream segments. The TVSs have 

been established for trace elements based on stream hardness. 

The CDPHE hardness-dependent TVSs were calculated for 

samples analyzed for trace elements using either a hardness 
Methods 17

Table 3. Selected Colorado Department of Public Health and Environment instream water-quality standards for stream segments in the Piceance study area, western Colorado. Segments are listed only if a surface-water-measurement site was matched to the segment and contained data for the given constituent.—Continued[mg/L, milligrams per liter, °C, degrees Celsius; col/mL, colonies per 100 milliliters; DM, daily maximum; MWAT, maximum weekly average temperature; TVS, table-value standard; MCL; maximum contaminant level; μg/L, micrograms per liter; sc, sculpin. Water-quality standards are from the Colorado Department of Public Health and Environment (2011) except for the recommended total phosphorus level, which is from the U.S. Environmental Protection Agency (2000)]

Physical

property or

constituent

(units)

Instream water-quality standard

Stream segment Type Value1 Qualification

Field parameters

pH (standard units) Aquatic life 6.5–9.0 allDissolved oxygen

(mg/L)

Aquatic life 5.0 Regulation 35, Lower Gunnison River: 4a, 4b and North Fork Gunnison River: 6b and Uncompahgre River: 4b, 12

Regulation 37, Lower Colorado River: 2a, 2b, 3, 4d, 13a, 13b, 14c and White River: 11, 12, 13b, 13c, 15, 16, 21, 22

6.0 Regulation 33, Upper Colorado River: 3

Regulation 35, Lower Gunnison River: 1, 2, 3, 5, 6, 7, 8, 10 and North Fork Gunnison River: 1, 2, 3, 4, 5Regulation 37, Lower Colorado River: 1, 5, 6, 7a, 7b, 8, 9b, 11a, 11b, 11d, 11e, 11f, 11g, 11h, 14a, 15, 16, 17a and 

White River: 4, 7, 9a, 9c, 14a, 14b, 17, 18, 20

7.0 spawning 

season only

Regulation 33, Upper Colorado River: 3Regulation 35, Lower Gunnison River: 1, 2, 3, 5, 6, 7, 8, 10 and North Fork Gunnison River: 1, 2, 3, 4, 5Regulation 37, Lower Colorado River: 1, 5, 6, 7a, 7b, 8, 9b, 11a, 11b, 11d, 11e, 11f, 11g, 11h, 14a, 15, 16, 17a and 

White River: 4, 7, 9a, 9c, 14a, 14b, 17, 18, 20

Water temperature

(°C)

Aquatic life 17.0

(MWAT3)

only for sites at 

greater than 7,000 feet 

elevation in listed 

segments

Regulation 35, Lower Gunnison River: 3, 7, 8 and North Fork Gunnison River: 4, 5, 6a, 6b

Aquatic life, cold class 1 or 2 20.0

(MWAT3)

Regulation 35, Lower Gunnison River: 1, 3, 5, 6, 7, 8,10 and North Fork Gunnison River: 1, 2, 3, 4, 5

Aquatic life, warm class 1 or 2 30.0

(MWAT3)

Regulation 35, Lower Gunnison River: 2, 4a, 4b and North Fork Gunnison River: 6a, 6b and Uncompaghre: 4b, 12

Aquatic life Cold Stream Tier I

(June–September)

TVS, 21.2

(acute, DM2)

Regulation 37, Lower Colorado River: 5, 6, 7a, 8, 11a, 11b, 11d, 11e, 11f, 11g, 14a and White River: 4, 9a, 9c, 14a, 

17, 20

Aquatic life Cold Stream Tier I

(October–May)

TVS, 13.0

(acute, DM2)

Regulation 37, Lower Colorado River: 5, 6, 7a, 8, 11a, 11b, 11d, 11e, 11f, 11g, 14a and White River: 4, 9a, 9c, 14a, 

17, 20

Aquatic life Cold Stream Tier II

(April–October)

TVS, 23.8

(acute, DM2)

Regulation 33, Upper Colorado River: 3Regulation 37, Lower Colorado River: 1, 4a, 4d, 7b, 10, 11h,14b, 16, 17a and White River: 7, 14b, 18

Aquatic life Cold Stream Tier II

(November–March)

TVS, 13.0

(acute, DM2)

Regulation 33, Upper Colorado River: 3Regulation 37, Lower Colorado River: 1, 4a, 4d, 7b, 10, 11h,14b, 16, 17a and White River: 7, 14b, 18

Aquatic life Cold Lake

(April–December)

TVS, 21.2

(acute, DM2)

Regulation 37, Lower Colorado River: 9b

Aquatic life Cold Lake

(January–March)

TVS, 13.0

(acute, DM2)

Regulation 37, Lower Colorado River: 9b

Aquatic life Warm Stream Tier II

(March–November)

TVS, 29.0

(acute, DM2)

Regulation 37, Lower Colorado River: 2a, 2b, 3,13b,14c and White River: 12, 13c, 15, 21

Aquatic life Warm Stream Tier II

(December–February)

TVS, 14.5

(acute, DM2)

Regulation 37, Lower Colorado River: 2a, 2b, 3,13b,14c and White River: 12, 13c, 15, 21

Aquatic life Warm Stream Tier IV

(March–November)

TVS, 28.6

(acute, DM2)

Regulation 37, Lower Colorado River: 13a and White River: 13b, 16, 22

Aquatic life Warm Stream Tier IV

(December–February)

TVS, 14.3

(acute, DM2)

Regulation 37, Lower Colorado River: 13a and White River: 13b, 16, 22
18 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009 Table 3. Selected Colorado Department of Public Health and Environment instream water-quality standards for stream segments in the Piceance study area, western Colorado. Segments are listed only if a surface-water-measurement site was matched to the segment and contained data for the given constituent.—Continued [mg/L, milligrams per liter, °C, degrees Celsius; col/mL, colonies per 100 milliliters; DM, daily maximum; MWAT, maximum weekly average temperature; TVS, table-value standard; MCL; maximum contaminant level; μg/L, micrograms per liter; sc, sculpin. Water-quality standards are from the Colorado Department of Public Health and Environment (2011) except for the recommended total phosphorus level, which is from the U.S. Environmental Protection Agency (2000)] Physical property or constituent (units) Instream water-quality standard Stream segment Type Value1 Qualification Field parameters—Continued Aquatic life Warm Lakes (April–December) TVS, 29.3 (acute, DM2

)

Regulation 37, White River: 11

Aquatic life Warm Lakes

(January–March)

TVS, 14.6

(acute, DM2

)

Regulation 37, White River: 11

Major ions

Sulfate, dissolved

(mg/L)

Domestic

water supply

250 Regulation 33, Upper Colorado River: 3

Regulation 35, Lower Gunnison River: 1, 3, 4a, 4b, 8 and North Fork Gunnison River: 1, 2, 4, 5, 6bRegulation 37, Lower Colorado River: 1, 2a, 2b, 7a, 7b, 8, 9b, 11a, 11e, 14c, 15, 16, 17a and White River: 4, 7, 9a, 

11, 12, 21

480 Regulation 35, Lower Gunnison River: 2

Chloride, 

dissolved(mg/L)

Domestic

water supply

250 Regulation 33, Upper Colorado River: 3

Regulation 35, Lower Gunnison River: 1, 2, 3, 4a, 4b, 7, 8 and North Fork Gunnison River: 1, 2, 4, 5, 6bRegulation 37, Lower Colorado River: 1, 2a, 2b, 7a, 7b, 8, 9b, 11a, 11e, 14c, 15, 16, 17a and White River: 4, 7, 9a, 

11, 12, 15, 16, 21

Nutrients

Nitrate, dissolved

(mg/L as N)

MCL, Domestic

water supply

10 Regulation 33, Upper Colorado River: 3

Regulation 35, Lower Gunnison River: 1, 2, 4a, 7, 8 and North Fork Gunnison River: 2Regulation 37, Lower Colorado River: 1, 2a, 2b, 4d, 7a, 7b, 8, 9b, 11a, 11e, 11f, 14c, 15, 16, 17a and White River: 

4, 7, 9a, 11, 12, 21

Nitrate, dissolved

(mg/L as N)

Agriculture 100 Regulation 35, Lower Gunnison River: 1, 2, 3, 4a, 4b, 7, 8 and North Fork Gunnison River: 1, 2, 4, 5, 6b

Regulation 37, Lower Colorado River: 1, 2a, 2b, 7a, 7b, 8, 9b, 11a, 11e, 14c, 15, 16, 17a and White River: 4, 7, 9a, 

11, 12, 15, 16, 21

Ammonia, total

(mg/L as N)

Aquatic life TVS

(acute, chronic) 

Regulation 35, Lower Gunnison River: 6, 10 and North Fork Gunnison River: 3 and Uncompaghre River: 4b, 12Regulation 37, Lower Colorado River: 11b, 11d, 11g, 13a, 13b and White River: 13b, 13c, 14a, 14b, 15, 16, 17, 

18, 20

Phosphorus, total

(mg/L as P)

Recommended 0.1 all

Trace elements

Copper, dissolved 

(μg/L)

Aquatic life TVS

(acute, chronic)

Regulation 33, Upper Colorado River: 3Regulation 35, Lower Gunnison River: 1, 2, 3, 4a, 4b, 5, 6, 7, 8, 10 and North Fork Gunnison River: 1, 2, 3, 4, 5, 6b 

and Uncompaghre River: 4b, 12

Regulation 37, Lower Colorado River: 1, 2a, 2b, 3, 5, 6, 7a, 7b, 8, 9b, 11a, 11d, 11f, 11h, 13b, 14a, 14c, 15, 16, 17a 

and White River: 4, 7, 9a, 9c, 12, 13b, 13c, 14a, 14b, 15, 16, 17, 18, 20, 21

Water and Fish 1,300 (acute) Regulation 35, North Fork Gunnison River: 6b

Copper, total

recoverable(μg/L)

Aquatic life 200 (chronic) Regulation 37, Lower Colorado River: 11b, 11e, 11g, 13a and White River: 22
Methods 19

Table 3. Selected Colorado Department of Public Health and Environment instream water-quality standards for stream segments in the Piceance study area, western Colorado. Segments are listed only if a surface-water-measurement site was matched to the segment and contained data for the given constituent.—Continued[mg/L, milligrams per liter, °C, degrees Celsius; col/mL, colonies per 100 milliliters; DM, daily maximum; MWAT, maximum weekly average temperature; TVS, table-value standard; MCL; maximum contaminant level; μg/L, micrograms per liter; sc, sculpin. Water-quality standards are from the Colorado Department of Public Health and Environment (2011) except for the recommended total phosphorus level, which is from the U.S. Environmental Protection Agency (2000)]

Physical

property or

constituent

(units)

Instream water-quality standard

Stream segment Type Value1 Qualification

Trace elements—Continued

Iron, dissolved

(μg/L)

Domestic

water supply

300 (chronic) Regulation 33, Upper Colorado River: 3

Regulation 35, Lower Gunnison River: 1, 2, 3, 4a, 4b, 8, 10 and North Fork Gunnison River: 1, 2, 4, 5, 6bRegulation 37, Lower Colorado River: 1, 2a, 2b, 4d, 5, 6, 7a, 7b, 8, 9b, 11a, 11e, 11f, 14a, 14c, 15, 16, 17a and 

White River: 4, 7, 9a, 9c, 12, 21

Iron, total

recoverable(μg/L)

Aquatic life 1,000 (chronic) Regulation 33, Upper Colorado River: 3

Regulation 35, Lower Gunnison River: 1, 2, 3, 4a, 4b, 6, 7, 8, 10 and North Fork Gunnison River: 1, 2, 3, 4, 5, 6a, 

6b and Uncompaghre River: 4b, 12

Regulation 37, Lower Colorado River: 1, 2a, 2b, 3, 4d, 5, 6, 7a, 7b, 8, 9b, 11a, 11d, 11f, 11h, 13b, 14a, 14c, 15, 16, 

17a and White River: 4, 7, 9a, 9c, 12, 13b, 13c, 14a, 14b, 15, 16, 17, 18, 20, 21

existing ambient

quality (chronic)

Regulation 35, North Fork Gunnison River: 6b

Lead, dissolved

(μg/L)

Aquatic life TVS

(acute, chronic)

Regulation 35, Lower Gunnison River: 1, 2, 3, 4a, 4b, 5, 6, 7, 8, 10 and North Fork Gunnison River: 1, 2, 3, 4, 5, 6a, 

6b and Uncompaghre River: 4b, 12

Regulation 37, Lower Colorado River: 1, 2a, 2b, 3, 5, 6, 7a, 7b, 8, 9b, 11a, 11d, 11f, 11h, 13b, 14a, 14c, 15, 16, 17a 

and White River: 4, 7, 9a, 9c, 12, 13b, 13c, 14a, 14b, 15, 16, 17, 18, 20, 21

Lead, total

recoverable(μg/L)

Aquatic life 100 (chronic) Regulation 37, Lower Colorado River: 11b, 11e, 11g, 13a and White River: 22

Selenium,

dissolved(μg/L)

Aquatic life TVS, 18.4 

(acute),

4.6 (chronic)

Regulation 33, Upper Colorado River: 3Regulation 35, Lower Gunnison River: 1, 2, 3, 4a, 4b, 5, 6, 7, 8, 10 and North Fork Gunnison River: 1, 2, 3, 4, 5, 6a, 

6b and Uncompaghre River: 4b, 12

Regulation 37, Lower Colorado River: 1, 2a, 2b, 3, 4d, 5, 6, 7a, 7b, 8, 11a, 11d, 11f, 11h, 13b, 14a, 14c, 15, 16, 17a 

and White River: 4, 7, 9a, 9c, 12, 13b, 13c, 14a, 14b, 15, 16, 17, 18, 20, 21

5.7 (chronic) temporary,

expires 12/31/2012

Regulation 35, North Fork Gunnison River: 3

8.4 (chronic) temporary,

expires 12/31/2012

Regulation 35, Lower Gunnison River: 2

9.3 (chronic) temporary,

expires 12/31/2012

Regulation 35, Lower Gunnison River: 7

20 (chronic) temporary,

expires 12/31/2012

Regulation 35, Uncompaghre River: 4b

Water and Fish 170 (acute) Regulation 35, North Fork Gunnison River: 6b

Fish ingestion 4,200 (acute) Regulation 37, White River: 17

Selenium, total

recoverable(μg/L)

Aquatic life existing ambient

quality (chronic)

temporary,

expires 12/31/2012

Regulation 35, Lower Gunnison River: 4a and North Fork Gunnison River: 5, 6b and Uncompaghre River: 12

20 (chronic) Regulation 37, Lower Colorado River: 11b, 11e, 11g, 13a and White River: 22
20 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009 Table 3. Selected Colorado Department of Public Health and Environment instream water-quality standards for stream segments in the Piceance study area, western Colorado. Segments are listed only if a surface-water-measurement site was matched to the segment and contained data for the given constituent.—Continued [mg/L, milligrams per liter, °C, degrees Celsius; col/mL, colonies per 100 milliliters; DM, daily maximum; MWAT, maximum weekly average temperature; TVS, table-value standard; MCL; maximum contaminant level; μg/L, micrograms per liter; sc, sculpin. Water-quality standards are from the Colorado Department of Public Health and Environment (2011) except for the recommended total phosphorus level, which is from the U.S. Environmental Protection Agency (2000)] Physical property or constituent (units) Instream water-quality standard Stream segment Type Value1 QualificationTrace elements—Continued Zinc, dissolved (μg/L) Aquatic life TVS (acute, chronic) Regulation 33, Upper Colorado River: 3 Regulation 35, Lower Gunnison River: 1, 2, 3, 4a, 4b, 5, 6, 7, 8, 10 and North Fork Gunnison River: 1, 2, 3, 4, 5, 6a, 6b and Uncompaghre River: 4b, 12 Regulation 37, Lower Colorado River: 1, 2a, 2b, 3, 5, 6, 7a, 7b, 8, 9b, 11a, 11d, 11h, 13b, 14a, 14c, 15, 16, 17a and White River: 4, 7, 9a, 9c, 12, 13b, 13c, 14a, 14b, 15, 16, 17, 18, 20, 21 TVS (sc) (chronic) Regulation 33: 3 Regulation 35, North Fork Gunnison River: 1, 2 Regulation 37, Lower Colorado River: 7a, 15 and White River: 4 Water and Fish 7,400 (acute) Regulation 35, North Fork Gunnison River: 6b Fish ingestion 26,000 (acute) Regulation 37, White River: 17 Zinc, total recoverable (μg/L) Aquatic life 2,000 (chronic) Regulation 37, Lower Colorado River: 11b, 11e, 11g, 13a and White River: 22 Microorganisms Escherichia coli (col/100 mL) Recreation, Class N (Not Primary Contact Use) 126/1004 Regulation 35, Lower Gunnison River: 1, 2, 4b, 8 and North Fork Gunnison: 3 (April 1 to September 30) Regulation 37, Lower Colorado River: 1, 2a, 2b, 13b and White River: 7 (March 2 to November 30), 12 Recreation, Class P (Potential Primary Contact Use) 205/1004 Regulation 35, North Fork Gunnison River: 5 Regulation 37, Lower Colorado River: 14c and White River: 7 (December 1 to March 1), 14b, 15 Recreation, Class E (Existing Primary Contact) 630/1004 Regulation 35, Lower Gunnison River: 4a and Uncompaghre River: 4b and North Fork Gunnision: 3 (October 1 to March 30) Regulation 37, White River: 13b, 13c

1Table value standards for trace elements vary with hardness. See Colorado Department of Public Health and Environment (2011).2Daily maximum (DM) is the highest two-hour average water temperature recorded during a given 24-hour period (Colorado Department of Public Health and Environment, 2011).3Maximum weekly average temperature (MWAT) is the maximum average of multiple, equally spaced, daily temperatures over seven consecutive days with a minimum of three data points spaced equally 

throughout the day. It is calculated from the optimum and upper temperatures tolerated by a species (Colorado Department of Public Health and Environment, 2011).

4Attainment of the standard is based on a two-month geometric mean of the data. 
Methods 21

value measured for the same sample or a calculated hardness 

derived from calcium and magnesium data for that sample. 

When hardness values exceed 400 mg/L, a hardness of 

400 mg/L (113 mg/L for zinc, sculpin standards) was used to 

determine trace element standards (Sarah Johnson, Colorado 

Department of Public Health and Environment, written commun., September 26, 2011).

Trend Analysis and Load Calculation

Data were selected from the original dataset of 347 sites 

for analysis of trends based on several criteria. Trend analysis 

using the method chosen was best for periods of 20 years or 

less; thus, data had to be collected after October 1, 1989, with 

a minimum of 8 years of continuous data. Data from 68 of 

the 347 sites met these criteria. Separate techniques for trends 

analysis were used depending on the constituent. Monotonic 

trends in field properties (water temperature, dissolved oxygen, and pH) were assessed using the seasonal Kendall test, a 

nonparametric technique (Hirsch and others, 1982; Helsel and 

Hirsch, 2002). Regression models define the relation between 

the concentration of a given water-quality constituent with 

explanatory variables such as streamflow, seasonality, and 

time (Helsel and Hirsch, 2002; Cohn, 2005). The relation of 

concentration with time in the regression model describes the 

time trend.

The load of a given constituent is the mass of the constituent transported in the water. Regression models, which are 

parametric techniques, were used for estimating loads from the 

concentration data. Loads calculated from the field properties 

are either not possible (temperature or pH) or not meaningful 

(dissolved oxygen).

Parametric techniques assume a normal distribution 

of the data, while nonparametric techniques do not require 

the data to be normally distributed (Helsel and Hirsch, 

2002). Where there is a perfect normal distribution of the 

data, parametric tests have more statistical power. However, 

water-quality data will only approximate a normal distribution, so the statistical power in parametric and nonparametric 

techniques is similar for analysis of water-quality data (Helsel 

and Hirsch, 2002). Statistical power, in this analysis, refers to 

the probability of rejecting the null hypothesis that there is no 

time trend when there is a net trend (Alley, 1988; Hirsch and 

others, 1991).

Seasonal Kendall Test

Monotonic trends in temperature, dissolved oxygen, and 

pH data were tested using the seasonal Kendall test (Hirsch 

and others, 1982, 1991; Schertz and others, 1991; Helsel and 

Hirsch, 2002). The seasonal Kendall test accounts for seasonal 

variability in the field property data through the separation 

and comparison of data by each season. The seasonal Kendall 

test was applied using the computer program Estimate Trend 

(ESTREND) (Schertz and others, 1991), which was modified 

to run in the S-Plus Statistical Package (TIBCO Software, Inc., 

1998–2008).

To run ESTREND, sites had to have a minimum of 

8 years of record with 10 or more samples and less than 

50 percent of the data could be censored. A total of 30 sites 

had sufficient data to meet these criteria for at least one of the 

three field properties. Seasonality was characterized within the 

ESTREND interface with input from the user. For the analysis 

presented in this report, a sampling frequency of 2 to 4 months 

was required, which allow trends to be run with 6 or 4 seasons, respectively. The choice of the number of seasons was 

determined using the first and last fifths of the record (Lanfear 

and Alexander, 1990; Schertz and others, 1991). If the site did 

not have at least one sample for each of at least four seasons 

in the first and last fifths of the record, the analysis was not 

completed. The user defines adequate seasonal characterization within ESTREND. For example, each season of every 

year for a 10-year study period is compared to that same 

season for all other years. The user for this analysis required 

that at least 50 percent of possible seasonal comparisons were 

possible and that at least 3 of 4 seasons or 5 of 6 seasons must 

meet the 50 percent criteria to qualify for analysis (Schertz and 

others, 1991).

The seasonal Kendall tests for the significance of 

Kendall’s tau, which in this case is testing time against concentration. The test is completed on each of the 4 to 6 seasons, the results are combined, and the resulting test statistic 

is evaluated against a standard normal distribution (Mann, 

1945; Kendall, 1975; Hirsch and others, 1982; Schertz and 

others, 1991; Helsel and Hirsch, 2002). The p-value associated with Kendall’s tau was used to determine the significance 

of a time trend, where the p-value is a measure of the probability of incorrectly rejecting the null hypothesis. The null 

hypothesis is that the probability distribution of the random 

concentration variable has not changed over time. The test 

statistic is adjusted in the ESTREND program to account for 

serial correlation among the seasons and compute a corrected 

p-value. The trend was considered highly significant when the 

corrected p-value was less than 0.01 and significant when the 

corrected p-value was greater than 0.01 and less than or equal 

to 0.05. The trend direction from the seasonal Kendall test is 

the sign on the slope, which is computed as the median of all 

slopes between data pairs within the same season (Sen, 1968; 

Schertz and others, 1991; Helsel and Hirsch, 2002). The slope 

describes the monotonic trend observed throughout the entire 

trend period instead of an average annual slope, and the trend 

is not necessarily linear.

