Prepared in cooperation with the Upper Colorado River Endangered Fish Recovery Program,

Bureau of Reclamation, U.S. Fish and Wildlife Service, Argonne National Laboratory,

Western Area Power Administration, and Wyoming State Engineer’s Office

Application of Sediment Characteristics and Transport

Conditions to Resource Management in Selected

Main-Stem Reaches of the Upper Colorado River, 

Colorado and Utah, 1965–2007

Scientific Investigations Report 2012–5195

U.S. Department of the Interior

U.S. Geological Survey

Application of Sediment Characteristics 

and Transport Conditions to Resource 

Management in Selected Main-Stem 

Reaches of the Upper Colorado River, 

Colorado and Utah, 1965–2007

By Cory A. Williams, Keelin R. Schaffrath, John G. Elliott, and Rodney J. Richards

Prepared in cooperation with the Upper Colorado River Endangered Fish 

Recovery Program, Bureau of Reclamation, U.S. Fish and Wildlife Service, 

Argonne National Laboratory, Western Area Power Administration, and 

Wyoming State Engineer’s Office

Scientific Investigations Report 2012–5195

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

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

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Suggested citation:

Williams, C.A., Schaffrath, K.R., Elliott, J.G., and Richards, R.J., 2013, Application of sediment characteristics and 

transport conditions to resource management in selected main-stem reaches of the Upper Colorado River, Colorado 

and Utah, 1965–2007: U.S. Geological Survey Scientific Investigations Report 2012–5195, 82 p.
iii

Contents

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

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

Description of Study Areas ..........................................................................................................................3

Upper Colorado River Basin................................................................................................................3

Gunnison River Basin...........................................................................................................................6

Green River Basin.................................................................................................................................7

Methods of Data Collection and Analysis .................................................................................................9

Topographical Surveying.....................................................................................................................9

Streambed-Sediment Characterization ..........................................................................................10

Suspended-Sediment Transport.......................................................................................................10

Suspended-Sediment Flux Transport Equations...................................................................11

Suspended-Sediment Concentration and Streamflow Relations......................................12

Two-Dimensional Streamflow and Sediment-Transport Model..................................................14

Incipient Motion of Streambed Materials ......................................................................................16

Rouse Number and Sediment-Transport Mode.............................................................................20

Two-Dimensional Streamflow and Sediment-Transport Model Calibration and Sensitivity

Analysis............................................................................................................................................21

Effects of Streamflow on Sediment Transport........................................................................................21

Suspended-Sediment Transport Equations....................................................................................25

Streamflow Effects on Suspended-Sediment Transport.....................................................25

Seasonal and Temporal Effects on Suspended-Sediment Transport ...............................32

Climatic Effects on Suspended-Sediment Transport Equations ........................................37

Suspended-Sediment Transport Equation-Error Analysis ..................................................39

Incipient Motion of Streambed Material ........................................................................................39

Gunnison River at Delta ............................................................................................................45

Gunnison at Whitewater...........................................................................................................51

Green River near Jensen..........................................................................................................55

Sediment-Transport Applications to Resource Management..............................................................61

Suspended-Sediment Transport.......................................................................................................62

Incipient Motion and Bed-Load Transport......................................................................................63

Case Study: Evaluation of Sand Transport in the Green River near Jensen, Utah ..................64

Evaluation of Sediment-Transport and Spawning-Habitat Conditions .............................65

Characterization of the Sand-Transport Conditions within the Study Reach..................70

Identification of Processes Controlling Sediment Transport in the Study Reach...........70

Summary........................................................................................................................................................74

References Cited..........................................................................................................................................76

Glossary.........................................................................................................................................................81
iv

Figures

1. Map showing selected U.S. Geological Survey streamflow-gaging station locations 

in the Upper Colorado River Basin.............................................................................................4

2. Map showing selected U.S. Geological Survey streamflow-gaging station locations 

in the Upper Colorado and Gunnison River Basins.................................................................5

3. Map showing selected U.S. Geological Survey streamflow-gaging station locations 

in the Green River Basin..............................................................................................................8

4. Map showing bed-material sampling locations. A, the Jensen mid-channel bar 

(spawning habitat), 5 miles downstream from the Green River near Jensen, 

Utah, streamflow-gaging station. B, 09261000, Green River near Jensen, Utah, 

streamflow-gaging station. C, 09152500, Gunnison River near Grand Junction, 

Colorado, streamflow-gaging station......................................................................................11

5. Map showing bed-material sampling location in the study reach on the Gunnison 

River near Delta, Colorado ........................................................................................................13

6. Map showing a Multi-Dimensional Surface-Water Modeling System 

(MD_SWMS) grid, 5 miles downstream from the Green River near Jensen, Utah, 

streamflow-gaging station ........................................................................................................17

7. Map showing temporary water-surface elevation gages and Acoustic Doppler 

Current Profiler (ADCP) cross-sections locations, 5 miles downstream from the 

Green River near Jensen, Utah, streamflow-gaging station...............................................19

8. Graph showing A, water-surface elevations and B, mean velocities for the 

best-fit model for the 9,000 cubic feet per second streamflow ..........................................22

9. Graph showing conceptual diagram of sediment transport with 

suspended-sediment load indicated by diagonal hachuring..............................................24

10. Graphs showing calibration data with sediment-transport equation predictions 

for suspended-sediment concentration at three hydrologic conditions calculated 

as (1) dry year, 5th-percentile; (2) average year, mean; and (3) wet year, 

95th-percentile of the daily mean streamflow record for each day...................................27

11. Graphs showing calibration data with sediment-transport equation predictions 

for suspended-sediment concentration at three time periods: (1) early year, 

beginning of sediment-transport equation period; (2) middle of 

sediment-transport equation period or year of minimum trend value; 

and (3) late year, end of sediment-transport equation period.............................................28

12. Graphs showing calibration data with sediment-transport equation predictions 

for the sand portion of the suspended-sediment concentration at three 

hydrologic conditions calculated as (1) dry year, 5th-percentile; (2) average year, 

mean; and (3) wet year, 95th-percentile of the daily mean streamflow record for 

each day.......................................................................................................................................29

13. Graphs showing calibration data with sediment-transport equation predictions 

for the sand portion of the suspended-sediment concentration at three time 

periods: (1) early year, beginning of sediment-transport equation period; 

(2) middle of sediment-transport equation period or year of minimum trend 

value; and (3) late year, end of sediment-transport equation period.................................30

14. Graphs showing comparison of the coefficient of determination (adjusted R2) 

for explanatory variables within the suspended-sediment-transport regression 

analysis at selected U.S. Geological Survey streamflow-gaging stations .......................31

15. Graphs showing statistical relation between median suspended-sediment 

concentration and streamflow at selected U.S. Geological Survey 

streamflow-gaging stations ......................................................................................................33
v

16. Graphs showing hysteresis loops (seasonal changes in suspended-sediment 

concentration) at selected U.S. Geological Survey streamflow-gaging stations............34

17. Graphs showing temporal trends in total suspended-sediment concentration at 

selected U.S. Geological Survey streamflow-gaging station locations ...........................36

18. Graphs showing temporal trends in sand portion of the suspended-sediment 

concentration at selected U.S. Geological Survey streamflow-gaging station 

locations.......................................................................................................................................37

19. Graphs showing differences in the statistical relation between 

suspended-sediment concentration and streamflow between wet and dry 

years at selected U.S. Geological Survey streamflow-gaging stations ............................38

20. Graphs showing error between the regression predictions and available daily 

suspended-sediment records at U.S. Geological Survey streamflow-gaging 

stations GUNNISON, 09152500, Gunnison River near Grand Junction, Colorado; 

and JENSEN, 09261000, Green River near Jensen, Utah; water years 2005–8 ................40

21. Map showing locations of the four cross sections of the study reach on the 

Gunnison River near Delta, Colorado ......................................................................................46

22. Graphs showing boundary shear stresses, water-surface elevations, and 

streambed elevations at cross-sections 2 and 3 for selected streamflows at 

U.S. Geological Survey streamflow-gaging station, 09144250, Gunnison River 

at Delta, Colorado .......................................................................................................................47

23. Graphs showing boundary shear stresses, water-surface elevations, and 

streambed elevations at cross-section 4 for selected streamflows at 

U.S. Geological Survey streamflow-gaging station, 09144250, Gunnison 

River at Delta, Colorado.............................................................................................................50

24. Map showing locations of the four cross sections of the study reach on the 

Gunnison River near Grand Junction, Colorado....................................................................52

25. Graphs showing boundary shear stresses, water-surface elevations, and 

streambed elevations for selected streamflows at the cross sections located 

450 and 300 feet upstream from U.S. Geological Survey streamflow-gaging 

station, 09152500, Gunnison River near Grand Junction, Colorado....................................53

26. Graphs showing shear stresses, water-surface elevations, and streambed 

elevations for selected streamflows at the cross sections located 150 feet 

upstream from and along the cableway of U.S. Geological Survey 

streamflow-gaging station, 09152500, Gunnison River near Grand Junction, 

Colorado .......................................................................................................................................54

27. Map showing shear stress cross-section locations, 5 miles downstream from 

the Green River near Jensen, Utah, streamflow-gaging station........................................55

28. Graphs showing cross-sections 1 and 2 boundary shear stresses for the median particle size of 56 millimeters, water-surface elevations, and streambed elevations 

for selected streamflows at U.S. Geological Survey streamflow-gaging station, 

09261000, Green River near Jensen, Utah ..............................................................................57

29. Graphs showing cross-sections 1 and 2 boundary shear stresses for the median 

particle size of 1.4 millimeters, water-surface elevations, and streambed elevations 

for selected streamflows at U.S. Geological Survey streamflow-gaging station, 

09261000, Green River near Jensen, Utah ..............................................................................58

30. Graphs showing cross-sections 3 and 4 boundary shear stresses for the median 

particle sizes of 1.4 and 56 millimeters, water-surface elevations, and streambed 

elevations for selected streamflows at U.S. Geological Survey streamflow-gaging 

station, 09261000, Green River near Jensen, Utah................................................................59
vi

31. Graphs showing cross-sections 5 and 6 boundary shear stresses for the median 

particle sizes of 1.4 and (or) 56 millimeters, water-surface elevations, and streambed 

elevations for selected streamflows at U.S. Geological Survey streamflow-gaging 

station, 09261000, Green River near Jensen, Utah................................................................60

32. Graph showing cross-section 6 boundary shear stresses for the median particle 

size of 1.4 millimeters, water-surface elevations, and streambed elevations for 

selected streamflows at U.S. Geological Survey streamflow-gaging station, 

09261000, Green River near Jensen, Utah ..............................................................................61

33. Maps showing comparison of the modes of sediment transport for sands in a 

reach of the Green River near identified razorback sucker spawning habitat at a 

modeled streamflow of 9,000 cubic feet per second............................................................65

34. Maps showing comparison of the modes of sediment transport for sands in a 

reach of the Green River near identified razorback sucker spawning habitat at a 

modeled streamflow of 10,600 cubic feet per second..........................................................66

35. Maps showing comparison of the modes of sediment transport for sands in a 

reach of the Green River near identified razorback sucker spawning habitat at a 

modeled streamflow of 14,100 cubic feet per second..........................................................67

36. Maps showing comparison of the modes of sediment transport for sands in a 

reach of the Green River near identified razorback sucker spawning habitat at a 

modeled streamflow of 17,700 cubic feet per second..........................................................68

37. Maps showing comparison of the modes of sediment transport for sands in a 

reach of the Green River near identified razorback sucker spawning habitat at a 

modeled streamflow of 19,000 cubic feet per second..........................................................69

38. Map showing longitudinal profile for modeled output, 5 miles downstream from 

the Green River near Jensen, Utah, streamflow-gaging station........................................70

39. Graph showing boundary shear stress along longitudinal profile of a reach 

5 miles downstream from the Green River near Jensen, Utah, streamflow-gaging 

station ...........................................................................................................................................72

40. Graphs showing A, relative water-surface slopes and B, water-surface elevations 

along longitudinal profile of a reach 5 miles downstream from the Green River near 

Jensen, Utah, streamflow-gaging station ..............................................................................72

Tables

1. Summary of streamflow and sediment data used in this study (calendar years) for 

selected U.S. Geological Survey streamflow-gaging stations in the Upper Colorado 

River Basin.....................................................................................................................................6

2. Mode of sediment transport based on Rouse number.........................................................21

3. Lateral eddy viscosity sensitivity analysis and results for the five streamflows 

simulated in the two-dimensional streamflow and sediment-transport model for 

the Green River near Jensen, Utah, study reach..................................................................23

4. Drag coefficient sensitivity analysis and results for the five streamflows simulated 

in the two-dimensional streamflow and sediment-transport model for the Green 

River near Jensen, Utah, study reach.....................................................................................23

5. Regression coefficients and equation properties for suspended-sediment transport 

at selected U.S. Geological Survey streamflow-gaging stations in the Upper 

Colorado River Basin..................................................................................................................26
vii

6. Sediment-particle-size distribution summary statistics of bed-material samples 

collected at selected locations in the Gunnison and Green Rivers in 2008, and 

2006–7, respectively ...................................................................................................................41

7. Summary of boundary shear stress and grain shear stress for selected locations 

in the Gunnison and Green Rivers ...........................................................................................42

8. Cross-section characteristics, grain shear stress, and critical shear stress for 

the median sediment-particle sizes (d50) at selected U.S. Geological Survey 

streamflow-gaging stations in the Upper Colorado River Basin ........................................48

9. Estimates of peak streamflow values for selected recurrence intervals at 

U.S. Geological Survey streamflow-gaging stations in the Upper Colorado 

River Basin...................................................................................................................................50
viii

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

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) 

Flow rate

cubic foot per second (ft3

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

Mass

ton per day (ton/d) 0.9072 metric ton per day

ton per day (ton/d) 0.9072 megagram per day (Mg/d)

Pressure

pound per square foot (lb/ft2

) 0.04788 kilopascal (kPa) 

Density

pound per cubic foot (lb/ft3

) 16.02 kilogram per cubic meter (kg/m3)

pound per cubic foot (lb/ft3

) 0.01602 gram per cubic centimeter (g/cm3)

SI to Inch/Pound

Multiply By To obtain

Length

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

Flow rate

meter per second (m/s) 3.281 foot per second (ft/s) 

Density

kilogram per cubic meter (kg/m3

) 0.06242 pound per cubic foot (lb/ft3) 

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).

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

A water year is the 12-month period from October 1 for any given year through September 30 

of the following year. The water year is designated by the calendar year in which it ends and 

which includes 9 of the 12 months. Thus, the year ending September 30, 2011, is called the 

“2011” water year.
ix

Abbreviations used in this report:

ADCP Acoustic Doppler Current Profiler 

ANCOVA ANalysis of COVAriance

d50 median sediment-particle size 

ERV estimated residual variance 

GPS global positioning system

ln natural logarithm

MD_SWMS Multi-Dimensional Surface-Water Modeling System 

MLE maximum likelihood estimation 

MVUE minimum variance unbiased estimate

NWIS National Water Information System 

R2 coefficient of determination

RM river mile(s)

RMSE root mean square error(s)

RTK Real-Time Kinematic

TIN Triangular Irregular Network 

USGS U.S. Geological Survey

UTM Universal Transverse Mercator

WY water year

Abstract

The Colorado River Basin provides habitat for 14 native 

fish, including 4 endangered species protected under the Federal Endangered Species Act of 1973. These endangered fish 

species once thrived in the Colorado River system, but waterresource development, including the building of numerous 

diversion dams and several large reservoirs, and the introduction of non-native fish, resulted in large reductions in the 

numbers and range of the four species through loss of habitat 

and stream function. Understanding how stream conditions 

and habitat change in response to alterations in streamflow 

is important for water administrators and wildlife managers 

and can be determined from an understanding of sediment 

transport. Characterization of the processes that are controlling sediment transport is an important first step in identifying 

flow regimes needed for restored channel morphology and 

the sustained recovery of endangered fishes within these river 

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

the Upper Colorado River Endangered Fish Recovery Program, Bureau of Reclamation, U.S. Fish and Wildlife Service, 

Argonne National Laboratory, Western Area Power Administration, and Wyoming State Engineer’s Office, began a study 

in 2004 to characterize sediment transport at selected locations on the Colorado, Gunnison, and Green Rivers to begin 

addressing gaps in existing datasets and conceptual models of 

the river systems.

This report identifies and characterizes the relation 

between streamflow (magnitude and timing) and sediment 

transport and presents the findings through discussions of 

(1) suspended-sediment transport, (2) incipient motion of 

streambed material, and (3) a case study of sediment-transport 

conditions for a reach of the Green River identified as a razorback sucker spawning habitat.

Suspended-sediment transport can be a large part of the 

total-sediment flux within the rivers of this study and as such 

is strongly related to the geomorphology and habitat conditions found in these reaches. Suspended-sediment transport 

affects the channel form, bank and bar development, and the 

availability and quality of habitat for multiple life-stages of 

aquatic species. Regression analysis was used in this report 

to estimate suspended-sediment transport as a function of 

streamflow, seasonality, and temporal trends. Estimates of 

suspended-sediment (SS) flux can be helpful in determining 

total flux of sediments within the river at a station or to evaluate sediment budgets between stations. Understanding the processes that explain the variability of SS concentration also can 

provide information needed to better manage water resources 

within these rivers (related to the timing and magnitude of 

flow releases and withdrawal from reservoirs and diversion 

structures) and to evaluate temporal and spatial changes at a 

station and within river reaches. 

Suspended-sediment transport equations using regression analysis were generated for the six stations that had 

sufficient data within the study area: three stations on the 

main-stem Colorado River between Cameo, Colorado, and 

the confluence with the Green River; one station on the 

Gunnison River downstream from the Aspinall Storage 

Unit; and two stations on the Green River below Flaming 

Gorge Reservoir, and downstream from the confluence of the 

Yampa River. Interpretations of the variables used within the 

regression analysis aid in identification and quantification 

of the processes or mechanisms that are important controls 

on suspended-sediment transport within the system and to 

provide information on the timing of sediment inputs (supply 

changes) to the system.

Regression analysis of the suspended-sediment data show 

that streamflow explains much of the variability in SS concentration at all stations and shows that increases in streamflow 

increase SS concentrations. Additional significant relations are 

characterized for SS concentration and SS flux that result from 

seasonality (time of year), temporal trends (time across multiple years), and climatic effect (wet and dry years). Changes 

in the streamflow and SS concentration relation based on time 

of year (hysteresis) demonstrate that for a specific streamflow 

there can be multiple predicted SS concentrations.

Application of Sediment Characteristics and Transport 

Conditions to Resource Management in Selected 

Main-Stem Reaches of the Upper Colorado River, 

Colorado and Utah, 1965–2007

By Cory A. Williams, Keelin R. Schaffrath, John G. Elliott, and Rodney J. Richards
2 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Incipient motion of streambed material (often occurring as bed-load transport) and the sorting of bed materials 

are important controls on channel form and habitat and are 

strongly related to the channel morphology and habitat conditions within these rivers. Comparison between boundary shear 

stresses of multiple streamflows and the relative mobility of 

bed material (median sediment-particle sizes) characterizes the 

effects of flow magnitude on mobilization of framework grain 

within the streambed. Observations at multiple cross sections 

within two reaches of the Gunnison River near Grand Junction downstream from the Aspinall Storage Unit show that 

peak streamflow conditions up to 14,000 cubic feet per second 

(ft3

/s) (recurrence interval of 5 to 10 years) produce ineffectual mobilization of most, if not all, areas within the surveyed 

cross sections. Observations at multiple cross sections within 

a study reach of the Green River downstream from Flaming Gorge Reservoir show peak streamflows of as much as 

19,000 ft3

/s (recurrence interval of 2.3 to 5 years) produce 

ineffectual mobilization of most, if not all, areas within the 

surveyed cross sections of the larger bed material. However, 

when the sand veneer is present at these cross sections, or 

where the portion of sand within the bed material exceeds 

20–30 percent of the total, mobilization of the bed material 

will occur at most locations within the surveyed cross sections 

for peak streamflows of 9,000–19,000 ft3

/s (recurrence intervals ranging from 1 to 5 years) with mobilization of gravels 

possible in some areas.

Application of the two-dimensional stream hydraulics 

and sediment-transport models provides enhanced capabilities 

for evaluations of dynamic reach-scale processes that affect 

habitat suitability. Understanding the processes that affect the 

sediment-transport characteristics, which are important to the 

maintenance of endangered fish spawning habitat, can be used 

to inform the flow-recommendations process that currently 

(2012) guides water management of Flaming Gorge Reservoir.

Evaluations of the processes controlling sediment deposition on the spawning habitat near a mid-channel bar are not 

limited to stream-transport conditions within the spawninghabitat reach. Considerations of sediment availability and net 

changes in sediment transport between upstream reaches and 

the spawning habitat are important. Sands are mobile throughout the main channel for all modeled streamflows (9,000–

19,000 ft3

/s), but in areas upstream from the mid-channel 

bar (and spawning habitat) increases in streamflow tend to 

increase transport rates. Within the spawning habitat, increases 

in streamflow result in decreases in water-surface slope and 

varied responses to boundary shear stress. At larger streamflows (14,100–17,700 ft3

/s), sediment upstream from the 

mid-channel bar is transported in greater amounts and likely 

at greater rates than can be transported by the conditions at the 

spawning-habitat reach. This may exceed a threshold between 

the two areas resulting in a disequilibrium and net deposition of sands on the spawning habitat at higher streamflows 

(14,100–17,700 ft3

/s). Spawning habitat may be less suitable at 

these higher streamflows owing to deposition of sands on the 

spawning habitat under these conditions.

Introduction

The Colorado River Basin provides habitat for 14 native 

fish, including 4 endangered species protected under the Federal Endangered Species Act of 1973—Colorado pikeminnow 

(Ptychocheilus lucius), razorback sucker (Xyrauchen texanus), 

bonytail (Gila elegans), and humpback chub (Gila cypha) 

(U.S. Fish and Wildlife Service, 2011a). In 1988, the Upper 

Colorado River Endangered Fish Recovery Program (hereafter Recovery Program) began conducting research and taking 

action to improve river habitat for these species (U.S. Fish 

and Wildlife Service, 2011a). The Recovery Program is a 

joint effort of the U.S. Fish and Wildlife Service; Bureau of 

Reclamation; Western Area Power Administration; States 

of Colorado, Utah, and Wyoming; Upper Basin water users; 

environmental organizations; the Colorado River Energy 

Distributors Association; and the National Park Service. These 

endangered fish species once thrived in the Colorado River 

system, but water-resource development, including the building of numerous diversion dams and several large reservoirs, 

and the introduction of non-native fish, resulted in large reductions in the numbers and range of the four species through loss 

of habitat and stream function (Valdez and Muth, 2005; U.S. 

Fish and Wildlife Service, 2011a).

Understanding how stream conditions and habitat change 

in response to alterations in streamflow is important for water 

administrators and wildlife managers and can be determined 

from an understanding of sediment transport. Coordinated 

releases from reservoirs within the Upper Colorado River 

Basin have been implemented to recreate more natural streamflow patterns to restore channel functions in the system and 

assist recovery efforts (U.S. Fish and Wildlife Service, 2011b). 

These more natural streamflows provide larger peaks during 

the snowmelt-runoff period and provide additional base flow 

during late summer in dry years. These streamflows are more 

similar to pre-water-development conditions, but a thorough 

understanding of the effects of these streamflows on geomorphic processes (such as sediment supply and transport) and 

habitat response has yet to be gained. 

Evaluation of endangered fishes habitats requires an 

understanding of the physical connection between streamflow 

and sediment-transport conditions. Characterization of the 

processes that are controlling sediment transport is an important first step in identifying flow regimes needed for restored 

channel morphology and the sustained recovery of endangered fishes within these river systems. Determination of the 

sediment-transport characteristics within selected reaches of 

the Upper Colorado River Basin has been underway since the 

1990’s (Elliott and Anders, 2005; Williams and others, 2009). 

The effects of peak- and base-flow variability (magnitude 

and duration) on sediment deposition, erosion, and antecedent conditions (such as quantity and availability of habitat) 

need further study. The U.S. Geological Survey (USGS), in 

cooperation with the Upper Colorado River Endangered Fish 

Recovery Program, Bureau of Reclamation, U.S. Fish and 

Wildlife Service, Argonne National Laboratory, Western Area 
Description of Study Areas 3

Power Administation, and Wyoming State Engineer’s Office, 

began a study in 2004 to characterize sediment transport at 

selected locations on the Colorado, Gunnison, and Green Rivers to begin addressing gaps in existing datasets and conceptual models of the river systems.

The purpose of this report is to characterize the magnitude, timing, and size distribution of sediment transport 

at selected locations on the Colorado, Gunnison, and Green 

Rivers in order to aid the Recovery Program in the evaluation 

of the effects of streamflow and sediment transport on critical 

habitat for the endangered fishes. Evaluation of the dynamics 

of sediment movement in representative locations was done 

to aid understanding of the relation between streamflow and 

sediment transport throughout the critical habitat reaches. 

This report identifies and characterizes the relation between 

streamflow (magnitude and timing) and sediment transport and 

presents the findings through discussions of (1) suspendedsediment transport, (2) incipient motion of streambed material, and (3) a case study of sediment-transport conditions for 

a reach of the Green River identified as a razorback sucker 

spawning habitat.

Description of Study Areas

Streamflow and sediment transport were characterized 

at selected streamflow-gaging stations from three main-stem 

reaches: (1) the Colorado River downstream from Cameo, 

Colorado, to the confluence with the Green River; (2) the 

lower Gunnison River downstream from the confluence with 

the North Fork of the Gunnison River to the confluence with 

the Colorado River near Grand Junction, Colorado; and (3) 

the Green River downstream from the confluence with the 

Yampa River to the confluence with the Colorado River, 60 mi 

south of Green River, Utah (fig. 1). The climate in the study 

area varies spatially and with elevation (Apodaca and others, 

1996). Common to the mountainous Western United States, 

the annual hydrographs of the main-stem rivers are dominated 

by snowmelt runoff, which usually begins in late April and 

peaks in late May or early June. Late-summer rain events 

cause localized flooding in tributaries and may increase mainstem streamflow by 10–20 percent (Pitlick and others, 1999). 

Upper Colorado River Basin

The Upper Colorado River Basin includes 25,910 mi2 of 

drainage upstream from the confluence with the Green River 

(Seaber and others, 1987). In general, streams and rivers in 

the headwaters of the Colorado River are characterized by 

lower sediment and cooler temperatures than areas in reaches 

associated with outcrops of sedimentary rock located in the 

downstream parts of the basin (Apodaca and others, 1996). 

Precipitation ranges from 40 in. or more at higher elevations 

in the basin to less than 10 in. per year at lower elevations 

(PRISM Climate Group, 2008).

The Gunnison and Dolores Rivers are the largest tributaries to the Upper Colorado River within the study area (fig. 2). 

The Gunnison River contributes more than 40 percent of the 

annual streamflow leaving Colorado [based on a comparison of annual streamflow record totals for 09152500, Gunnison River near Grand Junction, Colorado, period of record 

1897–2007; and 09163500, Colorado River near Colorado–

Utah State line, period of record 1951–2007 (U.S. Geological 

Survey, 2007)]. The Dolores River contributes 6 percent of 

the total streamflow of the Colorado River near Cisco, Utah 

[based on a comparison of annual streamflow record totals for 

09180500, Colorado River near Cisco, Utah, period of record 

1914–2007; and 09180000, Dolores River near Cisco, Utah, 

period of record 1950–2007 (U.S. Geological Survey, 2007)]. 

Various geologic formations are drained by the Upper 

Colorado River Basin. The Gunnison River and its tributaries drain alpine areas composed of crystalline metamorphic 

and igneous rocks of Tertiary and Precambrian age (Schruben 

and others, 1974). Commonly, the small tributaries in the 

Gunnison River below the Aspinall Storage Unit are seasonal 

streams driven by snowmelt and intense rain events. The 

nature of the geology in these areas and the intensity of the 

rain events allows for sediments to be transported into the 

Gunnison River (Apodaca and others, 1996; Williams and 

others, 2009).

The Dolores River drains much of southwestern Colorado, originating in the San Juan Mountains and flowing 

west-northwest. Various geological formations are found in 

the Dolores River Basin, most are Cretaceous sandstones and 

shale (Schruben and others, 1974), which are prone to erosion. 

Salt domes also are common along the Dolores River affecting water quality downstream. The Dolores River Basin also 

has many ephemeral streams that primarily are active during 

intense rain events. Intense rain events mobilize sand, silt, and 

gravel, which accumulates in the dry streambeds and empties 

into the Dolores River. 

The underlying geology in the region can influence the 

water quality. The bedrock in the region is made up of crystalline and sedimentary rock. Alluvium consisting of stream, 

landslide, terrace, and glacial deposits is present in valleys 

throughout the basin (Apodaca and others, 1996). Mining was 

a historically significant land use in the upper reaches of the 

Upper Colorado River Basin. Receiving water bodies have 

been affected by point-source mine discharge and nonpointsource runoff from mined areas. High concentrations of some 

materials, particularly salts derived from sedimentary rocks, 

are more common in the western part of the basin.

The water in the Upper Colorado River Basin is used for 

irrigation (Osmundson and others, 1995), but transmountain 

diversions (located near the headwaters) also provide water 

to municipalities along the eastern part of Colorado (Apodaca 

and others, 1996). Streamflows in the reach of the Colorado 

River from Cameo, Colorado, to the confluence with the Gunnison River are greatly reduced during the irrigation season 

(April–October) owing to local irrigation systems that have 

been in place since the early 1900s. Withdrawals by these 
4 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 1. Map showing selected U.S. Geological Survey streamflow-gaging station locations in the Upper Colorado River Basin.