Trends in field properties or concentrations can be due to 

variability in streamflow quantity or timing. Where adequate 

streamflow data were available and the amount of censored 

water-quality data was less than 8 percent, the field property 

data were flow adjusted to account for the variability that was 

related to streamflow (Helsel and Hirsch, 2002). The flowadjustment portion of this analysis is derived from the relation 

between streamflow and the field property result where the 

flow-adjusted data are the residuals from the relation. The 

relation between streamflow and the field property data was 

significant when the p-value on the streamflow term was less 
22 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

than or equal to 0.05. The ESTREND program has 13 flowadjustment models, and the best model was chosen based on 

the PRESS (prediction sum of squares) statistic (Myers, 1986; 

Schertz and others, 1991). The best model was the model with 

the minimum PRESS value, which indicates that the model 

has the lowest prediction error among the models compared. 

Residual plots were inspected qualitatively to assure that 

regression assumptions were met. Approximate normality of 

model residuals was apparent when the normal-probability 

plot was approximately linear relative to a 1:1 line and the 

plots of the residuals have no pattern and show uniformity of 

scatter (homoscedacity). Flow-adjusted analysis better quantifies changes in the field property over time that are not the 

result of changes in streamflow; therefore, where both trend 

tests were evaluated, preference was given to flow-adjusted 

trend results when the relation between streamflow and the 

field property was significant.

Regression Model

Additional selection criteria were applied to the dataset of 

68 sites for analysis using the regression model. A total of 28 

sites met the criteria of having a minimum of 8 years of record 

with at least 20 observations and less than 80 percent censoring of the data (Runkel and others, 2004).

Trends in concentration data were tested using regression models developed for each site, where constituent load 

was the response variable. The models were used to calculate 

annual load of each constituent. Concentrations are a mass 

per known volume of a constituent, and load represents the 

mass of the constituent in the river per unit time. Load (in 

tons or pounds) is computed by multiplying the concentration 

(milligrams or micrograms per liter) by the streamflow (cubic 

feet per second) and a unit conversion constant. Loads can 

be estimated for any day when a sample has been collected 

by assuming that the concentration represents the daily mean 

concentration. A regression model is used for the days when 

no sample was collected.

The regression model used for trend analysis was 

applied using a USGS statistical program, LOADEST (Load 

Estimation), that was developed by Runkel and others (2004). 

S-LOADEST is a version of the LOADEST software developed to run as a plug-in program to the PC-based statistical 

software package Spotfire S+ and was used in this study 

(TIBCO Software, Inc., 1998–2008). S-LOADEST uses up 

to six explanatory variables to build a regression model that 

defines the relation of a constituent load to streamflow, time, 

and season. The inclusion of streamflow in the regression 

meant that there had to be existing streamflow associated with 

each sample included in this part of the trend analysis. The 

resulting general equation form used in this analysis is similar 

to Runkel and others (2004), Cohn (2005), and Dalby (2006) 

and is represented below in equation 1.

ln L = b0 +(lnQ – lnQ*) + b2 (t – t*)

+ b3 (sin(2πT)) + b4 (cos(2πT)) + e (1)

where

L is the load, in tons, pounds, or million colonies;

b0 is the regression equation intercept;

bn is the coefficient on the nth regression variable, where 

n is 1 through 4;

Q is a streamflow term, in cubic feet per second;

Q* is the streamflow centering value, in cubic feet 

per second;

t is time, in decimal years;

t* is the time centering value from the calibration 

dataset, in decimal years;

T is the decimal portion of the year starting January 1;

e is the error associated with the regression equation;

sin is the sine; and

cos is the cosine.

The model is developed using a calibration dataset 

that includes the date of the periodic sample collection, the 

associated value of concentration, and a streamflow value 

associated with the sampling date. The input values for 

concentration and streamflow were log transformed to meet 

the assumptions of normality and constant variance (Hirsch 

and others, 1991). Quadratic terms for decimal time and (or) 

streamflow were significant variables in some of the final 

selected model equations. However, with both the linear and 

quadratic terms in the equation, the possibility of multicollinearity increases, which inflates the variance in the associated coefficients. Streamflow and decimal time were centered 

to reduce the likelihood of multicollinearity and to ensure 

orthogonality in the streamflow and decimal time variables 

(Cohn and others, 1992). Compensation for differences in seasonal flux was accomplished, where significant, using Fourier 

series (Runkel and others, 2004; Cohn, 2005; Dalby, 2006). 

Fourier series uses sine and cosine terms to describe continual 

changes over the seasonal period. Model coefficients (bn) were 

estimated using adjusted maximum likelihood estimation 

(Runkel and others, 2004).

The p-value associated with the model coefficient on the 

time parameter(s) was used to determine the significance of a 

time trend. The p-value associated with model coefficient(s) is 

the probability of obtaining the computed parameter coefficient when the null hypothesis is true, where the null hypothesis is that the coefficient is zero. The trend was considered 

highly significant when the p-value for the time term(s) was 

less than 0.01 and significant when the p-value was greater 

than 0.01 and less than or equal to 0.05. The sign (positive or 

negative) on the model coefficient(s) was used to determine 

the net direction of the trend. The time term in the model 

represents the trend over time for concentration and load and 

accounts for flow and seasonal variability. The net direction 

was only presented when the p-value indicated that the linear 

time term was significant. When quadratic time was significant, the trend was referred to as parabolic. The water year 

when the slope of the parabola was zero was presented as the 

year when the direction changed. The zero-slope year and the 
Characterization and Data-Gap Analysis of Surface-Water Quality 23

directions of the trend before and after the zero-slope year 

were visually determined using plots of the model line without 

streamflow or seasonality terms. The model line describes the 

mean response of the concentration and load variable relative 

to the explanatory variables (time, streamflow, and seasonality) that were significant.

The final model equations were obtained by iteration 

using the option that is built into S-LOADEST that chooses 

the best model from nine model options made up of varying 

combinations of the variables listed in equation 1. The best 

model has the lowest Akaike Information Criteria (Runkel 

and others, 2004). S-LOADEST outputs diagnostic plots and 

statistics that were used to determine whether the calibration 

data met the assumptions of normality. The plots included a 

normal-probability plot and plots of the standardized residuals. 

Normality of model residuals was apparent when the normalprobability plot was approximately linear relative to a 1:1 line 

and the plots of the residuals have no pattern and show uniformity of scatter (homoscedacity). The plots were assessed 

qualitatively by the authors of this report. The criteria for the 

model statistics were that the variance inflation factor had to be 

less than 10 for each parameter in the model; serial correlation 

of the residuals had to be less than 0.6 and estimated residual 

variance had to be less than 1. Additionally, the p-values of the 

model coefficients had to be significant, or less than 0.05, to 

be included in the final model (app. 2). This final criterion had 

two exceptions: (1) only one of the model coefficients on the 

sine-cosine pair of the Fourier series had to be significant for 

the pair to be included in the model and (2) the linear time term 

was included anytime quadratic time was significant, even if 

the linear time was not significant. If the final model failed any 

of these diagnostics, results from the trend analysis were not 

presented. This scenario may indicate that more data might be 

required or a more randomized sampling approach might be 

needed to acquire a normal distribution of data.

Annual loads were used for a regional loading analysis. 

Using the selected form of equation 1 that was unique for each 

site and an estimation dataset with daily streamflow values, 

daily load and concentration were estimated. Annual loads 

were the sum of the daily loads for the water year. Each site and 

constituent had different study periods for trend analysis and, 

in some cases, the daily streamflow record had missing years; 

therefore, a comparison of sites required the selection of a common year among the sites based on the average annual streamflows for each site. Discussion of the loads using a common 

year provided the opportunity to describe sources of the constituent of interest. For each constituent described in the regional 

loading analysis, the average annual streamflow was calculated 

for each site. The average annual streamflow was calculated for 

the common study period of all the sites where the same constituent was analyzed. For example, the Colorado River Basin had 

four DS sites that had sufficient data for trend analysis and load 

calculation. The longest study period was 1990 to 2009 and the 

shortest was 1992 to 2002. Thus, the average annual streamflow 

for those four sites was calculated for the period 1992 to 2002. 

The one year within that period was chosen that most closely 

matched the average annual streamflow for each site. That 

common year was the year that represented the common study 

period for that constituent and basin.

Temporal trends have both a statistical significance 

and an environmental significance, but this distinction is 

often a subjective decision based on the context of the current stream conditions. Review of trend summaries requires 

consideration of the specific constituent of concern and any 

corresponding standard.

Characterization and Data-Gap 

Analysis of Surface-Water Quality

Surface-water quality can be affected by natural and 

human factors. Natural factors affecting water quality include 

but are not limited to geology, soil type, vegetation, streamflow, precipitation, and climate. Human factors can include 

activities such as urbanization, agriculture, and other types 

of land development, including energy development and 

infrastructure. Potential effects of land-use activities on water 

quality may include changes in streamflow, changes in DS 

concentration and load, detection of chemicals associated with 

energy development, and increases in sediment in streams that 

can potentially transport chemicals that have adhered to the 

sediment. The relation between land use and surface-water 

quality is complex and often requires special monitoring 

efforts to identify specific sources contributing to changes in 

surface-water quality. Land and water-use managers need a 

better understanding of the relationship between land use and 

water quality. The descriptions of surface-water quality in this 

study are designed as an inclusive approach to help understand 

changes in the Piceance study area. Data gaps and limitations 

might inhibit the analysis from conveying specific conclusions that identify pollution sources or their immediate effects 

within the study area.

Summary Statistics and 

Comparison to Standards

Summary statistics and water-quality exceedances are 

discussed by basin to provide a general overview of water 

quality (app. 1). Throughout the Piceance study area, waterquality constituent sampling was variable among basins. Summary statistics and comparison to standards were provided for 

347 sites. The locations of these sites are shown on plate 1 and 

exceedances of water-quality standards are shown on plates 2 

through 5. The constituents summarized include field properties (pH, temperature, dissolved oxygen), nutrients (ammonia, 

nitrate, orthophosphate, total phosphorus, dissolved organic 

carbon), major ions (calcium, magnesium, sodium, potassium, chloride, sulfate, fluoride, silica, alkalinity, bicarbonate, carbonate, dissolved solids), dissolved trace elements 

(copper, iron, lead, zinc, selenium), total recoverable iron, 
24 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Escherichia coli (E. coli), suspended sediment, and BTEX 

compounds (benzene, toluene, ethylbenzene, xylene). The 

number of observations, number of censored observations, 

period of record, minimum, 25th percentile, median (50th percentile), 75th percentile, maximum values, and, where appropriate, information on censored values for each constituent, 

and comparison to water-quality standards are provided in 

appendix 1.

The collection of field properties is an important component to all water-quality sampling in order to properly characterize water-quality results. The majority of sites had information on field properties (app. 1, pl. 2). For the entire study 

area, 316 sites had temperature data collected between 1959 

and 2009: 41 sites in the White River Basin, 165 sites in the 

Colorado River Basin, and 110 sites in the Lower Gunnison 

River Basin. Median temperature values ranged from 0.5 to 

17.0 degrees Celsius (°C) in the White River Basin, from 

4.0 to 19.0 °C in the Colorado River Basin, and from 0.7 

to 19.5 °C in the Lower Gunnison River Basin. There were 

326 values out of a total of 32,006 values in the study area that 

exceeded the aquatic-life standard for daily maximum water 

temperature: 220 values in the White River Basin and 106 values in the Colorado River Basin. There were 220 values that 

exceeded the aquatic-life standard for maximum weekly 

average water temperature in the study area: all 220 occurred 

in the Lower Gunnison River Basin. Maximum weekly average water temperature standards only exist for the Lower 

Gunnison in the study area (table 3). For the entire study area, 

196 sites had dissolved-oxygen data collected between 1970 

and 2009: 34 sites in the White River Basin, 111 sites in the 

Colorado River Basin, and 51 sites in the Lower Gunnison 

River Basin. Median dissolved-oxygen concentrations ranged 

from 7.6 to 11.2 mg/L in the White River Basin, from 6.8 

to 10.9 mg/L in the Colorado River Basin, and from 7.0 to 

11.2 mg/L in the Lower Gunnison River Basin. There were 

185 concentrations that exceeded the dissolved oxygen 

aquatic-life standard out of a total of 11,248 values in the 

study area: 13 in the White River Basin, 168 in the Colorado 

River Basin, and 4 in the Lower Gunnison River Basin. 

There were 273 concentrations that exceeded the aquatic-life 

standard for dissolved oxygen (spawning season only) in the 

study area: 27 in the White River Basin, 214 in the Colorado 

River Basin, and 32 in the Lower Gunnison River Basin. For 

the entire study area, 276 sites had pH data collected between 

1958 and 2009: 39 sites in the White River Basin, 147 sites in 

the Colorado River Basin, and 90 sites in the Lower Gunnison 

River Basin. Median pH values ranged from 7.9 to 8.9 in the 

White River Basin, from 7.5 to 9.0 in the Colorado River 

Basin, and from 7.4 to 8.7 in the Lower Gunnison River Basin. 

There were 241 values out of a total of 16,307 values that 

exceeded the high pH standard in the study area: 32 in the 

White River Basin, 191 in the Colorado River Basin, and 18 

in the Lower Gunnison River Basin. There were 7 values that 

were less than the low pH standard in the study area: 1 in the 

White River Basin, 2 in the Colorado River Basin, and 4 in the 

Lower Gunnison River Basin.

Natural changes in precipitation and streamflow and 

anthropogenic changes in nutrient sources (such as wastewater 

treatment facilities, golf courses, urban runoff, agricultural 

fields, and septic tanks) can influence nutrient concentrations 

in streams (Sprague and others, 2009). Nitrogen and phosphorus inputs to the stream could be derived from fertilizer 

and manure applications to agricultural land areas (Puckett, 

1994; Paschke and others, 2008). Nutrients within the study 

area were not well represented in each basin and were often 

not being sampled currently (August 2009) (app. 1, pl. 3). The 

White River Basin, in contrast to the other basins, had recent 

nutrient data collected in the past 5 years and historic nutrient data. For the entire study area, 62 sites had nitrate data 

collected between 1958 and 2009: 24 sites in the White River 

Basin, 22 sites in the Colorado River Basin, and 16 sites in 

the Lower Gunnison River Basin. Median nitrate concentrations ranged from less than detection to 1.49 mg/L as nitrogen (N) in the White River Basin, from less than detection 

to 2.70 mg/L as N in the Colorado River Basin, and from 

less than detection to 3.72 mg/L as N in the Lower Gunnison 

River Basin. The MCL for domestic water supply for nitrate 

is 10 mg/L and was exceeded once in 3,736 samples. Total 

phosphorus data was better represented spatially throughout 

the study area relative to other nutrients. Total phosphorus 

was collected at 113 sites between 1974 and 2009: 32 sites in 

the White River Basin, 43 sites in the Colorado River Basin, 

and 38 sites in the Lower Gunnison River Basin. Median total 

phosphorus concentrations ranged from 0.02 to 5.04 mg/L in 

the White River Basin, from less than detection to 0.6 mg/L 

in the Colorado River Basin, and from less than detection to 

0.55 mg/L in the Lower Gunnison River Basin. The USEPA 

recommendation for phosphorus is less than 0.1 mg/L, and 

1,469 of 4,842 samples exceeded this recommended standard 

in the study area. Overall, 400 values in the White River 

Basin, 586 values in the Colorado River Basin, and 483 values 

in the Lower Gunnison River Basin exceeded the recommended standard.

Standards for major ions exist only for chloride and 

sulfate (app. 1, pl. 4). For the entire study area, 118 sites had 

chloride and sulfate concentration data collected between 1958 

and 2009: 27 sites in the White River Basin, 49 sites in the 

Colorado River Basin, and 42 sites in the Lower Gunnison 

River Basin. Median chloride concentrations ranged from 1.4 

to 165 mg/L in the White River Basin, from 1.4 to 280 mg/L in 

the Colorado River Basin, and from 0.085 to 190 mg/L in the 

Lower Gunnison River Basin. There were 120 samples with 

chloride concentrations that exceeded the chloride domestic 

water-supply standard of 250 mg/L from a total of 8,817 samples with chloride concentration data: 86 in the White River 

Basin and 34 in the Colorado River Basin. Median sulfate 

concentrations ranged from 57.5 to 1,780 mg/L in the White 

River Basin, from 11.0 to 15,000 mg/L in the Colorado River 

Basin, and from 4.57 to 1,680 mg/L in the Lower Gunnison 

River Basin. There were 1,111 samples with sulfate concentrations that exceeded the sulfate domestic water-supply standard 

of 250 mg/L (477 mg/L in the Lower Gunnison River Basin) 
Characterization and Data-Gap Analysis of Surface-Water Quality 25

(table 3) from a total of 8,736 samples with sulfate concentration data in the study area: 503 in the White River Basin, 

131 values in the Colorado River Basin, and 477 in the Lower 

Gunnison River Basin.

Many trace elements in natural waters are essential to 

plant and aquatic life. There are natural (geology) and anthropogenic sources of trace elements in streams. Mining can 

provide conduits for water and air to come in contact with 

the underlying geologic material, where both physical and 

chemical weathering can dissolve and transport these constituents into streams. River segments adjacent to urban areas are 

subject to mobilization of trace elements from urban runoff 

and treated wastewater. Trace elements were relatively well 

represented both temporally and spatially in the study area 

(app. 1, pl. 5), though the number of trace element samples 

per site was not typically enough to compute trends or loads 

except for selenium. There were 109 sites that had dissolved 

copper concentration data collected between 1972 and 2009: 

27 sites in the White River Basin, 42 sites in the Colorado 

River Basin, and 40 sites in the Lower Gunnison River Basin. 

Median copper concentrations ranged from less than detection to 4.5 μg/L in the White River Basin, from 0.62 to 6 μg/L 

in the Colorado River Basin, and from 0.53 to 5 μg/L in the 

Lower Gunnison River Basin. Copper concentrations were 

compared to two standards: the chronic (30-day) aquatic-life 

standard, which ranges from 1.57 to 29.3 μg/L, and the acute 

aquatic-life standard, which ranges from 1.96 to 49.6 μg/L in 

the study area (table 3). There were 69 samples with copper 

concentrations that exceeded the chronic standard from a total 

of 2,885 samples with copper concentration data: 12 in the 

White River Basin, 23 in the Colorado River Basin, and 34 

in the Lower Gunnison River Basin. There were 29 samples 

with copper concentrations that exceeded the acute standard: 

9 in the White River Basin, 2 in the Colorado River Basin, and 

18 in the Lower Gunnison River Basin. There were 127 sites 

that had dissolved iron concentration data collected between 

1961 and 2009: 33 sites in the White River Basin, 63 sites in 

the Colorado River Basin, and 31 sites in the Lower Gunnison 

River Basin. Median iron concentrations ranged from 7 to 

78 μg/L in the White River Basin, from less than detection 

to 1,100 μg/L in the Colorado River Basin, and from 4 to 

120 μg/L in the Lower Gunnison River Basin. The 30-day 

drinking-water standard for iron is 300 μg/L, and 203 samples 

exceeded the standard from a total of 5,027 samples with iron 

concentration data, 196 of which occurred in the Colorado 

River Basin, most of which are from Divide Creek. The samples on Divide Creek were collected as part of a multiphase 

water-quality investigation associated with a leaking natural 

gas well (Papadopulos & Associates, Inc., 2008). Selenium 

was the best represented trace element with selenium concentration data collected at 197 sites between 1973 and 2009: 

28 sites in the White River Basin, 94 sites in the Colorado 

River Basin, and 75 sites in the Lower Gunnison River Basin. 

Median selenium concentrations range from 0.79 to 5.7 μg/L 

in the White River Basin, from less than detection to 86 μg/L 

in the Colorado River Basin, and from less than detection to 

181 μg/L in the Lower Gunnison River Basin. For most stream 

segments in the study area, the chronic (30-day) aquatic-life 

selenium standard is 4.6 μg/L, but a few segments have temporary chronic standards based either on a fixed standard or on 

the 85th-percentile data value for a given site, which can be as 

high as 280 μg/L (table 3). The chronic standard for selenium 

concentrations was exceeded in 899 samples: 22 in the White 

River Basin, 741 in the Colorado River Basin, and 136 in the 

Lower Gunnison River Basin. The acute aquatic-life standard 

of 18.4 μg/L for selenium was exceeded in 629 samples: 202 

in the Colorado River Basin and 427 in the Lower Gunnison 

River Basin.

Statistics for suspended sediment, E. coli, and BTEX were 

summarized (app. 1). The study area included 53 sites with 

suspended sediment data. Sediment affects macroinvertebrate 

and fish habitat and municipal water treatment. Where sediment 

is on the monitoring and evaluation list of the CDPHE 303d list, 

there is not an easily defined standard. Only 18 sites had E. coli

concentration data that could provide an assessment of the 

suitability of the water for recreational use. The E. coli recreational standard is 630 colony forming units (CFU) in streams 

where primary contact (such as swimming or other water sports) 

will occur, 205 CFU in areas of potential primary contact, and 

126 CFU where the stream is not suitable for primary contact 

recreation (table 3). Of the 18 sites, 11 sites had exceedances of 

the E. coli recreational standard (app. 1). The seasonal E. coli

standard is 126 CFU and was only exceeded once in the White 

River Basin. There were 5 sites in the Colorado River Basin that 

had BTEX concentration data, which could be a constituent of 

interest when looking at energy-related activities. For example, 

in the Divide Creek and Mamm Creek area (fig. 1), BTEX 

concentration data were used to evaluate the impacts from 

faulty natural gas production well completion where detections 

and elevated concentrations of BTEX were observed in surface 

water and groundwater (Papadopulos & Associates, Inc., 2008). 

BTEX does not persist in the environment where conditions are 

typically well oxygenated, so BTEX might not be a constituent to add to routine monitoring of surface water, but more for 

use in evaluating known occurrences and persistent sources 

of BTEX.

Temporal Trends and Loads

The results of the trend analysis are presented for the 

three study basins starting with the northernmost basin 

(White River Basin) and ending with the southernmost basin 

(Lower Gunnison River Basin). Within each basin, results are 

presented beginning with the main-stem sites in the basin, 

starting with the most upstream site and ending with the most 

downstream site. The most downstream site on the main 

stem in each basin represents the entire drainage area of the 

basin. After the main-stem sites, tributary sites are presented 

from upstream to downstream. Finally, trends for lower order 

tributaries are presented where there were sufficient data for 

analysis. Only 37 sites met the final selection criteria for trend 
26 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

analysis: 31 sites had sufficient field property data for analysis 

using the seasonal Kendall test and 28 sites had sufficient concentration data for analysis using regression models (fig. 7).

Loads and exceedances are presented for some constituents not only to provide context to the trends analysis results, 

but also to identify data gaps. Additionally, the land use and 

geology for each basin, as it may relate to water quality, are 

presented in further detail. Loading profiles are presented for 

selected constituents for all sites where trend analysis was 

computed and where there were sufficient streamflow data 

to compute a load. The figures include both main-stem and 

tributary sites and are ordered from upstream to downstream 

(figs. 8–12).