112°30' 110°00' 107°30'

42°30'

40°00'

37°30'

Base from U.S. Geological Survey National Atlas

Universal Transverse Mercator North American Datum 1983, Zone 12 North

0 50 100 MILES

0 50 100 KILOMETERS

UTAH

COLORADO

WYOMING

IDAHO

ARIZONA NEW MEXICO

UTAH COLORADO

Delta

Grand

Junction

River

THE GREAT

 SALT LAKE

Flaming

Gorge

Fontenelle

Reservoir

Strawberry

 Reservoir

LAKE POWELL

ASPINALL

STORAGE UNIT

(BLUE MESA,

MORROW POINT,

CRYSTAL RESERVOIRS) 

Glenwood

Springs

 Vernal

 Ouray

 Green

River

Starvation

 Reservoir

EXPLANATION

Streamflow-gaging station and number 

CONTINENTAL DIVIDE

09152500

North Fork

 Cisco

SALT LAKE

CITY

 Cameo

!(

!(

!(

!

! (09152500

09163500

09315000

09307000

09261000

09144250

(! 09095500

(! 09180500

(

!(

!(

San Juan River

Colorado River

Gunnison Uncompahgre River

San Migel Rive

D

r

olores River

Great Divide

G

Closed Basin

reen River

Duchesne River

Price River

Colorado River

San Rafael River

Green River

Little Snake River Yampa River

White River
Description of Study Areas 5

Figure 2. Map showing selected U.S. Geological Survey streamflow-gaging station locations in the Upper Colorado and Gunnison 

River Basins.

COLORADO

UTAH

0 50 100 MILES

0 50 100 KILOMETERS

Delta

Grand

Junction

North Fork

Uncompahgre River

 Cisco

Glenwood

Springs

 San Juan Mountains

 Cameo

 Whitewater

09152500 09163500

09144250

09095500

09180500

108°

39°

38°

UTAH

COLORADO

WYOMING

IDAHO

NEW MEXICO ARIZONA

UTAH

Continental

Divide

Base from U.S. Geological Survey National Atlas

Universal Transverse Mercator North American Datum 1983, Zone 12 North

110°

!

!

!

!

!

San Migel River

Dolores River

Colorado

River

ASPINALL

STORAGE UNIT

(BLUE MESA,

MORROW POINT,

CRYSTAL RESERVOIRS) 

Gunnison

Tunnel

Colorado

River

Gunnison

River

Elk Mountains

EXPLANATION

Streamflow-gaging station and number 09144250 !
6 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

systems are approximately 1,200–1,600 ft3

/s depending on 

the month (Osmundson and others, 1995). Streamflows in this 

part of the reach are further diminished, especially during the 

spring runoff period, by large dams and transmountain diversions that were built in the headwaters (upstream from Cameo) 

beginning in the mid-1930s (Osmundson and others, 1995).

The USGS operates three streamflow-gaging stations on 

the main stem of the Colorado River (U.S. Geological Survey, 

2007) within the study area where suspended-sediment data are 

collected (fig. 2). Streamflow is recorded at streamflow-gaging 

station 09095500, Colorado River near Cameo, Colorado. The 

gage is located on the left bank 7 mi northeast of Cameo. The 

drainage area at the gaging station is approximately 8,050 mi2, 

and the period of streamflow record and sediment data used for 

this study were from 1982 to 1998 (table 1).

Streamflow is recorded at streamflow-gaging station 

09163500, Colorado River near the Colorado–Utah State line. 

The gage is located on the right bank 1.7 mi upstream from the 

Colorado–Utah State line. The drainage area at the gaging station is approximately 17,843 mi2

, and the period of streamflow 

record and sediment data used for this study were from 1976 

to 2007 (table 1).

Streamflow is recorded at streamflow-gaging station 

09180500, Colorado River near Cisco, Utah. The gage is 

located on the left bank 1 mi downstream from the Dolores 

River, and 11 mi south of Cisco. The drainage area at the 

gaging station is approximately 24,100 mi2, and the period of 

streamflow record and sediment data used for this study were 

from 1985 to 2000 (table 1).

Gunnison River Basin

The Gunnison River originates in south-central Colorado 

and drains approximately 8,000 mi2 at its confluence with 

the Colorado River at Grand Junction, Colorado (Elliott and 

Hammack, 1999). The upper Gunnison River drains areas west 

of the Continental Divide and flows into the Wayne Aspinall 

Unit of the Colorado River Storage Project (Aspinall Unit), 

which consists of three large reservoirs (Blue Mesa, Morrow 

Point, and Crystal Reservoirs) (figs. 1 and 2). The Aspinall 

Unit has a storage capacity of about 52 percent of the average 

annual streamflow of the Gunnison River (Elliott and Hammack, 1999). The lower Gunnison River begins downstream 

from Crystal Reservoir and continues flowing west through 

the town of Delta to the confluence with the Colorado River 

near Grand Junction, Colorado. Annual precipitation rates are 

a mixture of alpine and arid climates with annual totals ranging from 9 to 50 in. annually (PRISM Climate Group, 2008). 

Forest and herbaceous grasslands are the most abundant land 

cover in the alpine areas, with forest and shrublands most 

abundant in the high-desert landscapes; lesser areas of barren 

land lie along mountain peaks, and agricultural and urban 

areas are primarily located along the valley bottoms (National 

Atlas, 2010).

Tributaries in the Gunnison River Basin drain alpine 

areas predominately composed of igneous rocks of Tertiary 

age and metamorphic rocks of Precambrian age (Schruben 

and others, 1974). Tributaries in the Gunnison River Basin 

below the confluence with the North Fork drain arid areas 

Table 1. Summary of streamflow and sediment data used in this study 

(calendar years) for selected U.S. Geological Survey streamflow-gaging stations 

in the Upper Colorado River Basin.

[--, no data]

Station identification 

number

Abbreviation used 

in this report

Streamflow and sediment data 

used in regression analysis

Colorado River

09095500 CAMEO 1982–98

09163500 STATELINE 1976–2007

09180500 CISCO 1967–2000

Gunnison River

09144250 DELTA --

09152500 GUNNISON 1976–2007

Green River

09261000 JENSEN 1965–2007

09307000 OURAY1 --

09315000 GREEN 1965–2000

1

Sediment and streamflow data do not adequately characterize the conditions of the stream in 

the time period following completion and operation of Flaming Gorge Reservoir.
Description of Study Areas 7

predominantly composed of sedimentary rocks of Cretaceous 

and Jurassic age. Differences in lithology contribute to the 

width and slope of the river valleys; erosion-resistant crystalline rocks produce steeper, narrower canyons, and more erosive sedimentary rocks produce wider, lower-gradient reaches 

(for example, the Uncompahgre River valley). These differences also can affect sediment transport and storage and the 

relative thickness of alluvium in and around the river channel. 

Large tributaries to the Gunnison River Basin below the 

Aspinall Storage Unit are the Uncompahgre River and the 

North Fork of the Gunnison River. The Uncompahgre River 

originates in the San Juan Mountains to the south of Delta, 

Colorado, and flows northwest until converging with the Gunnison River in Delta, Colorado. The Uncompahgre River flows 

through large agricultural-use areas and is the water source 

for irrigated land along the Uncompahgre River (Butler and 

others, 1996). Additional water is diverted from the Gunnison 

River into the Uncompahgre through the Gunnison Tunnel 

(Butler and others, 1996) (fig. 2). The North Fork of the Gunnison River originates in the Elk Mountains and flows west 

until converging with the main stem of the Gunnison River 

near Delta, Colorado. The North Fork is used for municipal 

and agricultural use for numerous small communities before 

converging with the Gunnison River. The Mancos Shale is 

the dominant geologic formation located in the agricultural 

valleys (Butler and Leib, 2002). Mancos Shale weathers into 

various clays, which are easily transported in fluvial systems. 

Depending on the season, irrigation-return waters passing 

over unvegetated areas within agricultural fields can increase 

suspended-sediment (SS) concentration and turbidity of the 

river owing to the high erosivity of these landscapes (Apodaca 

and others, 1996; Butler and Leib, 2002).

With the exception of occasional monsoonal-rain events, 

infrequent fall-snowmelt events, and irrigation-return flows, 

base flow from the surrounding highlands in the lower Gunnison River contributes little streamflow to the main stem of 

the Gunnison River (Butler and Leib, 2002). Since completion 

of the Aspinall Storage Unit (1967), changes in the timing and 

volume of streamflow have been observed in the Gunnison 

River. Peak streamflows during April–July are attenuated, and 

low flows during August–March have increased; however, 

mean annual streamflow has decreased only slightly (Kuhn 

and Williams, 2004).

The USGS operates two streamflow-gaging stations on 

the main stem of the Gunnison River (U.S. Geological Survey, 

2007) downstream from the Aspinall Storage Unit in the study 

area (fig. 2). Streamflow is recorded at streamflow-gaging station 09144250, Gunnison River at Delta, Colorado. The gage is 

located on the left bank 0.7 mi downstream from the north edge 

of Delta, Colorado. The drainage area at the gaging station is 

approximately 5,628 mi2

, and the period of streamflow record 

used for this study were from 1976 to 2007. Suspended-sediment samples were not collected at this station (table 1). 

Streamflow is recorded at streamflow-gaging station 

09152500, Gunnison River near Grand Junction, Colorado. The 

gage is located on the right bank 0.5 mi south of Whitewater. 

The drainage area at the gaging station is approximately 

7,928 mi2

, and the period of streamflow record and sediment 

data used in this study were from 1976 to 2007 (table 1). 

Green River Basin

The Green River transports runoff from more than 

44,200 mi2 of contributing areas in Wyoming, Colorado, and 

Utah (not including the Great Divide Closed Basin) (fig. 1). 

It is the largest tributary in the Upper Colorado River Basin 

(Seaber and others, 1987). The Green River drains areas 

west of the Continental Divide in Wyoming, flowing first 

into Fontenelle Reservoir and then Flaming Gorge Reservoir 

near the Wyoming–Utah State line (fig. 1). The Green River 

flows east into Colorado before it continues back into Utah 

toward the town of Vernal. The Green River then flows south 

to Green River, Utah, and the confluence with the Colorado 

River (fig. 3).

The major tributaries are the Yampa River, Duchesne 

River, White River, Price River, and San Rafael River (fig. 3). 

The upper basin tributaries of the watershed generally drain 

snowmelt from the igneous and metamorphic lithologies of 

several mountain ranges, whereas the lower basin tributaries 

generally drain more arid regions of sedimentary lithologies 

(Schruben and others, 1974). Sediment sources tend to correlate with lithology and precipitation patterns, and a large 

amount of the annual sediment load is supplied to the Green 

River from the Little Snake River, by way of the Yampa 

River (Andrews, 1978, 1986). The Little Snake River, Yampa 

River, and parts of the Green River near Vernal, Utah, flow 

through a succession of wide, parklike reaches and narrow, 

steep canyons. Steep, confined canyon reaches may function 

as sediment-conveying zones during floods, whereas broad, 

park-like reaches with low gradients may be associated with 

depositional environments during the same floods (Elliott and 

Anders, 2005).

Streamflow in the Green River has been regulated by 

Flaming Gorge Reservoir since 1962 (Andrews, 1986). Flaming Gorge Reservoir, completed in 1964, has had a significant 

effect on streamflow, sediment transport, and the geomorphology of the Green River downstream from the dam (Andrews, 

1986). The Green River near Jensen gage has operated since 

1947, and streamflow characteristics from that gage reflect 

alterations in streamflow as a result of reservoir operation. 

Andrews (1986) used streamflow data recorded at this station from 1963 through 1981 in his analyses of downstream 

reservoir effects on the Green River. Annual peak streamflows 

and flow-duration curves for the Green River near Jensen gage, 

updated through water year (WY, a water year is the 12-month 

period from October 1 for any given year through September 

30 of the following year. The water year is designated by the 

calendar year in which it ends and which includes 9 of the 

12 months. Thus, the year ending September 30, 2011, is called 

the “2011” water year) 2002, reveal the changes in streamflow 

caused by Flaming Gorge Reservoir (Elliott and Anders, 2005). 

Regulation by the reservoir has altered the magnitude and 
8 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 3. Map showing selected U.S. Geological Survey streamflow-gaging station locations in the Green River Basin.

110° 108°

UTAH

WYOMING

WYOMING

COLORADO

0 50 100 MILES

0 50 100 KILOMETERS

Vernal

 Ouray

Green

River

 Jensen

09315000

09307000

09261000

UTAH

COLORADO

WYOMING

IDAHO

ARIZONA NEW MEXICO

UTAH

Base from U.S. Geological Survey National Atlas

Universal Transverse Mercator North American Datum 1983, Zone 12 North

41°

39° !

!

!

Divide

Continental

Flaming

Gorge

Strawberry

 Reservoir

Starvation

 Reservoir

Gunnison River

Duchesne River

Colorado River

Green River

Yampa River

White River

Price River

Little Snake River

San Rafael River

UTAH

COLORADO

EXPLANATION

Streamflow-gaging station and number 09315000 !
Methods of Data Collection and Analysis 9

timing of the instantaneous peak streamflow in the Green River 

downstream from the reservoir, but not the annual volume of 

runoff (Andrews, 1986; Elliott and Anders, 2005). Streamflow 

regulation also has had a significant effect on sediment transport and the geomorphology of the Green River downstream 

from Flaming Gorge (Andrews, 1986; Elliot and Anders, 

2005). Mean annual sediment load at the gage near Jensen, 

Utah, is estimated to have decreased by 54 percent relative to 

sediment load prior to the construction of the dam (Andrews, 

1986). Similarly, the mean annual sediment load at the gage 

near Green River, Utah, decreased by 48 percent following the 

completion of the dam (Andrews, 1986). 

Streamflow and sediment transport in the Little Snake 

and Yampa Rivers have been affected only slightly by water 

storage and transmountain diversions within the respective 

watersheds (Elliott and Anders, 2005), and no major dams 

have been constructed on the main stems of these rivers. 

The USGS operates three streamflow-gaging stations on 

the main stem of the Green River within the study area (U.S. 

Geological Survey, 2007) where suspended-sediment data 

are collected (fig. 3). Streamflow is recorded at streamflowgaging station 09261000, Green River near Jensen, Utah. The 

gage is located 6.5 mi northeast of Jensen, Utah. The drainage 

area at the gaging station is approximately 29,660 mi2, and 

the period of streamflow record and sediment data used in this 

study were from 1965 to 2007 (table 1).

Streamflow was recorded at streamflow-gaging station 

09307000, Green River near Ouray, Utah. The gage is located 

near Ouray, Utah. The drainage area at the gaging station is 

approximately 26,780 mi2, and the period of streamflow record 

is 1947–55, 1956–66, and 2009–2012. Suspended-sediment 

samples were collected during the periods 1950–52 and 

1958–66 but the streamflow and sediment data were not used 

in this study because the flow alterations related to Flaming 

Gorge Reservoir completion and operation in 1963 were not 

adequately characterized by the available data (table 1).

Streamflow was recorded at streamflow-gaging station 

09315000, Green River at Green River, Utah. The gage is 

located on the right bank 0.9 mi southeast of Green River, 

Utah. The drainage area at the gaging station is approximately 

44,850 mi2

, and the period of streamflow record and sediment 

data used in this study were from 1965 to 2000 (table 1).

Methods of Data Collection and 

Analysis

Topographical Surveying

Water-surface and streambed-elevation mapping was 

done to calculate hydrologic parameters at selected locations 

near three USGS streamflow-gaging stations: (1) Gunnison 

River at Delta, Colorado; (2) Gunnison River near Grand 

Junction, Colorado; and (3) Green River near Jensen, Utah 

(figs. 1–3). Water profiles were flagged at the three stations 

for various streamflow conditions covering the range of 

high-flow conditions and streamflow conditions typical of 

the rising- or falling-limb of the snowmelt-runoff hydrograph 

for WY 2005–8. Flagging of the water surface occurred 

under stable streamflow conditions when fluctuations of 

water-surface elevations were minimal. Multiple flagging 

expeditions were completed between topographical surveys 

to characterize streamflow conditions at each location during 

the near peak and falling-limb of the snowmelt-runoff hydrograph. Different colors of flagging were used to distinguish 

between the different water surfaces. Each water surface was 

flagged over an appropriate interval of 2 to 4 channel widths 

to ensure accurate characterization of the slope of the water 

surface within the reach. Where stream conditions and (or) 

vegetation density allowed for continuous surveys along one 

or both banks, flags were placed at regularly spaced intervals (5–10 ft). Under some streamflow conditions, greater 

spacing of flags (15– 20 ft) or the omission of some flagging 

locations was required to minimize the effects of changing 

water-surface elevations and because of bank accessibility 

and flagger safety.

Topographical surveying of the flagged water surfaces 

was done using survey-grade global positioning system (GPS) 

equipment, operated in a Real-Time Kinematic mode (RTK–

GPS) (Trimble Navigation Limited, 1998), or total-station 

laser theodolite, to determine the elevation and coordinate 

locations of each flagged point. The RTK–GPS utilized a 

stationary GPS receiver (base station), positioned over a reference benchmark, and roving GPS receivers (rovers) operated 

by separate hand-held computers (data collectors). The RTK–

GPS system calculates the locations of the rovers in real time, 

using the positions of orbiting NAVSTAR–GPS satellites and 

the known location of the base station. The total station was 

positioned over a reference benchmark, and the coordinate 

location of each of the surveyed points was determined on the 

basis of the relative positions from the benchmark. 

Total-station methods involved surveying from a known 

instrument-base location and elevation to roving rodmounted prisms placed on the ground and reference points 

of interest. The azimuth and distance from the instrument 

base to the prism was converted to local northing and easting 

coordinates. The ground-surface elevation was carried from 

the instrument base to the base of the prism rod by conventional surveying trigonometry. The completed northing, 

easting, and elevation data were subsequently rectified and 

converted to the Universal Transverse Mercator (UTM) coordinates of the RTK–GPS survey, such that data from both 

survey methods were compatible. 

All surveyed elevations (RTK–GPS) then were exported 

to a personal computer for post-processing of the orthometric 

heights. The survey data were output to a spreadsheet program in metric Northing, Easting, and Elevation format using 

a UTM coordinate system (UTM, Zone 12 North). Horizontal 

coordinate information was referenced to the North American 

Datum of 1983 (NAD 83), and vertical coordinate information was referenced to the North American Vertical Datum of 
10 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

1988 (NAVD 88). Elevation values were visually examined 

for relative accuracy by graphing and inspecting the cross 

section and by comparison of the elevation dataset between 

data-collection methods.

To determine streambed elevations, depth information 

at selected locations within the stream reaches was measured 

from a boat outfitted with a sounding reel, following standard 

USGS methods (Rantz and others, 1982). Cross-section locations were established within the surveyed reach perpendicular to the direction of flow. Each cross-section location was 

surveyed using RTK–GPS (and levels techniques) to register 

coordinate location and elevation. Depths along the cross section were referenced to the distance from one bank, and the 

elevations were determined by subtracting the depths at each 

location in the cross section from the established elevation at 

the junction of channel margin and the cross section.

Streambed-Sediment Characterization

Sediment characteristics were determined for the streambed and fluvial bars in the study reaches to characterize the 

range of sediment-particle sizes available for transport within 

the channel and typical of different geomorphic surfaces. 

Multiple sampling locations were selected within each reach 

to characterize specific features. Bars and channel margins 

(outside of areas strongly affected by eddies) were chosen to 

characterize the bed material of the channel. These areas are 

inundated most of the year and represent the coarser material 

within the river channel. Characterization of the bed material 

was done to determine the sediment-particle-size distribution 

and spatial extent of the bed materials within each reach. 

Bed-material sediment-particle-size analysis was performed by volumetric- and areal-sampling methods at Gunnison River near Grand Junction, Colorado, and Green River 

near Jensen, Utah, during 2006–7 (Williams and others, 2009), 

and at Gunnison River near Delta, Colorado, during 2008 

(figs. 4 and 5). Where the bed material was relatively fine 

(particle diameter less than 2 mm) or the streamflow was too 

deep to sample by wading, a boat-deployed, 7-in.-diameter 

pipe dredge was used to sample bed material (Benson and 

Dalrymple, 1967; Edwards and Glysson, 1999). Sedimentparticle-size characteristics for these samples were determined through volumetric techniques (dry sieving) of each 

sample following procedures described by Guy (1977) at the 

USGS Geomorphology and Sediment Transport Laboratory 

in Golden, Colorado. Where the bed material was gravel- or 

coarser-size material (particle diameter greater than 2 mm) and 

it was possible to wade, sediment-particle-size characteristics 

were determined in the field by using areal techniques (pebble 

count) described by Wolman (1954). A minimum of 100 clasts 

were measured during each pebble count. Most measurements 

were made linearly and parallel to the direction of streamflow 

at regularly spaced intervals along the streambed or alluvial 

bars at each sampling location. Typically, a tape measure or 

graduated tag line was set up along the geomorphic surface to 

be sampled, for example a streambank or an elongated alluvial 

bar. Predetermined intervals along the tape measure or tag line 

then were used to determine unbiased sampling points for the 

particle measurement. Measurements on submerged riffles and 

alluvial bars were made by a nonlinear, random-path method. 

With this method, the sampler wanders over the desired geomorphic surface, selecting a particle for measurement without 

looking at the particle. Sample spacing with the random-path 

method usually was one or two paces.

The intermediate or “b-axis” of the sediment particle 

was measured to the nearest millimeter for gravel and small 

cobbles, and to the nearest 5 mm for large cobbles and small 

boulders. The b-axis length was recorded in the field notes, 

and sediment-particle-size statistics (d10, size at the 10th 

percentile; d16, size at the 16th percentile; d50 size at the 

50th percentile; d65, size at the 65th percentile; d84 size at 

the 84th percentile; and d90, size at the 90th percentile) were 

computed in a spreadsheet from the cumulative-frequency 

distribution function of sampled-sediment particles. The d10

is used to conceptualize the threshold between components of 

sediment transport, described in the report section “Effects of 

Streamflow on Sediment Transport;” the d65 and d50 were used 

to determine the critical shear stress for sediment entrainment, 

described in the report section “Incipient Motion of Streambed 

Materials;” and the d16 and d84 are used to describe sediment 

transport of sands in a case study of the Green River spawning 

habitat near Jensen, Utah. 

Suspended-Sediment Transport

Standard techniques used to measure SS concentration and SS flux require the continuous measurement of 

streamflow and systematic measurement of SS concentration 

(Porterfield, 1972). The range of SS-concentration measurements needed to compute daily SS flux within these large 

river systems can range from multiple samples per hour to 

samples every third day depending on the time of year and 

hydrologic conditions within the stream (Williams and others, 2009). Daily mean streamflow data obtained from the 

USGS National Water Information System (NWIS) database (http://waterdata.usgs.gov/nwis) and instantaneous SS 

concentration calculated from manually collected isokinetic 

depth- and width-integrated samples were used in equation 1 

to calculate SS flux:

L = KC(t)Ԛ(t)P(t) (1)

where

L is the calculated SS flux, in tons per day;

K is a conversion factor, 0.0027;

C(t) is the average cross-sectional SS concentration

at time t, in milligrams per liter;

Ԛ(t) is the daily mean streamflow at time t, in 

cubic feet per second; and

P(t) is the proportion of the sediment-particle-size 

fraction of interest (sands or silt/clays) at 

time t, in percent of total concentration.
Methods of Data Collection and Analysis 11

Suspended-Sediment Flux Transport Equations

Estimation of SS flux can be accomplished by using 

sediment-transport curves, which define the relation between 

SS flux and relevant explanatory variables such as streamflow, 

seasonality, and time (Porterfield, 1972; Horowitz, 2003; 

Cohn, 2005; Elliott and Anders, 2005). The relations can be 

approximated by using simple hand-drawn curves or regression techniques. 

A common approach for developing sediment-transport 

curves using regression techniques is to relate SS flux (or concentration) as a power function of streamflow (Andrews, 1986; 

Elliott and Anders, 2005; Julien, 2010). Improvements to the 

accuracy of the relation can be made through the separation of 

the year into groupings based on seasonal periods or hydrological processes (Walling, 1977; Hansen and Bray, 1993; 

Sichingabula, 1998; Asselman, 2000). These power functions 

are useful for predictions of SS flux or concentration and provide an indication of seasonal influences of how the relation 

between streamflow and sediment transport changes relative 

to separate portions of the year. However, interpretation of 

the meaning of the streamflow variables is limited because a 

single explanatory variable is related to average responses of 

differing processes within the system and the relative significance of each variable cannot be compared directly between 

regression equations. The regression techniques used in this 

report avoid this limitation through inclusion of multiple 

explanatory variables (including streamflow, seasonality, and 

time) within a single equation.

Mathematical manipulation of the dataset (transformation) often is needed to better meet the assumptions of the linear regression in order to linearize the relation and to maintain 

constant variance. Compensation for differences in seasonal 

SS flux also can be accomplished using Fourier series and 

“dummy” variables to apply vertical shifts in the natural logarithm of SS flux and natural logarithm of streamflow relation 

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

series uses sine and cosine terms to account for continual 

changes over the seasonal period; dummy variables are used to 

account for more abrupt seasonal changes. The general equation form used in this report relates the natural logarithm of SS 

flux to daily mean streamflow and other explanatory variables 

using maximum likelihood estimation (MLE) methods within 

the USGS-developed LOADEST program (the FORTRAN 

program LOAD ESTimator, Runkel and others, 2004). The 

resulting general equation form used in this analysis is similar 

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

and is represented in equation 2.

ln ˆ (ln ln ) (ln ln )

( )( ) si

L Q Q Q Q

tt tt

= + − + − +

− + − +

∗ ∗

∗ ∗

β β β

β β β

0 1 2

2

3 4

2

5 n( )

(cos( )

K T

K T D

2

2 6 7

π

β π β ε

+

+ + (2)

where

ln is the natural logarithm function;

L

ˆ is the estimated SS flux, in tons per day;

β0 is the regression equation intercept;

βn is the coefficient on the nth regression 

variable;

Ԛ is daily mean streamflow, in cubic feet per 

second;

Ԛ* is the streamflow centering value from the

calibration dataset, in cubic feet per second;

t is time, in decimal years;

t

* is the time centering value from the 

calibration dataset, in decimal years;

K is an integer, 1 or 2, that defines the wavelength 

of the sine and cosine functions;

T is a seasonality term representing the decimal 

portion of the year starting January 1;

D is a seasonality dummy variable, for 

rain events or the rising-limb of the 

hydrograph; and

ɛ is the error associated with the regression 

equation.

Orthogonalizing of the explanatory variables (time and 

streamflow) was done following methods in Cohn and others 

(1992) to “center” the dataset and remove multicolinearity between the explanatory variables (equations 3–6). This 

removes the effects of using a function and additional mathematical relation of the function (for example in the quadratic 

terms related to flow and time) and also reduces the leverage 

within the regression analysis that results from differences in 

the magnitude of the measure of each explanatory variable 

(for example, time in decimal years is of the scale 103 years; 

daily mean streamflow is on the scale of 103 to 104 ft3/s; and 

seasonality is on the scale of 10-1 to 100 years), thus providing 

better relative comparisons between each.

ln ln

ln ln

ln ln

Q Q

Q Q

Q Q

i

i

N

i

i

N

∗ =

=

= +

−

−

( )

( )

∑

∑

3

1

2

1

2

 

and

ln

ln

Q

Q

N

i

i

N

= =

∑1 (3 and 4)

where

ln is the natural logarithm function;

Ԛ* is the streamflow centering value for the 

dataset, in cubic feet per second;

 Ԛ

– is the mean of the streamflow in the 

dataset, in cubic feet per second;

Ԛi is the i

th daily mean streamflow, in cubic feet 

per second; and

N is the number of observations in the dataset.
12 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

 

t t

t t

t t

i

i

N

i

i

N

∗ =

=

= +

−

−

( )

( )

∑

∑

3

1

2

1

2

 

and t

t

N

i

i

N

= =

∑1

 

(5 and 6)

where

t

* is the time centering value for the dataset, in 

decimal years;

t

– is the mean of the time values in the dataset, in 

decimal years;

t

i is the i

th time value, in decimal years; and

N is the number of observations in the dataset.

Retransformation of regression predictions back from 

logarithmic scale produces median SS flux estimates in tons 

per day. A bias-correction factor is applied to the retransformed estimates to correct for the transformation bias and to 

produce mean estimates. Using median estimates can result in 

underestimations of SS flux by as much as 50 percent (Ferguson, 1986; Cohn and others, 1989; Cohn, 1995). According to 

Bradu and Mundlak (1970), the majority of the transformation 

bias can be eliminated by multiplying the estimated response 

by a bias-correction factor. Bias-correction factors for the 

MLE estimates were applied following modified methods 

from Bradu and Mundlak (1970) described in Runkel and 

others (2004) and Likes (1980) and resulted in a minimum 

variance unbiased estimate (MVUE) of the SS flux. The biascorrection factor used for MLE estimates of SS flux within 

LOADEST (gm (m,s2

,V)) is replaced with a similar function, 

phi, that is described in Likes (1980):

ˆ

L e g m, , s V MVUE

X

m

i i i

M

= + ∑

=





















( ) b b 0 1 2 (7)

where

L

ˆ

MVUE is the minimum variance unbiased estimate of 

SS flux, in tons per day;

e is the base of the natural logarithm,

β0 is the regression-equation intercept estimated 

by the MLE method;

βi is the coefficient on the ith regression variable 

estimated by the MLE method;

Xi is the ith regression variable;

gm (m, s2, V) is the bias-correction factor,

m is the number of degrees of freedom,

s2 is the residual variance, and

V is a function of the explanatory variables 

(Cohn and others, 1989).

Error assessment was done at stations with available daily 

mean SS flux estimates. Root mean square errors (RMSE; 

Helsel and Hirsch, 2002) (as percent of the mean value) were 

calculated from comparison of daily mean SS flux and transport equation estimates. Although error is inherent in both of 

these methods, for this analysis, available daily mean SS flux 

data were assumed to be most accurate and were treated as the 

actual SS fluxes at the station for that day. 

Comparisons were made for multiple time steps (daily, 

weekly, monthly, and seasonal totals) corresponding to one 

of three hydrologic “seasons” (base flow, rising limb of the 

snowmelt hydrograph, and falling limb of the snowmelt 

hydrograph). To provide a worst-case estimation of error, 

consecutive days were used to preserve serial correlation 

of the predictions. Use of consecutive days may result in 

consistent biases (non-random errors) that would increase the 

error of the prediction. Consecutive 7-day periods were used 

for weekly totals, 30 or 31 day periods were used for monthly 

totals, and each day of each season was combined by year for 

seasonal totals. 

If data were insufficient to be totaled into each of these 

time steps, days were reused from other totals to complete the 

number of days in the time step. For example, if there were 

33 consecutive days that were used for weekly total calculation, the days would be totaled as follows: 1–7, 8–14, 15–21, 

22–28, and 27–33. This method results in the reuse of days 27 

and 28 in two weekly totals but is appropriate in this analysis 

(Brent Troutman, U.S. Geological Survey, Lakewood, Colorado, oral commun., 2009). Similarly, separation of monthly 

totals into 30 and 31 day periods was done to best fit the available data and minimize reuse of data.

Suspended-Sediment Concentration and 

Streamflow Relations

Understanding the relation between streamflow and 

suspended-sediment transport can aid in the evaluation of 

physical and temporal processes that affect sediment transport. Regression analysis can be used to detect processes 

that explain variability in sediment transport within the river 

systems. The general equations used in this report is similar to 

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

is represented in equation 8:

1n Ĉ = β0 + β1 (1n Ԛ – 1n Ԛ* ) + β2 (1n Ԛ – 1n Ԛ* )2 +

β3 (t – t*) + β4 (t – t*)

2

 + ɛ (8)

where

ln is the natural logarithm function;

Ĉ is the estimated SS concentration or sand 

portion of the SS concentration (sand SS), 

in milligrams per liter;

β0 is the regression equation intercept;

βn is the coefficient on the nth regression 

variable;

Q is daily mean streamflow, in cubic feet per 

second;

Ԛ* is the streamflow centering value from the 

calibration dataset, in cubic feet per second;

t is time, in decimal years;

t

* is the time centering value from the 

calibration dataset, in decimal years;

ɛ is the error associated with the regression 

equation.
09152500 09261000

110°00' 107°30'

40°00'

38°00'

UTAH COLORADO

WYOMING

River

Strawberry Reservoir

 AspinallStorage Unit

0 25 50 MILES

0 25 50 75 KILOMETERS

Gunnison

Green

River White River Duchesne River

Yampa River

Flaming Gorge

Colorado River

Colorado River

Base from U.S. Geological Survey National AtlasUniversal Transverse Mercator North American Datum 1983, Zone 12 North

!

!

C

A, B

109°14'30" 

40°24'30"

40°24'45"

092

B

108°27'15" 10

38°59'

38°58'45"

Orthoimages from U.S. Department of Agriculture NationUniversal Transverse Mercator North American Datum 19

! 

C

Gun-1

Gun-2

Gun-3

!

0 0.1 0.2 MILE

0 0.2 KILOMETER

1 L M R

2 L M R

3 L M R

4M

5M

6

Mid-channel bar R M L

109°17' 109°16'30"

40°24'

40°23'45"

A EXPLANATION

Streamflow-gaging stationand number

Flow direction

Bed-material sample locations and identification

Bed-material sample locations, at left 1/3 of channel, middle of channel, and right 1/3 of channel, respectively

09261000 !

LMR

Gr-1
14 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 4 (previous page). Map showing bed-material sampling 

locations. A, the Jensen mid-channel bar (spawning habitat), 

5 miles downstream from the Green River near Jensen, Utah, 

streamflow-gaging station. B, 09261000, Green River near Jensen, 

Utah, streamflow-gaging station. C, 09152500, Gunnison River near 

Grand Junction, Colorado, streamflow-gaging station.

Comparisons of the relations between the natural logarithm of streamflow and the natural logarthim of SS concentration were done to determine the effects of antecedent 

conditions on sediment transport within the river systems. 

Inter-annual conditions can be important in sediment supply 

and storage. The sediment-streamflow relation may change 

following a hydrological ”wet” or ”dry” year or period. An 

evaluation of peak streamflow magnitude (relative to postreservoir streamflow percentiles) was used to classify each 

year as (1) wet, peak streamflow greater than 75th percentile; 

(2) average, peak streamflow between 50–75th percentile; 

or (3) dry, peak streamflow less than 25th percentile. Comparisons were made between differing annual cycles (1-year 

periods) and between multi-year cycles (1-year periods 

following specific multi-year periods). Comparison of the 

relation between natural logarithm of streamflow and the 

natural logarthim of SS concentration was done between 

(1) wet and dry years, (2) wet years and wet years following two or more dry years, and (3) dry years and dry years 

following two or more wet years. This analysis was designed 

to identify antecedent conditions that produced discernable 

changes in the slope and intercept of the streamflow sediment-transport relation. Separation of the data into the rising 

and falling limbs of the snowmelt hydrograph was done to 

account for seasonal differences. ANalysis of COVAriance 

(ANCOVA) was used to test for significant differences in the 

slope and intercept of the relation between natural logarithm 

of streamflow and the natural logarthim of SS concentration 

for each station by using R statistical software (R Development Core Team, 2008). 

Two-Dimensional Streamflow and SedimentTransport Model

The Multi-Dimensional Surface-Water Modeling System (MD_SWMS) was used to model various streamflows 

for a study reach on the Green River near Jensen, Utah. 

MD_SWMS is a graphical user interface that was developed 

by the USGS (McDonald and others, 2001). The FaSTMECH computational model within MD_SWMS was used 

to simulate water-surface elevation, boundary shear stress, 

velocity, and sediment transport (Nelson and McDonald, 

1997; Thompson and others, 1998; Lisle and others, 2000; 

Nelson and others, 2003). The sediment-transport model 

followed methods described by Yalin (1977) as defined in 

equations 9 and 10: 

a

aq

u d

a

cr

t

s cr

τ

τ γ

τ

τ

  − 























− = + −















∗ 

1

1 575

1 1

50

. ln 

























 (9)

and

a

u

d

s

s

= 





















 ( ) −

∗ 2 45

2

50

. γ

γ

ρ

γ γ (10)

where

ln is the natural logarithm function;

t is the boundary shear stress, in pascal,

tcr is the critical shear stress of the d50, in pascal,

a is an intermediate variable,

qt is the bed-material load transport rate per unit 

width, in newtons per meter-second,

γs is the specific weight of sediment, in newtons 

per cubic meter,

γ is the specific weight of water, in newtons per 

cubic meter,

u* is the shear velocity, in meter per second,

d50 is the median sediment particle diameter of 

the bed material, in meters, and

ρ is the mass density of water, in kilograms per 

cubic meter.

Equation 9 can be converted from metric units (newtons per 

meter-second or pascals) to English units (pounds per footsecond) by multiplying qt 

by 0.06853.

The dataset requirements of the model include channel geometry, streamflow at the upstream end of the study 

reach, and water-surface elevation at the downstream end of 

the study reach. Velocity information also was used to verify 

model results following calibration of the model. The FaSTMECH model uses a curvilinear orthogonal grid with a userdefined centerline, which approximates the path of streamflow 

for the modeled reach. User-defined parameters are calculated 

for each node of the grid. Additional information on the 

interface and the model can be found in McDonald and others 

(2001) and Nelson and others (2003). 

The majority of the data collected to calibrate the twodimensional model were collected when the Green River 

streamflow was 9,000 ft3

/s. For that streamflow, there are 

110 measured water-surface elevations and 101 measurements 

of average velocity. For each of the other streamflows (10,600; 

14,100; 17,700; and 19,000 ft3/s), there are two measurements 

of water-surface elevation and no velocity measurements. 

Therefore, model calibration was performed most rigorously 

for the 9,000 ft3/s model (discussed in the “Two-Dimensional 

Streamflow and Sediment-Transport Model Calibration and 

Sensitivity Analysis” section).

In and near the channel, topographic and bathymetric 

data were collected using RTK-GPS in conjunction with a 

boat-mounted Acoustic Doppler Current Profiler (ADCP) and 

an echo sounder. The methodology is explained in further 

detail in Williams and others (2009). Topographic data needed 

to define channel-geometry were collected on May 8–12, 
Figure 5. Map showing bed-material sampling location in the study reach on the Gunnison River near Delta, Colorado.

108°04'50" 108°04'40" 

38°

45'

20"

38°

45'

10"

09144250

Delta-1

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)Universal Transverse Mercator North American Datum 1983, Zone 12 North

EXPLANATION

Streamflow-gaging station and number

Flow direction

Bed-material sample location and identification

09152500 !

Delta-1

0 0.05 0.1 KILOMETER0 0.05 0.1 MILE

!
16 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

2006, for a 1.5-mi reach of the Green River. These data were 

combined with existing LiDAR data (Bowen and others, 2001) 

to characterize the reach geometry. 

Interpolation between measured data points was done 

using two separate processes, in conjunction, to obtain the 

most accurate representation of the channel geometry for the 

study reach (see also, Barton and others, 2005). The template 

algorithm was used first, and then the Triangular Irregular Network (TIN) method was used to develop the final topographic 

surface. The template algorithm follows a method similar to a 

nearest neighbor search in which elevation values are interpolated based on comparisons to a selection of data points 

within a rectangular bin, which is oriented so that it is longest 

in the stream-wise direction (parallel to the stream channels). 

This approach leverages an observation that topographic data 

within a stream reach tend to be more strongly correlated over 

longer distances in the stream-wise direction (parallel to the 

general flow direction) than in the cross-stream direction. To 

optimize this observed relation between elevation data within 

a stream reach, the measured data for the study reach were 

initially divided into five subreaches. For each subreach the 

measured elevations were mapped to a 16 ft nominal grid. The 

resulting topography from the five subreaches were combined 

with the original measured data to form a densely spaced set 

of topographic data from which a final dataset for channel 

geometry was created using the TIN method. The final computational grid was approximately 9,842-ft (3,000-m) long and 

1,148-ft (350-m) wide with 601 stream-wise points, or nodes, 

and 71 cross-stream points, approximating a 16.4- by 16.4-ft 

grid area (5.0- by 5.0-m) (fig. 6). 

The other data requirements for the model are streamflow 

at the upstream boundary of the reach and the corresponding 

water-surface elevation at the downstream boundary of the 

reach. Instantaneous streamflows were obtained from USGS 

NWIS (http://waterdata.usgs.gov/ut/nwis/). The Green River 

near Jensen, Utah, 09261000, streamflow-gaging station was 

used for streamflow data within the study reach. 

Water-surface elevations were measured by using 

pressure transducers and RTK-GPS surveys for a range of 

streamflows. Water-surface elevations are used as the downstream-boundary condition for the model and for calibrating 

the model results in the remainder of the channel. During the 

survey and bathymetry mapping data collection, water-surface 

elevations were surveyed using the RTK-GPS (mentioned 

previously in the “Topographical Surveying” section) and 

described in further detail in Williams and others (2009). 

Those water-surface elevations were used to calibrate the 

model parameters for a streamflow of 9,000 ft3

/s at the gage 

upstream on the day that corresponded with the measurement 

of the elevations. Water-surface elevations also were measured for a range of streamflows (1,200–19,000 ft3

/s) through 

the deployment of temporary water-surface elevation gages 

(pressure transducers) located at two strategic locations (fig. 7) 

within the study reach during May 16–July 27, 2006. The 

pressure transducers were surveyed using the RTK-GPS to 

facilitate the calculation of water-surface elevations. 

Water-velocity data were collected at the 9,000 ft3

/s 

streamflow and were used for model calibration and verification. An ADCP was used to collect stream-velocity data at 

cross sections at important streamflow locations (fig. 7). At 

each location, 10 traverses were completed consecutively to 

represent the temporal and depth-averaged velocity along the 

cross section. Comparisons of the modeled velocities to the 

measured velocities were done to evaluate model accuracy 

for velocity data and are discussed in the “Two-Dimensional 

Streamflow and Sediment-Transport Model Calibration and 

Sensitivity Analysis” section.

The model uses a parameter referred to as “lateral eddy 

viscosity” to represent the lateral-momentum exchange owing 

to turbulence or other variability that is not generated by the 

bed (Nelson and others, 2003). The parameter was computed 

for each model by multiplying the average velocity and the 

average depth of the best-fit model by the lateral-eddy coefficient, which was assigned a value of 0.01 (Nelson and others, 

2003; Barton and others, 2005). Drag coefficients ranged from 

0.0078 for the modeled streamflow of 9,000 ft3

/s down to 

0.004 for the highest modeled streamflow of 19,000 ft3/s. 

Incipient Motion of Streambed Materials

Incipient motion of particles in gravel-bed streams is 

an important component of sediment transport. This process 

determines the relative grain stability and is the most important component of sediment transport relative to channel form 

adjustment (Knighton, 1998). In general, sediment transport occurs within a stream when the boundary shear stress 

exceeds the critical shear stress of the particle (Julien, 2010). 

In order to determine the precise conditions that will result in 

the initiation of motion for more than one particle of interest, 

reasonable generalizations of the particle shape, orientation, 

submerged weight, and protrusion into flow must be assessed. 

Analysis of each particle within a stream is unfeasible so 

instead particle movement is characterized for groups of particles classified by size distribution. Sediment entrainment in a 

streambed is a function of the boundary shear stress acting on 

sediment particles resting on or in the streambed or other inundated alluvial surfaces where boundary refers to the boundary between the channel bed and the water. Mean boundary 

shear stress in a channel cross section is approximated by the 

DuBoys’ equation (Chow, 1959):

τ γ o = hS (11)

where 

to is the mean boundary shear stress, in pounds 

per square foot;

γ is the specific weight of water (62.4 pounds 

per cubic foot);

h is the mean flow depth, in feet; and

S is the energy gradient for a specific 

streamflow, in feet per foot. 
Figure 6. Map showing a Multi-Dimensional Surface-Water Modeling System (MD_SWMS) grid, 5 miles downstream from the Green River nestreamflow-gaging station (see figure 4).

109°17' 109°16'

40°24'30"

40°24'

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)Universal Transverse Mercator North American Datum 1983, Zone 13 NorthScale 1:12,000

EXPLANATION

Flow direction

Multi-Dimensional Surface-Water Modeling System (MD_SWMS) grid 

0 0.25 0 
109°17'

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)Universal Transverse Mercator North American Datum 1983, Zone 13 NorthScale 1:10,000

40°24'

40°24'30"

0 0.2 0.4 KILOMETER0 0.2 0.4 MILE

!

EXPLANATION

Acoustic Doppler Current Profiler (ADCP) cross-section locations

! Temporary water-surface e

Flow direction

!
Methods of Data Collection and Analysis 19

The assumptions behind this equation include (1) the 

channel cross section has a regular, trapezoidal shape and 

that the width of the channel is at least 10 times the depth; 

(2) streamflow is steady or that there is a continuity of streamflow from one cross section to the next; and (3) streamflow 

is uniform or that velocity is constant in both magnitude and 

direction for the reach. In this study, the cross-section shapes 

were not trapezoidal though the widths of the cross sections 

were at least 10 times the mean flow depths at the smallest 

streamflow. Streamflow was assumed to be steady as there 

were no inflows into the study reaches, and exchange between 

surface water and groundwater were assumed to be negligible. 

Most natural streams do not satisfy all of the assumptions 

for equation 11, and the resulting boundary shear stress for a 

cross section is nonuniformly distributed across the channel. 

Additionally, in natural systems, lateral and downstream variations in cross-section morphology, flow depth, bedform and 

particle drag, and variations in energy gradient with streamflow result in a wide range of boundary shear stresses that are 

nonuniformly distributed across the channel (Graf, 1971). To 

rectify the violations of the assumptions made in equation 11, 

point depths along the cross sections were substituted for the 

cross-section mean flow depth to examine the relative effects 

on the boundary shear-stress distribution of different streamflows along multiple cross sections within a study reach. 

For areas where the calibrated two-dimensional streamflow and sediment-transport model was available, FaSTMECH 

was used to calculate boundary shear stress using the following equation (Barton and others, 2005): 

τ ρ

b

Cd u v

k = ( ) +2 2

(12)

where

tb is the boundary shear stress, in pounds per 

square foot;

ρ is the fluid density, in kilograms per cubic 

meter;

Cd is the non-dimensional drag coefficient;

u is the vertically averaged stream-wise 

velocity, in meters per second; 

v is the vertically averaged cross-stream 

velocity, in meters per second; and

k is a conversion factor, 47.88.

The critical shear stress (τ c ) for a particle is the minimum shear stress needed for general movement of the particle 

to begin. Sediment-particle size, density, shape, and sorting 

affect transport and have been related to sediment-particle-size 

characteristics (Shields, 1936; Lane, 1955; Fahnestock, 1963; 

Carling, 1983; Komar, 1987; Wilcock, 1992). Critical shear 

stress for entrainment of the sediment d50 particle was calculated using the Shields (1936) equation to estimate when many 

of the particles along the streambed within the reach would 

begin movement: 

τ τ γ γ c c s = − d *( ) 50 (13)

where

tc is the critical shear stress, in pounds per 

square foot; 

tc

* is the dimensionless critical shear stress or 

Shields parameter;

γs is the specific weight of sediment (165.5 

pounds per cubic foot);

γ is the specific weight of water (62.4 pounds 

per cubic foot); and

d50 is the median sediment-particle size, in feet.

Two critical shear stress values were selected for the 

incipient-motion analyses in this study. One critical shear 

stress value was computed with a dimensionless critical shear 

stress, or Shields (1936) parameter of 0.035, and the second critical shear stress value was computed with a Shields 

parameter of 0.050. The dimensionless critical shear stress and 

critical shear stress values have been experimentally determined for streambeds ranging in sediment-particle size from 

silt to boulders (Julien, 1998). The dimensionless critical shear 

stress values range from 0.054 for boulders to 0.033 for coarse 

sand and to 0.25 for medium silt (Julien, 1998). The channel beds in the rivers included in this study are composed of 

mixed sediment ranging from fine sands to cobbles up to 6 in. 

in diameter. The cobbles form a subsurface pavement layer 

that often is covered in a layer of sand. In channels where the 

channel bed is tightly structured or where the particles are 

strongly imbricated, the dimensionless critical shear stress was 

found to range from 0.055 to 0.065; in loosely structured beds 

the dimensionless critical shear stress is as low as 0.0096 to 

0.011 (Parker and others, 1982; Andrews, 1983; Komar, 1987; 

Powell and Ashworth, 1995). Shields parameter values of 

0.035 and 0.050 result in a range of possible hydraulic conditions at which incipient motion or sediment entrainment may 

begin in the study reaches. Incipient motion estimated with a 

Shields parameter value of 0.035 resulted in estimates of the 

critical shear stress, and therefore of the streamflow, necessary 

to entrain sediment of the d50 particle size on the streambed. 

Conversely, a Shields parameter value of 0.050 resulted in 

a more conservative estimate of the critical shear stress and 

streamflow necessary to entrain the same-size sediment.

In natural river systems, the portion of the boundary 

shear stress available to move sediment grains can be referred 

to as the “grain shear stress” (Julien, 2010). In wide, straight 

streams the boundary shear stress calculated using equations 

11 and 12 is equal to the grain shear stress. In other instances, 

the boundary shear stress estimates for the system include 

Figure 7 (previous page). Map showing temporary watersurface elevation gages and Acoustic Doppler Current Profiler 

(ADCP) cross-sections locations, 5 miles downstream from the 

Green River near Jensen, Utah, streamflow-gaging station.
20 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

energy that is unavailable for sediment transport owing to 

additional energy losses within the stream. These losses can be 

the result of turbulent eddy formation and bedforms. In sandbed streams, bedforms such as ripples, dunes, and anti-dunes 

are common causes for these energy losses. In gravel-bed 

streams, these losses can arise from channel expansions and 

contractions, alluvial bars, and meander bends. Study reaches 

presented in this report were located where these secondary 

losses were expected to be minimal. 

Comparisons of boundary shear stress and grain shear 

stress were made using two methods. For gravel reaches, estimates of grain shear stress were obtained following methods 

described in Wilcock and others (2009) and represented by 

equations 14–16: 

t

t

o

o

D n

n

' /

= 























3 2

(14)

nD = 0.013D1/6 (15)

n

Q

wh S = f

f 5 3/ /1 2 (16)

where

t

' is the grain shear stress, in pounds per square 

foot; 

t is the boundary shear stress, in pounds per 

square foot;

nD is the Manning coefficient of roughness 

attributed to grain roughness;

n is the Manning coefficient of roughness of the 

cross section;

D is two times the d65 sediment-particle size, in 

millimeters;

φ is a conversion factor, 1.486;

Ԛ is streamflow, in cubic feet per second;

w is the channel width, in feet;

h is the mean flow depth, in feet; and

Sf is the energy gradient for a specific 

streamflow, in feet per foot.

For sand-bed reaches, estimates of grain shear stress were 

obtained following methods described in Julien (2010) and 

represented by equations 17 and 18:

t∗ ≈ 





















 ( ) −































' .

/

0 04

1

50

50

1 3 2 d

h

V

g G d

(17)

τ τ γ γ '

'

= ∗ ( ) s − d

k

50 (18)

where

t*

' is the grain shear stress, dimensionless; 

d50 is median sediment-particle size, in meters;

h is the average flow depth, in meters;

G is the specific gravity of sediment, 2.65 

(dimensionless);

V is the average flow velocity, in meters per 

second;

g is the gravitation constant, 9.81 meters per 

square second;

t' is the grain shear stress, in pounds per square 

foot;

γs is the specific weight of sediment, 165.5 

pounds per cubic foot ; 

γ is the specific weight of water, 62.4 pounds 

per cubic foot; and

k is a conversion factor, 0.3048.

For reaches where differences between boundary and 

grain shear stress exceeded 2 percent, grain shear stress calculated from equations 14 or 18 was used to assess incipientmotion potentials for a range of streamflows at each cross section. Grain shear stress along intervals within the cross section 

were scaled by the proportion of grain shear stress to the bed 

shear stress of each cross section.

The boundary shear stresses were compared to the 

critical shear stresses for sediment in the channel to evaluate 

sediment-entrainment potential of each streamflow. Sedimententrainment potential at each cross section associated with 

the reference streamflows was expressed as the ratio of the 

shear stress (τ) to the critical shear stress for the median 

sediment-particle size at the cross section (τ c). The τ/τ c ratio 

(sediment-entrainment ratio) integrates several geomorphic 

and sediment variables (flow depth, energy gradient or watersurface slope, median sediment-particle size, and critical shear 

stress) and is applicable over a wide range of values (Elliott 

and Hammack, 1999, 2000). The sediment entrainment ratio 

also was calculated for each point along a cross section to 

evaluate incipient motion of sediment on different geomorphic 

surfaces traversed by the cross section. 

The critical shear stress should be considered the minimum value for incipient motion of the d50 particle because 

at that critical shear stress only a small fraction of the sediment of the d50 size class will be entrained (Milhous, 1982). 

Complete mobilization of the d50 size class has been shown 

to occur at roughly twice the value for incipient motion of the 

individual sediment particles of that size class (Wilcock and 

McArdell, 1993). Critical streamflow, or the minimum streamflow required to entrain the sediment d50, can be estimated by 

equating τ with τ c and using the relation between boundary or 

grain shear stress and streamflow at a specific cross section.

Rouse Number and Sediment-Transport Mode

The ratio of settling forces to suspension forces, Rouse 

number, can be used to determine the mode of sediment 

transport (bed load, suspended load, or wash load) within a 

stream reach (Julien, 2010). Values greater than one represent 
Effects of Streamflow on Sediment Transport 21

Rouse number:

R

W

ku

s =

* 

and u* = τ

ρ

(19 and 20)

where

R is the Rouse number, dimensionless;

Ws is the settling velocity of the sediment 

particle, in meters per second;

k is the Von Karman’s constant, 0.4;

u* is the shear velocity of the stream, in meters 

per second;

τ is the boundary shear stress, in pascals;

ρ is the density of the water in the stream, 

999.58 kilograms per square meter at 

12 degrees Celsius.

Two-Dimensional Streamflow and 

Sediment-Transport Model Calibration 

and Sensitivity Analysis

The two-dimensional model was first calibrated based on 

continuity of mass. Calibration was achieved when the rootmean squared value for streamflow was less than 6 percent 

from the nominal streamflow achieved in each model scenario. 

In each scenario, adjustments were made to the roughness 

value, as described by the drag-coefficient parameter, until 

model-predicted water-surface elevations and velocities (when 

available) acceptably matched those measured in the field 

(fig. 8). Water-surface elevations from the best-fit models were 

within 0.12 ft of measured water-surface elevations for all 

models except the model for the 9,000 ft3/s streamflow. For the 

9,000 ft3/s model, there were more data to compare, and the 

maximum difference was 0.39 ft. Generally, the larger differences between predicted and measured water-surface elevations for this model occurred in the middle of the study reach 

whereas the upstream and downstream boundaries had smaller 

differences, closer to 0.10 ft or less (fig. 8). For the other modeled streamflows, there were only data at the upstream and 

downstream boundaries. The velocity data from the ADCP 

measurements along the five transects were plotted against the 

modeled velocity at each of the five cross sections to ensure 

that the modeled velocities were within the range of observed 

values. Additional comparisons of measured velocities at 

selected cross sections to model output show general agreement in magnitude and distribution; however, high velocities 

at some locations were under predicted (fig. 8). 

Sensitivity of the lateral eddy viscosity and drag coefficient were evaluated by individually adjusting each parameter 

by plus or minus 25 percent relative to the calibrated value 

(tables 3 and 4). Differences relative to the mean were less 

than 1 percent for all models except the 10,600 ft3/s model. In 

that model, decreasing the lateral eddy viscosity by 25 percent 

resulted in a difference of 11.25 percent in mean velocity and 

16.91 percent in mean boundary shear stress. The model was 

more sensitive to adjustments of the drag coefficient parameter. Varying the drag coefficient by plus or minus 25 percent 

resulted in differences in the mean water-surface elevation of 

5 percent or less of mean depth. Differences in mean velocities 

were 1.8 percent of mean velocity or less, and differences in 

boundary shear-stress values were up to 23 percent of the calibrated model boundary shear stress. The large percentages are 

a reflection of the small values of mean boundary shear stress. 

Effects of Streamflow on Sediment 

Transport

Sediment transport can be conceptualized as the interaction of transport capacity and sediment supply for a given 

streamflow condition (depicted in fig. 9). Transport capacity 

refers to the ability of the stream to move sediment particles 

and is a function of hydraulic variables and the shape of the 

stream cross section; whereas, sediment supply is determined 

by the availability of the materials in the stream and can be a 

function of both in-stream processes and overland processes 

within the basin (Julien, 2010). 

In figure 9, the areas located below both of the curves 

represent the sediment transported within the stream at a fixed 

streamflow condition. The brown-shaded area to the left of 

the d10 represents conditions where sediment transport occurs 

in suspension and is limited by the availability of sediment 

delivered to the stream or found within the streambed (wash 

Table 2. Mode of sediment transport based on Rouse number 

(modified after Julien, 2010).

[>, greater than; %, percent; <, less than]

Rouse number Sediment-transport mode

>5.0 Bed load

2–5.0 <50% suspended, >50% bed load

0.5–1.99 >50% suspended, <50% bed load

<0.5 Suspended load

stream conditions where sediment particles are exposed to 

greater settling forces than suspension forces and will tend to 

bounce along the streambed as bed load. Rouse numbers less 

than one relate to stream conditions where sediment particles 

are exposed to greater suspension forces than settling forces 

and will tend to travel within the water column as suspended 

load. Wash load occurs when the sediment is transported in 

suspension without interaction with the streambed. Comparisons of the Rouse numbers to these definitions will be used to 

determine the primary mode of sediment transport within this 

report and are summarized in table 2.
22 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

0

4,747.5

4,748.0

4,748.5

4,749.0

4,749.5

4,750.0

4,750.5

4,751.0

4,751.5

4,752.0

4,752.5

4,753.0

4,753.5

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

Water-surface elevation, in feet

A

Vertically averaged velocity, in feet per second

B

2

4

6

8

10

12

14

16

18

20

Downstream distance, in feet

0

EXPLANATION

Measured

Predicted

EXPLANATION

Measured

Predicted

Figure 8. Graph showing A, water-surface elevations and B, mean velocities for the best-fit model for the 9,000 cubic 

feet per second streamflow.
Effects of Streamflow on Sediment Transport 23

Table 3. Lateral eddy viscosity sensitivity analysis and results for the five streamflows simulated in the two-dimensional streamflow 

and sediment-transport model for the Green River near Jensen, Utah, study reach.