Loads and loading profiles are presented in figures 8–12, and trend data are presented in tables 4–7. Table 4 

contains the results of the trend analysis for field properties using ESTREND. Tables 5–7 present the results of the 

trends analysis for concentration data (nutrients, major ions 

and dissolved solids, and trace elements, respectively) using 

S-LOADEST. Tables include the study period and a trend 

direction (where trends were significant) when sufficient data 

existed for trend analysis. The code “ND” was used to indicate 

that there were no data for that constituent at that site. The 

code “IS” indicates that there were data but they did not meet 

the selection criteria detailed in the “Trend Analysis and Load 

Calculation” section presented earlier in this report (p. 21). 

The code “NT” was used to indicate no trend, and “F” was 

used to indicate the model failed diagnostics. The code “NA” 

was used to indicate not applicable. In the field properties 

table (table 4), there are also dashes (—) that were used to 

indicate that the dataset met the initial criteria but did not meet 

the internal ESTREND criteria to adequately characterize 

seasonality.

White River Basin

Temporal and spatial variability of water-quality data in 

the White River Basin were evaluated at 10 sites: 6 sites on the 

White River main stem and 4 sites on tributaries to the White 

River (tables 4–7, fig. 7). Main-stem sites on the White River 

were 09304200 (White River above Coal Creek), 09304500 

(White River near Meeker), 09304800 (White River below 

Meeker), 09306224 (White River above Crooked Wash near 

White River City), 09306290 (White River below Boise 

Creek, near Rangely), and 09306305 (White River below 

Taylor Draw Reservoir, above Rangely) (fig. 1) in order from 

upstream to downstream. Tributary sites included 2 sites 

on Piceance Creek, 09306200 (Piceance Creek below Ryan 

Gulch, near Rio Blanco) and 09306222 (Piceance Creek at 

White River) from upstream to downstream; 09306242 (Corral 

Gulch near Rangely), which is tributary to Yellow Creek; and 

09306255 (Yellow Creek near White River), which then flows 

into the White River downstream from Piceance Creek.

Field Properties

Results of the trend analysis for water temperature, pH, 

and dissolved oxygen are presented in table 4. Sufficient 

data were available to analyze for water temperature trends 

at 8 sites in the White River Basin; however, there were no 

significant trends in water temperature at any of these sites. 

Sufficient data were available to analyze for dissolved-oxygen 

trends at 6 sites; however, no trends were detected from 1990 

to 2009 for all sites. Sufficient data existed to analyze for 

pH trends at 6 sites. An upward trend in pH was observed at 

the most upstream site, 09304200 (White River above Coal 

Creek), from 1990 to 2009, and no trends were detected at the 

remaining 5 sites for the same period.

Nutrients

Trends in nutrient concentration data were evaluated 

for ammonia, nitrate, orthophosphate, and total phosphorus 

in the White River main stem (table 5). In addition, organic 

carbon and E. coli are discussed in this section as well. At 

09304200 (White River above Coal Creek, near Meeker), a 

net, upward trend was detected in nitrate from 1990 to 2009. 

The trend was parabolic with a zero-slope year around 2002, 

after which the shape of the parabola indicated a downward 

trend. Trends were detected in other nutrients at this site, 

including an upward trend in total phosphorus from 1991 to 

2009 and a downward trend in orthophosphate from 1990 to 

2009. A net, downward trend in orthophosphate was detected 

at 09304800 (White River below Meeker) from 1990 to 2009. 

The trend was parabolic with a zero-slope year around 1997, 

prior to which the shape of the parabola indicated an upward 

trend. Trends in orthophosphate were consistently downward 

throughout the main stem of the White River. All other models 

failed diagnostics for nutrients for this site. Downstream at site 

09306290 (White River below Boise Creek, near Rangely), 

dissolved organic carbon had a net, downward trend from 

1990 to 2009. The trend was parabolic with a zero-slope year 

around 1999, prior to which the shape of the parabola indicated an upward trend.

Trends were analyzed for nutrients on tributary sites 

to the White River Basin (table 5). Downward trends were 

detected for nitrate, orthophosphate, and organic carbon at 

site 09306200 (Piceance Creek below Ryan Gulch, near Rio 

Blanco) from 1990 to 2009. Downstream, at site 09306222 

(Piceance Creek at White River), no trend was detected in 

orthophosphate and the model failed diagnostics for nitrate for 

the same period. It is unclear why the trend in orthophosphate 

is not consistent between Piceance Creek below Ryan Gulch, 

near Rio Blanco, and Piceance Creek at White River for the 

same period. All trend models failed diagnostics for nutrients 

at 09306255 (Yellow Creek near White River); however, no 

trend was detected in nitrate or orthophosphate from 1990 to 

2008 at 09306242 (Corral Gulch near Rangely), a tributary to 

Yellow Creek.
Characterization and Data-Gap Analysis of Surface-Water Quality 27

Figure 7. Location of the sites where trend analysis was completed, western Colorado.

White River

Roan Creek

Big

Salt Wash

Piceance Creek

Wolf Creek

Smith Fork

Plateau Creek

Kannah Creek

East Salt Creek

Flag Creek

Clear Creek

West Salt Creek

East Creek

Red Wash

Surface

Creek

Ryan Gulch

Yellow Creek

Big Creek

Cottonwood Creek

Carr Creek

Jerry Creek

Douglas Creek

Kelso Creek

North Fork White River

Dry Fork

Leon Creek

Hubbar

Anthracite 

Creek

Strawberry 

Creek

Fawn Creek

Dry Creek

Willow Creek

Kimball Creek

Criswell Creek

Missouri Creek

Sulphur Creek

Rifle 

Creek

Corral Gulch

Parachute Creek

Clear Fork

Sunflower

Drain

Gunnison 

Tunnel Uncompahgre River

Colorado River

d

Silt

Rifle

Delta

Meeker

Olathe

Fruita

Paonia

Rangely

Montrose

Palisade

De Beque

Collbran

Parachute

Cedaredge

New

Castle Glenwood Springs

MESA 

COUNTY

COLORADO

UTAH

COLORADO

UTAH

MOFFAT 

COUNTY

ROUTT

COUNTY

GUNNISON

COUNTY

GARFIELD

COUNTY

RIO BLANCO

COUNTY

MONTROSE

COUNTY

DELTA 

COUNTY

PITKIN 

COUNTY

Taylor Draw 

Reservoir

109° 108°30' 108° 107°30' 107°

40°

39°30'

39°

38°30'

Base from Environmental Research Systems Institute 

(ESRI) digital data, 2009, 1:24,000 and 

U.S. Geological Survey digital data, 2010, 1:100,000

Universal Transverse Mercator, Zone 13 North

0 10 20 30 MILES

0 10 20 30 KILOMETERS

EXPLANATION

White River Basin

Colorado River Basin

Lower Gunnison River Basin

Study area boundary

40

40

40

50

50

Dinosaur

64

65

13

13

139

West Rifle

Creek

East Rifle Creek

Mamm

Creek

Divide Creek

Buzzard Creek

Creek

70

70

Gunnison River

Grand

Junction

Roaring Fork

550

Hotchkiss

Roubideau Creek

Crawford

CoalCreek

Platea u Creek

Salt

Creek

Minnesota

Creek

Coal

Creek

North Fork

Gunnison River

Loutsenhizer

Arroyo

50

6

6

133

149

141

82

92

90

09304200

09136100

09306242

09306224

09306225

09106200 CDOWRW-560 CDOWRW-555

383528107552001

383528107572001

09306200

09085150

09306222

09306290

09304500

09304800

09306305

09153290

09106150

09095300

09089500

09163500 09105000

09095500

09135950

09143500

09143000

384551107591901

09134000

383946107595301

09149500

09149500

09152500

09132500

09144250

CDOWRW-550

CDOWRW-47

Analysis site and identifier 

Continuous streamflow

Concentration data trend

Field property data trend
28 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Figure 8. Loading profile for (A) nitrate and (B) orthophosphate in the White River Basin, 

western Colorado.

0

5

10

15

20

25

30

35

40

45

A

B

09304200

09304800

09306200

09306222

09306242

09306255

09306290

09304200

09304800

09306200

09306222

09306242

09306255

09306290

Nitrate load in water year 1996, in tons

0

10

20

30

40

50

60

Streamflow

data outside

of model 

range to 

calculate 

loads

Load could

not be 

calculated

because the 

model failed 

diagnostics

Load could

not be calculated

because the

model failed

diagnostics

Load could

not be calculated

because the

model failed

diagnostics 0.79

26.2

48.2

Orthophosphate load in water year 1996, in tons

27.3

39.5

2.28

3.60

39.7

0.04

Load could not

be calculated

because the

model failed

diagnostics

EXPLANATION

Main-stem site

Tributary site
Characterization and Data-Gap Analysis of Surface-Water Quality 29

Figure 9. Loading profile for (A) dissolved solids, (B) iron, and 

(C) selenium in the White River Basin, western Colorado.

09304200

09304800

09306200

09306222

09306242

09306255

09306290

09304200

09306200

09306222

09306255

09306290

09304200

09306200

09306222

09306290

300,000

Dissolved solids load in water year 2000, in tons Iron load in water year 1996, in pounds Selenium load in water year 2000, in pounds

250,000

200,000

150,000

100,000

50,000

40,000

35,000

30,000

25,000

20,000

15,000

10,000

5,000

800

700

600

500

400

300

200

100

0

28.7 45.6

Streamflow

data outside

of model

range to

calculate loads

0

21,000

508 688 57.2

35,000

102,000

164,000

11,800

26,600

763

245,000

Load could

not be

calculated

because the

model failed

diagnostics

Load could

not be

calculated

because the

model failed

diagnostics

0

A

B

C

EXPLANATION

Main-stem site

Tributary site
30 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Figure 10. Loading profile for (A) nitrate and (B) orthophosphate in the Colorado 

River Basin, western Colorado.

A

B

EXPLANATION

Main-stem site

Tributary site

F

09095300

09095500

09152500

09163500

09095300

09152500

09163500

215 0

Nitrate load in water year 1996, in tons Orthophosphate load in water year 1996, in tons

500

1,000

1,500

2,000

2,500

3,000

3,500

Load could

not be

calculated 

because the 

model failed

diagnostics

1,670

3,230

50

0

100

150

200

250

300

350

400

450

0.24

125

385
Characterization and Data-Gap Analysis of Surface-Water Quality 31

Figure 11. Loading profile for (A) dissolved solids, (B) iron, and 

(C) selenium in the Colorado River Basin, western Colorado.

09095500

09105000

09106150

09152500

09163500

09163500

09163500

09152500

09152500

09095500

09095500

3,000,000

1,380,000

59,700

1,090,000 1,064,000

2,850,000

2,500,000

2,000,000

1,500,000

1,000,000

500,000

0

200,000

180,000

160,000

140,000

120,000

100,000

80,000

60,000

40,000

20,000

0

40,000

3,900

18,900

36,200

134,000

41,700

177,000

Selenium load in water year 1999, in pounds Iron load in water year 1996, in pounds Dissolved solids load in water year 1999, in tons

C

B

A

35,000

30,000

25,000

20,000

15,000

10,000

5,000

0

EXPLANATION

Main-stem site

Tributary site
32 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Figure 12. Loading profile for (A) dissolved solids and (B) selenium in the Lower 

Gunnison River Basin, western Colorado.

09144250

09149500

09152500

09144250

09149500

09152500

1,200,000

1,000,000

800,000

600,000

400,000

200,000

0

Dissolved solids load in water year 1999, in tons

20,000

18,000

16,000

14,000

12,000

10,000

8,000

6,000

4,000

2,000

0

Selenium load in water year 1999, in pounds

582,000*

9,180

8,510

19,000

1,060,000

(1,070,000*, not graphed)

371,000*

* Value from models developed in Schaffrath (2012) 

 as loads could not be calculated from the trend 

 model developed for this report

A

B

EXPLANATION

Main-stem site

Tributary site
Characterization and Data-Gap Analysis of Surface-Water Quality 33

Table 4. Summary of the seasonal Kendall test trend analysis results for field properties, Piceance study area, western Colorado, 1990–2009.[NP, data not provided in the repository; IS, did not meet seasonal Kendall criteria due to insufficient data; —, data was not sufficient do adequately characterize seasonality; ND, no data available]

Site name

Site

identification

number

Drainage 

area,

in square

miles

Water temperature,

in degrees Celsius

Dissolved oxygen,

in milligrams per liter

pH,

in standard units

Study

period

Trend

type

Study

period

Trend

type

Study

period

Trend

type

White River Basin

White River above Coal Creek, near Meeker, Colo. 09304200 648 1990–2009 no trend 1990–2009 no trend 1990–2009 upwardWhite River near Meeker, Colo. 09304500 755 1990–2005 no trend ND ISWhite River below Meeker, Colo. 09304800 1,024 1990–2009 no trend 1990–2009 no trend 1990–2009 no trendPiceance Creek below Ryan Gulch, near Rio Blanco, Colo. 09306200 506 1990–2009 no trend 1990–2009 no trend1 1990–2009 no trendPiceance Creek at White River, Colo. 09306222 652 1990–2009 no trend 1990–2009 no trend1 1990–2009 no trendCorral Gulch near Rangely, Colo. 09306242 32 1990–2009 no trend

—

—

—

—

Yellow Creek near White River, Colo. 09306255 262 1990–2009 no trend 1990–2009 no trend 1990–2009 no trendWhite River below Boise Creek, near Rangely, Colo. 09306290 2,530 1990–2009 no trend 1990–2009 no trend 1990–2009 no trendWhite River below Taylor Draw Reservoir, above Rangely Colo. 09306305 2,776

—

—

—

Colorado River Basin

Colorado River Devereaux Bridge CDOWRW-47 NP 1991–2007 no trend 1991–2007 downward

—

West Divide Creek near Raven, Colo. 09089500 65

— IS IS

Colorado River Rifle Bridge CDOWRW-550 NP

—

—

—

Dry Fork at Upper Station, near DeBeque, Colo. 09095300 97

—

—

—

Colorado River near Cameo, Colo. 09095500 8,050 1990–2009 no trend 1991–2008 no trend 1990–2009 upwardPlateau Creek near Cameo, Colo. 09105000 592 1990–2009 no trend 1991–2008 no trend1 1991–2009 no trendColorado River below Grand Valley Diversion, 

near Palisade, Colo.

09106150 8,753

—

—

—

Colorado River Highway 6 CDOWRW-555 NP

—

—

—

Colorado River Watson CDOWRW-560 NP

—

—

—

Reed Wash near Mack, Colo. 09153290 16 1990–2000 no trend

—

—

Colorado River near Colorado-Utah state line 09163500 17,843 1990–2009 no trend 1990–2008 no trend 1990–2009 no trend

Lower Gunnison River Basin

North Fork Gunnison River near Somerset, Colo. 09132500 526

— ND IS

Minnesota Creek near Paonia, Colo. 09134000 41

— ND ND

North Fork of the Gunnison River below Leroux Creek, 

near Hotchkiss, Colo.

09135950 922

— IS IS

Smith Fork near Crawford, Colo. 09128500 43

— ND IS

Sunflower Drain at Highway 92, near Read 384551107591901 NP

—

—

—

Surface Creek near Cedaredge, Colo. 09143000 27

— ND ND

Surface Creek at Cedaredge, Colo. 09143500 39 1990–2004 no trend ND NDGunnison River at Delta, Colo. 09144250 5,628 1990–2009 no trend

—

—

Loutsenhizer Arroyo at North River Road 383946107595301 NP

—

—

—

Uncompahgre River at Delta, Colo. 09149500 1,115 1990–2009 no trend

—

—

Gunnison River near Grand Junction, Colo. 09152500 7,928 1990–2009 upward 1990–2009 no trend 1990–2009 no trend 1Indicates that there were not sufficient streamflow data to flow adjust the concentrations. 
34 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Table 5. Summary of regression model trend analysis results for nutrients and Escherichia coli, Piceance study area, western 

Colorado, 1990–2009.

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame of 

the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the respective 

time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and the time frame 

of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did not have data; 

IS, insufficient data for regression model analysis]

Site name

Site

identification 

number

Drainage 

area,

in square 

miles

Ammonia, filtered, 

in milligrams per liter 

as nitrogen

Nitrate, in milligrams

per liter as nitrogen

Upward Downward Upward Downward

White River Basin

White River above Coal Creek, 

near Meeker, Colo.

09304200 648 F; 1990–2009 1990–2002 2002–2009

White River below Meeker, Colo. 09304800 1,024 F; 1990–2009 F; 1990–2009

Piceance Creek below Ryan Gulch, 

near Rio Blanco, Colo.

09306200 506 NT; 1990–2009 NA 1990–2009

Piceance Creek at White River, Colo. 09306222 652 1990–2001 2001–2009 F; 1990–2009

White River above Crooked Wash, 

near White River City, Colo.

09306224 1,821 F; 1990–2008 NT; 1990–2008

Corral Gulch near Rangely, Colo. 09306242 32 F; 1990–2008 NT; 1990–2008

Yellow Creek near White River, Colo. 09306255 262 F; 1990–2009 F; 1990–2009

White River below Boise Creek, 

near Rangely, Colo.

09306290 2,530 F; 1990–2009 F; 1990–2009

White River below Taylor Draw Reservoir, 

above Rangely, Colo.

09306305 2,776 NT; 1995–2009 NT; 1995–2009

Colorado River Basin

Colorado River Devereaux Bridge CDOWRW-47 — ND ND

Colorado River above South Canyon Creek, 

near Glenwood Springs, Colo.

09085150 6,040 ND ND

Dry Fork at Upper Station, near DeBeque, Colo. 09095300 97 F; 1996–2004 1996–1998 1998–2004

Colorado River near Cameo, Colo. 09095500 8,050 F; 1991–2002 F; 1991–2002

Plateau Creek near Cameo, Colo. 09105000 592 IS IS

Colorado River below Grand Valley Diversion, 

near Palisade, Colo.

09106150 8,753 IS IS

Colorado River Hwy 6 CDOWRW-555 — ND ND

Lewis Wash near Grand Junction, Colo. 09106200 4.7 IS IS

Colorado River Watson CDOWRW-560 — ND ND

Reed Wash near Mack, Colo. 09153290 16 IS IS

Colorado River near Colorado-Utah State Line 09163500 17,843 2002–2008 1990–2002 NA 1990–2008

Lower Gunnison River Basin

North Fork Gunnison River above mouth, 

near Lazear, Colo.

09136100 969 IS IS

Sunflower Drain at Highway 92, near Read 384551107591901 — IS IS

Gunnison River at Delta, Colo. 09144250 5,628 IS IS

Loutsenhizer Arroyo at Falcon Road 383528107552001 — ND ND

West Tributary of Loutsenhizer Arroyo 

below East Canal

383728107572001 — ND ND

Loutsenhizer Arroyo at North River Road 383946107595301 — IS IS

Uncompahgre River at Delta, Colo. 09149500 1,115 IS —

Gunnison River near Grand Junction, Colo. 09152500 7,928 F; 1990–2002 NT; 1990–2002
Characterization and Data-Gap Analysis of Surface-Water Quality 35

Table 5. Summary of regression model trend analysis results for nutrients and Escherichia coli, Piceance study area, western 

Colorado, 1990–2009.—Continued

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame of 

the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the respective 

time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and the time 

frame of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did not have 

data; IS, insufficient data for regression model analysis]

Orthophosphate, filtered,

in milligrams per liter

Total phosphorous,

in milligrams per liter

Organic carbon, filtered,

in milligrams per liter

Escherichia coli,

colonies per 100 milliliters

Upward Downward Upward Downward Upward Downward Upward Downward

White River Basin

NA 1990–2009 1991–2009 NA IS NT; 1991–2004

1990–1997 1997–2009 F; 1991–2009 — F; 1991–2003

NA 1990–2009 — NA 1993–2009 IS

NT; 1990–2009 — NT; 1991–2009 IS

NT; 1990–2008 IS IS ND

NT; 1990–2008 — F; 1991–2008 IS

F; 1990–2009 — NT; 1991–2009 IS

NA 1990–2009 F; 1990–2009 1990–1999 1999–2009 IS

NA 1995–2009 1995–2009 NA ND IS

Colorado River Basin

ND IS ND ND

ND ND ND ND

NT; 1996–2004 F; 1996–2004 — IS

IS IS IS IS

— IS ND IS

IS IS ND IS

ND IS ND ND

— IS IS ND

ND IS ND ND

IS IS IS ND

NA 1990–2008 1990–2008 NA NT; 1995–2002 ND

Lower Gunnison River Basin

ND ND ND ND

IS IS IS ND

IS IS ND IS

ND ND ND ND

ND ND ND ND

IS ND ND ND

— IS IS IS

NT; 1990–1998 F; 1990–2002 NT; 1995–2002 IS
36 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Table 6. Summary of regression model trend analysis results for dissolved solids and major ions, Piceance study area, western 

Colorado, 1990–2009.

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame 

of the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the 

respective time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and 

the time frame of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did 

not have data; IS, insufficient data for regression model analysis]

Site name

Site

identification

number

Drainage 

area, in 

square miles

Calcium, filtered,

in milligrams per liter

Upward Downward

White River Basin

White River above Coal Creek, near Meeker, Colo. 09304200 648 NT; 1990–2002

White River below Meeker, Colo. 09304800 1,024 NT; 1990–2009

Piceance Creek below Ryan Gulch, near Rio Blanco, Colo. 09306200 506 1990–2009 NA

Piceance Creek at White River, Colo. 09306222 652 2000–2009 1990–2000

White Riv above Crooked Wash near White River City, Colo. 09306224 1,821 —

Corral Gulch near Rangely, Colo. 09306242 32 1990–1996 1996–2008

Yellow Creek near White River, Colo. 09306255 262 NT; 1990–2009

White River below Boise Creek, near Rangely, Colo. 09306290 2,530 NT; 1990–2009

White River below Taylor Draw Reservoir, above Rangely Colo. 09306305 2,776 IS

Colorado River Basin

Colorado River Devereaux Bridge CDOWRW-47 — NT; 2000–2007

Colorado River above South Canyon Creek near Glenwood Springs, Colo. 09085150 6,040 IS

Dry Fork at Upper Station, near DeBeque Colo. 09095300 97 IS

Colorado River near Cameo, Colo. 09095500 8,050 1990–2001 2001–2009

Plateau Creek near Cameo, Colo. 09105000 592 NT; 1991–2009

Colorado River below Grand Valley Diversion near Palisade, Colo. 09106150 8,753 NT; 1992–2002

Colorado River Hwy 6 CDOWRW-555 — IS

Lewis Wash near Grand Junction, Colo. 09106200 4.7 NT; 1991–2006

Colorado River Watson CDOWRW-560 — IS

Reed Wash near Mack, Colo. 09153290 16 IS

Colorado River near Colorado-Utah State Line 09163500 17,843 2001–2009 1990–2001

Lower Gunnison River Basin

North Fork Gunnison River above mouth near Lazear, Colo. 09136100 969 NA 1991–2009

Sunflower Drain at Highway 92, near Read 384551107591901 — NT; 1991–2003

Gunnison River at Delta, Colo. 09144250 5,628 F; 1991–2009

Loutsenhizer Arroyo at Falcon Road 383528107552001 — IS

West Tributary of Loutsenhizer Arroyo below East Canal 383728107572001 — IS

Loutsenhizer Arroyo at North River Road 383946107595301 — NT; 1991–2009

Uncompahgre River at Delta, Colo. 09149500 1,115 2001–2009 1991–2001

Gunnison River near Grand Junction, Colo. 09152500 7,928 2002–2009 1990–2002

Nitrate and orthophosphate loads and total phosphorus 

standard exceedances were evaluated in the White River 

Basin. The White River Basin had the greatest number of 

nitrate concentration samples; however, use of the loading profile for nitrate was limited at the main stem of the White River 

because load could not be calculated for the most downstream 

site 09306290 (White River below Boise Creek, near Rangely) 

(fig. 8A). A loading profile for orthophosphate in the White 

River Basin indicated a slight increase in orthophosphate from 

upstream to downstream (fig. 8B). Between 09304800 (White 

River below Meeker) and 09306290 (White River below 

Boise Creek, near Rangely), orthophosphate increased by only 

0.2 tons while tributaries between the two sites sum to more 

than 6 tons of additional orthophosphate. There were 29 sites 

that had exceedances of the recommended total phosphorus 

standard, with more than 402 exceedances, many of which 

occur prior to 2000 (21 sites and 323 samples had total phosphorus standard exceedances) (app. 1).