[Sensitivity analyses of calibrated lateral eddy viscosity were made at 75 (indicated in bold) and 125 (indicated in italics) percent of the lateral eddy viscosity 

value. The mean values are based on non-zero values in the model. Percent differences are relative to the mean of the calibrated model and percent difference in 

water-surface elevation is relative to the mean depth; ft3/s, cubic foot per second; ft, foot; ft/s, foot per second; lb/ft2, pound per square foot; --, not applicable]

Streamflow 

(ft3

/s)

Lateral eddy 

viscosity 

value (ft3

/s)

Model output Percent difference from the mean

Mean depth 

(ft )

Mean watersurface 

elevation (ft)

Mean velocity 

(ft/s)

Mean shear 

stress 

(lb/ft2

)

Watersurface 

elevation

Velocity Shear stress

9,000 0.00780 5.69 4,750.00 3.17 0.17 -- -- --

9,000 .00585 5.69 4,750.00 3.15 .17 –0.18 –0.35 –0.64

9,000 .00975 5.68 4,749.99 3.16 .17 .07 –.63 –1.10

10,600 .00550 6.11 4,750.35 3.42 .14 -- -- --

10,600 .00413 6.12 4,750.36 3.41 .14 –.87 –11.25 –16.91

10,600 .00688 6.08 4,750.30 3.03 .12 .20 –.32 –.49

14,100 .00450 7.08 4,751.53 3.92 .15 -- -- --

14,100 .00338 7.10 4,751.55 3.89 .15 –.14 .27 .53

14,100 .00563 7.07 4,751.52 3.93 .15 .37 –.58 –.94

17,700 .00470 8.04 4,752.75 4.11 .18 -- -- --

17,700 .00353 8.06 4,752.78 4.09 .17 –.20 .09 .28

17,700 .00570 8.02 4,752.74 4.11 .18 .30 –.34 –.62

19,000 .00400 8.27 4,753.01 4.28 .16 -- -- --

19,000 .00300 8.30 4,753.04 4.26 .16 –.15 –.31 –.32

19,000 .00480 8.26 4,753.00 4.27 .16 .35 –.45 –.83

Figure 4. Drag coefficient sensitivity analysis and results for the five streamflows simulated in the two-dimensional streamflow and 

sediment transport model for the Green River near Jensen, Utah, study reach.

[Sensitivity analyses of calibrated drag coefficient were made at 75 (indicated in bold) and 125 (indicated in italics) percent of the drag-coefficient value. 

Percent differences are relative to the mean of the calibrated model, and percent difference in water surface elevation is relative to the mean depth. The mean 

values are based on non-zero values in the model; ft3/s, cubic foot per second; ft, foot; ft/s, foot per second; lb/ft2, pound per square foot; --, not applicable]

Streamflow 

(ft3/s)

Dragcoefficient 

value

Model output Percent difference from the mean

Mean depth 

(ft )

Mean watersurface 

elevation (ft)

Mean velocity 

(ft/s)

Mean shear 

stress 

(lb/ft2

)

Watersurface 

elevation

Velocity Shear stress

9.000 0.0078 5.69 4,750.00 3.17 0.17 -- -- --

9.000 .0059 5.95 4,750.26 3.04 .19 –5.01 1.49 –16.70

9.000 .0098 5.41 4,749.71 3.22 .14 4.62 –4.31 13.18

10.600 .0055 6.11 4,750.35 3.42 .14 -- -- --

10.600 .0041 6.35 4,750.59 3.30 .16 –4.94 1.81 –20.18

10.600 .0069 5.82 4,750.05 3.48 .11 3.93 –3.52 15.02

14.100 .0045 7.08 4,751.53 3.92 .15 -- -- --

14.100 .0034 7.31 4,751.76 3.80 .17 –4.05 .91 –21.06

14.100 .0056 6.80 4,751.24 3.95 .12 3.35 –3.02 15.97

17.700 .0047 8.04 4,752.75 4.11 .18 -- -- --

17.700 .0035 8.29 4,753.00 4.00 .20 –4.38 –.06 –19.77

17.700 .0057 7.68 4,752.39 4.09 .14 3.08 –2.34 13.63

19.000 .0040 8.27 4,753.01 4.28 .16 -- -- --

19.000 .0030 8.48 4,753.23 4.19 .18 –3.92 –.39 –-22.52

19.000 .0048 7.95 4,752.69 4.26 .13 2.57 –2.22 13.20
24 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 9. Graph showing conceptual diagram of sediment transport with 

suspended-sediment load indicated by diagonal hachuring.

Supply limited

Sediment supply

Transport capacity

Graphic modified from Julien, 2010.

For a fixed streamflow condition

Transport capacity and sediment supply 

Bed-material load

Sediment-particle size, where d10 is the 10th percentile of the

cummulative sediment-particle size distribution of the bed material

d10

Bed material

Capacity limited

Wash load

Sediment transport

Suspended load (represented by hatchures) Wash load

Suspended

Bed-material load Bed load

(increasing )

load); the yellow-shaded area to the right of the d10 and below 

the transport-capacity curve represents conditions where capacity limitations dominate (bed-material load). The green-shaded 

area to the left of the d10 and above the transport-capacity curve 

represents the sediment-particle sizes and relative abundances 

within the streambed (bed material). Bed-material load can 

be further separated by mode of sediment motion as (1) bed 

load, a thin layer along the streambed; and (2) suspended load, 

within the water column. For sand-sized particles, both bedand suspended-load transport can occur simultaniously.

Sediment transport can be separated into bed-material 

load and wash load based on the sediment-particle-size distribution of the streambed (fig. 9). Bed-material load represents 

transport of sediment-particle sizes found in appreciable quantities within the size distribution of the bed material and relates 

to interaction between the bed and the transported material. 

The sediment-particle sizes of the wash load are not found 

in appreciable quantities within the streambed and represent 

transient deposition that has negligible effects on the streambed morphology over longer time periods (months to a year). 

The 10th percentile of the bed-material sediment-particle-size 

distribution (d10) often is designated as the threshold between 

bed-material load and wash load (wash-load sediment-particle 

sizes < d10 < bed-material load sediment-particle sizes) (Julien, 

2010). Separation of the components of sediment transport 

(bed-material load and wash load) can be useful when evaluating what factors relate to channel morphology and aquatic 

habitat within the stream. 

Within this report, incipient-motion analysis is used 

to characterize transport initiation of the bed-material load. 

Bed-material load is capacity limited and as such, transport 

conditions can be evaluated as a function of the forces acting 

on particles within the stream, providing a direct link between 

streamflow management and sediment-transport conditions.

Within this report, regression analysis is used to characterize the suspended-sediment load within the system (Cohn, 

2005; Dalby, 2006; Runkel and others, 2004). Complications arise from concurrent transport of both wash load and 

the suspended fraction of the bed-material load within the 

suspended-sediment load. Wash load is limited by sediment 

supply and is controlled by a range of in-channel and out-ofchannel processes that may not be directly related to streamflow conditions. As such, characterization of the suspendedsediment load within these systems must be empirically 

derived (SS flux and SS concentration transport equations) 

from observed conditions within the system. Separation of 

wash load from the suspended fraction of the bed-material 

load is done based on available sediment-particle-size information. In the following discussion, a distinction will be 

made between sediments that range from 0.0625 to 2.0 mm 

(sand SS flux) in diameter from SS flux, as warranted. Interpretations of the variables used within the regression analysis 

will aid in identification and quantification of the processes 

or mechanisms that are important controls on suspendedsediment transport within the system and to provide information on the timing of sediment inputs (supply changes).
Effects of Streamflow on Sediment Transport 25

Suspended-Sediment Transport Equations

Suspended-sediment transport equations were generated for the six stations that had sufficient data within the 

study area: (1) USGS streamflow-gaging station, 09095500, 

Colorado River near Cameo, Colorado, 1982–98, (hereafter, CAMEO); (2) USGS streamflow-gaging station, 

09163500, Colorado River near the Colorado–Utah State line, 

1976–2007 (hereafter, STATELINE); (3) USGS streamflowgaging station, 09180500, Colorado River near Cisco, Utah, 

1967–2000 (hereafter, CISCO); (4) USGS streamflow-gaging 

station, 09152500, the Gunnison River near Grand Junction, 

Colorado, 1976–2007 (hereafter, GUNNISON); (5) USGS 

streamflow-gaging station, 09261000, Green River near 

Jensen, Utah, 1965–2007 (hereafter, JENSEN); and (6) USGS 

streamflow-gaging station, 09315000, Green River at Green 

River, Utah, 1965–2000 (hereafter, GREEN) (table 5). 

Regression analysis using multiple explanatory variables can 

provide a means to assess the relative importance of differing 

variables and allows a single regression equation to be used 

to evaluate the entire dataset. Sediment-transport equations 

can be used to assess the persistence of temporal trends 

(between-year variations) and to quantify the seasonal variation (within-year variations) in sediment transport that may be 

important to future water management.

Comparisons of the calibration dataset to suspendedsediment-transport equation predictions (equation fit) are 

shown in figures 10–13 as scatterplots depicting the relations 

between streamflow and SS concentration or sand SS concentration (sand SS). This representation simplifies the depiction 

of the transport equation by excluding explicit representation 

of seasonality and temporal trends that would necessitate 

additional axes or the use of an axis that is the mathematical combination of all explanatory variables. Figures 10–13 

simplify the regression equations to a two-dimensional space, 

which aids understanding and interpretation; however, this 

representation requires incorporation of multiple data series 

within the graphs to accurately depict the equation fit. To 

account for seasonality, figures 10 and 12 present regression 

predictions for each day of the year derived from artificial 

hydrographs (produced from daily mean streamflow record) 

representing three hydrologic conditions: (1) a dry year, 5th 

percentile of the daily mean streamflow; (2) an average year, 

mean of the daily mean streamflow; and (3) a wet year, 95thpercentile of the daily mean streamflow. Similarly, to account 

for limitations in depictions of temporal trends, figures 11 and 

13 are used to present regression predictions for each day of 

the year given the average-year artificial hydrograph at three 

intervals within the transport-equation time period (where 

time trends were characterized as statistically significant): (1) 

early year, beginning of time period; (2) middle year, middle 

of time period or year of minimum trend value; and (3) late 

year, end of time period. 

The variables that were found to have a significant statistical relation to natural logarithm SS flux (and natural logarithm SS concentration) were typically consistent along river 

reaches and are shown in table 5. Based on the coefficient of 

determination (adjusted R2

 values) from manipulated forms 

of these equations, approximately 75 percent of the variability 

of the sampled natural logarithm SS flux at these stations can 

be explained by a combination of streamflow, seasonality, 

and temporal trends (approximately 80 percent for natural 

logarithm sand SS flux). Use of an adjusted R2 value prevents 

over estimation of the variance explained within the regression 

equation so that the addition of explanatory variables does 

not artificially inflate the perceived explanatory power of the 

regression (Helsel and Hirsch, 2002). 

Comparisons of the adjusted R2 for manipulated forms 

of the natural logarithm SS concentration equations show 

that approximately 49–60 percent of the variability of the 

sampled natural logarithm SS concentration is explained by a 

combination of streamflow, seasonality, and temporal trends 

(approximately 57–87 percent for natural logarithm sand SS 

concentration) (fig. 14). For each station, the linear or quadratic relation with natural logarithm streamflow (Q, Q2

, and 

β0, in table 5) explained 26–40 percent of the observed variability in natural logarithm SS concentration (39–72 percent 

for natural logarithm sand SS concentration); seasonality (time 

within the year) explained 13–16 percent of the observed variability in natural logarithm SS concentration (2.1–14 percent 

for natural logarithm sand SS concentration); and temporal 

trends (time over multiple years) explained 1.5–8.9 percent of 

the observed variability in natural logarithm SS concentration 

(0–6.2 percent for natural logarithm sand SS concentration).

Streamflow Effects on Suspended-Sediment 

Transport

Variation in seasonal streamflow source water and 

sediment supply can have a significant effect on the shape, 

slope, and intercept of the streamflow and sediment-transport 

relation (Glysson, 1987; Horowitz, 2003). This relation is 

dependent on the mobility and abundance of in-stream sediment supplies. When streambed sediments are immobile or 

sediment quantity is limited by out-of-channel sources, such 

as tributary input or streambank failure, the relation between 

streamflow and sediment transport may have greater variability or difference in shape. For a nonlinear fit of the data, 

quadratic natural logarithm streamflow (when statistically 

significant) helped define the natural logarithm SS concentration-streamflow relation as a portion of a parabola. To further 

explore the processes important to sediment transport, it is 

useful to relate each explanatory variable to the occurrences 

within the stream that result in suspension and transport of the 

sediment (forces) and the availability of the sediment to be 

transported (sediment supply). 

Streamflow quantity can be thought of as a surrogate 

for the forces within these streams. Within alluvial streams, 

increases in streamflow typically results in increased sediment 

transport. In general, this relation held true at each station. 

Natural logarithm streamflow explained 26–40 percent of the 

observed variability in natural logarithm SS concentration 
Table 5. Regression coefficients and equation properties for suspended-sediment transport at selected U.S. Geological Survey streamflow-gaging sColorado River Basin. [ β0, regression equation intercept; Ln, natural logarithm; K, positive integer used in seasonality variables; T, seasonal time; Q, centered streamflow; Q2, centered streamflow squ

streamflow; Sin, sine function; Cos, cosine function; t, centered decimal time in decimal years; t2, centered decimal time in decimal years, squared; t*, centering value for decima

variance; SCR, serial correlation of residual; R2, coefficient of determination (adjusted R2); N, number of data points; C, number of censored data points; SS, suspended-sedimen

(p-value <0.01); --, variables not used in the regression; #, not statistically significant (p-value >0.05); and Sand, sediments with diameters between 2.0–0.0625 millimeters] Seasonality variables Abbreviation β0 Ln streamflow Fourier series Dummy variables Decimal time 

Q Q2 Q* K 2πT, K = 1 K 2πT, K = 2 Rain event Rising limb t t2 t* ERV 

Sin Cos Sin Cos Ln SS flux Cameo 7.459* 2.087* -- 5,305 0.518* 0.215 0.297* –0.363* 1.077* 0.876* –0.047* -- 1,989.87 0.934 

Gunnison 6.165* 1.725* 0.245* 2,750 –.064# –.673* .031# –.275* .473* .670* -- 0.00465* 1,991.20 .748 

Stateline 7.857* 1.603* .168 7,710 .019# –.667* –.001# –.352* .730* .837* –.026* -- 1,991.02 .864 

Cisco 8.738* 1.892* –.252 8,306 –.179# –.582* .263 –.476* 1.148* .883* –.043* -- 1,984.42 1.182 

Jensen 7.761* 1.856* -- 5,178 .150# –.447* .224# –.701* .833* .549* –.023* .00187* 1,986.40 .983 

Green 9.500* 2.043* –.208 6,871 –.071# –.609* .182 –.515* -- -- –.040* -- 1,983.1 .94

Ln Sand SS flux Cameo 5.963* 2.313* -- 5,226 0.434* 0.0560# –0.094# –0.268* 0.408* 0.506* –0.029 -- 1,990.12 0.712 

Gunnison 4.875* 2.367* -- 2,797 .146# –.403* –.014# –.413* -- -- -- 0.00396* 1,994.33 .900 

Stateline 6.328* 2.016* -- 8,298 –.446* –.397* -- -- -- 1.302* –.038* .00453* 1,990.34 .936 

Cisco 6.729* 2.694* –0.392 7,869 .573* –.096# -- -- -- -- -- -- 1,988.05 1.852 

Jensen 5.822* 2.703* -- 4,407 1.030* .803* .585 .146# -- -- .054* -- 1,988.5 .710 

Green 7.261* 3.366* –.754* 6,575 -- -- -- -- –.968* -- -- -- 1,987.8 2.51

Ln SS concentration Cameo 4.797* 1.087* -- 5,305 0.518* 0.215 0.297* –0.363* 1.077* 0.876* –0.047* -- 1,989.87 0.934 

Gunnison 4.161* .725* 0.245* 2,750 –.064# –.673* .031# –.275* .473* .670* -- 0.00465* 1,991.20 .748 

Stateline 4.821* .603* .168 7,710 .019# –.667* –.001# –.352* .730* .837* –.026* -- 1,991.02 .864 

Cisco 5.627* .892* –.252 8,306 –.179# –.582* .263 –.476* 1.148* .883* –.043* -- 1,984.42 1.182 

Jensen 5.124* .856* -- 5,178 .150# –.447* .224# –.701* .833* .549* –.023* .00187* 1,986.40 .983 

Green 6.579* 1.040* –.208 6,871 –.071# –.609* .182 –.515* -- -- –.040* -- 1,983.1 .94

Ln Sand SS concentration Cameo 3.316* 1.313* -- 5,226 0.434* 0.0560# –0.094# –0.268* 0.408* 0.506* –0.029 -- 1,990.12 0.712 

Gunnison 2.854* 1.367* -- 2,797 .146# –.403* –.015# –.412* -- -- -- 0.00395* 1,994.33 .900 

Stateline 3.218* 1.016* -- 8,298 –.446* –.397* -- -- -- 1.302* –.038* .00453* 1,990.34 .936 

Cisco 3.673* 1.694* –0.393 7,869 .572* –.096# -- -- -- -- -- -- 1,988.05 1.852 

Jensen 3.342* 1.704* -- 4,407 1.039* .799* .588 .148# -- -- .054* -- 1,988.5 .706 

Green 4.384* 2.366* –.754* 6,575 -- -- -- -- –.968* -- -- -- 1,987.8 2.510 
Effects of Streamflow on Sediment Transport 27

Figure 10. Graphs showing calibration data with sediment-transport equation predictions for suspended-sediment concentration 

at three hydrologic conditions calculated as (1) dry year, 5th-percentile; (2) average year, mean; and (3) wet year, 95th-percentile of 

the daily mean streamflow record for each day. Suspended-sediment concentration, in milligrams per liter

1

1,000

100

10

10,000

1

1,000

100

10

10,000

1

1,000

100

10

10,000

Streamflow, in cubic feet per second

CAMEO

JENSEN GREEN

STATELINE CISCO

GUNNISON

Sediment-transport equation predictions

EXPLANATION

Dry year Wet year Average year

Calibration data

100 1,000 10,000 100 1,000 10,000
28 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 11. Graphs showing calibration data with sediment-transport equation predictions for suspended-sediment concentration 

at three time periods: (1) early year, beginning of sediment-transport equation period; (2) middle of sediment-transport equation 

period or year of minimum trend value; and (3) late year, end of sediment-transport equation period. Suspended-sediment concentration, in milligrams per liter

1

1,000

100

10

10,000

1

1,000

100

10

10,000

1

1,000

100

10

10,000

CAMEO

JENSEN GREEN

STATELINE CISCO

GUNNISON

100 1,000 10,000 100 1,000 10,000

2000

1965

1982

2007

1965

1992

2000

1967

1987

2006

1976

1989

2007

1976

1991

1998

1982

1990

Streamflow, in cubic feet per second

Sediment-transport equation predictions

EXPLANATION

Early year Middle year Late year

Calibration data
Effects of Streamflow on Sediment Transport 29

Figure 12. Graphs showing calibration data with sediment-transport equation predictions for the sand portion of the suspendedsediment concentration at three hydrologic conditions calculated as (1) dry year, 5th-percentile; (2) average year, mean; and (3) wet 

year, 95th-percentile of the daily mean streamflow record for each day. Sand portion of suspended-sediment concentration, in milligrams per liter

1

1,000

100

10

10,000

1

1,000

100

10

10,000

1

1,000

100

10

10,000

Streamflow, in cubic feet per second

CAMEO

JENSEN GREEN

STATELINE CISCO

GUNNISON

100 1,000 10,000 100 1,000 10,000

Sediment-transport equation predictions

EXPLANATION

Dry year Wet year Average year

Calibration data
30 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 13. Graphs showing calibration data with sediment-transport equation predictions for the sand portion of the suspendedsediment concentration at three time periods: (1) early year, beginning of sediment-transport equation period; (2) middle of 

sediment-transport equation period or year of minimum trend value; and (3) late year, end of sediment-transport equation period. Sand portion suspended-sediment concentration, in milligrams per liter

1

1,000

100

10

10,000

1

1,000

100

10

10,000

1

1,000

100

10

10,000

Streamflow, in cubic feet per second

CAMEO

JENSEN GREEN

STATELINE

GUNNISON

100 1,000 10,000 100 1,000 10,000

2007

1965

1992

2005

1977

1994

2007

1977

1996

1998

1982

1990

CISCO

No time trend

No time trend

Sediment-transport equation predictions

EXPLANATION

Early year Middle year Late year

Calibration data
Effects of Streamflow on Sediment Transport 31

Site abbreviation

EXPLANATION

61

50

39

53

72

56

5.2

5.6

14

4.4

9.4

2.1

0.4

4.7 6.2

5.7

0

10

20

30

40

50

60

70

80

90

100

36

38

40 33

26

30

16 13

15

15

15

12

1.5

8.5 2.7

6.6

8.5

8.9

0

10

20

30

40

50

60

70

Cameo Gunnison

Sand portion of natural logarithm suspended-sediment concentration regression

Natural logarithm suspended-sediment concentration regression

Coefficient of determination (adjusted R2

)

Stateline Cisco Jensen Green

Cameo Gunnison Stateline Cisco Jensen Green

Temporal trends

Seasonality

Natural-logarithm streamflow

Figure 14. Graphs showing comparison of the coefficient of determination (adjusted R2) for explanatory 

variables within the suspended-sediment-transport regression analysis at selected U.S. Geological Survey 

streamflow-gaging stations.
32 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

(39–72 percent for natural logarithm sand SS concentration); 

however, 60 percent or more of the variability in natural logarithm SS concentration is explained by variables other than 

streamflow or remains unexplained (28 percent or more for 

natural logarithm sand SS concentration). 

The streamflow relation to SS concentration inherently 

includes factors related to sediment supply when increases in 

streamflow include additions of sediment. Examples include 

intense snowmelt-runoff conditions or rain events that result 

in new sediment supplies to main-stem areas from tributaries, 

or initial inundation and transport of sediments from bars or 

overbank areas. Understanding the shape of the streamflow 

relation can provide information on how the rivers respond to 

changes in streamflow and if sediment supply is inherent in 

the relation (Asselman, 2000). The typical (median) relations 

between streamflow and SS concentration (and sand SS concentration) are shown in figure 15 for each station. 

The concavity (upward or downward) of the transport 

curve at a station relates how changes in streamflow relate 

to changes in SS concentration. Concave-downward SS 

concentration-transport equations may indicate that sediment 

supplies can become limited at larger streamflows (Horowitz, 2003) or relate to the effects of changes in the channel 

geometry as streamflow increases (for example, reductions 

in the rate-of-change of boundary shear stress as flow begins 

to transition into larger cross sections or out-of-bank areas 

may cause reduced slopes within the transport curve at larger 

streamflows). The streamflow and sediment-transport relation 

at CISCO and GREEN are the only stations with a concavedownward transport equation (fig. 15). The transport-curve 

shape for these stations, for both SS concentration and sand SS 

concentration, may indicate that sediment supplies are limited 

during larger streamflow events (because the reduction in 

transport occurs for both SS concentration and sand SS concentration, which is less likely to occur if the change is owing 

to out-of-bank flow).

Concave-upward transport equations may show that 

sediment transport is less restricted by streamflow forces at 

the lower end of the transport curve and are more strongly 

controlled by sediment supplies (Horowitz, 2003). The 

STATELINE and GUNNISON stations have concaveupward relations for SS concentration with linear relations 

at the remaining stations. The transport-curve shape at 

STATELINE and GUNNISON may result from sediment 

inputs derived from rain events, agriculture, or other processes that produce increases in SS concentration without 

substantial increases in main-channel streamflows during 

base-flow conditions.

Seasonal and Temporal Effects on SuspendedSediment Transport

Depictions of the typical annual cycle for each station 

were done to evaluate changes within the sediment-transport relation with streamflow. Figure 16 shows the annual 

cycle of SS concentration derived from each transport 

equation for an average year (artificial hydrograph produced from mean of daily mean streamflow record, shown 

as inset on each graph). Examination of the chronological 

sequences within the plots shows that the SS concentration for a given flow is seasonally dependent; that is, for 

a specific streamflow there can be multiple predicted SS 

concentrations depending on time of year. Seasonal differences in the relation between streamflow and SS concentration (hysteresis) are evident in the differences in the 

slopes and shapes of each plot when compared between 

stations or between SS concentration and sand SS concentration. Hysteresis can result from differences in source 

waters (tributary contributions) or sediment sources within 

the basin and may be owing to differing processes or sediment availability within the watershed (Cohn and others, 

1992; Asselman, 2000; Horowitz, 2003). To increase sediment transport, sediments of the correct size class must be 

available. Sediment supply is not limited to a single-source 

area or process, and these processes can vary within the 

system and through time (seasonally and over multiple 

years). First-flush events from early snowmelt, rainstorm 

runoff, and intermittent streamflows from ephemeral 

streams typically are characterized with high SS concentration relative to streamflow (Curtis and others, 2005; 

Williams and others, 2009). Conversely, late-season runoff 

from snowmelt and base-flow conditions typically are 

characterized by reduced SS concentration. Both observations are related to sediment-supply conditions within the 

system instead of the forces within the stream and can be 

observed through comparison in SS concentration and sand 

SS concentration in figure 16.

Seasonality will account for consistent changes in the 

availability of sediments that are not as well represented 

by changes in streamflow alone. Seasonality coefficients, 

including the Fourier series and dummy variables (rain 

events and rising-limb of the hydrograph), explain approximately 15 percent of the variability in natural logarithm SS 

concentration at each station (fig. 14). Within the seasonality grouping, the variables that represent the rain events 

and the rising-limb of the hydrograph were significant at all 

stations except the GREEN station for natural logarithm SS 

concentration. These variables augment the Fourier series 

and better represent more abrupt seasonal changes, as well 

as variations that occur in less consistent patterns. Augmentation of the Fourier series during rain events was most 

significant at CAMEO, CISCO, JENSEN, and STATELINE 

(4.8, 4.3, 2.6, and 2.5 percent of the variability in natural 

logarithm SS concentration, respectively); with less of the 

variability in natural logarithm SS concentration being 

explained at GUNNISON and GREEN (1.4 and 0 percent 

of the variability in natural logarithm SS concentration, 

respectively) (fig. 14). Augmentation of the Fourier series 

during the rising-limb of the hydrograph was most significant at STATELINE, CAMEO, CISCO, and GUNNISON 

(2.9, 2.4, 2.1, and 1.9 percent of the variability in natural 

logarithm SS concentration, respectively); with less of the 
Effects of Streamflow on Sediment Transport 33

Median suspended-sediment concentration, in milligrams per liter

1

1,000

100

10

10,000

1

1,000

100

10

10,000

1

1,000

100

10

10,000

Streamflow, in cubic feet per second

CAMEO

JENSEN GREEN

STATELINE

GUNNISON

EXPLANATION

100 1,000 10,000 100 1,000 10,000

CISCO

Natural-logarithm of the

 suspended-sediment concentration 

Natural-logarithm of the sand portion of

 the suspended-sediment concentration

Figure 15. Graphs showing statistical relation between median suspended-sediment concentration and streamflow at selected 

U.S. Geological Survey streamflow-gaging stations.
34 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 16. Graphs showing hysteresis loops (seasonal changes in suspended-sediment concentration) at selected U.S. Geological 

Survey streamflow-gaging stations. Suspended-sediment concentration, in milligrams per liter

1

1,000

100

10

10,000

1

1,000

100

10

10,000

1

1,000

100

10

10,000

Streamflow, in cubic feet per second (ft3/s)

CAMEO

JENSEN GREEN

STATELINE CISCO

GUNNISON

EXPLANATION

Suspended-sediment concentration Sand portion of the suspended-sediment concentration

100 1,000 10,000 100 1,000 10,000

1/1 4/1 7/1 10/1

Date Date

Date Date

Date Date

5/25 6/3

10

10 1/1 4/1 7/1 10/1

4/1 5/1

6/1

7/1 8/1

11/1

1/1

2/1

4/1 5/1

6/1

7/1

8/1

11/1

1/1

2/1

4/1

5/1

6/1

7/1

8/1

11/1 1/1

2/1

4/1

5/1

6/1

7/1 8/1

11/1

1/1

2/1

4/1

5/1

6/1

7/1

8/1

11/1

1/1

2/1

4/1

5/1 6/1

7/1

8/1

11/1 1/1

2/1

5/25

1/1 4/1 7/1 10/1

10

10

6/1

1/1 4/1 7/1 10/1

4/1 5/1

6/1

7/1

8/1

11/1

1/1

2/1

4/1

5/1

6/1

7/1

8/1

11/1 1/1

2/1

10

10

5/24

1/1 4/1 7/1 10/1

10

3

4/1

5/1 6/1

7/1

8/1 11/1

1/1 2/1

4/1

5/1

6/1

7/1

8/1

11/1

1/1

2/1

7/1

6/1

1/1 4/1 10/1

10

10

4/1

5/1

6/1

7/1

8/1 11/1

1/1

2/1

4/1 5/1

6/1

1/1

2/1

Streamflow (ft3/s)

Streamflow (ft3/s) Streamflow (ft3/s) Streamflow (ft3/s)

Streamflow (ft3/s)

4

3

4

3

3

4

7/1

104

103

4

3

10

7/1

8/1

11/1

Streamflow (ft3/s)
Effects of Streamflow on Sediment Transport 35

variability in natural logarithm SS concentration explained 

at JENSEN and GREEN (1.5 and 0 percent of the variability in natural logarithm SS concentration, respectively). 

Seasonal differences in SS concentration arising from the 

seasonality variables are shown in figure 16 for an average 

year (artificial hydrograph produced from mean of daily 

mean streamflow record).

The seasonality coefficients, including the Fourier 

series and dummy variables (rain events and rising-limb 

of the hydrograph), explain 2.1–14 percent of the variability in natural logarithm sand SS concentration at each 

station (STATELINE, 14; JENSEN, 9.4; GUNNISON, 

5.6; CAMEO, 5.2; CISCO, 4.4; and GREEN, 2.1 percent 

of the variability in natural logarithm sand SS concentration) (fig. 14). Within the seasonality grouping, the 

variables that represent the rain events and the rising-limb 

of the hydrograph were not significant at most stations 

for natural logarithm sand SS concentration. At CAMEO, 

both rain events and rising-limb of the hydrograph were 

significant (0.7 and 0.8 percent of the variability in natural 

logarithm sand SS concentration, respectively); at STATELINE the rising-limb of the hydrograph was significant 

(8.5 percent of the variability in natural logarithm sand SS 

concentration); at GREEN the rain event was significant 

and negatively correlated (2.1 percent of the variability 

in natural logarithm sand SS concentration). At stations 

where the rain-events dummy variable is significant for 

SS concentration and not for sand SS concentration (or 

negatively correlated to sand SS concentration), rain 

events increase fine-sediment supplies (particle diameters 

less than 0.0625 mm) without appreciable increases in 

sand. This explanation is supported by observed sedimentparticle sizes of suspended sediments from rain events at 

GUNNISON and JENSEN where nearly 100 percent of 

the suspended material transported from large rain events 

was less than 0.0625 mm in diameter (Williams and others, 

2009). Seasonal differences in sand SS concentration arising from the seasonality variables are shown in figure 16 

for an average year (artificial hydrograph produced from 

mean of daily mean streamflow record).

Temporal-trend analysis can identify consistent patterns in the dataset as changes over multiple years. Temporal 

trends within this analysis described changes in sediment 

transport and changes in suspended-sediment-particle 

sizes. Statistically significant temporal trends were found 

for all stations analyzed in this report for natural logarithm 

SS concentration and had adjusted R2

 ranging from 1.5 

to 8.9 percent (0 to 6.2 percent for natural logarithm sand 

SS concentration) (fig. 14). Temporal trends may be most 

substantial at stations located in reaches downstream from 

large main-stem reservoirs (GREEN, 8.9; GUNNISON, 8.5; 

JENSEN, 8.5; and CISCO, 6.6 percent of the variability in 

natural logarithm SS concentration) with less of the variability in natural logarithm SS concentration explained at 

STATELINE and CAMEO (2.7 and 1.5 percent of the variability in natural logarithm SS concentration, respectively). 

CAMEO, STATELINE, CISCO, and GREEN showed linear 

downward trends in natural logarithm SS concentration 

(fig. 17). GUNNISON and JENSEN were best fit by concave-upward natural logarithm SS concentration trends that 

describe downward trends followed by upward trends (trend 

reversals 1991 and 1992, respectively) (fig. 17). 

The temporal trends in natural logarithm sand SS 

concentration were similar in shape for GUNNISON and 

CAMEO (4.7, 0.4 percent of the variability in natural logarithm sand SS concentration, respectively); and with changes 

in the shape of the trends at STATELINE and JENSEN (6.2 

and 5.7 percent of the variability in natural logarithm sand 

SS concentration, respectively) (fig. 18). No trends were 

detected in natural logarithm sand SS concentration at CISCO 

and GREEN. For GUNNISON and STATELINE, the natural logarithm sand SS concentration trends were best fit by 

concave-upward parabolas that describe downward trends 

followed by upward trends (trend reversals 1996 and 1994, 

respectively). At JENSEN, trends in natural logarithm sand 

SS concentration are upward over the entire period. The trend 

at JENSEN shows reductions in overall natural logarithm SS 

concentration up to the early 1990s, followed by increases in 

natural logarithm SS concentration. The proportion of sand 

transported at this station increased over the entire period.

The temporal trends determined by this analysis 

show changes in the relation between streamflow and SS 

concentration within the post-reservoir period (post 1965 

for JENSEN and GREEN; post 1967 for GUNNISON, 

STATE, and CISCO). When these patterns are present at 

a station, interpretation of the time variable is a relative 

increase or decrease in sediment response under equivalent 

stream conditions (figs. 17 and 18). Time trends indicate 

that mean annual SS concentration for CAMEO, STATELINE, CISCO, and GREEN decreased by 12.9, 11.3, 37.6, 

and 62.6 milligrams per liter (mg/L) per year, respectively 

(total change in concentrations over period was 220; 350; 

1,278; and 2,255 mg/L, respectively). Linear approximations of the parabolic trends in mean annual SS concentration for GUNNISON and JENSEN decreased by 19.2 and 

47.4 mg/L per year, respectively (total change in concentrations over period was 307 and 1,328 mg/L, respectively); followed by increases of 27.1 and 14.1 mg/L, 

respectively (total change in concentrations over period 

was 460 and 226 mg/L, respectively). 

Mean annual sand SS concentration for CAMEO 

decreased by 2.0 mg/L per year (total change in concentration over period was 34 mg/L). At JENSEN, concentration increased by 4.1 mg/L per year with a total change in 

concentration over the period of 174 mg/L. Linear approximations of the parabolic trends in mean annual sand SS 

concentration for GUNNISON and STATELINE decreased 

by 5.6 and 12.4 mg/L per year, respectively (total change 

in concentrations over period was 112 and 224 mg/L, 

respectively); followed by increases of 2.2 and 4.6 mg/L, 

respectively (total change in concentrations over period 

was 26 and 55 mg/L, respectively).
36 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 17. Graphs showing temporal trends in total suspended-sediment concentration at selected U.S. Geological Survey streamflowgaging station locations. Partial residual for natural logarithm suspended-sediment concentration –4

–3

–2

–1

0

1

2

3

4

5

–4

–3

–2

–1

0

1

2

3

4

5

–4

–3

–2

–1

0

1

2

3

4

5

1960 1970 1980 1990 2000 2010

Time

1960 1970 1980 1990 2000 2010

350 milligrams per liter

decrease over 31 years

EXPLANATION

Partial residual

Trend line

220 milligrams per liter

decrease over 17 years

307 milligrams per liter

decrease over 16 years

226 milligrams per liter

increase over 16 years

CAMEO

JENSEN GREEN

STATELINE CISCO

GUNNISON

1,278 milligrams per liter

decrease over 34 years

1,328 milligrams per liter

decrease over 28 years 2,255 milligrams per liter

decrease over 36 years

{ }

460 milligrams per liter

increase over 17 years

 {

 { {

 { } {
Effects of Streamflow on Sediment Transport 37

Climatic Effects on Suspended-Sediment 

Transport Equations

As previously discussed, suspended-sediment transport is governed not only by sediment-transport capacity of 

a stream but also by sediment supply (fig. 9). During wet 

years, channel-bed scour and erosion can remove substantial 

amounts of stored bed sediment. The reduction in sediment 

abundance may result in an adjustment in the shape of the 

relation between streamflow and sediment concentration 

(Horowitz, 2003). In the same manner, dry years also can 

affect sediment storage. Periods of drought may result in 

temporary increases in sediment supply and storage when 

sediment is derived from in-stream sources (streambed and 

channel margins) or reduction of sediment storage when 

sediment is stored in overbank areas that are only inundated 

during high-flow periods. Comparisons between relations 

of natural logarithm streamflow and natural logarithm SS 

concentration were made between annual comparisons (wet 

and dry years) and multi-year cycles (wet years compared to 

wet years following dry periods, and dry years compared to 

dry years following wet periods). 

Significant differences (p-value less than 0.05) in the 

slope and intercepts of the relation of natural logarithm 

streamflow and natural logarithm SS concentration were 

determined between wet and dry years. For the rising-limb 

of the snowmelt-runoff hydrograph, four of the six stations 

showed significant differences (CAMEO, CISCO, JENSEN, 

and GREEN); on the falling-limb of the snowmelt-runoff 

hydrograph, one of six stations showed significant differences 

(GUNNISON) (fig. 19). For each of the four stations during the rising-limb of the snowmelt-runoff hydrograph, the 

natural logarithm SS concentration during wet years generally is higher than natural logarithm SS concentration during 

dry years for the same streamflow. This indicates that natural 

logarithm SS concentration is less strongly controlled (flatter 

slopes) by streamflow magnitude in wet years. At CAMEO for 

wet years, the slope of the relation between natural logarithm 

Figure 18. Graphs showing temporal trends in sand portion of the suspended-sediment concentration at selected U.S. Geological 

Survey streamflow-gaging station locations. Partial residual for natural logarithm sand portion suspended-sediment concentration

34 milligrams per liter

decrease over 17 years

{ {

112 milligrams per liter

decrease over 20 years

 }

26 milligrams per liter

increase over 12 years

 {

224 milligrams per liter

decrease over 18 years

 }

55 milligrams per liter

increase over 12 years

 }

174 milligrams per liter

increase over 42 years

–4

–3

–2

–1

0

1

2

3

4

5

–4

–3

–2

–1

0

1

2

3

4

5

CAMEO

STATELINE JENSEN

GUNNISON

1960 1970 1980 1990 2000 2010 1960 1970 1980 1990 2000 2010

Time

EXPLANATION

Partial residual

Trend line
38 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 19. Graphs showing differences in the statistical relation between 

suspended-sediment concentration and streamflow between wet and dry 

years at selected U.S. Geological Survey streamflow-gaging stations.

CAMEO

JENSEN

CISCO

GREEN

GUNNISON

Streamflow, in cubic feet per second

EXPLANATION

Dry year

Wet year

1,000 10,000

100

1,000

10,000

100

1,000

10,000

100

1,000

10,000

1,000 10,000

100

1,000

10,000

100

1,000

10,000

Suspended-sediment concentration, in milligrams per liter

Falling-limb of the snowmelt-runoff hydrograph

Rising-limb of the snowmelt-runoff hydrograph
Effects of Streamflow on Sediment Transport 39

streamflow and natural logarithm SS concentration is positive (upward) and small in magnitude; this means that large 

increases in streamflow correspond to small increases in 

natural logarithm SS concentration. At CISCO, JENSEN, and 

GREEN for wet years, the slope of the relation between natural logarithm streamflow and natural logarithm SS concentration is negative (downward) and small in magnitude; this 

means that large increases in streamflow correspond to small 

decreases in natural logarithm SS concentration. 

Significant differences between wet and dry years on the 

falling-limb of the hydrograph at GUNNISON differ depending on flow conditions. At smaller streamflow values (less than 

7,000 ft3/s), dry years have higher SS concentrations than wet 

years, and at larger streamflows the concentrations are lower 

than wet years. Differences in sediment-transport processes or 

water management on the Gunnison River (Aspinall Storage Unit and (or) Ridgeway Reservoir) may be causing the 

inconsistency along the study reaches of the Gunnison and 

Colorado Rivers between GUNNISON and between CAMEO 

and CISCO. Comparisons between wet and dry years for the 

rising-limb of the hydrograph at stations other than GUNNISON did not show significant (p-value less than 0.05) differences in the slope or intercept.

No statistically significant differences were determined 

between any multi-year cycle comparison and may be indicative of the smaller dataset available for such comparisons.

Suspended-Sediment Transport Equation-Error 

Analysis

Sediment-transport equations are based on periodic sediment data and represent average sediment-transport conditions 

in a river. The average condition defined by the equations 

may not adequately represent the true condition in the stream. 

Further, shorter duration sediment-transport characteristics 

may not be well defined by the average condition represented 

by the sediment-transport equations. 

It is useful to characterize the consistency of the relation 

between the explanatory and response variables over the period 

of data collection. The magnitude of the variability within the 

measured dataset can be identified within the regression analysis 

as the estimated residual variance (ERV) for regression equations. This is characterized by the error term in equation 2 and is 

summarized for each regression equation in table 5.

Two of the transport-equation datasets had daily SS flux 

data that were suitable for additional evaluation of transportequation error (GUNNISON and JENSEN). The analysis was 

performed to characterize the “error” of the estimated SS flux 

at varying time steps. RMSE were calculated (as percent of the 

mean) from a comparison of daily observations to predicted values. Comparisons of RMSE for the SS flux transport-equation 

estimates show that the error associated with the transport 

equation varied (1) between the two stations; (2) at each station depending on the time step of the estimate (daily, weekly, 

monthly, or seasonal estimates); and (3) between the different 

seasons (rising limb, falling limb, or base flow) (fig. 20).

Both GUNNISON and JENSEN show decreasing errors 

as the time step increases for all seasons. Base-flow errors 

were highest at a daily time step and lowest at a seasonal time 

step at both stations. The variability of the base-flow analysis could be attributed to rain events, which affect the daily 

predictions. The variability observed during estimates of the 

rising-limb appears consistent regardless of the specified time 

step. This could be attributed to the high streamflows and concentrations associated with snowmelt. This analysis shows that 

applications of transport equations for suspended-sedimenttransport estimates need to be used in accordance with the 

level of accuracy the specific application warrants. To limit the 

amount of error in any application, the largest applicable time 

step needs to be used.

Incipient Motion of Streambed Material

Determination of the incipient motion for streambeds 

composed of mixtures of sediment-size classes including sand, 

and gravel- or cobble-sized particles (hereafter referred to as 

“sands” or “gravels,” respectively) requires an understanding 

of how these sediments are arranged within the streambed 

(bed structure). The bed structure can occur over a continuum 

from two end-member conditions: pure sands and pure gravels. For each of these two conditions, the prediction of motion 

can be defined by sediment-particle size (Julien, 2010). When 

sands and gravels are intermixed, substantial increases or 

decreases in the sediment mobility (or incipient motion) can 

occur for both size classes. In a gravel-framework bed (less 

than 20–30 percent sand), the gravel dominates the sediment 

mixture, and the bed structure is supported by gravel-ongravel contact with sand filling the interstitial spaces between 

and beneath the gravel clasts. Under these conditions, the 

larger clasts shelter the sand and both grains remain immobile 

until the critical-shear stress for the gravels is exceeded. This 

produces conditions where as the portion of sand decreases to 

zero, the critical shear stress of both particles approaches that 

of pure gravels (Wilcock, 1998). In a sand-matrix bed (greater 

than 20–30 percent sand), the gravel clasts are supported by 

contact with sand deposits between each gravel clast. Under 

these conditions, sheltering of the sands is minimal and incipient motion of the gravels occurs at boundary shear stresses 

lower than the critical shear stress of gravels alone. This 

produces conditions where as the portion of sand approaches 

100 percent, the critical shear stress for both size classes 

approaches that of pure sand (Wilcock, 1998). 

Characterization of the sediment-particle size for each 

location is presented in table 6. For locations that are relatively 

free of sand, characterization of the d50 sediment-particle 

size is used to determine the boundary shear stress needed to 

entrain the streambed material within a given reach. At locations that demonstrate bimodal sediment-particle size distributions, the analysis is separated into the end-member conditions 

of sands and gravel and can be used to infer the range of 

mobility of these sediments along the continuum of possible 

combinations found within the study reaches. Comparisons of 
40 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 20. Graphs showing error between the regression predictions and available daily suspendedsediment records at U.S. Geological Survey streamflow-gaging stations GUNNISON, 09152500, Gunnison River 

near Grand Junction, Colorado; and JENSEN, 09261000, Green River near Jensen, Utah; water years 2005–8.

JENSEN

GUNNISON

EXPLANATION

Rising

Falling

Base flow

All data

0

100

200

300

400

Root mean square error as percent of the mean

Time interval for error estimate

Daily Weekly Monthly Seasonally

0

100

200
Effects of Streamflow on Sediment Transport 41

Table 6. Sediment-particle size distribution summary statistics of bed-material samples collected at selected locations in the 

Gunnison and Green Rivers in 2008 and 2006–7, respectively.

[mm, millimeters; <, less than; Gun, Gunnison River; Gr, Green River; L, bed material sampled at the center of the left 1/3 of the channel; M, bed material 

sampled at the center of the channel; R, bed material sampled at the center of the right 1/3 of the channel]

Site number

(figs. 4 and 5)

Size distribution, in mm, shown for the following percentiles Percent sand

10 16 50 65 84

Gunnison River at Delta, Colorado1

 (09144250) 

Delta-1 11.9 23 79 104 137 < 2

Gunnison River near Grand Junction, Colorado1

 (09152500)

Gun-1 30.9 37 77 104 124 < 1

Gun-2 37.6 50 74 81 106 < 1

Gun-3 30.9 35 71 92 112 < 1

Green River near Jensen, Utah1

 (09261000)

Gr-1 20 25 56 69 124 < 1

Gr-2 .1 .4 64 80 106 11

Gr-3 .3 13 56 82 112 < 2

Spawning-bar habitat, 5 miles downstream of Green River near Jensen, Utah2

 (09261000)

1-L 0.500–0.710 0.710–1.0 1.0–1.4 1.0–1.4 1.4–2.0 91

1-M 0.250–0.355 0.355–0.500 0.710–1.0 1.0–1.4 16.0–22.4 67

1-R 0.355–0.500 0.355–0.500 0.500–0.710 0.710–1.0 0.710–1.0 99

2-L 0.500–0.710 0.710–1.0 1.0–1.4 1.0–1.4 1.4–2.0 92

2-M 0.355–0.500 0.500–0.710 0.710–1.0 1.0–1.4 1.4–2.0 86

2-R 0.180–0.250 0.250–0.355 0.500–0.710 0.710–1.0 0.710–1.0 92

3-L 0.250–0.355 0.355–0.500 0.500–0.710 0.710–1.0 0.710–1.0 91

3-M 0.355–0.500 0.500–0.710 0.710–1.0 0.710–1.0 0.710–1.0 100

3-R 0.500–0.710 0.500–0.710 1.0–1.4 16.0–22.4 16.0–22.4 54

4-M 0.250–0.355 0.355–0.500 0.710–1.0 0.710–1.0 1.0–1.4 97

5-M 0.180–0.250 0.180–0.250 0.355–0.500 0.355–0.500 0.500–0.710 100

6-L 0.180–0.250 0.180–0.250 0.250–0.355 0.355–0.500 0.500–0.710 99

6-M 0.250–0.355 0.355–0.500 0.710–1.0 0.710–1.0 1.4–2.0 91

6-R 0.500–0.710 0.710–1.0 1.4–2.0 2.0–2.8 4.0–5.6 62

1

Areal-sampling method (Wolman, 1954).

2

Volumetric-sampling method (Guy, 1977).
42 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Table 7. Summary of boundary shear stress and grain shear stress for selected locations in the Gunnison and Green Rivers.—

Continued

[Q, streamflow; ft3/s, cubic foot per second; w, width of channel; ft, foot; h, mean flow depth; Sf, friction slope; ft/ft, feet per foot; n, Mannings coefficient 

of roughness of the cross section; V, mean velocity; ft/s, feet per second; d65, size distribution of bed sediment for the 65-percentile; mm, millimeter; nD, the 

Mannings coefficient of roughness attributed to grain roughness; lb/ft2, pound per square foot]

Q (ft3/s) w (ft) h (ft) Sf (ft/ft) n V (ft/s) d65 (mm) nD

Grain shear 

stress (lb/ft2

)

Grain shear stress as 

percent of boundary 

shear stress

Cross section 450 feet upstream from cableway – Gunnison River near Grand Junction, Colorado (09152500) 

1,950 248 2.41 0.00036 0.016 3.257 81 0.030 0.05 100

3,750 249 3.22 0.00063 0.017 4.670 81 0.030 0.13 100

7,700 250 5.81 0.00083 0.026 5.303 81 0.030 0.30 100

11,000 253 7.31 0.00082 0.027 5.948 81 0.030 0.37 100

14,000 260 8.85 0.00094 0.032 6.087 81 0.030 0.48 92

Cross section 300 feet upstream from cableway – Gunnison River near Grand Junction, Colorado (09152500) 

1,950 171 3.56 0.00036 0.020 3.207 81 0.030 0.08 100

3,750 172 4.89 0.00063 0.024 4.454 81 0.030 0.19 100

7,700 178 7.36 0.00083 0.028 5.876 81 0.030 0.38 100

11,000 181 8.92 0.00082 0.027 6.810 81 0.030 0.46 100

14,000 185 10.64 0.00094 0.031 7.111 81 0.030 0.61 97

Cross section 150 feet upstream from cableway – Gunnison River near Grand Junction, Colorado (09152500)

1,950 173 4.63 0.00036 0.032 2.437 81 0.030 0.10 91

3,750 178 5.80 0.00063 0.033 3.630 81 0.030 0.20 87

7,700 181 8.16 0.00083 0.033 5.212 81 0.030 0.37 87

11,000 185 9.46 0.00082 0.030 6.283 81 0.030 0.49 100

14,000 189 11.07 0.00094 0.034 6.694 81 0.030 0.55 85

Cross section at Cableway – Gunnison River near Grand Junction, Colorado (09152500) 

1,950 165 4.91 0.00036 0.034 2.407 81 0.030 0.09 85

3,750 170 5.96 0.00063 0.033 3.704 81 0.030 0.21 88

7,700 178 8.37 0.00083 0.034 5.170 81 0.030 0.36 84

11,000 181 10.02 0.00082 0.033 6.068 81 0.030 0.46 90

14,000 187 11.17 0.00094 0.034 6.700 81 0.030 0.55 84

Cross-section 2 – Gunnison River at Delta, Colorado (09144250)

1,400 154 2.66 0.00080 0.024 3.417 104 0.032 0.13 100

2,870 163 3.93 0.00130 0.030 4.476 104 0.032 0.32 100

11,250 241 6.30 0.00160 0.027 7.408 104 0.032 0.63 100

13,300 241 6.71 0.00160 0.026 8.225 104 0.032 0.67 100

Cross-section 3 – Gunnison River at Delta, Colorado (09144250)

1,400 147 4.36 0.00080 0.051 2.184 104 0.032 0.11 48

2,870 150 5.66 0.00130 0.050 3.382 104 0.032 0.23 50

11,250 190 8.46 0.00160 0.035 7.000 104 0.032 0.72 85

13,300 209 8.85 0.00160 0.035 7.177 104 0.032 0.75 84

Cross-section 4 – Gunnison River at Delta, Colorado (09144250)

1,400 198 2.90 0.00080 0.035 2.439 104 0.032 0.12 86

2,870 208 4.14 0.00130 0.041 3.336 104 0.032 0.22 67

11,250 227 7.55 0.00160 0.035 6.560 104 0.032 0.65 86

13,300 244 8.10 0.00160 0.036 6.729 104 0.032 0.68 84
Effects of Streamflow on Sediment Transport 43

Table 7. Summary of boundary shear stress and grain shear stress for selected locations in the Gunnison and Green Rivers.—

Continued

[Q, streamflow; ft3/s, cubic foot per second; w, width of channel; ft, foot; h, mean flow depth; Sf, friction slope; ft/ft, feet per foot; n, Mannings coefficient 

of roughness of the cross section; V, mean velocity; ft/s, feet per second; d65, size distribution of bed sediment for the 65-percentile; mm, millimeter; nD, the 

Mannings coefficient of roughness attributed to grain roughness; lb/ft2, pound per square foot]

Q (ft3/s) w (ft) h (ft) Sf (ft/ft) n V (ft/s) d65 (mm) nD

Grain shear 

stress (lb/ft2

)

Grain shear stress as 

percent of boundary 

shear stress

Cross-section 1 – Sand - Green River near Jensen, Utah (09261000)

9,000 460 4.64 0.00063 0.025 4.217 1.4 0.015 0.14 75

10,600 459 5.63 0.00061 0.028 4.102 1.4 0.015 0.12 57

14,100 459 6.54 0.00062 0.028 4.697 1.4 0.015 0.15 60

17,700 476 7.43 0.00061 0.028 5.005 1.4 0.015 0.17 59

19,000 476 7.58 0.00058 0.026 5.266 1.4 0.015 0.18 66

Cross-section 2 – Sand - Green River near Jensen, Utah (09261000)

9,000 820 3.07 0.00100 0.028 3.575 1.4 0.015 0.11 59

10,600 820 3.86 0.00093 0.033 3.349 1.4 0.015 0.09 41

14,100 820 4.96 0.00191 0.054 3.467 1.4 0.015 0.09 15

17,700 853 5.96 0.00145 0.053 3.482 1.4 0.015 0.09 16

19,000 1,050 6.00 0.00042 0.033 3.016 1.4 0.015 0.06 41

Cross-section 3 – Sand - Green River near Jensen, Utah (09261000)

9,000 245 3.58 0.00076 0.009 10.261 1.4 0.015 0.17 100

10,600 246 4.51 0.00072 0.011 9.554 1.4 0.015 0.20 100

14,100 279 5.09 0.00076 0.012 9.929 1.4 0.015 0.24 100

17,700 344 5.37 0.00046 0.010 9.582 1.4 0.015 0.15 100

19,000 361 5.36 0.00088 0.014 9.819 1.4 0.015 0.29 100

Cross-section 4 – Sand - Green River near Jensen, Utah (09261000)

9,000 279 3.53 0.00065 0.010 9.138 1.4 0.015 0.14 100

10,600 279 4.33 0.00048 0.010 8.774 1.4 0.015 0.13 100

14,100 279 5.59 0.00034 0.010 9.041 1.4 0.015 0.12 100

17,700 279 6.85 0.00031 0.010 9.261 1.4 0.015 0.13 100

19,000 279 7.12 0.00027 0.009 9.565 1.4 0.015 0.12 100

Cross-section 5 – Sand - Green River near Jensen, Utah (09261000)

9,000 262 4.20 0.00017 0.006 8.179 1.4 0.015 0.04 100

10,600 262 4.42 0.00013 0.005 9.153 1.4 0.015 0.04 100

14,100 262 5.67 0.00009 0.005 9.491 1.4 0.015 0.03 100

17,700 262 6.93 0.00007 0.005 9.749 1.4 0.015 0.03 100

19,000 279 6.68 0.00007 0.004 10.195 1.4 0.015 0.03 100

Cross-section 6 – Sand - Green River near Jensen, Utah (09261000)

9,000 409 5.86 0.00035 0.024 3.755 1.4 0.015 0.10 79

10,600 410 7.38 0.00091 0.049 3.503 1.4 0.015 0.08 19

14,100 410 8.67 0.00037 0.030 3.967 1.4 0.015 0.10 49

17,700 426 9.43 0.00052 0.034 4.406 1.4 0.015 0.12 39

19,000 426 9.73 0.00042 0.030 4.584 1.4 0.015 0.13 50
44 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Table 7. Summary of boundary shear stress and grain shear stress for selected locations in the Gunnison and Green Rivers.—

Continued

[Q, streamflow; ft3/s, cubic foot per second; w, width of channel; ft, foot; h, mean flow depth; Sf, friction slope; ft/ft, feet per foot; n, Mannings coefficient 

of roughness of the cross section; V, mean velocity; ft/s, feet per second; d65, size distribution of bed sediment for the 65-percentile; mm, millimeter; nD, the 

Mannings coefficient of roughness attributed to grain roughness; lb/ft2, pound per square foot]

Q (ft3/s) w (ft) h (ft) Sf (ft/ft) n V (ft/s) d65 (mm) nD

Grain shear 

stress (lb/ft2

)

Grain shear stress as 

percent of boundary 

shear stress

Cross-section 1 – Gravel - Green River near Jensen, Utah (09261000)

9,000 460 4.64 0.00063 0.025 4.217 82 0.030 0.18 100

10,600 459 5.63 0.00061 0.028 4.102 82 0.030 0.21 100

14,100 459 6.54 0.00062 0.028 4.697 82 0.030 0.25 100

17,700 476 7.43 0.00061 0.028 5.005 82 0.030 0.28 100

19,000 476 7.58 0.00058 0.026 5.266 82 0.030 0.27 100

Cross-section 2 – Gravel - Green River near Jensen, Utah (09261000)

9,000 820 3.07 0.00100 0.028 3.575 82 0.030 0.19 100

10,600 820 3.86 0.00093 0.033 3.349 82 0.030 0.20 87

14,100 820 4.96 0.00191 0.054 3.467 82 0.030 0.25 42

17,700 853 5.96 0.00145 0.053 3.482 82 0.030 0.23 43

19,000 1,050 6.00 0.00042 0.033 3.016 82 0.030 0.14 87

Cross-section 3 – Gravel - Green River near Jensen, Utah (09261000)

9,000 245 3.58 0.00076 0.009 10.261 82 0.030 0.17 100

10,600 246 4.51 0.00072 0.011 9.554 82 0.030 0.20 100

14,100 279 5.09 0.00076 0.012 9.929 82 0.030 0.24 100

17,700 344 5.37 0.00046 0.010 9.582 82 0.030 0.15 100

19,000 361 5.36 0.00088 0.014 9.819 82 0.030 0.29 100

Cross-section 4 – Gravel - Green River near Jensen, Utah (09261000)

9,000 279 3.53 0.00065 0.010 9.138 82 0.030 0.14 100

10,600 279 4.33 0.00048 0.010 8.774 82 0.030 0.13 100

14,100 279 5.59 0.00034 0.010 9.041 82 0.030 0.12 100

17,700 279 6.85 0.00031 0.010 9.261 82 0.030 0.13 100

19,000 279 7.12 0.00027 0.009 9.565 82 0.030 0.12 100

Cross-section 5 – Gravel - Green River near Jensen, Utah (09261000)

9,000 262 4.20 0.00017 0.006 8.179 82 0.030 0.04 100

10,600 262 4.42 0.00013 0.005 9.153 82 0.030 0.04 100

14,100 262 5.67 0.00009 0.005 9.491 82 0.030 0.03 100

17,700 262 6.93 0.00007 0.005 9.749 82 0.030 0.03 100

19,000 279 6.68 0.00007 0.004 10.195 82 0.030 0.03 100

Cross-section 6 – Gravel - Green River near Jensen, Utah (09261000)

9,000 409 5.86 0.00035 0.024 3.755 82 0.030 0.13 100

10,600 410 7.38 0.00091 0.049 3.503 82 0.030 0.21 50

14,100 410 8.67 0.00037 0.030 3.967 82 0.030 0.20 100

17,700 426 9.43 0.00052 0.034 4.406 82 0.030 0.26 83

19,000 426 9.73 0.00042 0.030 4.584 82 0.030 0.26 100
Effects of Streamflow on Sediment Transport 45

boundary shear stress and calculated grain shear stress at each 

location is presented in table 7. At most locations, less than 

2 percent difference exists between boundary shear stress and 

grain shear stress. Where differences exceeded 2 percent, grain 

shear stress was used to assess entrainment potential of the 

streambed material in the reach.