Dissolved Solids and Major Ions

Dissolved solids (DS) refers to the concentration of dissolved solids in water, including calcium, magnesium, sodium, 

potassium, silica, chloride, sulfate, and carbonate species. 

Although DS has not been a significant water-quality concern 

in the White River Basin, a potential source of the DS might 

be 55 mi2 of irrigated land in the basin. Irrigation occurs primarily near Meeker, Colo., and in the Piceance Creek Basin. 

Prior to 1980, Meeker Dome, 3 miles east of the town of 

Meeker, was a point source for DS on the White River owing 

to highly saline water that was discharging at the surface 

through abandoned and improperly plugged exploration oil 

wells drilled during the 1920s (Liebermann and others, 1989). 

The wells were eventually plugged during the 1960s and 

1980s and the source was mitigated. However, results from 

this previous study indicated that there were potentially large 

conduits for high DS groundwater to upwell to the surface and 

enter surface water.
Characterization and Data-Gap Analysis of Surface-Water Quality 37

Table 6. Summary of regression model trend analysis results for dissolved solids and major ions, Piceance study area, western 

Colorado, 1990–2009.—Continued

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame 

of the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the 

respective time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and 

the time frame of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did 

not have data; IS, insufficient data for regression model analysis]

Magnesium, filtered,

in milligrams per liter

Sodium, filtered,

in milligrams per liter

Potassium, filtered,

in milligrams per liter

Chloride, filtered,

in milligrams per liter

Upward Downward Upward Downward Upward Downward Upward Downward

White River Basin

NT; 1990–2002 1990–1992 1992–2002 F; 1990–2002 NT; 1990–2009

NT; 1990–2009 NT; 1990–2009 NT; 1990–2009 NA 1990–2009

NT; 1990–2009 1997–2009 1990–1997 NT; 1990–2009 2003–2009 1990–2003

1999–2009 1990–1999 NT; 1990–2009 NT; 1990–2009 NA 1990–2009

— — — —

1990–1996 1996–2008 NA 1990–2008 NT; 1990–2008 2002–2008 1990–2002

F; 1990–2009 NT; 1990–2009 NT; 1990–2009 1999–2009 1990–1999

1990–1999 1999–2009 1990–1998 1998–2009 1990–1999 1999–2009 NA 1990–2009

IS IS IS IS

Colorado River Basin

NT; 2000–2007 ND ND ND

IS IS IS IS

IS IS IS NT; 1996–2004

NT; 1990–2009 NT; 1990–2009 NT; 1990–2009 1990–2009 NA

NT; 1991–2009 NA 1991–2009 NT; 1991–2009 1991–2002 2002–2009

NT; 1992–2002 NT; 1992–2002 NT; 1992–2002 NT; 1992–2002

IS ND ND ND

NA 1991–2006 NT; 1991–2006 NT; 1991–2006 F; 1991–2006

IS ND ND ND

IS IS IS IS

2004–2009 1990–2004 2002–2009 1990–2002 1999–2009 1990–1999 NT; 1990–2009

Lower Gunnison River Basin

NA 1991–2009 NA 1991–2009 NT; 1991–2009 F; 1991–2009

NT; 1991–2003 NT; 1991–2003 NT; 1991–2003 NT; 1991–2003

NA 1991–2009 F; 1991–2009 NT; 1991–2009 F; 1991–2009

IS IS IS IS

IS IS IS IS

NT; 1991–2009 NT; 1991–2009 NT; 1991–2009 NT; 1991–2009

2000–2009 1991–2000 2000–2009 1991–2000 NT; 1991–2009 2000–2009 1991–2000

2003–2009 1990–2003 2005–2009 1990–2005 2000–2009 1990–2000 2002–2009 1990–2002

Sufficient data were available to analyze for trends in DS 

and other major ions for 3 sites on the White River main stem: 

09304200 (White River above Coal Creek, near Meeker), 

09304800 (White River below Meeker), and 09306290 (White 

River below Boise Creek, near Rangely). No trends were 

detected from 1990 to 2002 at 09304200 (White River above 

Coal Creek, near Meeker) for calcium, magnesium, chloride, 

sulfate, silica, and DS (table 6). Sodium had a net, downward 

trend at 09304200 from 1990 to 2002. The trend was parabolic with a zero-slope year around 1992, after which the 

shape of the parabola indicated an upward trend. No trends 

were detected downstream at 09304800 (White River below 

Meeker) from 1990 to 2009 for calcium, magnesium, sodium, 

potassium, sulfate, fluoride, silica, or DS. A downward trend 

was detected for chloride at 09304800 from 1990 to 2009. Net, 

downward trends were detected for DS and sodium from 1990 

to 2009 at site 09306290 (White River below Boise Creek, 

near Rangely). The trend for both constituents was parabolic 

with a zero-slope year around 1998, prior to which the shape 

of the parabola indicated an upward trend. It is unclear what 

contributed to the fluctuation in DS throughout the main stem 

of the White River.

Trends in DS and other major ions were analyzed 

for 4 tributary sites to the White River. At site 09306200 

(Piceance Creek below Ryan Gulch, near Rio Blanco), a net, 

downward trend was detected for DS from 1990 to 2009. 

The trend was parabolic with a zero-slope year of 2003, after 

which the shape indicated an upward trend (table 6). At the 

next site downstream, 09306222 (Piceance Creek at White 

River), a downward trend was detected for DS from 1990 to 

2009 (table 6). No trends were detected at 09306255 (Yellow 

Creek near White River); however, at 09306242 (Corral Gulch 

near Rangely), a tributary to Yellow Creek, a net, downward 

trend was detected for DS from 1990 to 2008. The trend was 

parabolic with a zero-slope year around 1993 prior to which 

the shape of the parabola indicated an upward trend.
38 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Table 6. Summary of regression model trend analysis results for dissolved solids and major ions, Piceance study area, western 

Colorado, 1990–2009.—Continued

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame of 

the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the respective time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and the 

time frame of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did not 

have data; IS, insufficient data for regression model analysis]

Site name

Site

identification

number

Sulfate, filtered, 

in milligrams per liter

Upward Downward

White River Basin

White River above Coal Creek, near Meeker, Colo. 09304200 NT; 1990–2002

White River below Meeker, Colo. 09304800 NT; 1990–2009

Piceance Creek below Ryan Gulch, near Rio Blanco, Colo. 09306200 NA 1990–2009

Piceance Creek at White River, Colo. 09306222 2004–2009 1990–2004

White Riv above Crooked Wash near White River City, Colo. 09306224 —

Corral Gulch near Rangely, Colo. 09306242 F; 1990–2008

Yellow Creek near White River, Colo. 09306255 NT; 1990–2009

White River below Boise Creek, near Rangely, Colo. 09306290 NA 1990–2009

White River below Taylor Draw Reservoir, above Rangely Colo. 09306305 IS

Colorado River Basin

Colorado River Devereaux Bridge CDOWRW-47 ND

Colorado River above South Canyon Creek near Glenwood Springs, Colo. 09085150 IS

Dry Fork at Upper Station, near DeBeque Colo. 09095300 1996–1999 1999–2004

Colorado River near Cameo, Colo. 09095500 NA 1990–2009

Plateau Creek near Cameo, Colo. 09105000 NA 1991–2009

Colorado River below Grand Valley Diversion near Palisade, Colo. 09106150 NT; 1992–2002

Colorado River Hwy 6 CDOWRW-555 ND

Lewis Wash near Grand Junction, Colo. 09106200 NA 1991–2006

Colorado River Watson CDOWRW-560 ND

Reed Wash near Mack, Colo. 09153290 IS

Colorado River near Colorado-Utah State Line 09163500 2008–2009 1990–2008

Lower Gunnison River Basin

North Fork Gunnison River above mouth near Lazear, Colo. 09136100 NA 1991–2009

Sunflower Drain at Highway 92, near Read 384551107591901 NT; 1991–2003

Gunnison River at Delta, Colo. 09144250 F; 1991–2009

Loutsenhizer Arroyo at Falcon Road 383528107552001 IS

West Tributary of Loutsenhizer Arroyo below East Canal 383728107572001 IS

Loutsenhizer Arroyo at North River Road 383946107595301 NT; 1991–2009

Uncompahgre River at Delta, Colo. 09149500 2000–2009 1991–2000

Gunnison River near Grand Junction, Colo. 09152500 NA 1990–2009

Generally, the trend analysis indicated that there was 

either no change or a net, downward trend in DS and other 

major ions. However, there were exceedances of chloride and 

sulfate standards in the upstream area of the basin on tributaries to the White River. Only 2 sites had exceedances of 

the chloride standard, most of these exceedances occurred at 

09304550 (Curtis Creek), and all exceedances occurred from 

data sampled prior to 1985 (app. 1). There were a total of 504 

exceedances of the sulfate standard at 6 sites, although most 

of the exceedances occurred at 09304480 (Coal Creek) and 

09304550 (Curtis Creek), 196 and 294 exceedances respectively. Most exceedances occurred prior to 1986; no sampling 

for chloride and sulfate occurred after that time at Curtis Creek 

and Coal Creek (app. 1). Insufficient data were available on 

the remaining tributaries to further aid in the analysis of DS in 

the White River Basin.

A loading profile for the White River Basin indicated 

increasing DS loads from upstream to downstream (fig. 9A). 

The total DS load from the White River Basin was represented 

by the most downstream site, 09306290 (White River below 

Boise Creek, near Rangely), where the load in water year 2000 

was 245,000 tons. The DS load at 09304200 for water 

year 2000 was 102,000 tons, which was about 41 percent 

of the load in the White River Basin at site 09306290. The 

DS load at 09304800 (White River below Meeker) for water 

year 2000 was 164,000 tons, which was about 67 percent 

of the load from the White River Basin. Between 09304200 

and 09304800 more than 60,000 tons of DS load are generated that could potentially be from irrigated agriculture. Load 

from 09306222 (Piceance Creek at White River) for water 

year 2000 was about 26,600 tons, which was about 11 percent 

of the load from the White River Basin. Alkali Flats is an area 
Characterization and Data-Gap Analysis of Surface-Water Quality 39

Table 6. Summary of regression model trend analysis results for dissolved solids and major ions, Piceance study area, western 

Colorado, 1990–2009.—Continued

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame of 

the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the respective time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and the time 

frame of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did not have 

data; IS, insufficient data for regression model analysis]

Fluoride, filtered,

in milligrams per liter

Silica, filtered,

in milligrams per liter

Alkalinity, filtered,

in milligrams per liter as

calcium carbonate

Dissolved solids,

in milligrams per liter

Upward Downward Upward Downward Upward Downward Upward Downward

White River Basin

IS NT; 1990–2002 — NT; 1990–2002

NT; 1990–2009 NT; 1990–2009 — NT; 1990–2009

NT; 1990–2009 NT; 1990–2009 NT; 1999–2009 2003–2009 1990–2003

NT; 1990–2009 NT; 1990–2009 NT; 1998–2009 NA 1990–2009

— — IS —

NT; 1990–2008 1990–1999 1999–2008 NA 1999–2008 1990–1993 1993–2008

1990–2000 2000–2009 NT; 1990–2009 F; 1999–2009 F; 1990–2009

NT; 1990–2009 NT; 1990–2009 IS 1990–1998 1998–2009

IS IS IS IS

Colorado River Basin

ND ND ND ND

IS IS IS IS

IS IS 1996–1999 1999–2004 IS

F; 1990–2009 NA 1990–2009 NT; 1996–2009 NA 1990–2009

NT; 1991–2009 NT; 1991–2009 1995–2002 2002–2009 NA 1991–2009

IS NT; 1992–2002 IS NT; 1992–2002

ND ND ND ND

NT; 1991–2006 NT; 1991–2006 NT; 1998–2006 NT; 1991–2006

ND ND ND ND

IS IS IS IS

NT; 1990–2009 F; 1990–2009 2001–2009 1990–2001 2005–2009 1990–2005

Lower Gunnison River Basin

NT; 1991–2009 NT; 1991–2009 1999–2004 2004–2009 NA 1991–2009

1991–2003 NA 1991–2003 NA IS NT; 1991–2003

F; 1990–2009 NT; 1991–2009 IS F; 1991–2009

IS IS IS IS

IS IS IS IS

NT; 1991–2009 1991–2009 NA NT; 2001–2009 NT; 1991–2009

1991–2009 NA 1991–2009 NA NT; 1998–2009 2001–2009 1991–2001

NT; 1990–2009 NT; 1990–2009 1999–2009 1990–1999 2005–2009 1990–2005

of known groundwater upwelling upstream from 09306222 

(Piceance Creek at White River). The area could represent 

an important input of DS to surface water, though losses in 

streamflow in the Alkali Flats area may also be occurring 

(Tobin and others, 1985; Ortiz, 2002). The sum of the loads at 

09304800 (White river below Meeker) and the tributary sites 

do not equal the load calculated at the most downstream site 

09306290 (White River below Boise Creek, near Rangely). 

The remaining DS load measured at the gage and unaccounted 

for by tributary inputs might be sourced from groundwater or 

unsampled tributaries.

Trace Elements

Sufficient data were available to compare the results of 

the trends analysis only for iron and total recoverable iron in 

the White River Basin (table 7). Along the main stem of the 

White River, no trend was detected in iron or total recoverable iron at either 09304800 (White River below Meeker) or 

09306290 (White River below Boise Creek, near Rangely) 

for the periods 1995 to 2009 and 1990 to 2009, respectively 

(table 7). At site 09306200 (Piceance Creek below Ryan Gulch, 

near Rio Blanco), no trend was detected in iron from 1990 to 

2009. Downstream at site 09306222 (Piceance Creek at White 

River), there was no net trend from 1991 to 2009, although 

there was a parabolic trend. The parabolic trend in iron was 

initially downward until around 2001, after which the trend was 

upward. An upward trend in iron was detected at 09306255 

(Yellow Creek near White River) from 1991 to 2009. Only 2 

of the 33 sites had exceedances of the 30-day drinking-water 

standard for iron; 1,871 samples had iron data (app. 1). The 

loading profile for the of the White River Basin indicated that 

iron load between the two White River sites (below Meeker and 

near Rangely) increased although the sampled tributaries did not 
40 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Table 7. Summary of regression model trend analysis results for trace elements and suspended sediment, Piceance study area, 

western Colorado, 1990–2009.

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame 

of the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the 

respective time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and 

the time frame of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did 

not have data; IS, insufficient data for regression model analysis]

Site name

Site

identification

number

Drainage

area, in

square miles

Copper, filtered,

in micrograms per liter

Upward Downward

White River Basin

White River above Coal Creek, near Meeker, Colo. 09304200 648 IS

White River below Meeker, Colo. 09304800 1,024 F; 1991–2009

Piceance Creek below Ryan Gulch, near Rio Blanco, Colo. 09306200 506 1999–2002 2002–2009

Piceance Creek at White River, Colo. 09306222 652 1999–2003 2003–2009

White River above Crooked Wash, near White River City, Colo. 09306224 1,821 IS

Corral Gulch near Rangely, Colo. 09306242 32 —

Yellow Creek near White River, Colo. 09306255 262 —

White River below Boise Creek, near Rangely, Colo. 09306290 2,530 —

White River below Taylor Draw Reservoir, above Rangely, Colo. 09306305 2,776 IS

Colorado River Basin

Colorado River Devereaux Bridge CDOWRW-47 — 1991–1999 1999–2006

Colorado River above South Canyon Creek, near Glenwood Springs, Colo. 09085150 6,040 ND

Dry Fork at Upper Station, near DeBeque Colo. 09095300 97 ND

Colorado River near Cameo, Colo. 09095500 8,050 IS

Plateau Creek near Cameo, Colo. 09105000 592 IS

Colorado River below Grand Valley Diversion, near Palisade, Colo. 09106150 8,753 IS

Colorado River Hwy 6 CDOWRW-555 — IS

Lewis Wash near Grand Junction, Colo. 09106200 4.7 IS

Colorado River Watson CDOWRW-560 — IS

Reed Wash near Mack, Colo. 09153290 16 ND

Colorado River near Colorado-Utah State Line 09163500 17,843 —

Lower Gunnison River Basin

North Fork Gunnison River above mouth, near Lazear, Colo. 09136100 969 IS

Sunflower Drain at Highway 92, near Read 384551107591901 — IS

Gunnison River at Delta, Colo. 09144250 5,628 IS

Loutsenhizer Arroyo at Falcon Road 383528107552001 — ND

West Tributary of Loutsenhizer Arroyo below East Canal 383728107572001 — ND

Loutsenhizer Arroyo at North River Road 383946107595301 — IS

Uncompahgre River at Delta, Colo. 09149500 1,115 —

Gunnison River near Grand Junction, Colo. 09152500 7,928 —

account for the increase (fig. 9B). Load from 09304800 (White 

River below Meeker) for water year 1996 was 21,000 pounds 

per year, which is 60 percent of the load from the White River 

Basin (fig. 9B). The remaining load might be sourced from 

groundwater or unsampled tributaries.

Suspended Sediment

Suspended sediment is a water-quality concern in the 

White River Basin, specifically in Douglas Creek. Douglas 

Creek is listed on the CDPHE 303(d) list for suspended sediment (table 2), yet there were no suspended sediment data 

available to evaluate trends and or calculate suspended sediment load. Suspended sediment loads were previously evaluated on the White River as part of the design of the Taylor 

Draw Reservoir (also known as Kenney Reservoir) (Salas and 

Shin, 1999).

 Trends in suspended sediment were analyzed for 4 sites 

on the White River main stem. No trends were detected from 

1990 to 2001 at 09304200 (White River above Coal Creek, near 

Meeker) (table 7). The suspended sediment model failed diagnostics at 09304800 (White River below Meeker) from 1990 

to 2009. A downward trend was detected at 09306290 (White 

River below Boise Creek, near Rangely) in suspended sediment from 1990 to 2009. A net, downward trend was detected 

at 09306305 (White River below Taylor Draw Reservoir, above 

Rangely) from 1995 to 2002. The trend was parabolic with a 

zero-slope year around 1996, prior to which the shape of the 

parabola indicated a downward trend. The downward trend at 

09306305 could be related to Taylor Draw Reservoir, which 

was constructed in 1984. The efficiency of a reservoir to retain 

sediment is a function of reservoir capacity, inflow volume, 

mean velocity of flow through the reservoir, and size composition of the sediment load (Churchill, 1948; Brune, 1953). A 

reservoir’s ability to retain sediment can increase as the ratio of 

the reservoir capacity to inflow volume increases or the percent 

composition of silt and clay in the sediment load decreases, or 

both. The downward trend at 09306305 might reflect a decrease 

in inflow volume or changes in sources of fluvial sediment.
Characterization and Data-Gap Analysis of Surface-Water Quality 41

Table 7. Summary of regression model trend analysis results for trace elements and suspended sediment, Piceance study area, 

western Colorado, 1990–2009.—Continued

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame 

of the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the 

respective time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and 

the time frame of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did 

not have data; IS, insufficient data for regression model analysis]

Iron, filtered,

in micrograms per liter

Iron, total recoverable,

in micrograms per liter

Lead, filtered,

in micrograms per liter

Zinc, filtered,

in micrograms per liter

Selenium, filtered,

in micrograms per liter

Upward Downward Upward Downward Upward Downward Upward Downward Upward Downward

White River Basin

IS NA 1991–2001 IS IS IS

NT; 1995–2009 NT; 1991–2002 — F; 1991–2009 F; 1991–2009

NT; 1990–2009 IS F; 1999–2009 NA 1990–2009 NT; 1999–2009

2001–2009 1991–2001 IS NT; 1999–2009 NA 1991–2009 NT; 1999–2009

IS IS IS IS IS

— IS — — —

1991–2009 NA IS — F; 1991–2009 —

NT; 1990–2009 NT; 1991–2001 — — NT; 1990–2009

IS IS ND ND IS

Colorado River Basin

NA 1991–2007 2000–2007 1991–2000 IS 1991–1995 1995–2007 IS

ND ND ND ND NT; 2006–2009

IS ND ND ND IS

1999–2002 1995–1999 IS IS IS NT; 1991–2009

— IS IS IS IS

— IS IS IS IS

IS IS IS IS IS

— ND IS IS 2000–2006 1991–2000

IS IS ND IS IS

IS ND ND ND IS

1997–2002 1990–1997 IS — — NA 1990–2009

Lower Gunnison River Basin

ND IS IS IS NT; 1991–2009

IS ND IS IS NA 1991–2003

ND IS IS IS NA 1991–2009

ND ND ND ND IS

ND ND ND ND IS

IS IS IS IS 1991–2009 NA

— — — IS 2002–2009 1991–2002

1999–2002 1990–1999 — — — NA 1990–2009

Trends in suspended sediment were analyzed for 4 tributary sites to the White River. A downward trend in suspended 

sediment was detected at 09306200 (Piceance Creek below 

Ryan Gulch, near Rio Blanco) from 1990 to 2009. A net, 

downward trend in suspended sediment was detected at 

09306222 (Piceance Creek at White River) from 1990 to 2009. 

The trend was parabolic with a zero-slope year around 2003, 

prior to which the shape of the parabola indicates a downward trend. Both site 09306255 (Yellow Creek near White 

River) and site 09306242 (Corral Gulch near Rangely) failed 

model diagnostics.