Gunnison River at Delta

A study reach was established near the Gunnison River 

at Delta, Colorado (0914450) streamflow-gaging station to 

re-evaluate incipient-sediment-motion estimates at a previously studied location, 57 river miles (RM) upstream from the 

confluence of the Gunnison River with the Colorado River 

(cross-section 57 in Pitlick and others, 1999). The exact location of the 1999 cross section at RM 57 could not be determined; therefore, an 1,800-ft long reach consisting of four 

cross sections that bracketed the original 1999 cross section 

was established near the USGS streamflow-gaging station 

Gunnison River at Delta, Colorado (fig. 21). Initially, a fourth 

cross section, cross-section 1, was established; however, this 

cross section was not monumented or surveyed because, on 

closer inspection, it was not representative of the study reach 

channel geometry (width, depth, gradient) and sedimentparticle size. Cross-section 3 in this report is believed to most 

closely replicate the cross section at RM 57 of the 1999 report 

(Pitlick and others, 1999). 

Incipient motion analysis was performed for stream conditions of 13,300 ft3

/s (05/22/2008); 11,250 ft3/s (05/29/2008); 

2,850 ft3

/s (07/02/2008); and 1,400 ft3/s (09/24/2008). On-site 

observations indicated that the streambed sediment in the 

Gunnison River at Delta study reach was relatively uniform. 

The median sediment-particle size (d50) of the streambed 

sediment was 79 mm within a gravel-framework bed in the 

Gunnison River at Delta study reach (table 6). The critical 

shear stress for this material was 0.93 and 1.33 lb/ft2

 using 

dimensionless Shields parameter values of 0.035 and 0.050, 

respectively (table 8).

Cross-sections 2 and 3 in the Delta study reach had relatively uniform cross-channel geometries and, consequently, 

relatively uniform cross-channel boundary shear-stress 

distributions (fig. 22). Mean boundary shear stresses at crosssections 2 and 3 (table 7) do not approach the minimum critical shear stress for 79 mm sediment in the Delta study reach 

(calculated with a Shields parameter of 0.035) at any evaluated streamflow (table 8). Boundary shear stresses, calculated 

for a continuum of points along cross-sections 2 and 3, do not 

approach the minimum critical shear stress for sediment in the 

Delta study reach until streamflows approach or exceed the 

11,250 ft3

/s reference streamflow (fig. 22). The critical shear 

stress calculated with the more conservative 0.050 Shields 

parameter cannot be attained at these cross sections, even 

with the 2008 peak streamflow of 13,300 ft3

/s. These plots 

indicate that the streambed sediment in cross-sections 2 and 

3 potentially is mobile only in limited locations and at high 

streamflows like that of 2008.

Cross-section 4 in the Delta study reach is slightly asymmetrical in cross-channel geometry because of the presence 

of a low-elevation, partially submerged gravel and cobble bar, 

which occupies the left half of the streambed (fig. 23). As at 

cross-sections 2 and 3, mean boundary shear stress at crosssection 4 (table 7) does not approach the minimum critical 

shear stress for 79 mm sediment at any streamflow evaluated 

in 2008 (table 8). Boundary shear stress, calculated with a 

Shields parameter of 0.035, did not exceed the minimum 

critical shear stress for 79 mm sediment even in the deeper, 

right side of the streambed when the streamflow approached 

11,250 and 13,300 ft3

/s (fig. 23). The critical shear stress 

calculated with the more conservative 0.050 Shields parameter was not attained at any location on cross-section 4. The 

left side of the streambed and alluvial bar at cross-section 4 

likely is a place of sediment accumulation of d50-size material 

transported from upstream owing to the lesser boundary shear 

stresses in this area. This gravel and cobble bar was the location of the 2008 pebble count. Field observations confirm the 

above transport conditions; while the pebble count was being 

made it was noted that the sediment in this area was loosely 

compacted indicating that the particles recently had been 

entrained or deposited.

The mean boundary shear stress was highest for all cross 

sections for the peak streamflow of 13,300 ft3

/s (table 7). Yet, 

it was still no more than 81 percent of the minimum critical 

shear stress for the d50 in the Delta study reach (table 8) and 

represents a peak streamflow with a 5- to 10-year recurrence 

interval and streamflow values of 11,000 ft3

/s and 14,900 ft3/s, 

respectively (table 9).

Pitlick and others (1999) evaluated sediment-entrainment 

potential for a 56-mi reach of the Gunnison River from 

Delta, Colorado, to the confluence with the Colorado River 

(fig. 2) and for specific cross sections at 1-mi intervals in this 

reach. Pitlick and others (1999) noted that “framework gravel 

and cobble particles begin to move at about half-bankfull 

streamflow” and that “mobilization and reworking of most 

all particles on the bed (termed significant motion) is associated with...bankfull streamflow,” which is a median flow of 

13,300 ft3

/s within the reach analyzed by Pitlick within the 

Gunnison River. Coincidently, the 2008 Gunnison River peak 

streamflow at Delta was 13,300 ft3

/s, and this streamflow 

exceeded a streamflow that would be needed to overtop the 

banks (a condition used to define bankfull streamflow in stable 

stream reaches) within the study reach (water-surface elevations of 4,927, 4,927, and 4,928 at cross-sections 2, 3, and 

4, respectively; figs. 21–23). Flood-frequency analysis was 

completed using U.S. Geological Survey software PeakFQ, 

version 4.1 (Flynn and others, 2006) following Bulletin 17-B 

Guidelines (U.S. Interagency Advisory Committee on Water 

Data, 1982). The flood-frequency analysis of the streamflow 

data recorded at the Gunnison River at Delta, indicated that 

13,300 ft3/s has a recurrence interval of 5 to 10 years (table 9) 

or less frequently than the bankfull discharge, which generally 
Figure 21. Map showing locations of the four cross sections of the study reach on the Gunnison River near Delta, Colorado. (Cross-sesurveyed in the study.)

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)Universal Transverse Mercator North American Datum 1983, Zone 12 North

09144250 !

XS-4

XS-2

XS-3

XS-1

Cross-section 57 from Pitlick and others (1999) near here

108°04'50" 108°04'40" 

38°

45'

20"

38°

45'

10"

!

EXPLANATION

Streamflow-gaging station and number

Flow direction

Cross-section location and identification

09152500 !

0 0.05 0.1 KILOMETER0 0.05 0.1 MILE

XS-4
Effects of Streamflow on Sediment Transport 47

Figure 22. Graphs showing boundary shear stresses, water-surface elevations, and streambed elevations at crosssections 2 and 3 for selected streamflows at U.S. Geological Survey streamflow-gaging station, 09144250, Gunnison 

River at Delta, Colorado.

4,915

4,920

4,925

4,930

0 4,935

0.5

1.0

1.5

0 20 40 60 80 100 120 140 160 180

0 20 40 60 80 100 120 140 160 180

Elevation above North American

Vertical Datum of 1988, in feet

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot Shear stress, in pounds per square foot 

Horizontal distance, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x4

Horizontal distance, in feet

Streambed

2,850 cubic feet per second

1,400 cubic feet per second

11,250 cubic feet per second

13,300 cubic feet per second

Distance from left bank, in feet

VERTICAL EXAGGERATION x5

1.3

0.93

4,915

4,920

4,925

4,930

0

0.5

1.0

1.5

0 20 40 60 80 100 120 140 160 180 200 220 240

0 20 40 60 80 100 120 140 160 180 200 220 240

2,850 cubic feet per second

1,400 cubic feet per second

11,250 cubic feet per second

13,300 cubic feet per second

Cross-section 3, located 3,300 feet downstream from U.S. Geological Survey streamflow-gaging station 09144250

Cross-section 2, located 2,330 feet upstream from U.S. Geological Survey streamflow-gaging station 09144250

Critical shear stress for 79 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 79 millimeter particles with dimensionless Shields parameter of 0.035

0.45

Critical shear stress for 53 millimeter particles with dimensionless

Shields parameter of 0.025

1.3

0.93

Critical shear stress for 79 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 79 millimeter particles with dimensionless Shields parameter of 0.035

0.45

Critical shear stress for 53 millimeter particles with dimensionless Shields

parameter of 0.025

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation

EXPLANATION

Water-surface elevation

EXPLANATION

Boundary shear stress
48 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Table 8. Cross-section characteristics, grain shear stress, and critical shear stress for the median sediment-particle sizes (d50) at 

selected U.S. Geological Survey streamflow-gaging stations in the Upper Colorado River Basin.—Continued

[ft3/s, cubic foot per second; ft/ft, feet per foot; ft, foot; lb/ft2, pound per square foot]

Discharge

(ft3

/s)

Cross-section

location identification

(figs. 21, 24, and 27)

Slope 

(ft/ft)

Mean flow

depth (ft)

Grain shear 

stress

(lb/ft2

)

Critical shear stress

(Shields parameter 

0.035)

(lb/ft2

)

Critical shear stress

(Shields parameter

0.050)

(lb/ft2

)

Gunnison River near Delta, Colorado (09144250)

1,400 Cross-section 2 0.0008 2.66 0.13 0.93 1.33

2,850 Cross-section 2 0.0013 3.93 0.32 0.93 1.33

11,250 Cross-section 2 0.0016 6.30 0.63 0.93 1.33

13,300 Cross-section 2 0.0016 6.71 0.67 0.93 1.33

1,400 Cross-section 3 0.0008 4.36 0.11 0.93 1.33

2,850 Cross-section 3 0.0013 5.66 0.23 0.93 1.33

11,250 Cross-section 3 0.0016 8.46 0.72 0.93 1.33

13,300 Cross-section 3 0.0016 8.85 0.75 0.93 1.33

1,400 Cross-section 4 0.0008 2.90 0.12 0.93 1.33

2,850 Cross-section 4 0.0013 4.14 0.22 0.93 1.33

11,250 Cross-section 4 0.0016 7.55 0.65 0.93 1.33

13,300 Cross-section 4 0.0016 8.10 0.68 0.93 1.33

Gunnison River near Grand Junction, Colorado (09152500)

1,950 450 feet upstream from cableway 0.00036 2.41 0.05 0.88 1.25

3,750 450 feet upstream from cableway 0.00063 3.22 0.13 0.88 1.25

7,700 450 feet upstream from cableway 0.00083 5.81 0.30 0.88 1.25

11,000 450 feet upstream from cableway 0.00082 7.31 0.37 0.88 1.25

14,000 450 feet upstream from cableway 0.00094 8.85 0.48 0.88 1.25

1,950 300 feet upstream from cableway 0.00036 3.56 0.08 0.88 1.25

3,750 300 feet upstream from cableway 0.00063 4.89 0.19 0.88 1.25

7,700 300 feet upstream from cableway 0.00083 7.36 0.38 0.88 1.25

11,000 300 feet upstream from cableway 0.00082 8.92 0.46 0.88 1.25

14,000 300 feet upstream from cableway 0.00094 10.64 0.61 0.88 1.25

1,950 150 feet upstream from cableway 0.00036 4.63 0.09 0.88 1.25

3,750 150 feet upstream from cableway 0.00063 5.80 0.21 0.88 1.25

7,700 150 feet upstream from cableway 0.00083 8.16 0.37 0.88 1.25

11,000 150 feet upstream from cableway 0.00082 9.46 0.48 0.88 1.25

14,000 150 feet upstream from cableway 0.00094 11.07 0.56 0.88 1.25

1,950 Cableway 0.00118 4.91 0.09 0.88 1.25

3,750 Cableway 0.00063 5.96 0.21 0.88 1.25

7,700 Cableway 0.00083 8.37 0.36 0.88 1.25

11,000 Cableway 0.00082 10.02 0.46 0.88 1.25

14,000 Cableway 0.00094 11.17 0.55 0.88 1.25

Green River near Jensen, Utah (09261000)

9,000 Cross-section 1 0.00059 5.26 0.18/0.141 0.66/0.012 0.95/0.022

10,600 Cross-section 1 0.00051 5.49 0.21/0.121 0.66/0.012 0.95/0.022

14,100 Cross-section 1 0.00045 6.28 0.25/0.151 0.66/0.012 0.95/0.022
Effects of Streamflow on Sediment Transport 49

Table 8. Cross-section characteristics, grain shear stress, and critical shear stress for the median sediment-particle sizes (d50) at 

selected U.S. Geological Survey streamflow-gaging stations in the Upper Colorado River Basin.—Continued

[ft3/s, cubic foot per second; ft/ft, feet per foot; ft, foot; lb/ft2, pound per square foot]

Discharge

(ft3

/s)

Cross-section

location identification

(figs. 21, 24, and 27)

Slope 

(ft/ft)

Mean flow

depth (ft)

Grain shear 

stress

(lb/ft2

)

Critical shear stress

(Shields parameter 

0.035)

(lb/ft2

)

Critical shear stress

(Shields parameter

0.050)

(lb/ft2

)

17,700 Cross-section 1 0.00045 7.45 0.28/0.171 0.66/0.012 0.95/0.022

19,000 Cross-section 1 0.00042 7.60 0.27/0.181 0.66/0.012 0.95/0.022

9,000 Cross-section 2 0.00059 3.35 0.19/0.111 0.66/0.012 0.95/0.022

10,600 Cross-section 2 0.00051 3.63 0.20/0.091 0.66/0.012 0.95/0.022

14,100 Cross-section 2 0.00045 4.60 0.25/0.091 0.66/0.012 0.95/0.022

17,700 Cross-section 2 0.00045 5.78 0.23/0.091 0.66/0.012 0.95/0.022

19,000 Cross-section 2 0.00042 6.00 0.14/0.061 0.66/0.012 0.95/0.022

9,000 Cross-section 3 0.00059 3.69 0.17 0.66/0.012 0.95/0.022

10,600 Cross-section 3 0.00051 3.63 0.20 0.66/0.012 0.95/0.022

14,100 Cross-section 3 0.00045 4.80 0.24 0.66/0.012 0.95/0.022

17,700 Cross-section 3 0.00045 5.91 0.15 0.66/0.012 0.95/0.022

19,000 Cross-section 3 0.00042 6.19 0.29 0.66/0.012 0.95/0.022

9,000 Cross-section 4 0.00059 4.89 0.14 0.66/0.012 0.95/0.022

10,600 Cross-section 4 0.00051 5.21 0.13 0.66/0.012 0.95/0.022

14,100 Cross-section 4 0.00045 6.39 0.12 0.66/0.012 0.95/0.022

17,700 Cross-section 4 0.00045 7.66 0.13 0.66/0.012 0.95/0.022

19,000 Cross-section 4 0.00042 7.93 0.12 0.66/0.012 0.95/0.022

9,000 Cross-section 5 0.00059 4.17 0.04 0.66/0.012 0.95/0.022

10,600 Cross-section 5 0.00051 4.68 0.04 0.66/0.012 0.95/0.022

14,100 Cross-section 5 0.00045 5.62 0.03 0.66/0.012 0.95/0.022

17,700 Cross-section 5 0.00045 6.83 0.03 0.66/0.012 0.95/0.022

19,000 Cross-section 5 0.00042 7.10 0.03 0.66/0.012 0.95/0.022

9,000 Cross-section 6 0.00059 6.38 0.13/0.101 0.66/0.012 0.95/0.022

10,600 Cross-section 6 0.00051 6.76 0.21/0.081 0.66/0.012 0.95/0.022

14,100 Cross-section 6 0.00045 7.90 0.20/0.101 0.66/0.012 0.95/0.022

17,700 Cross-section 6 0.00045 9.11 0.26/0.121 0.66/0.012 0.95/0.022

19,000 Cross-section 6 0.00042 9.42 0.26/0.131 0.66/0.012 0.95/0.022

1

Grain shear stress for sand veneer differs from grain shear stress calculated from median particle size (d50).

2

Critical shear stress calculated from median particle size (d50) of transient sand veneer.
50 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 23. Graphs showing boundary shear stresses, water-surface elevations, and streambed elevations at cross-section 

4 for selected streamflows at U.S. Geological Survey streamflow-gaging station, 09144250, Gunnison River at Delta, Colorado.

Table 9. Estimates of peak streamflow values for selected recurrence intervals at U.S. Geological Survey streamflow-gaging stations 

in the Upper Colorado River Basin.

[Data are in cubic feet per second]

Recurrence interval, years1

Station 

number Abbreviation 1 1.3 2 2.3 5 10 25 50 100 200 500

09095500 CAMEO 8,300 15,100 18,300 19,700 25,400 29,300 34,200 37,400 40,300 43,000 46,300

09144250 DELTA 970 3,400 6,150 7,050 11,000 14,900 20,400 25,000 30,000 35,400 43,200

09152500 GUNNISON 2,000 5,100 8,050 8,900 12,800 16,300 21,100 24,900 28,900 33,200 39,300

09163500 STATELINE 4,150 13,900 22,900 25,100 35,700 44,300 54,800 62,400 69,700 76,900 89,200

09180500 CISCO 5,050 15,700 25,400 28,000 39,600 49,200 61,200 70,000 78,700 87,300 98,600

09261000 JENSEN 5,500 12,200 17,000 18,100 22,800 26,200 30,000 32,700 35,100 37,400 40,200

09315000 GREEN 5,650 14,400 21,200 22,900 30,000 35,400 41,700 46,100 50,300 54,300 59,200

1

The “100-year recurrence interval” means that a flood of that magnitude has a one percent chance of occurring in any given year. In other words, the chances 

that a river will exceed the 100-year flood stage in any given year is 1 in 100. Each year begins with the same 1-percent chance that a 100-year event will occur. 

Recurrence intervals were calculated based on flood-frequency analysis using U.S. Geological Survey software PeakFQ, version 4.1 (Flynn and others, 2006) 

following Bulletin 17-B Guidelines (U.S. Interagency Advisory Committee on Water Data, 1982).

Streambed

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x5

2,850 cubic feet per second

1,400 cubic feet per second

11,250 cubic feet per second

13,300 cubic feet per second

Critical shear stress for 79 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 79 millimeter particles with dimensionless Shields parameter of 0.035

Critical shear stress for 53 millimeter particles with

dimensionless Shields parameter of 0.025

4,915

4,920

4,925

4,930

4,935

0 20 40 60 80 100 120 140 160 180 200 220 240

0 20 40 60 80 100 120 140 160 180 200 220 240

0

0.5

1.0

1.5

1.3

0.93

0.45

Cross-section 4, located 4,840 feet downstream from U.S. Geological Survey streamflow-gaging station 09144250

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation
Effects of Streamflow on Sediment Transport 51

is less than a 5-year (and closer to a 2-year ) recurrence for 

many Rocky Mountain regions and perennial rivers (Williams, 

1978; Andrews, 1980).

Pitlick and others (1999) surveyed channel geometry and 

calculated cross-section average hydraulic characteristics for 

13,300 ft3

/s at RM 57, which is comparable with cross-section 

3 of this study (figs. 21 and 22). Pitlick and others (1999) 

estimated “bankfull” boundary shear stress at RM 57 to be 

1.09 lb/ft2

 (52.4 N/m2, table A-9), with isolated locations across 

the streambed in the three Delta reach cross sections surveyed 

in 2008 showing similar values for grain shear stress (approximaltey 1.0 lb/ft2

) (figs. 21–23). Observations from the 2008 surveys and the flood-frequency analysis at the Delta streamgage 

indicate that 13,300 ft3

/s was a greater-than bankfull flood; 

therefore, entrainment of the streambed in the Delta reach likely 

occurs less frequently than previously estimated by Pitlick and 

others (1999). Widespread entrainment (or “significant motion”) 

of the streambed likely occurs only at streamflows greater than 

13,300 ft3

/s. These comparisons are for the Delta reach only; no 

analysis was performed near the other cross sections surveyed 

by Pitlick and others (1999) for this river reach.

The disparity between the two studies of entrainment 

potential for the Delta study reach stems from differences in 

the bed-material sediment-particle sizes, Shields parameters 

selected, and energy slopes used in the calculations. Pitlick 

and others (1999) measured d50 at RM 56.6 as 53 mm assessed 

with a Shields paramter of 0.025; this study characterized the 

d50 at cross-section 4 (or RM 56.9) as 79 mm and selected 

Shields’ parameters of 0.035 and 0.050 (table 6). The difference in bed-material sediment-particle size likely is because 

two different techniques were used for the sediment-particlesize analysis. Pitlick and others (1999) classified sedimentparticle sizes using a gravelometer to categorically assign 

counts of sediment particles to different ranges of sizes. 

This technique mirrors sieve-analysis techniques, wherein 

square cutouts of specific sizes are used to assign a count of 

each sediment particle within each given size range. This 

report provides information based on direct measure of each 

sediment particle, producing more precise estimates of the 

sediment-particle size distribution of the reach. Comparison 

between the two techniques for the Delta reach from this study 

results in a maximum d50 of 64 mm (gravelometer) compared 

to the measured 79 mm of this study, showing that the gravelometer technique resulted in a d50 that is 19 percent smaller 

than observed. The reader is referred to the methods section of 

the report under “Streambed-sediment characterization” and 

“Incipient motion of streambed materials” for further discussion of methods used in this report regarding d50 and Shields 

parameter selection.

For the Delta study reach, bank-top survey and direct 

observation of water-surface slope produced different estimates of the energy-grade line. Pitlick and others (1999) 

estimated a bankfull energy slope of 0.0019 from a banktop survey at RM 57. In general, the estimated energy slope 

performed by Pitlick and others (1999) relies on channel form 

(bank-top heights) as an indicator of energy gradient in the 

reach. In this study, the energy slope of 0.0016 for 13,300 ft3

/s 

was based on a survey of high-water marks between crosssections 2 and 4, which encompass RM 57 (fig. 21, table 8). 

The smaller d50 and steeper “bankfull” energy slope used by 

Pitlick and others (1999) indicates potential bed-material 

entrainment at 13,300 ft3

/s streamflow conditions; whereas, 

the calculations in this study, using a coarser-sediment-particle 

size and lesser energy slope, indicate only limited bed-material 

entrainment for the same streamflow.

Gunnison at Whitewater

A study reach was established near the Gunnison River 

near Grand Junction, Colorado (09152500), streamflowgaging station. The reach was 450 ft long and began at 

the cableway that is colocated with the streamflow-gaging 

station. Water surfaces were flagged when streamflow was 

11,000 ft3

/s (05/25/2005); 1,950 ft3/s (07/08/2005); 14,000 

ft3

/s (05/23/2008); 7,700 ft3/s (06/18/2008); and 3,750 ft3/s 

(07/01/2008). Four cross sections were surveyed on October 9, 

2007: (1) at the cableway, (2) 150 ft upstream from the cableway, (3) 300 ft upstream from the cableway, and (4) 450 ft 

upstream from the cableway (fig. 24). Sediment characteristics 

were sampled at two locations upstream from the cableway 

and one location downstream from the cableway (fig. 4). The 

median sediment-particle size (d50) of the streambed sediment 

ranged from 71 to 77 mm, with a mean of 74 mm determined 

in this investitgation (table 6). The critical shear stress to 

move this particle within a gravel-framework bed is 0.88 and 

1.25 lb/ft2

 using the Shields parameter values of 0.035 and 

0.050, respectively (table 8).

Three of the four cross sections were relatively symmetrical whereas the fourth cross section, 450 ft upstream 

from the cableway, has an exposed bar along the right side 

(viewed looking downstream) of the channel (figs. 25 and 

26). The cross-channel calculated boundary shear stresses do 

not approach the minimum critical shear stress for any cross 

section or any streamflow. This indicates that the d50 particle is 

not moving at streamflows of 14,000 ft3/s or less in this study 

reach (figs. 25 and 26). The critical shear stress calculated 

with the more conservative Shields parameter (0.050) is not 

attained in any of these cross sections or streamflows. 

The mean boundary shear stress was highest for all cross 

sections for the peak streamflow of 14,000 ft3

/s (table 7). Yet, 

it was still no more than 76 percent of the minimum critical shear stress for the d50 in the GUNNISON study reach 

(table 8) and represents a peak streamflow with a 5- to 10-year 

recurrence interval and streamflow values of 12,800 and 

16,300 ft3/s, respectively (table 9).

The median sediment-particle size (d50) of the streambed 

sediment was characterized by Pitlick and others (1999) as 

50 mm near this study reach. The cross-channel calculated 

shear stresses approach or exceed the minimum critical shear 

stress for 50 mm particles at some locations in some cross 

sections for streamflows of 7,700 ft3

/s or greater (figs. 25 and 

26). This indicates that the d50 determined by Pitlick and others 
52 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

450

300

150

Cableway 09152500

108°27'15"

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)

Universal Transverse Mercator North American Datum 1983, Zone 12 North

Scale 1:6,500

38°

58'

45"

38°

59'

108°27' 108°26'45"

! 09152500

Streamflow-gaging station and number

Flow direction

Cross-section location (number indicates

 distance, in feet, upstream from cableway)

09152500 !

150

0 0.2 KILOMETER

0 0.1 0.2 MILE

0.1

EXPLANATION

Figure 24. Map showing locations of the four cross sections of the study reach on the Gunnison River near Grand 

Junction, Colorado.
Effects of Streamflow on Sediment Transport 53

Figure 25. Graphs showing boundary shear stresses, water-surface elevations, and streambed elevations 

for selected streamflows at the cross sections located 450 and 300 feet upstream from U.S. Geological Survey 

streamflow-gaging station, 09152500, Gunnison River near Grand Junction, Colorado.

EXPLANATION

Water-surface elevation

EXPLANATION

Boundary shear stress

EXPLANATION

Boundary shear stress

Streambed

Streambed

Mid-channel bar

 not surveyed

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x4

7,700 cubic feet per second

3,750 cubic feet per second

1,950 cubic feet per second

11,000 cubic feet per second

14,000 cubic feet per second

Critical shear stress for 74 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 74 millimeter particles with dimensionless Shields parameter of 0.035

Critical shear stress for 50 millimeter particles with

dimensionless Shields parameter of 0.025

4,625

4,630

4,635

4,640

4,645

0 20 40 60 80 100 120 140 160 180

0 20 40 60 80 100 120 140 160 180

0

0.5

1.0

1.5

1.25

0.88

0.42

Cross-section 300, located 300 feet upstream from U.S. Geological Survey streamflow-gaging station 09152500

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x5

7,700 cubic feet per second

1,950 cubic feet per second

3,750 cubic feet per second

11,000 cubic feet per second

14,000 cubic feet per second

Critical shear stress for 74 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 74 millimeter particles with dimensionless Shields parameter of 0.035

Critical shear stress for 50 millimeter particles with 

dimensionless Shields parameter of 0.025

4,625

4,630

4,635

4,640

4,645

0 20 40 60 12010080 240220200180160140 260

0 20 40 8060 120100 240220200180160140 260

0

0.5

1.0

1.5

1.25

0.88

0.42

Cross-section 450, located 450 feet upstream from U.S. Geological Survey streamflow-gaging station 09152500

EXPLANATION

Water-surface elevation
54 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 26. Graphs showing shear stresses, water-surface elevations, and streambed elevations for selected 

streamflows at the cross sections located 150 feet upstream from and along the cableway of U.S. Geological Survey 

streamflow-gaging station, 09152500, Gunnison River near Grand Junction, Colorado.

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation

Streambed

Streambed

Mid-channel bar

 not surveyed

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x4

7,700 cubic feet per second

3,750 cubic feet per second

1,950 cubic feet per second

11,000 cubic feet per second

14,000 cubic feet per second

Critical shear stress for 74 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 74 millimeter particles with dimensionless Shields parameter of 0.035

Critical shear stress for 50 millimeter particles with

dimensionless Shields parameter of 0.025

4,625

4,630

4,635

4,640

4,645

0 20 40 60 80 100 120 140 160 180

0 20 40 60 80 100 120 140 160 180

0

0.5

1.0

1.5

1.25

0.88

0.42

Cross-section 300, located 300 feet upstream from U.S. Geological Survey streamflow-gaging station 09152500

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x5

7,700 cubic feet per second

1,950 cubic feet per second

3,750 cubic feet per second

11,000 cubic feet per second

14,000 cubic feet per second

Critical shear stress for 74 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 74 millimeter particles with dimensionless Shields parameter of 0.035

Critical shear stress for 50 millimeter particles with

dimensionless Shields parameter of 0.025

4,625

4,630

4,635

4,640

4,645

0 20 40 8060 100 120 140 220200180160 240 260

0 20 40 8060 100 200180160140120 240220 260

0

0.5

1.0

1.5

1.25

0.88

0.42

Cross-section 450, located 450 feet upstream from U.S. Geological Survey streamflow-gaging station 09152500
Effects of Streamflow on Sediment Transport 55

(1999) is potentially moving at streamflows of 7,700 ft3/s or 

greater in this study reach (figs. 25 and 26). However, the critical shear stress calculated with the more conservative Shields 

parameter (0.050) cannot be attained in any of these cross sections or streamflows. Widespread entrainment (or “significant 

motion”) of the streambed likely occurs only at discharges 

greater than 14,000 ft3

/s. These comparisons are for the Gunnison at Whitewater reach only; no analysis was performed near 

the other cross sections surveyed by Pitlick and others (1999) 

for this river reach.

Green River near Jensen

The study reach on the Green River 5 miles downstream 

from the Green River near Jensen, Utah, streamflow-gaging 

station (09261000) was 10,000 ft long, began about 2,000 ft 

upstream from the meander bend where the first cross section 

was located, and ended about 3,800 ft downstream from an 

island that sits in the middle of the study reach. Water surfaces 

and boundary shear-stress values were obtained from the 

calibrated two-dimensional streamflow and sediment-transport 

models developed for this area representing streamflows of 

9,000, 10,600, 14,100, 17,700, and 19,000 ft3

/s. Six cross 

sections were surveyed (1) at the meander bend, (2) upstream 

from the island, (3) in the first half of the portion of the channel that flows along the left side of the island, (4) in the second 

half of the portion of the channel that flows along the left side 

of the island, (5) in the portion of the channel that flows on the 

right side of the channel, and (6) downstream from the island 

(fig. 27).

Streambed conditions within the study reach can be characterized by two dominant sediment-particle size distributions, 

which vary spatially and temporally within the system. There 

is a gravel-dominated pavement layer, which is intermittently 

exposed within the channel with varying thicknesses of a sand 

veneer along the surface. Within the study reach, flow velocities and water depths prevented direct sampling of the gravelly 

bed material so sediment-particle-size analysis was based on 

pebble-count data from exposed bars and channel margins 

in the vicinity of the gaging station located 5 mi upstream. 

Dredge samples of the sand veneer also were characterized 

at multiple locations within the reach (fig. 4). Evaluation of 

transport characteristics of each of the two sediment-particlesize distributions were used to produce the end members of a 

continuum that represent the characteristics of the channel. In 

the areas best characterized as gravel-framework beds (less 

than 20–30 percent sand), incipient motion of the gravels and 

sands are represented by the gravel critical shear stress. For 

the areas with larger portions of sand (typically expressed as 

a sand veneer overlaying the gravel-framework bed), incipient motion of the sand is represented by the sand critical shear 

stress and may decrease the shear stress needed for incipient 

motion of the gravels.

In the sand-matrix framework, the d50 of the sand veneer 

of the streambed sediment ranged from 0.25 to 2.0 mm, 

and 1.4 mm was used for the analysis of incipient-motion 

calculations (table 6). The critical shear stress needed to move 

the sand-sized particles was 0.01 and 0.02 lb/ft2 using Shields 

parameter values of 0.035 and 0.050, respectively (table 8). 

The median d50 of the bed material 5 mi upstream from the 

study reach was 56 to 64 mm, and 56 mm was used for the 

incipient-motion calculations (table 6). The critical shear stress 

to move the cobble-sized particles within the gravel-framework bed was 0.66 and 0.95 lb/ft2

 using Shields parameter 

values of 0.035 and 0.050, respectively (table 8).

For all streamflows at all cross sections the boundary 

shear stress exceeded the critical shear stress to move the 

sand-sized particles (d50 from 0.4 to 1.4 mm); however, the 

boundary shear stress does not reach the critical shear stress 

to move the cobble-sized particles (d50 from 56 to 64 mm) for 

any modeled streamflow at these cross sections (figs. 28–32). 

At cross-section 1 (upstream end of reach) boundary shear 

stress generally is symmetrical and increases slightly with 

increasing streamflow (fig. 28). The shear stress at crosssection 2 has the opposite pattern; the boundary shear stress 

decreases as streamflow increases, indicative of a backwater 

effect from the island (figs. 28 and 29). At cross-section 3, the 

boundary shear stress does not have a consistent pattern with 

increasing streamflow, which may indicate that the island continues to influence the boundary shear stress with either backwater or other eddy effects at this location (fig. 30). Moving 

downstream, cross-sections 4 and 5 have relatively constant 

boundary shear stress regardless of streamflow (figs. 30 and 

31). Cross-section 6 has a pattern similar to cross-section 1 

where boundary shear stress generally increases with increasing streamflow (figs. 31 and 32). 

The mean boundary shear stress was greatest at all cross 

sections at 17,700 ft3/s (table 7) and was greatest within the 

reach at cross-section 1 (the upstream-most cross section), 

located at the meander bend. Even the maximum was less 

than the minimum critical shear stress necessary to move the 

d50 of the cobble-sized particles that were sampled (table 8) 

and represents a peak streamflow with a 2- to 2.3-year recurrence interval (streamflow values of 17,000 and 18,100 ft3

/s, 

respectively) (table 9). The maximum modeled streamflow 

of 19,000 ft3/s represents a peak streamflow with a 2.3- to 

5-year recurrence interval (streamflow values of 18,100 and 

22,800 ft3/s, respectively) (table 9).

Figure 27 (following page). Map showing shear stress crosssection locations, 5 miles downstream from the Green River near 

Jensen, Utah, streamflow-gaging station.
109°17'

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)Universal Transverse Mercator North American Datum 1983, Zone 13 NorthScale 1:10,000

40°24'

40°24'30"

0 0.2 0.4 KILOMETER0 0.2 0.4 MILE

EXPLANATION

Cross-section location and identification

Flow direction

2 3

4

5

6

1

small secondarychannel

identified razorback sucker

spawning habitat

mid-channel bar

1

 U.S. Geological Survey 

 located 5 
Effects of Streamflow on Sediment Transport 57

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation

EXPLANATION

Water-surface elevation

EXPLANATION

Boundary shear stress

Streambed

Streambed

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

VERTICAL EXAGGERATION x18

14,100 cubic feet per second

9,000 cubic feet per second

19,000 cubic feet per second

14,100 cubic feet per second

9,000 cubic feet per second

19,000 cubic feet per second

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.035

4,740

4,745

4,750

4,755

4,760

0 80 160 240 320 400 480 560 640 720 800 880 960

0 80 160 240 320 400 480 560 640 720 800 880 960

0

0.5

1.0

1.5

0.95

0.66

Cross-section 2, upstream from island, 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x9

10,600 cubic feet per second

17,700 cubic feet per second

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.035

4,740

4,745

4,750

4,755

4,760

0

0.5

1.0

1.5

0.95

0.66

Cross-section 1, at bend in stream , 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

0 40 80 120 160 200 240 280 320 360 400 440 480

10,600 cubic feet per second

17,700 cubic feet per second

0 40 80 120 160 200 240 280 320 360 400 440 480

Figure 28. Graphs showing cross-sections 1 and 2 boundary shear stresses for the median particle size of 

56 millimeters, water-surface elevations, and streambed elevations for selected streamflows at U.S. Geological Survey 

streamflow-gaging station, 09261000, Green River near Jensen, Utah.
58 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

EXPLANATION

Water-surface elevation

EXPLANATION

Boundary shear stress

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation

Streambed

Streambed

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

14,100 cubic feet per second

9,000 cubic feet per second 10,600 cubic feet per second

19,000 cubic feet per second 17,700 cubic feet per second

Critical shear stress for 1.4 millimeter particles with dimensionless Shields parameter of 0.035 and 0.050

4,740

4,745

4,750

4,755

4,760

0 80 160 240 320 400 480 560 640 720 800 880 960

0 80 160 240 320 400 480 560 640 720 800 880 960

0

0.5

1.0

1.5

0.01−0.02

Cross-section 2, upstream from island, 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

0.01−0.02

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x9

14,100 cubic feet per second

9,000 cubic feet per second 10,600 cubic feet per second

19,000 cubic feet per second 17,700 cubic feet per second

Critical shear stress for 1.4 millimeter particles with dimensionless Shields parameter of 0.035

4,740

4,745

4,750

4,755

4,760

0

0.5

1.0

1.5 Cross-section 1, at bend in stream, 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

0 40 80 120 160 200 240 280 320 360 400 440 480

0 40 80 120 160 200 240 280 320 360 400 440 480

Distance from left bank, in feet

VERTICAL EXAGGERATION x18

Figure 29. Graphs showing cross-sections 1 and 2 boundary shear stresses for the median particle size of 

1.4 millimeters, water-surface elevations, and streambed elevations for selected streamflows at U.S. Geological 

Survey streamflow-gaging station, 09261000, Green River near Jensen, Utah.
Effects of Streamflow on Sediment Transport 59

Figure 30. Graphs showing cross-sections 3 and 4 boundary shear stresses for the median particle sizes of 1.4 and 

56 millimeters, water-surface elevations, and streambed elevations for selected streamflows at U.S. Geological Survey 

streamflow-gaging station, 09261000, Green River near Jensen, Utah.

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation

EXPLANATION

Water-surface elevation

EXPLANATION

Boundary shear stress

Streambed

Streambed

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

VERTICAL EXAGGERATION x7

14,100 cubic feet per second

9,000 cubic feet per second 10,600 cubic feet per second

19,000 cubic feet per second 17,700 cubic feet per second

Critical shear stress for 1.4 millimeter particles with dimensionless Shields parameter of 0.035 and 0.050

4,740

4,745

4,750

4,755

4,760

0 40 80 120 160 200 240 280 320 360 400

0

0.5

1.0

1.5

0.01−0.02

Cross-section 4, channel left of island, 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

0.01−0.02

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.035

0.95

0.66

0 40 80 120 160 200 240 280 320 360 400

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x8

14,100 cubic feet per second

9,000 cubic feet per second

10,600 cubic feet per second

19,000 cubic feet per second 17,700 cubic feet per second

Critical shear stress for 1.4 millimeter particles with dimensionless Shields parameter of 0.035

4,740

4,745

4,750

4,755

0

0.5

1.0

1.5Cross-section 3, channel left of island , 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

0 40 80 120 160 200 240 280 320 360 400 440

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.035

0.95

0.66

Distance from left bank, in feet

0 40 80 120 160 200 240 280 320 360 400 440
60 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

EXPLANATION

Water-surface elevation

EXPLANATION

Boundary shear stress

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation

Streambed

Streambed

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

VERTICAL EXAGGERATION x7

14,100 cubic feet per second

9,000 cubic feet per second 10,600 cubic feet per second

19,000 cubic feet per second 17,700 cubic feet per second

4,740

4,745

4,750

4,755

0 40 80 120 160 200 240 280 320 360 400 440

0

0.5

1.0

1.5

Cross-section 6, downstream from island, 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.035

0.95

0.66

0 40 80 120 160 200 240 280 320 360 400 440

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

Distance from left bank, in feet

Distance from left bank, in feet

VERTICAL EXAGGERATION x5

14,100 cubic feet per second

9,000 cubic feet per second 10,600 cubic feet per second

19,000 cubic feet per second 17,700 cubic feet per second

Critical shear stress for 1.4 millimeter particles with dimensionless Shields parameter of 0.035

0

0.5

1.0

1.5

0.01– 0.02

Cross-section 5, channel right of island, 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

0 20 40 60 80 100 120 140 160 180 200 220 240

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.050

Critical shear stress for 56 millimeter particles with dimensionless Shields parameter of 0.035

0.95

0.66

4,740

4,745

4,750

4,755

260

0 20 40 60 80 100 120 140 160 180 200 220 240 260

Figure 31. Graphs showing cross-sections 5 and 6 boundary shear stresses for the median particle sizes of 1.4 and 

(or) 56 millimeters, water-surface elevations, and streambed elevations for selected streamflows at U.S. Geological 

Survey streamflow-gaging station, 09261000, Green River near Jensen, Utah.
Sediment-Transport Applications to Resource Management 61

Figure 32. Graph showing cross-section 6 boundary shear stresses for the median particle size of 1.4 millimeters, watersurface elevations, and streambed elevations for selected streamflows at U.S. Geological Survey streamflow-gaging 

station, 09261000, Green River near Jensen, Utah.

Sediment-Transport Applications to 

Resource Management

The native fishes of the Upper Colorado River Basin 

have adapted to the diverse and unique habitat characteristics 

and geomorphic features found within the Colorado River. 

The streams that provide this habitat are characterized by 

larger channel gradients, high levels of water turbidity and 

salinity, and extreme seasonal variation in water temperature 

and streamflow. As a result, the native fishes are highly susceptible to the ecological changes that result from anthropogenic activities including streamflow regulation, habitat 

destruction and alteration, introduction of non-native fishes, 

and degraded water quality (Valdez and Muth, 2005). Habitat 

for endangered fishes in these rivers includes both gravelbed reaches (spawning-habitat and food-source locations), 

backwater areas, and overbank habitat (juvenile habitat) 

formed along the banks of sand-bed reaches (Andrews, 1986; 

McAda, 2003). The formation and maintenance of these 

habitats historically (pre-reservoir) were assumed to be in 

equilibrium with streamflow conditions and sediment supplies (Andrews, 1986).

Creation and operation of large reservoirs and other 

anthropogenic water uses (irrigation and municipal diversions) 

within these river systems have resulted in reductions of peak 

streamflows and reduced effective discharge (where effective 

discharge is defined as the flow responsible for the majority 

of geomorphic work done by a stream over a period of several 

years) (Andrews, 1986; Elliott and Parker, 1997; McAda, 

2003). Effective discharge has been reduced by as much as 

one-half in the Green River and has resulted in a 10-percent 

reduction in stream widths, which has lead to vegetation 

encroachment (Andrews, 1986). Channel narrowing and vegetation encroachment also has been observed in the Gunnison 

River (Elliott and Parker, 1997) and in the Colorado River 

near Grand Junction, Colorado (Osmundson and Kaeding, 

1991; Pitlick, 2005). Understanding how stream conditions 

EXPLANATION

Boundary shear stress

EXPLANATION

Water-surface elevation

Streambed

Elevation above North American

Vertical Datum of 1988, in feet

Shear stress, in pounds per square foot 

Distance from left bank, in feet

VERTICAL EXAGGERATION x7

Distance from left bank, in feet

14,100 cubic feet per second

9,000 cubic feet per second 10,600 cubic feet per second

19,000 cubic feet per second 17,700 cubic feet per second

4,740

4,745

4,750

4,755

0 40 80 120 160 200 240 280 320 360 400 440

0 40 80 120 160 200 240 280 320 360 400 440

0

0.5

1.0

1.5 Cross-section 6, downstream from island, 5 miles downstream from U.S. Geological Survey streamflow-gaging station 09261000

0.01–0.02 Critical shear stress for 1.4 millimeter particles with dimensionless Shields parameter of 0.035
62 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

and habitat change in response to alterations in streamflow is 

important for water administrators and wildlife managers and 

can be determined with an understanding of sediment transport 

(both bed- and suspended-sediment load).

Alteration of historic channel characteristics through 

streamflow regulation has resulted in observable changes in 

the range and number of multiple native and endangered species (Valdez and Muth, 2005; U.S. Fish and Wildlife Service, 

2011a). Separation and identification of the processes and sediment characteristics that support important physical (channel 

morphology) and biological (habitat) stream attributes within 

priority reaches of this system allows for better applied watermanagement strategies and aids recovery of the endangered 

fishes. Determination of the processes that control sediment 

transport within this system is a key step in identifying streamflow conditions responsible for restored channel morphology and habitat. Restored channel morphology and habitat is 

needed in conjunction with other non-native fish management 

for sustained recovery of endangered fishes within these river 

systems. This report demonstrates that sediment-transport conditions at selected locations within the system have significant 

dependence on the magnitude and timing of streamflows and 

water management within the system. The following section 

will present findings from this report that can aid resource 

management within the study area.

Suspended-Sediment Transport

Suspended-sediment transport can be a large part of the 

total-sediment flux within the rivers of this study and as such 

is strongly related to the geomorphology and habitat conditions found in these reaches. Suspended-sediment transport 

affects the channel form, bank and bar development, and the 

availability and quality of habitat for multiple life-stages of 

aquatic species. Regression analysis was used in this report to 

estimate suspended-sediment transport as a function of streamflow, seasonality, and temporal trends. Estimates of SS flux 

can be helpful in determining total flux of sediments within 

the river at a station or to evaluate sediment budgets between 

stations. Understanding the processes that explain the variability of SS concentration also can provide information needed 

to better manage water resources within these rivers (related 

to the timing and magnitude of flow releases and withdrawal 

from reservoirs and diversion structures) and to evaluate temporal and spatial changes at a station and within river reaches.

The particle-size range of transported sediments plays 

a strong role in many processes related to channel form and 

habitat. The primary effect of sediment transported as wash 

load is related to the clarity or turbidity of the water column, 

though wash load also effects transient depositional features 

within the stream. Wash load has limited longstanding (more 

than a few months to a year) influence on processes controlling the channel form or streambed habitat within the active 

channel. Sand-sized particles can be transported as wash load 

and as suspended load and, relative to silt/clay-sized particles, 

will interact with the streambeds at greater frequencies over 

the majority of the wetted-channel area. Thus, sand SS flux 

(and sand SS concentration) may be more strongly related to 

channel-forming fluvial processes and habitat conditions than 

silt/clay SS flux (and silt/clay SS concentration). 

Suspended-sediment transport equations using regression 

analysis were generated for the six stations that had sufficient 

data within the study area: three stations on the main-stem 

Colorado River between Cameo, Colorado, and the confluence with the Green River (CAMEO, STATELINE, and 

CISCO); one station on the Gunnison River downstream from 

the Aspinall Storage Unit (GUNNISON); and two stations on 

the Green River below Flaming Gorge Reservoir, and downstream from the confluence of the Yampa River (JENSEN and 

GREEN) (table 5). Interpretations of the variables used within 

the regression analysis aid in identification and quantification 

of the processes or mechanisms that are important controls 

on suspended-sediment transport within the system and to 

provide information on the timing of sediment inputs (supply 

changes) to the system. 

Regression analysis of the suspended-sediment data 

show that streamflow explains 40 percent or less of the variability in natural logarithm SS concentration and 72 percent 

or less of the variability in natural logarithm sand SS concentration (fig. 14). For each station, natural logarithm streamflow including y-intercept, explained 26–40 percent of the 

observed variability in natural logarithm SS concentration 

(39–72 percent for natural logarithm sand SS concentration); 

seasonality (time within the year) explained 13–16 percent of 

the observed variability in natural logarithm SS concentration 

(2.1–14 percent for natural logarithm sand SS concentration); 

and temporal trends (time over mulitple years) explained 

1.5–8.9 percent of the observed variability in natural logarithm SS concentration (0–6.2 percent for natural logarithm 

sand SS concentration). 

Identified patterns in SS concentration related to seasonal 

variations (time within year, fig. 16); temporal trends (time over 

multiple years, figs. 17 and 18); and climatic effects (differences 

between wet and dry years, fig. 19) influence sediment-transport 

conditions and have a significant effect on the shape, slope, 

and intercept of the streamflow sediment-transport relation 

(Glysson, 1987). Depictions of the typical (median) relation 

between streamflow and SS concetration is provided for each 

station in figure 15 with additional depiction of seasonal differences between SS concentration and streamflow shown in 

figures 16–19, as previously indicated. 

Figure 16 shows the annual cycle of SS concentration 

derived from each transport equation for an average year 

(artificial hydrograph produced from mean daily streamflows). Differences in the slopes and shapes of each plot 

when compared between stations or between SS concentration and sand SS concentration show seasonal differences in 

the relation between SS concentration and streamflow, also 

known as hysteresis (see section “Seasonal and Temporal 

Effects on Suspended-Sediment Transport” for further discussion on hystereisis effects) (fig. 16). Examination of the 

chronological sequences within the plots shows that the SS 
Sediment-Transport Applications to Resource Management 63

concentration for a given streamflow is seasonally dependent; that is, for a specific streamflow there can be multiple 

predicted SS concentrations depending on the time of year.

For the stations in this study where the combination of 

streamflow and seasonality terms explains a smaller portion 

of the overall variability, sediment supply to these systems is 

inherently more variable and complex. Those stations are not 

as well characterized by the transport equations and continued 

sediment monitoring through daily data collection (in place of 

transport equations) may be warranted depending on the monitoring objectives. The systems associated with those stations 

may have increased variability owing to streamflow conditions 

in tributary areas or owing to spatial variations in geology 

(erosivity) within contributing areas.

Consistent temporal patterns in the dataset may represent 

adjustments to multi-season processes within the basin. The 

trends in natural logarithm SS concentration at the GUNNISON and Green River stations (GREEN and JENSEN) may 

be a continued response to channel adjustments that have been 

underway following completion of the Aspinall Storage Unit 

and the Flaming Gorge Reservoir. Previous investigations have 

documented the effects of reductions of peak streamflow and 

reduced effective discharge on the balance of sediment storage and transport within these river systems (Andrews, 1986; 

Elliott and Parker, 1997; McAda, 2003). Relative occurrence 

of the trend-direction reversal (progression through time from 

upstream to downstream) is consistent with a basin response 

to an upstream alteration of flow regime and sediment supply. 

In general, the upstream stations (the stations closer to the 

location of the alteration) will respond more quickly to the 

alteration and reach a new equilibrium ahead of downstream 

locations, although multiple oscillations may occur within the 

system before equilibrium is achieved. The trend-direction 

reversal clearly evident on the Green River where JENSEN 

reached a trend minimum in 1992, may be followed by a trend 

reversal at GREEN, but the lack of recent data (last sample 

was collected in 2000) precludes an assessment of the last 

decade (fig. 17). Trends in sand SS concentration at JENSEN 

may be an effect of bank stabilization, vegetation encroachment, or other anthropogenic changes (water management or 

land use) or climatic effects within the basin that have reduced 

fine-sediment (less than 0.0625 mm) entrainment (fig. 18). The 

Colorado (CAMEO) and Gunnison River (GUNNISON) have 

no evidence of reaching equilibrium conditions in SS concentration. This indicates that larger time scales may be needed to 

reach stable conditions within this system or that the observed 

trends are in response to more temporally continuous anthropogenic changes or climatic effects within the basin (fig. 17). 

The reversal in natural logarithm sand SS concentration at 

STATELINE and GUNNISON may indicate that a similar 

reduction in fine-sediment (less than 0.0625 mm) entrainment 

is occurring in the Colorado River from bank stabilization, 

vegetation encroachment, or land-use changes (fig. 18).

Significant differences (p-value less than 0.05) in the 

slope and intercept between natural logarithm streamflow 

and natural logarithm SS concentration were tested for at all 

stations, based on classification as wet and dry years, and were 

determined at five of the six stations (rising-limb: CAMEO, 

CISCO, JENSEN, and GREEN; falling-limb: GUNNISON) 

(fig. 19). No statistically significant differences were determined between any multi-year cycle comparison and may 

be indicative of the smaller dataset available for such comparisons. The natural logarithm SS concentration during wet 

years is typically higher than during dry years for the same 

streamflow (rising-limb) and is less strongly controlled (flatter 

slopes) by streamflow magnitude. For GUNNISON (fallinglimb), differences in natural logarithm SS concentration at 

smaller streamflow values (less than 7,000 ft3

/s) show that dry 

years have higher concentrations than wet years, and at larger 

streamflows the concentrations are lower than wet years. Differences in sediment-transport processes or water management 

on the Gunnison River (Aspinall Storage Unit and (or) Ridgeway Reservoir) may be causing the inconsistency between 

GUNNISON and nearby CAMEO and CISCO. 

Some of the differences determined between wet and dry 

years (rising-limb) may be affected by the sediment continuity 

between reaches and the size and location of reservoirs. Areas 

that are downstream from large main-stem reservoirs may not 

show as strong an influence between wet and dry years. This 

may be because the reservoirs act effectively as sediment traps, 

resulting in reduced downstream transport of sediment, thus 

lessening the effect that wet and dry years have on sedimenttransport dynamics. As such, stations unaffected by large mainstem reservoirs, like CAMEO, have stronger effects from wet 

and dry years because reservoirs are located distally within the 

watershed. Reduced effects of wet and dry years occur at GUNNISON and STATELINE and are likely related to the effects 

from sediment traps on the Gunnison River (Aspinall Storage 

Unit and Ridgeway Reservoir). The effect of these reservoirs is 

no longer observable at CISCO, potentially in response to sediment inputs from the Dolores River. The sediment-rich Yampa 

River Basin may alleviate the effects from sediment storage in 

Flaming Gorge Reservoir for stations on the Green River below 

the Yampa River confluence (JENSEN and GREEN) such that 

differences in sediment-transport conditions between wet and 

dry years are significant. Future sediment monitoring at locations in reaches on the Green River below Flaming Gorge and 

upstream from the Yampa River confluence could be used for 

confirmation of this hypothesis.

Incipient Motion and Bed-Load Transport

Incipient motion of streambed material (often occurring 

as bed-load transport) and the sorting of bed materials are 

important controls on channel form and habitat and are strongly 

related to the channel morphology and habitat conditions within 

these rivers (Knighton, 1998). The characteristics of bed material strongly control the down-cutting and transport of sediments 

especially in basins with modifications to flow regimes resulting 

from water management. To prevent further channel narrowing 

and loss of functioning side channel- and backwater-habitat, it 

may be necessary to break up the layer of gravels and cobbles 
64 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

that have created a pavement layer in the streambeds of these 

channels through armoring. When the pavement layer is broken 

up and possibly entrained, the finer gravels and sands that 

underlie the pavement layer, or are trapped between the cobbles, 

also are entrained allowing for adjustment and maintenance of 

channel dimensions (Milhous, 1982). Encroaching vegetation in 

the riparian areas can be eradicated when the alluvial banks and 

bars are regularly inundated and when significant entrainment 

of the d50 occurs (Friedman and Auble, 1999). The composition of streambeds also relates to aquatic ecosystem food 

supply (benthic invertebrates) as well as spawning conditions 

(McAda, 2003). Deposition of fine sediment on top of benthic 

or spawning habitat (seasonally dependent) can reduce habitat 

quality and require stream conditions capable of (1) removal 

of fine sediments (flushing of fines) from gravel-bed reaches or 

(2) entrainment of the gravel-bed material to expose and transport fine materials, which are sheltered by the larger gravels, in 

order to restore the habitat quality. Characterization of bedmaterial sediment-particle sizes and forces needed to initiate 

motion of these particles can provide information to better manage water resources within these rivers.

Comparison between boundary shear stresses of multiple 

streamflows and the relative mobility of bed material (d50, 

median sediment-particle sizes) characterizes the effects of 

flow magnitude on mobilization of framework grains within 

the streambed. Observations at multiple cross sections within 

two reaches of the Gunnison River downstream from the 

Aspinall Storage Unit (09144250, Gunnison River at Delta, 

Colorado, figs. 21–23; and 09152500, Gunnison River at 

Grand Junction, Colorado, figs. 24–26) show ineffectual mobilization of most, if not all, areas within the surveyed cross 

sections. The largest surveyed streamflow exceeded bankfull 

conditions at the Gunnison River at Delta, Colorado, with a 

peak streamflow magnitude of 13,300 ft3

/s (recurrence interval 

of 5 to 10 years, table 9). At the Gunnison River near Grand 

Junction, Colorado, the largest surveyed peak streamflow was 

14,000 ft3

/s (recurrence interval of 5 to 10 years, table 9). 

Observations at multiple cross sections within a study 

reach of the Green River downstream from Flaming Gorge 

Reservoir (09261000, Green River near Jensen, Utah, 

figs. 27–32) show a range of potential transport conditions. 

Streambed conditions within the study reach on the Green 

River can be characterized by two dominant-size distributions 

that vary spatially and temporally within the system. A graveldominated pavement layer was exposed intermittently within 

the channel with varying thicknesses of a sand veneer along the 

surface. Evaluation of transport characteristics of each of the 

two size distributions was used to produce the end members 

of a continuum that represent the characteristics of the channel. Incipient motion of specific particles within this area may 

occur along a continuum that is defined by the proportion of 

sand within a given gravel mixture (gravel critical shear stresses 

were less than 20–30 percent sand; sand critical shear stress for 

sand veneer with reduction in the gravel critical shear possible). 

Incipient-motion analysis shows ineffectual mobilization of 

most, if not all, areas within the surveyed cross sections of the 

larger bed material (based on gravel d50) including peak streamflows of as much as 19,000 ft3

/s (recurrence interval of 2.3 to 

5 years, table 9). However, when the sand veneer is present at 

these cross sections, or where the portion of sand within the 

bed material exceeds 20–30 percent of the total, mobilization of 

the bed material (based on sand d50) will occur at most locations within the surveyed cross sections for peak streamflows 

of 9,000–19,000 ft3/s (recurrence intervals ranging from 1 to 

5 years, table 9) with mobilization of gravels possible in some 

areas. Further sediment-particle-size classification and determination of the portions of sands throughout the reach would be 

needed to quantify the portion of the gravel bed that is mobilized within the reach.