Colorado River Basin

Temporal and spatial variability of water-quality data 

in the Colorado River Basin were evaluated at 13 sites: 

8 sites on the Colorado main stem and 5 sites on tributaries to the Colorado River (tables 4–7, fig. 7). Main-stem 

sites on the Colorado River were CDOWRW-47 (Colorado 

River Deveraux Bridge), 09085150 (Colorado River above 

South Canyon near Glenwood Springs), CDOWRW-550 

(Colorado River Rifle Bridge), 09095500 (Colorado River 

near Cameo), 09106150 (Colorado River below Grand Valley 

Diversion near Palisade), CDOWRW-555 (Colorado River 

Highway 6), CDOWRW-560 (Colorado River Watson), 

and 09163500 (Colorado River near Colorado-Utah state 

line). Tributary sites were 09089500 (West Divide Creek 

near Raven), 09095300 (Dry Fork at Upper Station, near 

DeBeque), 09105000 (Plateau Creek near Cameo), 09106200 

(Lewis Wash near Grand Junction), and 09153290 (Reed 

Wash near Mack). The Gunnison River is also a tributary to 

the Colorado River, and it is discussed as a separate basin in 

this report. The most downstream site in the Lower Gunnison 

River Basin, 09152500 (Gunnison River near Grand Junction), 

is included in the figures and discussion of loading profiles 

for the Colorado River Basin to complete the discussion of 

spatial patterns.
42 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Table 7. Summary of regression model trend analysis results for trace elements and suspended sediment, Piceance study area, 

western Colorado, 1990–2009.—Continued

[The upward and downward columns are populated whenever there is a significant trend. If the trend was parabolic, then both columns contain the time frame 

of the respective trend direction, the net direction of the trend is indicated by shading. If the trend was monotonic, then the respective column contains the 

respective time frame and the other columns contains NA. If no significant trend was detected, then the combined columns contain an indicator of no trend and 

the time frame of the analysis; NT, no trend detected; F, model failed the model diagnostics; —, site did not have sufficient data for trend analysis; ND, site did 

not have data; IS, insufficient data for regression model analysis]

Site name

Site

identification

number

Suspended sediment,

in milligrams per liter

Upward Downward

White River Basin

White River above Coal Creek, near Meeker, Colo. 09304200 NT; 1990–2001

White River below Meeker, Colo. 09304800 F; 1990–2009

Piceance Creek below Ryan Gulch, near Rio Blanco, Colo. 09306200 NA 1990–2009

Piceance Creek at White River, Colo. 09306222 2003–2009 1990–2003

White River above Crooked Wash, near White River City, Colo. 09306224 —

Corral Gulch near Rangely, Colo. 09306242 F; 1990–2008

Yellow Creek near White River, Colo. 09306255 F; 1990–2009

White River below Boise Creek, near Rangely, Colo. 09306290 NA 1990–2009

White River below Taylor Draw Reservoir, above Rangely, Colo. 09306305 1995–1996 1996–2002

Colorado River Basin

Colorado River Devereaux Bridge CDOWRW–47 ND

Colorado River above South Canyon Creek, near Glenwood Springs, Colo. 09085150 ND

Dry Fork at Upper Station, near DeBeque Colo. 09095300 F; 1996–2004

Colorado River near Cameo, Colo. 09095500 F; 1990–1998

Plateau Creek near Cameo, Colo. 09105000 ND

Colorado River below Grand Valley Diversion, near Palisade, Colo. 09106150 ND

Colorado River Hwy 6 CDOWRW–555 ND

Lewis Wash near Grand Junction, Colo. 09106200 IS

Colorado River Watson CDOWRW–560 ND

Reed Wash near Mack, Colo. 09153290 IS

Colorado River near Colorado–Utah State Line 09163500 F; 1990–2008

Lower Gunnison River Basin

North Fork Gunnison River above mouth, near Lazear, Colo. 09136100 IS

Sunflower Drain at Highway 92, near Read 384551107591901 IS

Gunnison River at Delta, Colo. 09144250 ND

Loutsenhizer Arroyo at Falcon Road 383528107552001 ND

West Tributary of Loutsenhizer Arroyo below East Canal 383728107572001 ND

Loutsenhizer Arroyo at North River Road 383946107595301 ND

Uncompahgre River at Delta, Colo. 09149500 —

Gunnison River near Grand Junction, Colo. 09152500 F; 1990–2007

Field Properties

Results of the trend analysis for water temperature, pH, 

and dissolved oxygen are presented in table 4. Sufficient data 

were available to analyze for temperature trends at 5 sites in 

the Colorado River Basin. No significant trends in temperature 

were detected throughout the Colorado main-stem section. 

Sufficient data were available to analyze for pH trends at 

3 sites in the Colorado River Basin. An upward trend in pH 

was detected at 09095500 (Colorado River near Cameo) from 

1990 to 2009. Sufficient data were available to analyze for 

dissolved-oxygen trends at 4 sites. A downward trend in dissolved oxygen was detected at CDOWRW-47 (Colorado River 

Devereux Bridge) from 1991 to 2007.

Nutrients

Trends in nutrient concentration data were evaluated for 

ammonia, nitrate, orthophosphate, and total phosphorus. Models 

failed diagnostics for ammonia and nitrate at site 09095500 

(Colorado River near Cameo) from 1991 to 2002 (table 5). 

Additionally, between 1980 and 1998, there were 16 exceedances for total phosphorus (app. 1). At 09163500 (Colorado 

River near Colorado-Utah state line), a downward trend was 

detected in nitrate and orthophosphate from 1990–2008. A net, 

downward trend in ammonia was detected at this site from 1990 

to 2008. The trend was parabolic with a zero-slope year around 

2002, prior to which the shape of the parabola indicates a downward trend. An upward trend was detected in total phosphorus 

at the same site during the same time period, and there were 

122 exceedances from 1979–2008 (app. 1). Without a regression model for nutrient data upstream from 09095500 (Colorado 

River near Cameo) on the main stem of the Colorado River, 

it is difficult to determine what the potential upstream sources 

were contributing to the observed trends at 09163500 (Colorado 

River near Colorado-Utah state line).

Limited nutrient data were available for tributaries to 

the Colorado main stem. Sufficient data were not available 

for trend analysis at 09153290 (Reed Wash near Mack), but 
Characterization and Data-Gap Analysis of Surface-Water Quality 43

there were 40 exceedances in total phosphorus from 1995 to 

1998 (app. 1). As such, Reed Wash was a probable source of 

total phosphorus to the Colorado River. No trend was detected 

at 09095300 (Dry Fork at Upper Station, near DeBeque) for 

orthophosphate from 1996 to 2004, and a net, downward trend 

in nitrate was detected from 1996 to 2004. The total phosphorus model failed diagnostics for site 09095300 (Dry Fork at 

Upper Station, near DeBeque) from 1996 to 2004; 24 exceedances were observed for the same period (app. 1).

Although neither the nitrate nor the orthophosphate loading profile for the Colorado River has sufficient information 

for a comprehensive analysis (fig. 10), the lower Colorado 

River was analyzed with respect to the contributions from its 

principal tributary, the Gunnison River. The total nitrate load 

from the Gunnison River, represented by 091520500 (Gunnison 

River near Grand Junction), was 1,670 tons in 1996, which was 

52 percent of the total load at 09163500 (Colorado River near 

Colorado-Utah state line) (fig. 10A). The total nitrate load from 

the Colorado River Basin, represented by the most downstream 

site 09163500 (Colorado River near Colorado-Utah state line), 

was 3,230 tons. Orthophosphate load from the Gunnison River 

in water year 1996 was 125 tons, 32 percent of the total load 

at the Colorado River near Colorado-Utah state line (385 tons) 

(fig. 10B). These results indicated that the Gunnison River 

is a substantial source of nitrate and orthophosphate to the 

Colorado River.

Dissolved Solids and Major Ions

Trends in DS were evaluated at 3 sites on the Colorado 

main stem. A downward trend was detected in DS at 09095500 

(Colorado River near Cameo) from 1990 to 2009, and no 

trend was detected at 09106150 (Colorado River below Grand 

Valley Diversion near Palisade) from 1992 to 2002 (table 6). 

A net, downward trend in DS was detected at 09163500 

(Colorado River near Colorado-Utah state border) from 1990 

to 2009. The trend was parabolic with a zero-slope year 

around 2005, prior to which the shape of the parabola indicates a downward trend. Salinity control work in the Grand 

Valley could have contributed to the downward trend at 

09163500 (Colorado River near Colorado-Utah state border). 

Trends in other major ion concentrations may aid in identifying sources of DS based on mineral composition, where dissolution of these sources might be controlling DS contribution 

to the Colorado River. The trend results indicated that other 

major ions (sulfate, chloride, magnesium, and sodium) had 

similar trend patterns as DS throughout the basin.

The three tributary sites for the Colorado River that had 

sufficient data for trend analysis for the majority of major ions 

were 09095300 (Dry Fork at Upper Station, near DeBeque), 

09105000 (Plateau Creek near Cameo), and 09106200 

(Lewis Wash near Grand Junction) (table 6). Net, downward 

trends were detected for sulfate, alkalinity, and bicarbonate 

at site 09095300 (Dry Fork at Upper Station, near DeBeque) 

from 1996 to 2004. The trends were parabolic with a zeroslope year around 1999, prior to which the shape of the 

parabola indicated an upward trend. No trends were detected 

at 09095300 (Dry Fork at Upper Station, near DeBeque) 

for chloride and carbonate, and there were insufficient data 

to analyze trends in DS. A downward trend was detected at 

09105000 (Plateau Creek near Cameo) from 1991 to 2009 for 

DS, sulfate, and sodium. A net, downward trend was detected 

for chloride from 1991 to 2009. The trend was parabolic with 

a zero-slope year around 2002, prior to which the shape of 

the parabola indicated an upward trend. There were no trends 

detected in calcium, magnesium, potassium, fluoride, or silica. 

An upward trend was detected for bicarbonate from 1995 to 

2009, while no trend was detected for carbonate during the 

same period. The headwaters of Plateau Creek originate on 

the Grand Mesa (fig. 1) where the geology is dominated by 

vesicular basalt. The Grand Mesa has relatively little urban 

development in comparison to the Colorado River mainstem corridor, but the area is experiencing increasing energy 

development. Downstream, Plateau Creek flows over Tertiary 

sedimentary formations composed of mudstone and sandstone, 

which are a likely source for DS in Plateau Creek. Downward 

trends were detected at 09106200 (Lewis Wash near Grand 

Junction) for magnesium and sulfate from 1991 to 2006; no 

trends were detected for DS and the other major ions (table 6).

Natural sources and anthropogenic activities contribute 

to DS along the Colorado River main stem. The Eagle Valley 

Evaporite (fig. 3), present upstream from Glenwood Springs 

and in the Roaring Fork drainage area, is a natural source of 

DS in the upper part of the basin. Chafin and Butler (2002) 

reported that the Eagle Valley Evaporite contributed approximately 800,000 metric tons of salt per year to the Colorado 

River. Salts from the Eagle Valley Evaporite contributed 

nearly 60 percent of the annual DS load observed at the 

USGS gaging station Colorado River near Cameo (09095500) 

(Chafin and Butler, 2002). The high concentrations of DS 

downstream from 09095500 (Colorado River near Cameo) can 

be attributed to irrigation of the sedimentary formations such 

as the Mancos Shale and Dakota Sandstone (fig. 3). Irrigation 

return flows generally have a higher salinity concentration 

than the applied water because of the effect of salt dissolution in the soil and subsurface materials and the concentrating 

effect of evapotranspiration (Vaill and Butler, 1999). A loading 

profile for the Colorado River Basin indicated increasing DS 

load from upstream to downstream with the exception of the 

Colorado River below the Grand Valley Diversion (fig. 11A). 

The total DS load from the Colorado River Basin is represented by the most downstream site, 09163500 (Colorado 

River near Colorado-Utah state line). The load in water 

year 1999 was 2,850,000 tons (fig. 11A), which is about 

10 times larger than the DS load from the White River Basin 

in water year 2000 (fig. 9A). Load at 09095500 (Colorado 

River near Cameo) for water year 1999 was 1,380,000 tons, 

which was about 48 percent of the load from the Colorado 

River Basin (fig. 11A). Load from 09105000 (Plateau Creek 

near Cameo) for water year 1999 was 59,700 tons, which was 

about 2 percent of the load from the Colorado River Basin 
44 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

(fig. 11A). Load from 09106150 (Colorado River below the 

Grand Valley Diversion near Palisade) was 1,090,000 tons 

for water year 1999, which was about 38 percent of the 

load from the Colorado River Basin. The reduction in load 

from 09095500 (Colorado River near Cameo) to 09106150 

(Colorado River below the Grand Valley Diversion near 

Palisade) indicated that DS loads were removed along with 

significant diversions in this area (fig. 11A). Downstream 

from 09095500 (Colorado River near Cameo) there are two 

diversions of irrigation water that have an estimated capacity 

of 2,380 cubic feet per second (ft3/s), and about 650 ft3/s is 

returned to the Colorado River just above the site 09106150 

(Colorado River below the Grand Valley Diversion near 

Palisade) (Butler, 1985; Kuhn and Williams, 2004). Leib and 

Bauch (2008) estimated an average annual DS concentration 

of 374 mg/L for 09095500 in water year 1999, which included 

both irrigated and non-irrigated seasons. Using the concentration of 374 mg/L resulted in an estimation of approximately 

350,000 tons of dissolved solids that could be diverted 

between 09095500 and 09106150, and this estimation would 

vary based on season and water availability. The Gunnison 

River, represented by 09152500 (Gunnison River near Grand 

Junction), contributed 1,064,000 tons of dissolved solids to 

the Colorado River in water year 1996 (fig. 11A), which was 

37 percent of the most downstream site, 09163500 (Colorado 

River near Colorado-Utah state line).

Trace Elements

Sufficient data were available to compare the results 

of the trends analysis for iron in the Colorado River Basin 

(table 7). A downward trend for iron was detected at site 

CDOWRW-47 (Colorado River Devereux Bridge) from 1991 

to 2007 (table 7). At 09095500 (Colorado River near Cameo), 

a net, downward trend in iron was detected from 1995 to 2002. 

The trend was also parabolic with a zero-slope year around 

1999, after which the shape of the parabola indicated an 

upward trend. At 09163500 (Colorado River near ColoradoUtah state line), a net, downward trend was detected in iron 

from 1990 to 2002. The trend also was parabolic with a zeroslope year around 1997, after which the shape of the parabola 

indicated an upward trend. The loading profile for iron indicated a decreasing iron load downstream (fig. 11B). The iron 

load in water year 1996 at 09163500 (Colorado River near 

Colorado-Utah state line) was 134,000 pounds, which was 

43,000 pounds less than the iron load from the upstream site, 

09095500 (Colorado River near Cameo) (177,000 pounds). 

Despite the contribution of 41,700 pounds of iron in water 

year 1996 from 09152500 (Gunnison River near Grand 

Junction), there still was a loss in iron load (1,300 pounds) 

at 09163500 (Colorado River near Colorado-Utah state line). 

There are no major hard-rock mines in the Colorado River 

Basin that could have been potential point sources for selected 

trace elements like iron. Further study of iron sources and 

sinks in the Colorado River Basin near Grand Junction would 

be beneficial to better understand these results. Results for 

total recoverable iron throughout the Colorado River Basin 

reported 600 exceedances of the chronic aquatic-life standard 

(app. 1). There were approximately 82 exceedances observed 

at 4 sites on Plateau Creek, although the sampling period was 

from 1992 to 2004. Insufficient data were available to perform 

a trend analysis on any Plateau Creek site.

Similar to DS, selenium is a water-quality concern in 

the Colorado River Basin because of the combination of 

geologic formations and land use. The CDPHE has listed 

many stream segments from East Rifle Creek to the ColoradoUtah state border for selenium impairments (table 2). No 

trend was detected in selenium at 09095500 (Colorado River 

near Cameo) from 1991 to 2009, and a downward trend was 

detected at 09163500 (Colorado River near Colorado-Utah 

state line) from 1990 to 2009. Results for selenium in the 

Colorado River Basin reported 741 exceedances of the chronic 

aquatic-life standard and 201 exceedances of the acute standard (app. 1).

A loading profile for the Colorado River Basin indicated 

increased selenium load between the 09095500 (Colorado 

River near Cameo) and 09163500 (Colorado River near 

Colorado-Utah state line) sites (fig.11C). The total selenium 

load from the Colorado River Basin at the most downstream 

site 09163500 (Colorado River near Colorado-Utah state line) 

in water year 1999 was 36,200 pounds. Load at 09095500 

(Colorado River near Cameo) for water year 1999 was 

3,900 pounds, which was about 11 percent of the load from 

the Colorado River Basin. Load at 09152500 (Gunnison River 

near Grand Junction) for water year 1999 was 18,900 pounds, 

which was about 52 percent of the load from the Colorado 

River Basin, indicating that the Lower Gunnison River Basin 

is one of the major source of selenium in this part of the 

Colorado River Basin.

Insufficient data were available to analyze selenium 

data for trends or loads on tributaries to the Colorado River 

upstream from Plateau Creek. Median selenium concentration 

at 09095300 (Dry Fork at Upper Station, near De Beque) was 

4 μg/L, and there were 16 exceedances from 1996 to 2001 

of the chronic aquatic-life standard. The site is listed on the 

CDPHE 303d list for selenium impairment. Additional waterquality monitoring could help land managers to identify what 

is causing the selenium impairment. Sites on Divide Creek 

(LANG2ST-LANG8ST) had a median selenium concentration 

of 5.6 μg/L and approximately 62 exceedances from 2004 to 

2005 of the chronic aquatic-life standard. Other tributaries in 

the basin such as East Rifle Creek, West Rifle Creek, and Rifle 

Creek are listed on the CDPHE 303d list for selenium impairment, but insufficient data were available from this study to 

analyze for trends.
Characterization and Data-Gap Analysis of Surface-Water Quality 45

Suspended Sediment

Suspended sediment data did not meet the criteria for 

trend analysis at most sites, and the models failed diagnostics 

at sites where there were sufficient data. Failed diagnostics 

were reported at sites 09095300 (Dry Fork at Upper Station, 

near DeBeque), 09095500 (Colorado River near Cameo), and 

09163500 (Colorado River near Colorado-Utah state line). 

Sediment is listed on the 303d list for Salt Creek, which is a 

tributary to the Colorado River (table 2).

Lower Gunnison River Basin

Temporal and spatial variability of water-quality data in the 

Lower Gunnison River Basin were evaluated at 14 sites: 2 sites 

on the Gunnison River main stem and 12 sites on tributaries to the Gunnison River (tables 4–7, fig.7). Main-stem sites 

on the Gunnison River were 09144250 (Gunnison River at 

Delta) and 09152500 (Gunnison River near Grand Junction). 

Tributary sites included 09132500 (North Fork Gunnison 

River near Somerset), 09136100 (North Fork Gunnison River 

above mouth near Lazear), 09134000 (Minnesota Creek near 

Paonia), 09135950 (North Fork of the Gunnison below Leroux 

Creek, near Hotchkiss), 09128500 (Smith Fork near Crawford), 

384551107591901 (Sunflower Drain at Highway 92, near 

Read), 09143000 and 09143500 (Surface Creek near and at 

Cedaredge, respectively), and 09149500 (Uncompahgre River 

at Delta). There were 3 sites on Loutsenhizer Arroyo, which 

is a tributary to the Uncompahgre River: 383528107552001 

(Loutsenhizer Arroyo at Falcon Road), 383728107572001 

(West tributary of Loutsenhizer Arroyo below East Canal), and 

383946107595301 (Loutsenhizer Arroyo at North River Road).

Field Properties

Results of the trend analysis for water temperature, pH, 

and dissolved oxygen are presented in table 4. Sufficient data 

were available to analyze for temperature trends at 4 sites in 

the Lower Gunnison River Basin. No trends were detected at 3 

of these sites. However, an upward trend was detected in water 

temperature from 1990 to 2009 at 09152500 (Gunnison River 

near Grand Junction), the most downstream site. This same 

site, 09152500, also had sufficient data to analyze for trends 

in dissolved oxygen and pH from 1990 to 2009 and no trends 

were detected.

Nutrients

There are limited nutrient data in the Lower Gunnison 

River Basin (table 5). Only one site, 09152500 (Gunnison 

River near Grand Junction), met the criteria for the trend 

analysis. No trend was detected in nitrate from 1990 to 

2002, orthophosphate from 1990 to 1998, or organic carbon 

from 1995 to 2002. Comparisons to the recommended total 

phosphorus standard showed nearly 500 exceedances out of 

1,538 samples. Additional long-term monitoring of nutrients 

in surface water could provide an opportunity to describe the 

current nutrient levels in the Lower Gunnison River Basin.

Dissolved Solids and Major Ions

Dissolved solids are a water-quality concern to land and 

water managers in the Lower Gunnison River Basin because 

of the combination of geologic formations and land use. This 

scenario is in contrast to the Colorado River Basin where DS 

levels are greatly elevated from natural sources such as the 

Eagle Valley Evaporite Formation (Chafin and Butler, 2002). 

Natural sources of DS include seeps or springs that originate 

from geological formations with high DS content, such as the 

Mancos Shale and Dakota Sandstone in the Lower Gunnison 

River Basin (fig. 3). Another source of DS in the Lower 

Gunnison River Basin is the result of irrigated agriculture in 

areas underlain by Mancos Shale (Butler and others, 1996).

In the Lower Gunnison River Basin, trends in DS and 

other major ions were tested at 2 sites on the main stem and 

4 tributary sites of the Gunnison River. The main-stem sites 

were 09152500 (Gunnison River near Grand Junction) and 

09144250 (Gunnison River at Delta). The DS model failed 

diagnostics at 09144250 (app. 1, table 6); many of the other 

models for trends in major ions also failed model diagnostics for this site. However, a downward trend at 09144250 

(Gunnison River at Delta) was detected in magnesium, and no 

trend was detected in potassium or silica from 1991 to 2009. 

Schaffrath (2011) reported a downward trend in DS for the 

period 1989 through 2004. The most downstream site in the 

basin was 09152500 (Gunnison River near Grand Junction), 

where a net, downward trend was detected from 1990 to 2009. 

The trend was parabolic with a zero-slope year around 2005, 

after which the shape of the parabola indicated an upward 

trend. This conclusion is supported by the findings reported 

by Schaffrath (2012); that is, a downward trend from 1989 

through 2003 and a net, downward trend from 1989 through 

2007 for DS. Other major ions analyzed for trends at this site 

(and study period) generally had the same result. Calcium, 

magnesium, sodium, and chloride all had the same general 

trend pattern. Parabolic trends were detected for potassium and alkalinity with zero slope years of 2000 and 1999, 

respectively. No net trend was detected for the time period for 

both of these constituents. No trend was detected for silica or 

bicarbonate. Downward trends were detected for sulfate and 

carbonate, while an upward trend was detected for fluoride 

from 1990 to 2009.

Trends were analyzed at 4 tributary sites: 09136100 

(North Fork Gunnison River above mouth near Lazear), 

384551107591901 (Sunflower Drain at Highway 92, near 

Read), 09149500 (Uncompahgre River at Delta), and 

383946107595301 (Loutsenhizer Arroyo at North River 

Road) (table 6). The first three sites are tributaries to the main 

stem of the Gunnison River while the fourth site is tributary 
46 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

to the Uncompahgre River. A downward trend was detected 

for DS, calcium, magnesium, sodium, and sulfate at site 

09136100 (North Fork Gunnison River above mouth near 

Lazear) from 1991 to 2009, and no trends were detected for 

potassium, fluoride, or silica. No trends were detected for DS, 

calcium, magnesium, sodium, potassium, chloride, or sulfate 

at 384551107591901 (Sunflower Drain at Highway 92, near 

Read) for the period from 1991 to 2003. However, upward 

trends were detected for fluoride and silica from 1991 to 2003 

at 384551107591901 (Sunflower Drain at Highway 92, near 

Read). The trend analysis period for this site may not reflect 

the most recent condition in that area. A portion of the DS 

(and other major ions) load measured at site 384551107591901 

(Sunflower Drain at Highway 92, near Read) was from water 

diverted from the Uncompahgre River Basin; however, the 

actual amount is unknown because of data limitations. A 

net, downward trend was detected for DS at site 09149500 

(Uncompahgre River at Delta) from 1991 to 2009. The trend 

was parabolic with a zero-slope year around 2001, after which 

the shape of the parabola indicated an upward trend. Downward 

trends with significant parabolic trends similar to DS were 

detected for calcium, magnesium, sodium, chloride, and sulfate. 

An upward trend was detected for fluoride from 1991 to 2009. 

The shape of the major ion trends at 09149500 (Uncompahgre 

River at Delta) was similar to those detected at 09152500 

(Gunnison River near Grand Junction), but the zero-slope years 

differed slightly. Both the North Fork and the Uncompahgre 

River Basins have similar DS and major ion trends and are the 

two major tributaries to the Gunnison River. This would indicate 

that both the North Fork and Uncompahgre River Basins were 

controlling the trends at the 09152500 (Gunnison River near 

Grand Junction) site; however, the trend at 09149500 (Uncompahgre River at Delta) may have more influence based on its 

similar trend slope and direction to that found for 09152500 

(Gunnison River near Grand Junction). Schaffrath (2012) 

reported a downward trend in DS at 09149500 (Uncompahgre 

River at Delta) from 1989 to 2004. The drainage area above 

this site is dominated by agricultural land and is underlain by 

Mancos Shale. Salinity-control efforts have been focused in 

this area since the 1980s. The site that was a tributary to the 

Uncompahgre River, 383946107595301 (Loutsenhizer Arroyo 

at North River Road), did not have a trend in DS or other major 

ions except for an upward trend for silica from 1991 to 2009.

The DS load from the Gunnison River Basin is represented by the most downstream site, 09152500 (Gunnison 

River near Grand Junction). The Gunnison River is a tributary 

to the Colorado River, so the loading profile was compared 

to 09163500 (Colorado River at the Colorado-Utah state 

line) (fig. 12A). Load at 09152500 (Gunnison River near 

Grand Junction) for water year 1999 was approximately 

1,060,000 tons (fig. 12A), which was about 37 percent of 

the load calculated for 09163500 (Colorado River at the 

Colorado-Utah state line) (fig. 11A). Load at 09136100 (North 

Fork Gunnison River above mouth near Lazear) could not 

be calculated because of an incomplete streamflow record. 

The DS load in the North Fork of the Gunnison River drainage area is primarily from natural and agricultural sources 

based on the low levels of industrial and residential uses 

(Homer and others, 2004), and salinity control efforts are 

ongoing in the area. The models failed diagnostics for loads 

in DS at 09144250 (Gunnison River at Delta) and 09149500 

(Uncompahgre River at Delta). However, Schaffrath (2012) 

developed model equations for 09144250, 09149500, and 

09152500. Using those equations, the 1999 water year 

load calculated for 09152500 (Gunnison River near Grand 

Junction) was 1,070,000 tons, which was only 10,000 tons 

more than the load calculated using the model equations 

developed in this report. The DS load in water year 1999 at 

09144250 (Gunnison River at Delta), for comparison, was 

582,000 tons, which was about 54 percent of the load from the 

Lower Gunnison River Basin. The Uncompahgre River flows 

into the Gunnison River just downstream from site 09149500 

(Uncompahgre River at Delta). The DS load at 09144250 

(Gunnison River at Delta) for water year 1999, also calculated using equations from Schaffrath (2012), was approximately 371,000 tons, which was about 35 percent of the load 

from the Lower Gunnison River Basin that year. Load at the 

Loutsenhizer Arroyo site could not be calculated because of 

insufficient streamflow data.

The majority of DS load and respective salinity-control 

efforts have occurred in the Gunnison River drainage area 

downstream from the Gunnison Tunnel (Lower Gunnison 

River Basin). Schaffrath (2012) reported no downward trends 

in DS in the Upper Gunnison River drainage area, defined in 

this report as the region of the Gunnison River upstream from 

the Gunnison Tunnel. Efforts to reduce DS load in the Lower 

Gunnison River Basin have been ongoing since the 1980s 

through salinity control efforts. On-farm and small irrigation ditch improvements as of 2007 had been implemented 

in 76 mi2 in the Lower Gunnison River Basin, resulting in 

estimates of DS load reduction of 95,200 tons (Frank Riggle, 

Natural Resources Conservation Service, written commun., 

July 28, 2010; Schaffrath, 2011). Bureau of Reclamation also 

sponsors programs to reduce DS load in the Lower Gunnison 

River Basin; they had participated in projects that included 

29 miles of canal lining and elimination of stock watering areas that resulted in estimates of DS load reduction of 

49,520 tons as of 2007 (Mike Baker, Bureau of Reclamation, 

written commun., September 20, 2010; Schaffrath, 2012).

Trace Elements

Sufficient data were available only for trend analysis of 

iron at site 09152500 (Gunnison River near Grand Junction) 

and selenium at various other sites in the Lower Gunnison 

River Basin (table 7). A net, downward trend in iron was 

detected at 09152500 (Gunnison River near Grand Junction) 

from 1990 to 2002. The trend also was parabolic with a zeroslope year of 1999, prior to which the shape of the parabola 

indicated an upward trend. The Lower Gunnison River Basin 

had 326 exceedances of the chronic (30-day) aquatic-life 
Characterization and Data-Gap Analysis of Surface-Water Quality 47

standard for iron (app. 1). There were exceedances for many 

of the trace elements sampled in the basin. For example, 

34 exceedances for the aquatic-life 30-day standard for copper, 

18 exceedances for the acute copper standard, 73 exceedances 

of the chronic (30-day) aquatic-life standard for lead, and 

4 exceedances of the acute standard for lead were observed. 

Zinc had no more than 7 exceedances of the chronic or acute 

water-quality standards. About 25 mi2 of the Lower Gunnison 

River Basin are Federal coal leases, and Oxbow Mining and 

Mountain Coal Company are interested in developing approximately 3 mi2

 (U.S. Forest Service, 2011). The infrequent 

sampling for trace elements and high number of exceedances 

in the Lower Gunnison River Basin illustrated a data gap in 

the Piceance study area.

Selenium is a major water-quality concern for land and 

water managers in the Lower Gunnison River Basin. Similar 

to DS, high selenium concentrations are due to the combination of geologic formations and land use. Selenium is primarily sourced from a geologic formation known as the Mancos 

Shale; that is, DS is sourced from the Mancos Shale formation and a variety of sedimentary rock formations in the area. 

Selenium is leached from soils in a similar manner as DS by 

way of irrigation and natural chemical processes. Selenium is 

more chemically reactive than the major ions included in the 

DS measurements. The reactive nature of selenium can cause 

selenium to oxidize and reduce between mobile and immobile 

forms. Therefore, there is a high degree of the temporal and 

spatial variability in selenium concentrations. This extreme 

variability is complicated, and scientists and land managers 

often have a difficult time understanding the effects that various types of land use in the Lower Gunnison River Basin have 

on selenium concentrations in rivers and streams. Previous 

studies in the Lower Gunnison River Basin have documented 

that high selenium concentrations correlate with high DS 

concentrations. The nature of this paired occurrence means 

that when salinity control efforts are conducted in seleniumrich areas of the Lower Gunnison River Basin, both DS and 

selenium concentrations have the potential to decrease (Butler 

and others, 1996; Moore, 2011).

Trends in selenium were analyzed at 2 sites on the main 

stem of the Gunnison River and at 4 sites on tributaries to the 

Gunnison River. Main-stem sites were 09144250 (Gunnison 

River at Delta) and 09152500 (Gunnison near Grand 

Junction). Downward trends in selenium were detected at both 

main-stem sites from 1991 to 2009 at 09144250 (Gunnison 

River at Delta) and from 1990 to 2009 at 09152500 (Gunnison 

near Grand Junction) (table 7).

The 4 tributary sites to the Gunnison River were 09136100 

(North Fork of the Gunnison above mouth near Lazear), 

09149500 (Uncompahgre River at Delta), 384551107591901 

(Sunflower Drain at Highway 92, near Read), and 

383946107595301 (Loutsenhizer Arroyo at North River Road). 

No selenium trend was detected at site 09136100 (North Fork of 

the Gunnison near the mouth of Lazear) from 1991 to 2009. A 

net, downward trend for selenium was detected at site 09149500 

(Uncompahgre River at Delta) from 1991 to 2009. The trend 

was also parabolic with a zero-slope year of 2002, after which 

the shape of the parabola indicates an upward trend. The shape 

of the selenium trend at this site was very similar to that of 

the DS trend observed at this site. A downward trend in selenium was detected at 384551107591901 (Sunflower Drain at 

Highway 92, near Read) from 1991 to 2003. The period of 

record for 384551107591901 (Sunflower Drain at Highway 92, 

near Read) ends in 2003; therefore, it is unknown if the downward trend for the 1991 to 2003 period is representative of 

current conditions. An upward trend in selenium was detected at 

383946107595301 (Loutsenhizer Arroyo at North River Road), 

a tributary to the Uncompahgre River, from 1991 to 2009. This 

was the only site tested in the Lower Gunnison River Basin 

that had an upward trend in selenium. Selenium load reported 

by Butler and Leib (2002) indicated that Loutsenhizer Arroyo 

drainage area is one of the largest sources of selenium load in 

the Lower Gunnison River Basin. This may explain why there 

is a parabolic trend in selenium at the 09149500 (Uncompahgre 

River at Delta) while 09152500 (Gunnison River near Grand 

Junction) only had a downward trend.

The loading profile includes the two main-stem Gunnison 

River sites, 09144250 (Gunnison River at Delta) and 09152500 

(Gunnison River near Grand Junction), and a site on the 

Uncompahgre River, 09149500 (Uncompahgre River at Delta) 

(fig. 12B). The other sites for which selenium trends were 

analyzed did not have sufficient streamflow data to calculate annual loads. The load at the most downstream site in 

the basin, 09152500 (Gunnison River near Grand Junction), 

was 19,000 pounds in 1999. This basin is a tributary to the 

Colorado River, and 19,000 pounds is about 52 percent of the 

load estimated for 09163500 (Colorado River at the ColoradoUtah state line) (fig. 11C). Mayo and Leib (2012) reported a 

downward trend in load at this site for the period 1986 to 2008. 

Mayo and Leib also reported the magnitude of the trend to be an 

approximate decrease of 2 μg/L, which is about 6,000 pounds 

annual difference between 1986 and 2008. Selenium load at 

09144250 (Gunnison River at Delta) for water year 1999 was 

9,180 pounds in 1999, which was about 48 percent of the load 

from site 09152500 (Gunnison River near Grand Junction). 

Selenium load at 09144250 (Gunnison River at Delta) is 

sourced not only from the Gunnison River and North Fork of 

the Gunnison River Basins, but also from parts of the Uncompahgre River Basin as a result of multiple water diversions from 

the Uncompahgre River. The elevated selenium load is counterintuitive because the Uncompahgre River Basin is a tributary 

to the Gunnison River downstream from 09144250 (Gunnison 

River at Delta). The actual portion of selenium load from the 

Uncompahgre River Basin at 09144250 (Gunnison River at 

Delta) is unknown because of data limitations. Moore (2011) 

reported upward trends in selenium concentration and load in 

Montrose Arroyo. Montrose Arroyo is situated geologically in a 

similar manner and has similar geology as Loutsenhizer Arroyo 

in the Uncompahgre River Basin but is outside the study area. 

Moore (2011) suggested that changes in land use and possible 

geochemical factors could be causing the increases in selenium.
48 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Suspended Sediment

Sufficient data were available at 09152500 (Gunnison 

River near Grand Junction) to perform trend analysis, but the 

model failed diagnostics. Therefore, insufficient data were 

available and trend analysis could not be performed for the 

Lower Gunnison River Basin (table 7).

Data Gaps

Spatial, temporal, and analytical data gaps were identified in the study area. Spatial data gaps were identified where 

surface-water monitoring sites were not sufficient to characterize trends and loads, especially in areas contributing to a 

municipal drinking-water intake. Temporal data gaps were 

identified where data were collected in the past but are not 

being collected currently. Analytical data gaps were identified where analysis was incomplete (for example, not enough 

major ions to do a charge balance), entire constituent groups 

were omitted (for example, nutrients in the Lower Gunnison 

River Basin), or select constituents were not sampled for (for 

example, BTEX in the White River Basin).

White River Basin

The White River Basin had 45 water-quality sites of which 

10 could be used for analysis of trends and loads (fig. 13). Sites 

where trends or loads were not analyzed included sites that were 

not currently being sampled, did not have sufficient data for 

analysis beyond summary statistics and comparison to standards, or lacked continuous streamflow data.

The spatial coverage of sampling sites could be expanded 

in the White River Basin by adding more tributary sites. 

Water-quality and streamflow data for Douglas Creek are not 

currently being collected. The exception is a single site located 

at the mouth of Douglas Creek where streamflow gaging and 

sampling were discontinued in 1996. Douglas Creek has a 

drainage area of 425 mi2 of the 2,776 mi2 (about 15 percent) of 

the White River Basin. Water-quality samples are collected on 

Coal, Flag, and Strawberry Creeks, but the addition of streamflow data could greatly enhance these datasets. No waterquality data exists for tributaries in the area north of Rangely, 

Colo., where extensive energy development has occurred in a 

complex geologic setting.

Analytical data gaps were identified in several constituent groups in the White River Basin. Owing to the amount 

of natural gas development and the potential for naturally 

occurring sources of BTEX, a synoptic sampling of BTEX at 

surface-water sites and springs could provide useful baseline 

information to better understand BTEX concentrations in the 

White River Basin, specifically in the Piceance and Yellow 

Creek drainage areas. Trace elements were collected at a 

few sites, mostly on tributaries (Piceance Creek), thus limiting the ability to understand occurrence, concentrations, and 

load. Selenium is identified on the 303d list for Black Sulphur 

Creek and Flag Creek (table 2), both tributaries to the White 

River. However, sufficient data were not available at either site 

to obtain an understanding of the sources or sinks of selenium 

in the area. Furthermore, neither site has continuous streamflow to enable calculation of loads. Sediment is identified on 

the 303d list for Douglas Creek and West Evacuation Creek 

(table 2), but water-quality and quantity data are not currently 

being collected on Douglas Creek or West Evacuation Creek.

Colorado River Basin

Data collection has occurred at numerous sites throughout the Colorado River Basin (fig.14). The spatial and temporal continuity of these data efforts are often inconsistent. An 

attempt to calculate loads in the Colorado River Basin resulted 

in only 13 of the 179 sites meeting the criteria for trend analysis. Limited data were available for field properties, major 

ions, nutrients, and trace elements on the main stem of the 

Colorado River between Glenwood Springs and Cameo, Colo. 

Limited data were available on Plateau Creek for nutrients and 

trace elements. Urban growth, energy development, and landuse change in the Colorado River Basin increases the need to 

understand changes in water quality in the main stem and the 

respective tributaries.

The main analytical data gaps identified in the Colorado 

River Basin were nutrients and trace elements. The nitrate and 

orthophosphate trend analysis demonstrated at the Colorado 

River near the Colorado-Utah state line (09163500) is a downward trend from 1990 to 2008. Nutrient data were collected 

minimally upstream from 09163500 on the main stem of the 

Colorado River, and data were not collected on the Gunnison 

River (major tributary in the reach). Therefore, existing data 

are not sufficient to identify the land-use change and sources 

of the nutrient trends.

Iron loads decreased between 09095500 (Colorado River 

at Cameo) and 09163500 (Colorado River near ColoradoUtah state line), and further study is needed to understand iron 

sources and sinks in this area. Selenium has been identified on 

the 303d list for all tributaries to the Colorado River between 

the confluence of the Roaring Fork and the Colorado River 

downstream to Parachute Creek (fig. 1). These tributaries have 

limited or no streamflow or water-quality data to complete 

load or trend analysis. Sediment has been identified on the 

303d list for Salt Creek and E.coli and total recoverable iron 

for Adobe Creek (table 2, fig. 14). Salt Creek and Adobe Creek 

are tributaries to the Colorado River, and water-quality and 

water-quantity data are not being collected currently.

Lower Gunnison River Basin

There were 130 water-quality sites in the Lower 

Gunnison River Basin: 17 sites had sufficient data for trends 

analysis and 3 sites had sufficient streamflow data to calculate loads (fig. 15). Other sites were not currently being 

sampled, did not have sufficient data for analysis beyond 

summary statistics and comparison to standards, or lacked 

continuous streamflow.
Characterization and Data-Gap Analysis of Surface-Water Quality 49 Figure 13. Locations of continuous streamflow, physical parameter data trend, concentration data trend, and summary statistic sites in the White River Basin, western Colorado.

COLORADO

UTAH

81 82 159

160

16

18

163 161

162

68

20

61

59

60

60

34

75

153

63

86

106

69

72

71

67 66

45

65

64

39

167

158

9

28 51

154

74

169

185 189

179 190

175

181

White River

Wolf Creek

Flag Creek

Clear Creek

Ryan Gulch

Yellow Creek

Carr Creek

Brush Creek

Main Elk Creek

Williams Fork

Coal Creek

Morapos Creek

Wilson Creek

Cliff Creek

Morgan Gulch

Canyon Creek

West Douglas Creek

East Douglas Creek

North Fork White River

Black Sulphur Creek

Rifle Creek

Big Horse Draw

Stinking Water Creek

Hunter Creek

Fawn Creek

Coyote Wash

South Fork Williams Fork

West Salt Creek

East Salt

Creek

Big Beaver Creek

East Willow Creek

Curtis Creek

Silt

Meeker

Rangely

New

Castle

Rifle

Dinosaur

Glenwood 

Springs

Taylor Draw Reservoir

108°45' 108°30' 108°15' 107°45' 107°30' 108° 109°

40°15'

40°

39°45'39°30'

Base from Environmental Research Systems Institute (ESRI) digital data, 2009, 1:24,000 and U.S. Geological Survey digital data, 2010, 1:100,000Universal Transverse Mercator, Zone 13 North

0 10 5 15 20 MILES

0 10 15 5 20 KILOMETERS

Cro eko Wd ash

Dee p

Channel Creek

Red Wash

i ppir D

gn oR kc r C ee k

40

40

64

64

13

13

139

Douglas

139

Creek

CgnirpS keer

Strawberry Creek

42

o G od Sp

rCgnir eek

Milk

Creek

ece D t p oi n Creek

Dry Fork Piceance Creek

Piceance Creek

RIO BLANCO

COUNTY

MOFFAT 

COUNTY

ROUTT

COUNTY

70

Colorado River

GARFIELD

COUNTY

West Evacuation Creek

Evacuation Creek

Missouri Cree k

Roan Creek

E a ts

keer Celfi R

Middle Rifle Creek

EXPLANATION

White River Basin

86

Analysis site and downstream order number

Continuous streamflow

Field property data trend

Concentration data trendUsed for summary statistics

6
50 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Figure 14. Locations of continuous streamflow, physical parameter data trend, concentration data trend, and summary statistic sites in the Colorado River Basin, western Colorado.

COLORADO

UTAH

COLORADO

UTAH

494

487

491, 492

532

527, 530 584

505

499

507

1229

1230

226

1211

1291

1290

1289

382

12461251

1247

1259, 1260, 1261

325

386

630

204

590

1272

1270, 1271

1157, 1158, 1160,1161, 1162, 1163

701

215

225

628

399

299

200

216

636

695

485

1296

454

12411240

380

635

377

696, 697

625

644

640 1140

305

212

274

221

387

1277

223

1255

670, 672, 673,683, 685, 687, 688

1209

694

1121,1123

1256

621

254, 255, 256, 260,

263, 265, 268, 271

1137, 1138

1245

1268

610

1281

366

202 201

1176

211

603

608

1266

1264

393

1293

602

234

233

235

219

1285

1287

1288

435

469

472 474

433

432

416

422 418

417

439, 440

434

437 436

420

421

428

419

424

425

423

414

445

446

441 459

475

461

476

470

429, 430

426

509, 511

407

210

649, 665

646, 647, 648

1110

1151, 1152 693

1166

1191

438

1237, 1238, 1239

Vega 

Reservoir

Highline Lake

Colorado River

Roan Creek

Big Salt Wash

Kannah Creek

East Salt Creek

Clear Creek

West Salt Creek

Big Creek

Carr Creek Brush Creek

Jerry Creek

Little Salt Wash

Kimball Creek

Main Elk Creek

Crystal River

Prairie Canyon

Canyon Creek

East Creek

Coates Creek

North Dry Fork

East Rifle Creek

Leon Creek

Rifle Creek

Currant Creek

East Douglas Creek

West Douglas Creek

Middle Rifle Creek

Clear Fork

West Evacuation Creek

West Fawn Creek

East Willow Creek

Divide 

Creek

Adobe Creek

Silt

Rifle

Fruita

Palisade

De Beque

Parachute

Cedaredge

Glenwood 

Springs

Collbran

New

Castle

Grand Junction

107°15' 107°30' 107°45' 108° 108°15' 108°30' 108°45' 109°

39°45'39°30'39°15'

39°

MESA 

COUNTY

DELTA 

COUNTY

PITKIN 

COUNTY

GUNNISON

COUNTY

RIO BLANCO

COUNTY

GARFIELD

COUNTY

6

6

50

50

65

65

82

133

141

640

Base from Environmental Research Systems Institute (ESRI) digital data, 2009, 1:24,000 and U.S. Geological Survey digital data, 2010, 1:100,000Universal Transverse Mercator, Zone 13 North

0 10 5 15 20 MILES

0 10 15 5 20 KILOMETERS

EXPLANATION

Colorado River Basin Analysis site and downstream order number

630 Continuous streamflow Field property data trend

Concentration data trendUsed for summary statistics

West Divide Creek

East Divide Creek

Plateau Creek

Piceance Creek

West Muddy Creek

East Leroux C er ek

North East Creek

Little Dolores River

13

139

70

70
Characterization and Data-Gap Analysis of Surface-Water Quality 51 Figure 15. Locations of continuous streamflow, physical parameter data trend, concentration data trend, and summary statistic sites in the Lower Gunnison River Basin, western Colorado. 868, 869, 871 1010

839

836

705

706

797

1102

708

896

800, 801

809

713

862, 863

901

962 978

974

976

759

1017

1014

1013, 1019 914 877

872, 873

744

734

1052, 1053

1055 1069

1068

1048, 1049, 1050, 1051 893

816

808

1082

936

958

955

957

731 732

776, 777

775

718

835

833

1058

1060

1059

1057

849, 850,

851 794

730, 749, 750

721

1109

795

793

998

1007

1001

995

804

876

888

889

881

772

966

979, 980

856

1045, 1046, 1047 892

1021

733

712

711

714

940

1029

1083

1097 897 1098, 1099, 1100, 1101

830, 831, 

832

931

840, 841,842, 843

Delta

Olathe

Fruita

Paonia

Hotchkiss

Montrose

Palisade

Collbran

Crawford

Cedaredge

Grand

Junction

Gunnison River

Smith Fork

Dry Creek

Uncompahgre River

Roubideau Creek

Kannah

Creek

Ohio Creek

East Creek

Soap Creek

Coal Creek

Big Creek

Crystal River

Cottonwood Creek

Cedar Creek

Slate River

Monitor Creek

Beaver Creek

Spring Creek

Curecanti Creek

West Elk Creek

Criswell Creek

Big Dominguez Creek

West Muddy Creek

Kelso Creek

Snowmass Creek

Escalante

Creek

Buzzard Creek

North East Creek

East River

Leon Creek

Capitol Creek

Willow Creek

Big Blue Creek

Cebolla Creek

Clear Fork

Iron Creek

East Leroux

Creek

Gunnison River

Gunnison

River

Willow Creek

Plateau Creek

Gunnison

Tunnel

Surface Creek

North Fork Gunnison River Juniata Reservoir

Wayne N. Aspinal 

Federal Storage Unit

107° 107°15' 107°30' 107°45' 108° 108°15' 108°30' 108°45' 39°15'

39°

38°45'38°30'

65

65

50

50

50

50

50

Colorado River

Little Sal Wt a hs

Jerry Creek

Plateau Creek

141

141

133

133

149

92

92

550

uC r ar n Ct er ek

Crysta Cl reek

931

Base from Environmental Research Systems Institute (ESRI) digital data, 2009, 1:24,000 and U.S. Geological Survey digital data, 2010, 1:100,000Universal Transverse Mercator, Zone 13 North

0 10 5 15 20 MILES

0 10 15 5 20 KILOMETERS

139

70

70

MESA

COUNTY

DELTA

COUNTY

MONTROSE

COUNTY

GUNNISON

COUNTY

PITKIN

COUNTY

EXPLANATION

Lower Gunnison River Basin Analysis site and downstream order number

914 Continuous streamflow Field property data trend

Concentration data trendUsed for summary statistics

6

6
52 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Geographic coverage of surface-water-quality sites in 

the Lower Gunnison River could be enhanced to include more 

tributaries. The majority of sampling has occurred near Delta, 

Colo. Additional sampling of tributaries to the Gunnison River 

could enhance the existing dataset. The only data for Surface 

Creek and the North Fork of the Gunnison River were field 

properties. Downstream from Delta, Colo., to the Gunnison 

River near Grand Junction (09152500), no surface-water 

quality data were available that could be used for trends or 

loads. Additional measurement of streamflow at the majority 

of these sites could greatly enhance the dataset and provide a more complete loading profile for the basin for any 

constituent sampled.

Analytical data gaps were identified in several constituent groups in the Lower Gunnison River Basin. A total of 84 

samples were collected for E. coli, and 17 samples exceeded 

the recommended standard (app. 1). However, insufficient 

data were available to do any trend analysis of E.coli. Almost 

30 percent of the samples for total phosphorus in the basin 

exceeded the recommended standard (app. 1), yet there 

were insufficient data to do trend analysis at all but one site 

(09152500) (table 5). A better understanding of nutrient levels 

in the Lower Gunnison River Basin will not be possible without additional nutrient sampling in the area. The same data gap 

exists for trace elements. Only one site, Gunnison River near 

Grand Junction, had sufficient data for trend analysis in iron. 

There were exceedances in copper, total recoverable iron, lead, 

zinc, and selenium, yet data were insufficient to complete a 

trend analysis or calculate load. Additional sampling is necessary to understand the occurrence, concentrations, and loads of 

these elements. Continuous streamflow data are necessary to 

calculate loads for any of the constituents sampled.

Summary

Northwestern Colorado is experiencing changes in landuse including urbanization, agriculture, and increasing energy 

development and infrastructure. These land-use changes can 

result in short- and long-term changes in the water resources 

in the study area. Ongoing monitoring and assessment are 

required to periodically reestablish our understanding of 

baseline conditions and to detect changes. Substantial waterresource datasets, publications, and other materials have been 

developed in past years and can be used to assess baseline 

conditions and to evaluate land-use effects. The U.S. Geological 

Survey (USGS), in cooperation with Federal, State, county and 

industry partners, developed a Web-accessible common data 

repository to provide energy operators, researchers, consultants, 

agencies, and interested stakeholders equal access to historical and current (as of August 2009) water-quality information 

(available on the Internet at http://rmgsc.cr.usgs.gov/cwqdr/

Piceance/index.shtml).

The following is an alphabetical list of cooperators 

involved in this study: Antero Resources, Bureau of Land 

Management, Chevron Corporation, City of Grand Junction, 

City of Rifle, Colorado Department of Agriculture, Colorado 

Department of Natural Resources, Colorado Department 

of Public Health and Environment, Colorado Division of 

Wildlife–River Watch, Colorado Oil and Gas Conservation 

Commission, Colorado River Water Conservation District, 

Delta County, EnCana Oil & Gas (USA) Inc., Garfield County, 

Gunnison Energy Corp, National Park Service, Natural 

Soda, Inc., North Fork River Improvement Association, 

Oxy Petroleum Corporation, Petroleum Development Corp, 

Rio Blanco County, Shell Oil Company, Solvay Chemicals, 

Town of Carbondale, Town of De Beque, Town of Palisade, 

Town of Parachute, Town of Rangely, Town of Silt, Bureau 

of Reclamation, U.S. Forest Service, West Divide Water 

Conservancy District, and Williams Companies, Inc. These 

data are analyzed to provide a baseline assessment of available 

water-resource data and aid in the development of regional 

monitoring strategies.

The Piceance study area is subdivided into three study 

basin areas: the White River Basin, the Colorado River Basin, 

and the Lower Gunnison River Basin. The White River Basin 

is partially defined by the Piceance Structural Basin boundary 

and begins roughly at the mouth of Coal Creek and extends 

downstream to the White River at the Colorado-Utah state 

border. The Colorado River Basin includes the drainage area 

from Glenwood Springs to the Colorado-Utah state border. 

The Gunnison River is the largest tributary to the Colorado 

River in Colorado. The Lower Gunnison River Basin is only a 

part of the entire Gunnison River Basin. The Lower Gunnison 

River Basin for this study included the entire drainage area of 

the North Fork of the Gunnison River and the drainage area 

beginning slightly downstream from the Gunnison Tunnel on 

both the Gunnison River and the Uncompahgre River.

The area of the White River Basin is 3,160 mi2. Land use 

in the White River Basin is affected by oil shale and natural 

gas development. Conventional and unconventional natural 

gas extraction and the associated infrastructure are becoming 

increasingly prevalent in this basin. The area of the Colorado 

River Basin (study area) is 3,560 mi2, and the area of the drainage area of the Colorado River upstream from the site at the 

Colorado-Utah state border is 17,843 mi2. The economy of 

the Colorado River Basin is dominated by agriculture, energy 

development, industry, real estate development, tourism, and 

recreation. The area of the Lower Gunnison River Basin is 

2,700 mi2, and the entire drainage area (measured from where 

the Gunnison River enters the Colorado River) is 7,900 mi2. 

A primary concern of water managers in the Lower Gunnison 

River Basin is the presence of salinity and selenium in the 

surface water as a result of irrigated agriculture. The complex 

geology, combined with various land-use types such as irrigation and residential development, can influence water-quality 

conditions in the Lower Gunnison River Basin.
Summary 53

Data were summarized to identify available data and 

evaluate temporal and spatial patterns in the Piceance study 

area. The report contains data summaries, comparison to 

water-quality standards, trend analysis, a generalized spatial 

analysis, and a data-gap analysis for select water-quality properties and constituents. Gaps in available data were identified 

from these analyses and are provided in this report. A repository of available water-quality data was compiled from local, 

State, and Federal agencies and private entities (consulting 

firms, energy, and mining companies). The data repository 

contained 1,433 surface-water sites, 45,008 samples, and 

1,144,808 water-quality results from 1931 to 2009. A subset of 

surface-water-quality data from the repository was compiled, 

reviewed, and checked for quality assurance for this report.

Summary statistics and comparison to standards were 

provided for 347 sites for 33 constituents including field 

properties, nutrients, major ions, trace elements, suspended 

sediment, Escherichia coli, and BTEX (benzene, toluene, ethylbenzene, xylene). Data from the study area were compared 

to the Colorado Department of Public Health and Environment 

and U.S. Environmental Protection Agency standards and recommendations to guide interpretation of surface-water quality, 

evaluate spatial patterns, and obtain a broad understanding of 

water-quality conditions across the study area. When sufficient 

data were available, trends over time were analyzed and loads 

were calculated for those sites where there were also continuous streamflow data.

Summary statistics and water-quality exceedances are 

discussed by basin to provide a general overview of water 

quality. The collection of field properties is an important 

component to all water-quality sampling in order to properly 

characterize water-quality results. The majority of sites had 

information on field properties. For the entire study area, 

316 sites had temperature data collected between 1959 and 

2009. There were 326 values out of a total of 32,006 values 

in the study area that exceeded the aquatic-life standard for 

daily maximum water temperature. For the entire study area, 

196 sites had dissolved-oxygen data collected between 1970 

and 2009. Median dissolved-oxygen concentrations ranged 

from 6.8 to 11.2 mg/L. There were 185 concentrations that 

exceeded the dissolved oxygen aquatic-life standard out of a 

total of 11,248 values in the study area. For the entire study 

area, 276 sites had pH data collected between 1958 and 

2009. Median pH values ranged from 7.5 to 9.0. There were 

241 values out of a total of 16,307 values that exceeded the 

high pH standard in the study area, while there were 7 values 

that were less than the low pH standard in the study area. 

Nutrients within the study area were not well represented in 

each basin and were often not being sampled currently. For the 

entire study area, 62 sites had nitrate data collected between 

1958 and 2009, and median nitrate concentrations ranged 

from less than detection to 3.72 mg/L as nitrogen (N). The 

maximum contaminate level for domestic water supply for 

nitrate is 10 mg/L and was exceeded once in 3,736 samples. 

Total phosphorus was collected at 113 sites between 1974 

and 2009, and median total phosphorus concentrations ranged 

from less than detection to 5.04 mg/L. The USEPA recommendation for phosphorus is less than 0.1 mg/L, and 1,469 

of 4,842 samples exceeded this recommended standard in the 

study area. Standards for major ions exist only for chloride 

and sulfate. For the entire study area, 118 sites had chloride 

and sulfate concentration data collected between 1958 and 

2009. Median chloride concentrations ranged from 0.085 to 

280 mg/L. There were 120 of the 8,817 chloride concentration samples that exceeded the chloride domestic watersupply standard of 250 mg/L. Median sulfate concentrations 

ranged from 4.57 to 15,000 mg/L. There were 1,111 of the 

8,736 sulfate concentration samples that exceeded the sulfate 

domestic water-supply standard of 250 mg/L. Trace elements 

were relatively well represented both temporally and spatially 

in the study area, though the number of trace element samples 

per site was not typically enough to compute trends or loads 

except for selenium. There were 127 sites that had dissolved 

iron concentration data collected between 1961 and 2009, and 

median iron concentrations ranged from less than detection 

to 1,100 μg/L. The 30-day drinking-water standard for iron is 

300 μg/L, and 203 samples exceeded the standard. Selenium 

was the best represented trace element with selenium concentration data collected at 197 sites between 1973 and 2009, and 

median selenium concentrations range from less than detection 

to 181 μg/L. The chronic aquatic-life standard of 4.6 μg/L for 

selenium concentrations was exceeded in 899 samples, and 

the acute aquatic-life standard of 18.4 μg/L for selenium was 

exceeded in 629 samples.

Natural changes in precipitation and streamflow and 

anthropogenic changes in nutrient sources (such as wastewater 

treatment facilities, golf courses, urban runoff, agricultural 

fields, and septic tanks) can influence nutrient concentrations 

in streams throughout the study area. Upward trends in nitrate 

and total phosphorus were detected in the White River Basin 

at 09304200 (White River above Coal Creek near Meeker) 

from 1990 to 2009 and 1991 to 2009, respectively. Downward 

trends in DS were detected at 09163500 (Colorado River near 

Colorado-Utah state line) from 1990 to 2009. Salinity control 

work in the Colorado River Basin near Grand Junction might 

have contributed to the downward trend. Field properties such 

as water temperature, pH, and dissolved oxygen were tested 

for trends over time. An upward trend in water temperature 

was detected at the Gunnison River near Grand Junction 

(09152500). There are limited trace element data except for 

selenium in the Lower Gunnison River Basin. Concentrations 

of trace elements, and more specifically selenium, are of concern to water and land managers in the Lower Gunnison River 

Basin because of the combination of geologic formations and 

land use. Downward trends in selenium were detected at both 

main-stem sites, from 1991 to 2009 at 09144250 (Gunnison 

River at Delta) and from 1990 to 2009 at 09152500 (Gunnison 

River near Grand Junction). High selenium concentrations 

correlate with high salinity concentrations; thus, when salinity 

control efforts are conducted in selenium-rich areas in the 

Lower Gunnison River Basin, both salinity and selenium have 

the potential to decrease.
54 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Spatial, temporal, and analytical data gaps were identified 

in the study area. No water-quality data exist for tributaries 

in the area north of Rangely, Colo., where extensive energy 

development has occurred in a complex geologic setting. The 

spatial coverage of sampling sites could be expanded in the 

White River Basin by adding more tributary sites. Douglas 

Creek has a drainage area of 425 mi2, and no water-quality or 

quantity data are currently being collected at this site. Data 

in the Colorado River Basin for all constituent groups were 

limited on the main stem of the Colorado River between 

Glenwood Springs and Cameo, Colo. Nutrient data were 

minimally collected upstream from Cameo, Colo., on the main 

stem of the Colorado River and were minimally collected on 

the Gunnison River (a major tributary in the reach). Almost 

30 percent of the samples for total phosphorus in this Lower 

Gunnison River Basin exceeded the recommended standard, 

yet there were insufficient data to do trends analysis in the 

Lower Gunnison River Basin except at the Gunnison River 

near Grand Junction site. Only one site had sufficient data for 

trends analysis in iron (Gunnison River near Grand Junction). 

Additional sampling is necessary to better understand the 

occurrence, concentrations, and loads of these elements.

Acknowledgments

The author wished to express thanks and appreciation 

to the many agencies that provided data for this report. The 

author would like to acknowledge Berry Petroleum Company 

for their contribution to this project, which was undertaken in 

connection with the settlement of an enforcement action taken 

by the Colorado Department of Public Health and Environment for violations of the Water Quality Control Act. The 

author would like to express appreciation to David Lorenz and 

Alisa Mast for their technical review of the manuscript, which 

aided in the overall improvement of this report.

References Cited

Alley, W.M., 1988, Using exogenous variables in testing 

for monotonic trends in hydrologic time series: Water 

Resources Research, v. 24, no. 11, p. 1955–1961.

Brooks, T., and Ackerman, D.J., 1985, Reconnaissance of 

ground-water resources in the Lower Gunnison River Basin, 

southwestern Colorado: U.S. Geological Survey WaterResources Investigations Report 84–4185, 35 p.

Brune, G.M., 1953, Trap efficiency of reservoirs: American 

Geophysical Union Transactions, v. 34, no. 3, p. 407–418.

Bureau of Land Management, 2002, Roan Plateau Eligibility Report for the national wild and scenic rivers system: 

Bureau of Land Management, 28 p., accessed November 

8, 2011, at http://www.saveroanplateau.org/documents/

scenicrivers.pdf.

Bureau of Land Management, 2004, Oil and gas potential and 

reasonable foreseeable development (RFD) scenarios in 

the Grand Mesa, Uncompahgre, and Gunnison (GMUG) 

National Forests Colorado: Bureau of Land Management, 

accessed December 31, 2012, at http://www.fs.fed.us/

outernet/r2/gmug/policy/plan_rev/final/comp_assess/doc2_

Oil_Gas_Potential_RFDS_8-27-04R.pdf.

Bureau of Land Management, 2009, BLM Colorado Statewide 

Geospatial Database, 1st conflated poly: Bureau of Land 

Management, Colorado State Office, Geosciences Team, 

Dave Taylor (ed.).

Bureau of Land Management, 2011a, BLM Colorado’s Wild 

Horse and Burro Program: Bureau of Land Management, 

accessed November 8, 2011, at http://www.blm.gov/co/st/en/

BLM_Programs/wild_horse_and_burro.html/.

Bureau of Land Management, 2011b, Reasonable foreseeable development scenario for oil and gas activities in the 

BLM White River Field Office—Rio Blanco, Moffat And 

Garfield Counties, Colorado: Bureau of Land Management, accessed January 17, 2011, at http://www.blm.gov/

pgdata/etc/medialib/blm/co/programs/land_use_planning/

rmp/white_river/documents.Par.86610.File.dat/RFD_

Executuve_Sumnmary.pdf.

Bureau of Reclamation, 2009, Colorado River Basin salinity 

control program—Federal accomplishments report for fiscal 

year 2009: Bureau of Reclamation, accessed August 13, 

2010, at http://www.usbr.gov/uc/progact/salinity/pdfs/

FedAccompRep-2009.pdf.

Bureau of Reclamation, 2011, Colorado River Storage 

Project—Wayne N. Aspinall Unit: Bureau of Reclamation, 

accessed November 14, 2011, at http://www.usbr.gov/uc/

feature/crsp/aspinall.html.

Butler, D.L., 1985, Discharge and water quality of springs in 

Roan and Parachute Creek Basins, northwestern Colorado, 

1981–1983: U.S. Geological Survey Water-Resources 

Investigations Report 85–4078, 150 p.

Butler, D.L., and Leib, K.J., 2002, Characterization of 

selenium in the lower Gunnison River Basin, Colorado, 

1988–2000: U.S. Geological Survey Water-Resources 

Investigations Report 02–4151, 26 p.

Butler, D.L., Wright, W.G., Stewart, K.C., Osmundson, B.C., 

Krueger, R.P., and Crabtree, D.W., 1996, Detailed study of 

selenium and other constituents in water, bottom sediment, 

soil, alfalfa, and biota associated with irrigation drainage 

in the Uncompahgre Project area and in the Grand Valley, 

west-central Colorado, 1991–93: U.S. Geological Survey 

Water-Resources Investigations Report 96–4138, 136 p.
References Cited 55

Chafin, D.T., and Butler, D.L., 2002, Dissolved-solids-load 

contributions off the Pennsylvanian Eagle Valley Evaporite 

to the Colorado River, west-central Colorado, in Kirkham, 

R.M., Scott, R.B., and Judkins, T.W., eds., Late Cenezoic 

evaporite tectonism and volcanism in west-central Colorado: Geological Society of America Special Paper 366, 

p. 149–156.

Churchill, M.A., 1948, Analysis and use of reservoir sedimentation data with discussion by L.C. Gottschalk, in Federal 

Inter-Agency Sedimentation Conference, Denver, Colo., 

1947, Proceedings: U.S. Geological Survey, p. 139–140.

Cohn, T.A., 2005, Estimating contaminant loads in rivers—An 

application of adjusted maximum likelihood to type 1 censored data: Water Resources Research, v. 41, no. 7, 13 p.

Cohn, T.A., Caulder, D.L., Gilroy, E.J., Zynjuk, L.D., and 

Summers, R.M., 1992, The validity of a simple statistical 

model for estimating fluvial constituent loads—An empirical study involving nutrient loads entering Chesapeake Bay: 

Water Resources Research, v. 28, no. 9, p. 2353–2364.

Colorado Department of Public Health and Environment, 

2010, Regulation no. 93, Colorado’s Section 303(D) List of 

impaired waters and monitoring and evaluation list: Colorado Department of Public Health and Environment, Water 

Quality Control Commission, accessed October 14, 2011.

Colorado Department of Public Health and Environment, 

2011, Water Quality Control Commission regulations—

Surface water quality classifications and standards: 

Colorado Department of Public Health and Environment, 

accessed October 25, 2011, at http://www.cdphe.state.co.us/

regulations/wqccregs/.

Colorado Oil and Gas Conservation Commission, 2010, 

GIS downloads, wells: Colorado Oil and Gas Conservation Commission, accessed January 26, 2010, at 

http://cogcc.state.co.us/.

Colorado Oil and Gas Conservation Commission, 2011, News 

and media, Colorado weekly and monthly information: 

Colorado Oil and Gas Conservation Commission, accessed 

October 26, 2011, at http://cogcc.state.co.us/.

Dalby, C.E., 2006, Use of regression and time-series methods 

to estimate a sediment budget for Nevada Creek Reservoir, Montana: Proceedings of the 2006 AWRA Summer 

Specialty Conference, Adaptive Management of Water 

Resources, Missoula, Mont., June 26–28, 2006: American 

Water Resources Association, 10 p.

Green, G.N., 1992, The digital geological map of Colorado 

in Arc/Info format: U.S. Geological Survey Open-File 

Report 92–0507, scale 1:500,000.

Helsel, D.R., 2005a, Insider censoring—Distortion of data 

with nondetects: Human and Ecological Risk Assessment, 

v. 11, p. 1127–1137.

Helsel, D.R., 2005b, Non-detects and data analysis—Statistics 

for censored environmental data: New Jersey, John Wiley 

and Sons, Inc., 268 p.

Helsel, D.R., and Hirsch, R.M., 2002, Statistical methods in 

water resources: U.S. Geological Survey Techniques of 

Water-Resources Investigation, book 4, chap. A3, 523 p.

Hirsch, R.M., Slack, J.R., and Smith, R.A., 1982, Techniques 

of trend analysis for monthly water-quality data: Water 

Resources Research, v. 18, no. 6, p. 107–121.

Hirsch, R.M., Alexander, R.B., and Smith, R.A., 1991, Selection of methods for the detection and estimation of trends 

in water quality: Water Resources Research, v. 27, no. 5, 

p. 803–813.

Homer, C., Huang, C., Yang, L., Wylie, B.K., and Coan, M., 

2004, Development of a 2001 National Landcover Database 

for the United States: Photogrammetric Engineering and 

Remote Sensing, v. 70, no. 7, p. 829–840.

Iorns, W.V., Hembree, C.H., and Oakland, G.L., 1965, Water 

resources of the Upper Colorado River Basin—Technical 

report: U.S. Geological Survey Professional Paper 441, 

370 p.

Johnson, R.C., 1989, Geologic history and hydrocarbon potential of late Cretaceous-age, low permeability reservoirs, 

Piceance Basin, western Colorado: U.S. Geological Survey 

Bulletin 1787–E, 51 p.

Johnson, R.C., and Flores, R.M., 2003, History of the Piceance 

Basin from latest Cretaceous through early Eocene and 

the characterization of lower Tertiary sandstone reservoirs, 

chap. 3 in Peterson, K.M., Olson, T.M., and Anderson, D.S., 

eds., Piceance Basin guidebook: Denver, Colo., Rocky 

Mountain Association of Geologists, p. 21–61.

Kanzer, D., and Merritt, D., 2008, The TDS control story of 

the Upper Colorado River Basin illustrated by case studies: Adelaide, Australia, 2nd International Salinity Forum, 

4 p., available online at http://www.internationalTDSforum.

org/14_final.html.

Kendall, M.G., 1975, Rank correlation methods (4th ed.): 

London, Charles Griffin.

Kenney, T.A., Gerner, S.J., Buto, S.G, and Spangler, L.E., 

2009, Spatially referenced statistical assessment of 

dissolved-solids load sources and transport in streams of 

the Upper Colorado River Basin: U.S. Geological Survey 

Scientific Investigations Report 2009–5007, 50 p.

Kuhn, G., and Williams, C.A., 2004, Evaluation of streamflow 

losses along the Gunnison River from Whitewater downstream to the Redlands Canal Diversion Dam, near Grand 

Junction, Colorado, water years 1995–2003: U.S. Geological Survey Scientific Investigations Report 2004–5095, 

22 p.
56 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Lanfear, K.J., and Alexander, R., 1990, Methodology to derive 

water-quality trends for use by the National Water Summary 

Program of the U.S. Geological Survey: U.S. Geological 

Survey Open-File Report 90–359, 10 p.

Leib, K.J., 2008, Concentrations and loads of selenium in 

selected tributaries to the Colorado River in the Grand Valley, western Colorado, 2004–2006: U.S. Geological Survey 

Scientific Investigations Report 2008–5036, 36 p.

Leib, K.J., and Bauch, N.J., 2008, Salinity trends in the Upper 

Colorado River Basin upstream from the Grand Valley 

Salinity Control Unit, Colorado, 1986–2003: U.S. Geological Survey Scientific Investigations Report 2007–5288, 

21 p.

Liebermann, T.D., Mueller, D.K., Kircher, J.E., and Choquette, A.F., 1989, Characteristics and trends of streamflow 

and dissolved solids in the upper Colorado River Basin, 

Arizona, Colorado, New Mexico, Utah, and Wyoming: 

U.S. Geological Survey Water-Supply Paper 2358, 64 p.

Lund, J., and Hunter, G., 2009, A review of the geothermal 

resources underlying Glenwood Springs, Colorado and 

of the technologies appropriate for use in their potential 

development: City of Glenwood Springs Geothermal Task 

Force, 87 p.

Mann, H.B., 1945, Non-parametric test against trend: 

Econometrica, v. 13, p. 245–259.

Mayo, J.W., 2008, Estimating the effects of conversion of agricultural land to urban land on deep percolation of irrigation 

water in the Grand Valley, western Colorado: U.S. Geological Survey Scientific Investigations Report 2008–5086, 

58 p.

Mayo, J.W., and Leib, K.J., 2012, Flow-adjusted trends in 

dissolved selenium load and concentration in the Gunnison 

and Colorado Rivers near Grand Junction, Colorado, water 

years 1986–2008: U.S. Geological Survey Scientific Investigations Report 2012–5088, 33 p.

Moore, J.L., 2011, Effects of land use change on salinity and 

selenium loading in Montrose Arroyo, western Colorado, 

from 1992 to 2010: U.S. Geological Survey Scientific 

Investigations Report 2011–5106.

Mueller, D.K., and Osen, L.L., 1988, Estimation of natural 

dissolved-solids discharge in the Upper Colorado River 

Basin, Western United States: U.S. Geological Survey 

Water-Resources Investigations Report 87–4069, 62 p.

Myers, R.H., 1986, Classical and modern regression with 

applications: Boston, Mass., Duxbury Press.

Nelson, P.H., and Santus, S.L., 2010, Gas, water, and oil production from Grand Valley, Parachute, Rulison, and Mamm 

Creek fields in the Piceance Basin, Colorado: U.S. Geological Survey Open-File Report 2010–1110, 28 p.

Ortiz, R.F., 2002, Baseline characterization of water quality 

and mass loading in Piceance Creek, Rio Blanco County, 

Colorado, December 2000: U.S. Geological Survey WaterResources Investigations Report 02–4134, 29 p.

Ortiz, R.F., 2005, Characterization of water quality in Government Highline Canal at Camp 7 Diversion and Highline 

Lake, Mesa County, Colorado, July 2000 through September 2003: U.S. Geological Survey Scientific Investigations 

Report 2004–5281, 30 p.

Papadopulos & Associates, Inc., 2008, Phase II hydrogeologic 

characterization of the Mamm Creek Field area, Garfield 

County, Colorado: Prepared for the Board of County Commissioners, Garfield County, Colorado, 41 p.

Paschke, S.P., Schaffrath, K.R., and Mashburn, S.L., 2008, 

Near-decadal changes in nitrate and pesticide concentrations in the South Platte River alluvial aquifer, 1993–2004: 

Journal of Environmental Quality, v. 37, p. S281–S295.

Prairie, J.R., Rajagopalan, B., Fulp, T.J., and Zagona, E.A., 

2005, Statistical nonparametric model for natural salt 

estimation: Journal of Environmental Engineering, v. 131, 

no. 1, p. 130–138.

Puckett, L.J, 1994, Nonpoint and point sources of nitrogen in 

major watersheds in the United States: U.S. Geological Survey Water-Resources Investigations Report 94–4001, 12 p.

Reinecke, K.M., Rice, D.D. and Johnson, R.C., 1991, Characteristics and development of fluvial sandstone and coalbed 

reservoirs of Upper Cretaceous Mesaverde Group, Grand 

Valley field, Colorado, in Schwochow, S.D., Murray, D.K., 

and Fahy, M.F., eds., Coalbed methane of western North 

America: Rocky Mountain Association of Geologists 1991 

Guidebook, p. 209–225.

Runkel, R.L., Crawford, C.G., and Cohn, T.A., 2004, Load 

Estimator (LOADEST)—A FORTRAN program for 

estimating constituent loads in streams and rivers: U.S. 

Geological Survey Techniques of Water-Resources Investigations, book 4, chap. A5, 69 p.

Salas, J.D., and Shin, H., 1999, Uncertainty analysis of reservoir sedimentation: Journal of Hydraulic Engineering, 

v. 125, no. 4, p. 339–350.

Schaffrath, K.R., 2012, Surface-water salinity in the Gunnison 

River Basin, Colorado, 1989 through 2007: U.S. Geological 

Survey Scientific Investigations Report 2012–5128, 82 p.

Schertz, T.L., Alexander, R.B., and Ohe, D.J., 1991, The computer program Estimate Trend (ESTREND), a system for 

the detection of trends in water-quality data: U.S. Geological Survey Water Resources Investigations Report 91–4040, 

72 p. (Also available at http://water.usgs.gov/pubs/wri/

wri91-4040/).

Sen, P.K., 1968, Estimates of the regression coefficient based 

on Kendall’s tau: Journal of the American Statistical Association, v. 63, no. 325, p. 1379–1389.

Sprague, L.A., Muller, D.K., Schwarz, G.E., and Lorenz, D.L., 

2009, Regional nutrient trends in streams and rivers of the 

United States, 1993–2003: U.S. Geological Survey Scientific Investigations Report 2008–5202, 196 p.
References Cited 57

Techni Graphics Systems, Inc., 2004, Colorado Decision 

Support Systems, http://cdss.state.co.us/DNN/GIS/tabid/67/

Default.aspx, accessed September 28, 2010.

Thomas, J.C., Leib, K.J., Mayo, J.W., 2008, Analysis of dissolved selenium loading for selected sites in the Lower Gunnison River Basin, Colorado, 1978–2005: U.S. Geological 

Survey Scientific Investigations Report 2007–5287, 25 p.

TIBCO Software, Inc., 1998–2008, TIBCO Spotfire S+ 

Release 8.1 for Windows: TIBCO Software Inc.

Tobin, R.L., Stranathan, H.E., Covay, K.J., 1985, Waterquality characteristics of streams in the Piceance Creek 

and Yellow Creek drainage basins, northwestern Colorado, 

water years 1977–81: U.S. Geological Survey WaterResources Investigations Report 84–4261, 78 p.

Tobin, R.L., 1993, Sediment transport and water-quality characteristics and loads, White River, northwestern Colorado, 

water years 1975–88: U.S. Geological Survey WaterResources Investigations Report 92–4031, 68 p.

Tweto, Ogden, comp., 1979, Geologic map of Colorado: 

U.S. Geological Survey State Geologic Map, scale 1:500,000 

(reprinted).

U.S. Census Bureau, 2011, Population estimates: U.S. Census 

Bureau, accessed October 6, 2011, at http://www.census.gov/

popest/cities/files/SUB-EST2009_8.csv.

U.S. Energy Information Administration, 2011, Rifle mills (old 

and new) mill sites: U.S. Energy Information Administration, Nuclear and Uranium, accessed October 24, 2011, at 

http://205.254.135.24/cneaf/nuclear/page/umtra/rifle_mills_

title1.html.

U.S. Environmental Protection Agency, 2000, Nutrient criteria 

technical guidance manual—River and streams, 2000: U.S. 

Environmental Protection Agency Report 822B–00–002.

U.S. Fish and Wildlife Services, 2011, Fish and aquatic species: 

U.S. Fish and Wildlife Service, accessed October 10, 2011, at 

http://www.fws.gov/mountain-prairie/fisheries/fish.htm.

U.S. Geological Survey, 2011, User’s manual for the 

National Water Information System of the U.S. Geological Survey—Water-quality system, version 4.11: 

U.S. Geological Survey, accessed November 15, 2010, at 

http://nwis.usgs.gov/currentdocs/qw/QW.user.book.html.

U.S. Geological Survey Oil Shale Assessment Team, 2010, Oil 

shale and nahcolite resources of the Piceance Basin, Colorado: U.S. Geological Survey Digital Data Series DDS–69–Y, 

7 chapters, pages variable.

Vaill, J.E., and Butler, D.L., 1999, Streamflow and dissolvedsolids trends, through 1996, in the Colorado River Basin 

upstream from Lake Powell—Colorado, Utah, and Wyoming: U.S. Geological Survey Water-Resources Investigations Report 99–4097, 47 p.

Weeks, J.B., Leavesley, G.H., Welder, F.A., and Saulnier, G.J., 

Jr., 1975, Simulated effects of oil-shale development on the 

hydrology of Piceance Basin, Colorado: U.S. Geological 

Survey Professional Paper 908, 84 p.

Western Regional Climate Center, 2012, Colorado climate 

summaries: Western Regional Climate Center, accessed 

December 31, 2011, at http://www.wrcc.dri.edu/summary/

climsmco.html.

Wright, W.G., and Butler, D.L., 1993, Distribution and 

mobilization of dissolved selenium in ground water of the 

irrigated Grand and Uncompahgre Valleys, western Colorado, in Allen, R.G., and Neale, C.M.U., eds., Management 

of irrigation and drainage systems—Integrated perspectives. 

Proceedings of the 1993 National Conference on Irrigation 

and Drainage Engineering, Park City, Utah, July 21–23, 

1993: American Society of Civil Engineers, p. 770–777.

Appendixes
60 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Appendix 1. Summary of Surface-Water-Quality Data by Site, by Constituent, 

Piceance Study Area, Western Colorado

The appendix is available in Excel format at the following URL:

http://pubs.usgs.gov/sir/2013/5015/appendix/appendix_1.xlsx.
Appendixes 61

Appendix 2. Model Coefficients and Statistical Diagnostics from Regression

Models Used for Trend Analysis in the Piceance Study Area, Colorado

The appendix is available in Excel format at the following URL:

http://pubs.usgs.gov/sir/2013/5015/appendix/appendix_2.xlsx.
62 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Appendix 3. Schematic diagrams of the model line without streamflow or seasonality terms to facilitate the determination of zeroslope year, net trend direction, and direction of the trend before and after the zero-slope year. Appendix 3A illustrates net, downward 

trends where quadratic term (t2) is either positive or negative, and appendix 3B illustrates a net, upward trend where quadratic term 

(t2) is either positive or negative. (t, t2, and t*central value available in appendix 2; time, years from period of record available in tables 

5, 6, and 7; centered time value = time – t*central value)

A

B

t * centered time value + t2 * (centered time value)2 t * centered time value + t2 * (centered time value)2

Time, in years

Time, in years Zero-slope year Zero-slope year 

EXPLANATION

Negative t2 coefficient

Positive t2

 coefficient
Plates
64 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009 Plates 65 Plate 1. Water-quality sites with downstream order number from appendix 1 in the Piceance study area, western Colorado. 109°00' 40°00' 39°30' 39°00' 38°30' 108°30' 108°00' 107°30'

Uncompahgre R

Gu nnison River

Co ol rado

R vi

e

P

r

iceance Cr eek

White Rive r

Douglas Creek

1259, 1260, 1261

Dinosaur

Rangely

WHITE RIVER

BASIN

Parachute

DeBeque

Collbran

Glenwood Springs

Meeker

Rifle Silt

New Castle

Grand

Junction

Palisade

Colorado River

Main Stem

LOWER GUNNISON

RIVER BASIN

Olathe

Hotchkiss

Cedaredge

Crawford

Paonia

Delta

Montrose

Fruita

P al et au Creek

190 189

185

179

175 169

167

158

154

153

51 45

106 86 163 160 161

159 162

82

81 75 69

68 63

65,66

64 67

71

74

72

42 39

34

28 20 19

9

16

18

3

2

5

61 59

60

416

414 437

438

435

434

433 441

429,430 439,440 436 432

387

393

219 217,218220

221

210

212

211

202

299

223

216

215

204

201

200 194,195, 196,198 325

366

377

254,255,256,260,263,265,268,271 305

225

226

382

380

407

472

459

461

469

470

474

476 475 454

584

527,530

532 485

590

625

610

603

602 644

646,647,648

694 649,665 693

695

1102

1083 1058 1057

1097

670,672,673,

683,685,687,688

1098, 1099,

1100,1101

1069

1068

1029

1237,1238,1239

1240

1241

1229 1230

1209

1191

1121,1123

1176 1270,1271 1272

1211

1110

1166

1151,1152

1137,1138

701 1109

1140

1268

1246

1285

1289

1290

1277 1291 1287

1288

1293

1296

1082

1060

1247 1255 1281

1256

1264

1266

1251

1245

696,697

1021

1013,1019

1017

1014

1010

995

1007

1001

998

990,991 913 914

889

904,905

888

872,873 862,863

868,869,871 979,980

978

962

877

966

876

856

849,850,851 803

804 833 839

835

836

840,841,842,843

775 777

776

793

795797

800,801

816

830,831,832

794

772

892 893 881

897

896

901

733

744

809

808

759

749 730

750 721

718

705

706

957 958

955

936

940

974

931

924,926

976

1059

1045,1046,1047 1052,1053 1055

608 628 630

621

635

636

640

1048,1049,1050,1051

1157,1158,1160,1161,1162,1163

274

234

235

233

487

708 711

713

712

494

491,492

505

509,511

507

714

731

732 734

499

386

399 445

424

446

419

420

421

425

426

422

423

428

417

418

181

U.S. Department of the InteriorU.S. Geological Survey

Scientific Investigations Report 2013

–5015

Plate 1 of 5

Base from U.S. Geological Survey digital dataUniversal Transverse Mercator, Zone 13 North

EXPLANATION

Colorado River Basin Lower Gunnison River Basin White River Basin

50 MILES

40 30 20 10

00

10 20 30 40

50 KILOMETERS
66 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959

–2009 Plates 67Plate 2. Exceedances of water-quality standards for temperature, pH, and dissolved oxygen from appendix 1 in the Piceance study area, western Colorado.

108°30' 108°00' 107°30' 109°00'

40°00'39°30'39°00'38°30'

WhiteRiver

PiceanceCreek

C

ol o

ar doR vi er

P al et auCreek

Gunnison River

DouglasCreek

Uncompahgre

R

Dinosaur

Rangely

Meeker

WHITE RIVER

BASIN

Colorado River

Main Stem

Fruita

Palisade

Delta

Montrose

Cedaredge

Hotchkiss

Crawford

Paonia

Olathe

LOWER GUNNISON

RIVER BASIN

Collbran

Grand

Junction

Parachute

Rifle

Silt

New Castle

Glenwood Springs

DeBeque

U.S. Department of the InteriorU.S. Geological Survey

Scientific Investigations Report 2013–5015

Plate 2 of 5

Base from U.S. Geological Survey digital dataUniversal Transverse Mercator, Zone 13 North

EXPLANATION

Site where one or more data values did not meet standard (for 30-day standards,  site has one or more data values greater than standard)

Dissolved oxygen value less than minimum aquatic-life standardph value less than minimum aquatic-life standardph value greater than maximum aquatic-life standardTemperature value greater than daily maximum aquatic-life standardTemperature value greater than maximum weekly average temperature  (MWAT) aquatic-life standard

50 MILES

50 KILOMETERS 40 30 20 10

00

10 20 30 40
68 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959

–2009 Plates 69Plate 3. Exceedances of water-quality standards for nitrate and phosphorus from appendix 1 in the Piceance study area, western Colorado.

40°00'

109°00' 108°30' 108°00' 107°30'

39°30'39°00'38°30'

WhiteRiver

PiceanceCreek

C

ol o

ar doR vi er

PlateauCreek

GunnisonRiver

DouglasCreek

Uncompahgre R

Dinosaur

Rangely

Meeker

WHITE RIVER

BASIN

Colorado River

Main Stem

Fruita

Palisade

Delta

Montrose

Cedaredge

Hotchkiss

Crawford

Paonia

Olathe

LOWER GUNNISON

RIVER BASIN

Collbran

Grand

Junction

Parachute

Rifle Silt

New Castle

Glenwood Springs

DeBeque

1

1 1

U.S. Department of the InteriorU.S. Geological Survey

Scientific Investigations Report 2013–5015

Plate 3 of 5

Base from U.S. Geological Survey digital dataUniversal Transverse Mercator, Zone 13 North

EXPLANATION

Site where one or more data values did not meet standard (for 30-day  standards, site has one or more data values greater than standard)

Nitrate value greater than 1-day water-supply standardU.S. Environmental Protection Agency recommended standard

00

10 20 30 40 50 MILES

10 20 30 40 50 KILOMETERS
70 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959

–2009 Plates 71 Plate 4. Exceedances of water-quality standards for chloride and sulfate from appendix 1 in the Piceance study area, western Colorado.

109°00' 108°30' 108°00' 107°30'

40°00'39°30'39°00'38°30'

WhiteRiver

PiceanceCreek

C

ol o

ar doR vi er

PlateauCreek

GunnisonRiver

DouglasCreek

Uncompahgre R

Dinosaur

Rangely

Meeker

WHITE RIVER

BASIN

Colorado River

Main Stem

Fruita

Palisade

Delta

Montrose

Cedaredge

Hotchkiss

Crawford

Paonia

Olathe

LOWER GUNNISON

RIVER BASIN

Collbran

Grand

Junction

Parachute

Rifle

Silt

New Castle

Glenwood Springs

DeBeque

U.S. Department of the InteriorU.S. Geological Survey

Scientific Investigations Report 2013–5015

Plate 4 of 5

Base from U.S. Geological Survey digital dataUniversal Transverse Mercator, Zone 13 North

EXPLANATION

Site where one or more data values did not meet standard (for 30-day  standards, site has one or more data values greater than standard)

Chloride value greater than 30-day water-supply standardSulfate value greater than 30-day water-supply standard

00

10 20 30 40 50 MILES

10 20 30 40 50 KILOMETERS
72 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959

–2009 Plates 73Plate 5. Exceedances of water-quality standards for copper, iron (total and dissolved), lead, zinc, and selenium from appendix 1 in the Piceance study area, western Colorado.

109°00' 108°30' 108°00' 107°30'

40°00'39°30'39°00'38°30'

WhiteRiver

PiceanceCreek

C

ol o

ar doR vi er

PlateauCreek

GunnisonRiver

DouglasCreek

Uncompahgre R

Dinosaur

Rangely

Meeker

WHITE RIVER

BASIN

Colorado River

Main Stem

Fruita

Palisade

Delta

Montrose

Cedaredge

Hotchkiss

Crawford

Paonia

Olathe

LOWER GUNNISON

RIVER BASIN

Collbran

Grand

Junction

Parachute

Rifle

Silt

New Castle

Glenwood Springs

DeBeque

U.S. Department of the InteriorU.S. Geological Survey

Scientific Investigations Report 2013–5015

Plate 5 of 5

Base from U.S. Geological Survey digital dataUniversal Transverse Mercator, Zone 13 North

EXPLANATION

Site where one or more data values did not meet standard (for 30-day standards, site has one or more data values greater  than standard)

Copper value greater than  acute aquatic-life standard

Lead value greater than acute aquatic-life standardLead value greater than 30-day chronic aquatic-life standardSelenium, greater than acute aquatic-life standardSelenium, greater than 30-day chronic aquatic-life standard

Zinc value greater than acute  aquatic-life standardZinc value greater than 30-day chronic aquatic-life standard for sculpinZinc value greater than 30-day chronic aquatic-life standard

Copper value greater than 30-day  chronic aquatic-life standardIron value greater than 30-day  water-supply standardIron, total recoverable, value  greater than 30-day chronic aquatic-life standard

00

10 20 30 40 50 MILES

10 20 30 40 50 KILOMETERS
74 Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009

Publishing support provided by:

Raleigh Publishing Service Center, Raleigh, North Carolina

Denver Publishing Service Center, Denver, Colorado

For more information concerning this publication, contact:

Director, USGS Colorado Water Science Center

Box 25046, Mail Stop 415

Denver, CO 80225

(303) 236-4882

Or visit the Colorado Water Science Center Web site at:

http://co.water.usgs.gov/

This publication is available online at:

http://pubs.usgs.gov/sir/2013/5015/
Thomas and others—Characterization and Data-Gap Analysis of Surface-Water Quality in the Piceance Study Area, 1959–2009—Scientific Invesigations Report 2013–5015