Case Study: Evaluation of Sand Transport in the 

Green River near Jensen, Utah

Application of the two-dimensional stream hydraulics 

and sediment-transport models provides enhanced capabilities 

for evaluations of dynamic reach-scale processes that affect 

habitat suitability. An evaluation of the sediment-transport 

conditions for sand-sized particles in spawning habitat can be 

used to determine streambed conditions and provide enhancement to conceptual models within these systems. Identification 

of processes that limit sediment transport within these systems 

is necessary to correctly identify proper streamflow targets 

that create and maintain habitat within these systems. Linking physical measurements of critical habitat to conceptual 

and process-based models can define critical relations between 

habitat and streamflow conditions. Those links provide a better 

understanding of the processes that affect the sediment-transport 

characteristics, which are important to the maintenance of 

endangered fish spawning habitat, and can be used to inform 

the flow-recommendations process that currently (2012) 

guides water management of Flaming Gorge Reservoir (fig. 3). 

Razorback sucker spawning occurs over cobble- or gravel-sized 

streambed material, with streamflow velocities less than 3.3 ft/s 

and flow depths of less than 3.3 ft (Valdez and Muth, 2005). 

Spawning occurs during the rising-limb of the snowmelt-runoff 

hydrograph when water temperatures are approximately 15°C, 

typically mid-April to June (Valdez and Muth, 2005). The eggs 

are a sticky mass laid down by the females, and when gravels 

are present and flushed of finer sediments (sands) the egg-mass 

adheres to the surface of the gravels and remains in place. When 

sands overlay the gravels along the streambed, the egg-mass 

adheres to the sands instead of the gravels. Without the added 

weight of the gravels, the egg-mass can be transported downstream where predation and scattering of the eggs is more likely 

to occur. During spawning seasons, female razorback suckers 

have been reported to remove thin layers of sands in order to 

expose the covered gravels along the spawning habitat (Wick, 

1997). If changes in sediment transport within the reach result in 

the migration of sands along the streambed (transported as bed 

load), deposits of eggs that have adhered to the gravel bed can 

become smothered by sand preventing successful emergence of 

the larvae (Wick, 1997). 
Sediment-Transport Applications to Resource Management 65

Figure 33. Maps showing comparison 

of the modes of sediment transport for 

sands in a reach of the Green River near 

identified razorback sucker spawning 

habitat at a modeled streamflow of 

9,000 cubic feet per second.

Evaluation of SedimentTransport and SpawningHabitat Conditions

Transport conditions for two 

selected sizes of sands were compared 

within the Green River study reach 

(fig. 27). Sand-sized particles ranging from 0.5 to 1.4 mm represent the 

range in sediment-particle size that 

is commonly present in the reach 

upstream from the spawning habitat 

and are consistent with sedimentparticle sizes found in previous investigations (Wick, 1997). These two 

sediment-particle sizes represent the 

d16 through the d84 sizes for sediments 

sampled at selected locations within 

the reach using dredge samplers (Williams and others, 2009). Using this 

range of sand-sized particles provides 

representative measures of how most 

sands are moving within the system. 

Variations in sediment mobility 

and transport mode can be characterized within the study reach over the 

range of streamflows typical of the 

spawning seasons (mid-April to June, 

post-Flaming Gorge Reservoir, WY 

1965–2008). Streamflow conditions 

ranged from 5,030 to 13,500 ft3

/s and 

typically were between 7,310 and 

12,250 ft3/s, based on the 25th and 

75th percentiles of mean daily streamflows at USGS streamflow-gaging 

station, 09261000, Green River near 

Jensen, Utah (April 15–May 31 for 

WY 1965–2008) (U.S. Geological 

Survey, 2011). Characterizations 

of sand transport for a reach of the 

Green River containing identified 

razorback sucker spawning habitat 

were evaluated using the output from 

modeled stream hydraulics representative of 9,000; 10,600; 14,100; 

17,700; and 19,000 ft3/s (figs. 33–37, 

respectively).

109°17'30" 109°17' 109°16'30"

40°

24'

30"

40°

24'

40°

24'

30"

40°

24'

109°17'30" 109°17' 109°16'30"

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)

Universal Transverse Mercator North American Datum 1983, Zone 13 North

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 1.4

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 0.5

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended
66 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Figure 34. Maps showing comparison 

of the modes of sediment transport for 

sands in a reach of the Green River near 

identified razorback sucker spawning 

habitat at a modeled streamflow of 

10,600 cubic feet per second.

109°17'30" 109°17' 109°16'30"

40°

24'

30"

40°

24'

40°

24'

30"

40°

24'

109°17'30" 109°17' 109°16'30"

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)

Universal Transverse Mercator North American Datum 1983, Zone 13 North

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 1.4

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 0.5

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended
Sediment-Transport Applications to Resource Management 67

Figure 35. Maps showing comparison 

of the modes of sediment transport for 

sands in a reach of the Green River near 

identified razorback sucker spawning 

habitat at a modeled streamflow of 

14,100 cubic feet per second. 

109°17'30" 109°17' 109°16'30"

40°

24'

30"

40°

24'

40°

24'

30"

40°

24'

109°17'30" 109°17' 109°16'30"

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)

Universal Transverse Mercator North American Datum 1983, Zone 13 North

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 1.4

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 0.5

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended
68 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

109°17'30" 109°17' 109°16'30"

40°

24'

30"

40°

24'

40°

24'

30"

40°

24'

109°17'30" 109°17' 109°16'30"

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)

Universal Transverse Mercator North American Datum 1983, Zone 13 North

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 1.4

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 0.5

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended

Figure 36. Maps showing comparison 

of the modes of sediment transport for 

sands in a reach of the Green River near 

identified razorback sucker spawning 

habitat at a modeled streamflow of 

17,700 cubic feet per second.
Sediment-Transport Applications to Resource Management 69

Figure 37. Maps showing comparison 

of the modes of sediment transport for 

sands in a reach of the Green River near 

identified razorback sucker spawning 

habitat at a modeled streamflow of 

19,000 cubic feet per second.

109°17'30" 109°17' 109°16'30"

40°

24'

30"

40°

24'

40°

24'

30"

40°

24'

109°17'30" 109°17' 109°16'30"

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)

Universal Transverse Mercator North American Datum 1983, Zone 13 North

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

0 0.2 0.4 KILOMETERS

0 0.2 0.4 MILES

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 1.4

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended

EXPLANATION

Mode of sediment transport,

 in percent suspended, for 0.5

 millimeter sediment-particles

Flow direction

0 Bed load (dunes)

50 Mixed

100 Suspended
70 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Characterization of the Sand-Transport 

Conditions within the Study Reach

Increasing streamflow within the study reach has variable effects on sand-transport conditions (figs. 27, and 

33–37). Transport of both sand sizes occurs throughout the 

main channel of the reach over all modeled streamflows 

(9,000–19,000 ft3/s). Along and upstream from the meander 

bend for modeled streamflows up to 14,100 ft3/s, increases in 

streamflow results in increases in the proportion of sands carried in suspension (based on calculations of the Rouse numbers 

and reference to table 2); increases in streamflow between the 

largest modeled streamflows (17,700 and 19,000 ft3/s) results in 

a reduction in the percentage of sand transported in suspension. 

The areas immediately upstream from the mid-channel bar generally show decreases in the percentage of sand transported in 

suspension as streamflow increases. The small secondary channel along river-right (right side of the river, as viewed looking 

downstream) just upstream from the mid-channel bar becomes 

inundated at 9,000 ft3

/s and begins transporting 0.5 and 1.4 mm 

sands into the main channel at a streamflow of 17,700 ft3/s. 

Flow along river-left of the mid-channel bar shows reductions 

in the percentage of sand transported in suspension between 

streamflows 9,000 and 14,100 ft3/s followed by marked 

increase in the percentage of sand transported in suspension at 

larger streamflows (17,700 and 19,000 ft3/s). The percentage of 

sand transported in suspension is relatively consistent over the 

entire range of modeled streamflows river-right of the midchannel bar (between cross-sections 2, 5, and 6; fig. 27). Transport conditions downstream from the mid-channel bar show a 

decrease in the percentage of sand transported in suspension 

with increases in streamflow between 9,000 and 17,700 ft3/s. 

However, the percentage of sand transported in suspension 

increases at larger streamflows (17,700 and 19,000 ft3/s) and is 

greatest at modeled streamflows of 17,700 ft3/s.

Identification of Processes Controlling Sediment 

Transport in the Study Reach

The constraints on sand transport within the study reach 

can be shown in comparisons of boundary shear stress for 

the five modeled streamflows. Evaluation of model conditions along a longitudinal profile (fig. 38) was done to compare changes in transport conditions along the study reach 

from upstream to downstream. Boundary shear stress for all 

modeled streamflows generally was greater upstream and 

decreased downstream from the mid-channel bar, with the 

reductions occurring just upstream from or along the midchannel bar (fig. 39). In areas river-right of the mid-channel 

bar, there is a sudden reduction in boundary shear stress 

of approximately 50 percent (relative to conditions justupstream-from the bar), which is maintained downstream from 

the mid-channel bar. Along river-left of the mid-channel bar 

there is a similar reduction in boundary shear stress, which is 

quickly regained and then gradually reduced to levels similar 

to river-right of the mid-channel bar. 

Comparisons between the modeled streamflows show 

that in areas upstream from the mid-channel bar, increases 

in streamflow generally correspond to increases in boundary 

shear stress (fig. 40). In areas just upstream from the midchannel bar there is a reversal in the relation between boundary shear stress and streamflow and increases in streamflow 

result in decreases in boundary shear stress. Within areas 

river-right of and downstream from the mid-channel bar, 

the boundary shear stress tends to be largest for the 9,000 

and 17,700 ft3

/s streamflows and smallest for the 10,600 and 

14,100 ft3/s streamflows. Along areas river-left of the midchannel bar, larger streamflows (17,700 and 19,000 ft3

/s) have 

increased boundary shear stresses and smaller streamflows 

have decreased boundary shear stresses.

Comparisons were done among water-surface elevations 

for the five modeled streamflows and the effects on sand transport to investigate causality. Increases in streamflow result in 

changes in flow depth and changes to water-surface slopes, 

though, these changes may not always be unidirectional within 

a channel. Water-surface elevations for the streamflow models 

show that in the reach upstream from the mid-channel bar, 

water-surface slope remains nearly constant (fig. 40). For areas 

along and downstream from the mid-channel bar, as streamflow increases water-surface slopes decrease (fig. 40). Along 

the mid-channel bar, water-surface slopes decrease from 

0.00069 (9,000 ft3/s) to 0.00043 (19,000 ft3/s), and downstream from the mid-channel bar they decrease from 0.00038 

(9,000 ft3/s) to 0.00024 (19,000 ft3/s). This is approximately a 

37-percent reduction in water-surface slope between 9,000 and 

19,000 ft3/s for areas along and downstream from the midchannel bar.

A previous investigation (Wick, 1997) reported that 

sediment deposition on the spawning habitat (figs. 38–40) 

may result from backwater effects (decreases in water-surface 

slope) produced in the areas along the mid-channel bar at 

streamflows above 14,500 ft3/s. The backwater effect is 

reported to arise from a channel constriction (reduction in flow 

area) just downstream from the mid-channel bar (Wick, 1997). 

Reductions in water-surface slope are observed within the 

simulations of this analysis along the mid-channel bar (at the 

downstream end) and are consistent with findings from Wick 

(1997), although backwater effects appear more substantial 

along river-left (fig. 40). A small secondary channel (identified in figs. 27 and 38) also was identified as a locally important source area for sands that are deposited on the spawning 

habitat at streamflows of 11,500 ft3/s and greater. Comparisons of model simulations from this analysis showed limited 

transport of sands in isolated locations within the secondary 

channel at streamflow of 10,600 ft3/s with more extensive 

continuous transport at streamflows of 14,100 ft3/s and greater 

(figs. 33–37). 

Figure 38 (following page). Map showing longitudinal profile for 

modeled output, 5 miles downstream from the Green River near 

Jensen, Utah, streamflow-gaging station.
EXPLANATION Longitudinal profile of modeled output Flow direction smalllsecondary channel small secondary

109°17'

Orthoimages from U.S. Department of Agriculture National Agriculture Imagery Program (2007)Universal Transverse Mercator North American Datum 1983, Zone 13 NorthScale 1:10,000

40°24'

40°24'30"

0 0.2 0.4 KILOMETER0 0.2 0.4 MILE

identified razorback suckerspawning habitat

mid-channel bar
72 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Evaluations of the processes that are important in understanding sediment deposition on the spawning habitat near the 

mid-channel bar are not limited to stream-transport conditions 

within the spawning-habitat reach. Considerations of sediment 

availability and net changes in sediment transport between 

upstream reaches and the spawning habitat are important. As 

previously mentioned, sands are mobile throughout the main 

channel for all modeled streamflows (9,000–19,000 ft3

/s), but 

in areas upstream from the mid-channel bar (and spawning 

habitat) increases in streamflow tend to increase boundary 

shear stress and the percentage of sediment transported in 

suspension. Increases in boundary shear stress increase the 

percentage of sediment transported in suspension resulting in 

increased transport rates (bed-load transport tends to occur in 

sporadic starts and stops and suspended transport moves at 

rates closer to water velocities). 

Within the spawning habitat, increases in streamflow 

result in decreases in water-surface slope and varied responses 

to boundary shear stress, although the percentage of sand 

transported in suspension is relatively unchanged. Recall that 

Wick (1997) reported that deposition of sand on the spawning 

habitat does not occur at streamflows less than 14,500 ft3/s, 

which corresponds to a difference in boundary shear stress 

between the upstream reach and the spawning areas of 

Figure 39. Graph showing boundary shear stress along longitudinal profile of a reach 5 miles downstream from the Green River near 

Jensen, Utah, streamflow-gaging station.

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

Distance downstream along longitudinal profile (see figure 38), in feet

EXPLANATION

Boundary shear stress for selected streamflows (dashed lines represent conditions river-left of mid-channel bar)

9,000 cubic feet per second

10,600 cubic feet per second

14,100 cubic feet per second

17,700 cubic feet per second

19,000 cubic feet per second

Boundary shear stress, in punds per square foot

River-right along

mid-channel bar

River-left along

mid-channel bar

Identified

razorback sucker

spawning habitat

Upstream from mid-channel bar Mid-channel bar Downstream from mid-channel bar

Figure 40 (following page). Graphs showing A, relative watersurface slopes and B, water-surface elevations along longitudinal 

profile of a reach 5 miles downstream from the Green River near 

Jensen, Utah, streamflow-gaging station.

0.06 lb/ft2 or 33 percent. At larger streamflows where depositions are reported to occur, the difference in boundary shear 

stress between the upstream reach and the spawning-habitat 

areas increases to 0.13 lb/ft2 or 68 percent. 

At larger streamflows (14,100–17,700 ft3/s), sediment 

upstream from the mid-channel bar is transported in greater 

amounts and likely at greater rates than can be transported 

by the conditions at the spawning-habitat reach. This may 

exceed a threshold between the two areas, thus resulting in a 

disequilibrium and net deposition of sands on the spawning 

habitat at higher streamflows (14,100–17,700 ft3

/s). Spawning habitat may be less suitable at these higher streamflows 

owing to deposition of sands on the spawning habitat under 

these conditions.
Sediment-Transport Applications to Resource Management 73

4,747

4,748

4,749

4,750

4,751

4,752

4,753

4,754

4,755

4,756

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

Relative water-surface profiles for slope comparisons

Distance downstream along longitudinal profile (see figure 38), in feet

Upstream from mid-channel bar Mid-channel bar Downstream from mid-channel bar

River-left along

mid-channel bar

River-right along

mid-channel bar Identified

razorback sucker

spawning habitat

EXPLANATION

Water-surface elevations for selected streamflows (dashed lines represent conditions river-left of mid-channel bar)

9,000 cubic feet per second

10,600 cubic feet per second

14,100 cubic feet per second

17,700 cubic feet per second

19,000 cubic feet per second

Elevation above North American Vertical Datum of 1988, in feet

VERTICAL SCALE GREATLY EXAGGERATED

4747

4748

4749

4750

4751

4752

4753

4754

4755

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

4747

4748

4749

4750

4751

4752

4753

4754

4755

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

A

B
74 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Summary

The Colorado River Basin provides habitat for 14 native 

fish, including 4 endangered species protected under the Federal Endangered Species Act of 1973. These endangered fish 

species once thrived in the Colorado River system, but waterresource development, including the building of numerous 

diversion dams and several large reservoirs, and the introduction of non-native fish, resulted in large reductions in the 

numbers and range of the four species through loss of habitat 

and stream function. Understanding how stream conditions 

and habitat change in response to alterations in streamflow 

is important for water administrators and wildlife managers 

and can be determined from an understanding of sediment 

transport. Characterization of the processes that are controlling sediment transport is an important first step in identifying 

flow regimes needed for restored channel morphology and 

the sustained recovery of endangered fishes within these river 

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

the Upper Colorado River Endangered Fish Recovery Program, Bureau of Reclamation, U.S. Fish and Wildlife Service, 

Argonne National Laboratory, Western Area Power Administation, and Wyoming State Engineer’s Office, began a study 

in 2004 to characterize sediment transport at selected locations on the Colorado, Gunnison, and Green Rivers to begin 

addressing gaps in existing datasets and conceptual models of 

the river systems.

This report identifies and characterizes the relation 

between streamflow (magnitude and timing) and sediment 

transport and presents the findings through discussions of 

(1) suspended-sediment transport, (2) incipient motion of 

streambed material, and (3) a case study of sediment-transport 

conditions for a reach of the Green River identified as a razorback sucker spawning habitat.

Estimation of suspended sediment (SS) flux can be 

accomplished using sediment-transport curves, which define 

the relation between SS flux and relevant explanatory variables such as streamflow, seasonality, and time. Understanding the relation between streamflow and suspended-sediment 

transport can aid in the evaluation of physical and temporal 

processes that affect sediment transport. Inter-annual conditions can be important in sediment supply and storage. The 

sediment-streamflow relation may change following a hydrological ‘wet’ or ‘dry’ year or period. Comparisons were made 

between differing annual cycles (1-year periods) and between 

multi-year cycles (1-year periods following specific multi-year 

periods). This analysis was designed to identify antecedent 

conditions that produced discernable changes in the slope and 

intercept of the streamflow sediment-transport relation.

Suspended-sediment transport can be a large part of the 

total-sediment flux within the rivers of this study and as such 

is strongly related to the geomorphology and habitat conditions found in these reaches. Suspended-sediment transport 

affects the channel form, bank and bar development, and the 

availability and quality of habitat for multiple life-stages of 

aquatic species. Regression analysis was used in this report to 

estimate SS transport as a function of streamflow, seasonality, 

and temporal trends. Estimates of SS flux can be helpful in 

determining total flux of sediments within the river at a station 

or to evaluate sediment budgets between stations. Understanding the processes that explain the variability of SS concentration also can provide information needed to better manage 

water resources within these rivers (related to the timing and 

magnitude of flow releases and withdrawal from reservoirs 

and diversion structures) and to evaluate temporal and spatial 

changes at a station and within river reaches.

The sediment-particle-size range of transported sediments plays a strong role in many processes related to channel 

form and habitat. The primary effect of sediment transported 

as wash load is related to the clarity or turbidity of the water 

column, though wash load also effects transient depositional 

features within the stream. Wash load has limited longstanding (more than a few months to a year) influence on processes 

controlling the channel form or streambed habitat within the 

active channel. Sand-sized particles can be transported as 

wash load and as suspended load and, relative to silt/clay-sized 

particles, will interact with the streambeds at greater frequencies over the majority of the wetted-channel area. Thus, sand 

SS flux (and sand SS concentration) may be more strongly 

related to channel-forming fluvial processes and habitat conditions than silt/clay SS flux (and silt/clay SS concentration). 

Suspended-sediment transport equations using regression 

analysis were generated for the six stations that had sufficient 

data within the study area: three stations on the main-stem 

Colorado River between Cameo, Colorado, and the confluence with the Green River; one station on the Gunnison River 

downstream from the Aspinall Storage Unit; and two stations 

on the Green River below Flaming Gorge Reservoir, and 

downstream from the confluence of the Yampa River. Interpretations of the variables used within the regression analysis aid 

in identification and quantification of the processes or mechanisms that are important controls on suspended-sediment 

transport within the system and to provide information on the 

timing of sediment inputs (supply changes) to the system. 

Regression analysis of the suspended-sediment data 

show that streamflow explains 40 percent or less of the variability in natural logarithm SS concentration and 72 percent 

or less of the variability in natural logarithm sand SS 

concentration. For each station, natural logarithm streamflow including y-intercept, explained 26–40 percent of the 

observed variability in natural logarithm SS concentration 

(39–72 percent for natural logarithm sand SS concentration); 

seasonality (time within the year) explained 13–16 percent of 

the observed variability in natural logarithm SS concentration (2.1–14 (Wick, 1997) percent for natural logarithm sand 

SS concentration); and temporal trends (time over mulitple 

years) explained 1.5–8.9 percent of the observed variability 

in natural logarithm SS concentration (0–6.2 percent for 

natural logarithm sand SS concentration).

Identified patterns in SS concentration related to 

seasonal variations (time within year); temporal trends 

(time over multiple years) and climatic effects (differences 
Summary 75

between wet and dry years) influence sediment-transport 

conditions and have a significant effect on the shape, slope, 

and intercept of the streamflow sediment-transport relation. 

Depictions of the typical (median) relation between streamflow and SS concentration shows that the SS concentration 

for a given streamflow is seasonally dependent; that is, for 

a specific streamflow there can be multiple predicted SS 

concentrations depending on the time of year. For the stations in this study where the combination of streamflow and 

seasonality terms explains a smaller portion of the overall 

variability, sediment supply to these systems is inherently 

more variable and complex. Those stations are not as well 

characterized by the transport equations and continued sediment monitoring through daily data collection (in place of 

transport equations) may be warranted depending on the 

monitoring objectives. The systems associated with those 

stations may have increased variability owing to streamflow 

conditions in tributary areas or owing to spatial variations in 

geology (erosivity) within contributing areas.

Consistent temporal patterns in the dataset may represent 

adjustments to multi-season processes within the basin. The 

trends in natural logarithm SS concentration at the Gunnison and Green River stations may be a continued response 

to channel adjustments that have been underway following 

completion of the Aspinall Storage Unit and the Flaming 

Gorge Reservoir, respectivley. Previous investigations have 

documented the effects of reductions of peak streamflow and 

reduced effective discharge on the balance of sediment storage 

and transport within these river systems. Relative occurrence 

of the trend-direction reversal (progression through time from 

upstream to downstream) is consistent with a basin response 

to an upstream alteration of flow regime and sediment supply. 

The Colorado and Gunnison River stations have no evidence 

of reaching equilibrium conditions in SS concentration. This 

indicates that larger time scales may be needed to reach stable 

conditions within this system or that the observed trends are 

in response to more temporally continuous anthropogenic 

changes or climatic effects within the basin.

Significant differences (p-value less than 0.05) in the 

slope and intercept between natural logarithm streamflow and 

natural logarithm SS concentration were tested for at all stations, based on classification as wet and dry years, and were 

determined at five of the six stations. No statistically significant differences were determined between any multi-year 

cycle comparison and may be indicative of the smaller dataset 

available for such comparisons. The natural logarithm SS 

concentration during wet years is higher than during dry years 

for the same streamflow (rising-limb) and is less strongly 

controlled (flatter slopes) by streamflow magnitude. Some of 

the differences determined between wet and dry years (risinglimb) may be affected by the sediment continuity between 

reaches and the size and location of reservoirs. Areas that are 

downstream from large main-stem reservoirs may not show 

as strong an influence between wet and dry years. This may 

be because the reservoirs act effectively as sediment traps, 

resulting in reduced downstream transport of sediment, thus 

lessening the effect that wet and dry years have on sedimenttransport dynamics.

Incipient motion of streambed material (often occurring as bed-load transport) and the sorting of bed materials 

are important controls on channel form and habitat and are 

strongly related to the channel morphology and habitat conditions within these rivers. Comparison between boundary shear 

stresses of multiple streamflows and the relative mobility of 

bed material (d50, median sediment-particle sizes) characterizes 

the effects of flow magnitude on mobilization of framework 

grains within the streambed. Observations at multiple cross 

sections within two reaches of the Gunnison River downstream 

from the Aspinall Storage Unit show ineffectual mobilization 

of most, if not all, areas within the surveyed cross sections. The 

largest surveyed streamflow exceeded bankfull conditions at 

the Gunnison River at Delta, Colorado, with a peak streamflow 

magnitude of 13,300 cubic feet per second (ft3

/s) (recurrence 

interval of 5 to 10 years). At the Gunnison River near Grand 

Junction, Colorado, the largest surveyed peak streamflow was 

14,000 ft3

/s (recurrence interval of 5 to 10 years).

Observations at multiple cross sections within a study 

reach of the Green River downstream from Flaming Gorge 

Reservoir show a range of potential transport conditions. 

Streambed conditions within the study reach on the Green 

River can be characterized by two dominant-size distributions 

that vary spatially and temporally within the system. A graveldominated pavement layer was exposed intermittently within 

the channel with varying thicknesses of a sand veneer along 

the surface. Evaluation of transport characteristics of each of 

the two size distributions was used to produce the end members of a continuum that represent the characteristics of the 

channel. Incipient motion of specific particles within this area 

may occur along a continuum that is defined by the proportion 

of sand within a given gravel mixture. Incipient-motion analysis shows ineffectual mobilization of most, if not all, areas 

within the surveyed cross sections of the larger bed material 

including peak streamflows of as much as 19,000 ft3

/s (recurrence interval of 2.3 to 5 years). However, when the sand 

veneer is present at these cross sections, or where the portion 

of sand within the bed material exceeds 20–30 percent of the 

total, mobilization of the bed material will occur at most locations within the surveyed cross sections for peak streamflows 

of 9,000–19,000 ft3

/s (recurrence intervals ranging from 1 to 

5 years) with mobilization of gravels possible in some areas. 

Further sediment-particle-size classification and determination 

of the portions of sands throughout the reach would be needed 

to quantify the portion of the gravel bed that is mobilized 

within the reach.

Application of the two-dimensional stream hydraulics 

and sediment-transport models provides enhanced capabilities 

for evaluations of dynamic reach-scale processes that affect 

habitat suitability. Understanding the processes that affect the 

sediment-transport characteristics, which are important to the 

maintenance of endangered fish spawning habitat, can be used 

to inform the flow-recommendations process that currently 

(2012) guides water management of Flaming Gorge Reservoir.
76 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Evaluations of the processes controlling sediment deposition on the spawning habitat near the mid-channel bar are 

not limited to stream-transport conditions within the spawning-habitat reach. Considerations of sediment availability and 

net changes in sediment transport between upstream reaches 

and the spawning habitat are important. Sands are mobile 

throughout the main channel for all modeled streamflows 

(9,000–19,000 ft3

/s), but in areas upstream from the midchannel bar (and spawning habitat) increases in streamflow 

tend to increase transport rates. Within the spawning habitat, 

increases in streamflow result in decreases in water-surface 

slope and varied responses to boundary shear stress. At larger 

streamflows (14,100–17,700 ft3/s), sediment upstream from 

the mid-channel bar is transported in greater amounts and 

likely at greater rates than can be transported by the conditions at the spawning-habitat reach. This may exceed a 

threshold between the two areas resulting in a disequilibrium 

and net deposition of sands on the spawning habitat at higher 

streamflows (14,100–17,700 ft3/s). Spawning habitat may be 

less suitable at these higher streamflows owing to deposition 

of sands on the spawning habitat under these conditions.

References Cited

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terms (revised ed.): Garden City, N.Y., Anchor Books.

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U.S. Geological Survey Water-Resources Investigations 

Report 78–105, 33 p.

Andrews, E.D., 1980, Effective and bankfull discharges of 

streams in the Yampa River Basin, Colorado and Wyoming: 

Journal of Hydrology, v. 46, p. 311–330.

Andrews, E.D., 1983, Entrainment of gravel from naturally 

sorted riverbed material: Geological Society of America 

Bulletin, v. 94, p. 1225–1231.

Andrews, E.D., 1986, Downstream effects of Flaming Gorge 

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Bradu, Dan, and Mundlak, Yair, 1970, Estimation in lognormal linear models: Journal of the American Statistical 

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Butler, D.L., and Leib, K.L., 2002, Characterization of 

selenium in the lower Gunnison River Basin, Colorado, 

1998–2000: U.S. Geological Survey Water-Resources 

Investigations Report 2002–4151, 26 p.

Butler, D.L., Wright, W.G., and Stewart, K.C., 1996, Detailed 

study of selenium, alfalfa, and biota associated with irrigation drainage in the Uncompahgre Project Area and in 

the Grand Valley, West-Central Colorado, 1991–93: U.S. 

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96–4138, 136 p.

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Publishing support provided by: 

Denver Publishing Service Center

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/

(303) 236-2000

Glossary 81

Glossary

sizes of the sediment particles (Osterkamp, 

2008, p. 19).

Estimated residual variance The sum of 

the squared deviations (deviations of the 

measurements from their mean) divided 

by the sample size minus the degrees of 

freedom, or the number of estimated slope 

coefficients plus the intercept (simple linear 

regression has two degrees of freedom for 

the estimation of the intercept and one slope 

coefficient). This quantity is often thought 

of as the variance (measure of variability) 

around the regression line. Some textbooks 

refer to this as mean-square error (Ott and 

Longnecker, 2001, p. 546).

Fourier series An expansion of a periodic 

function as a series of trigonometric functions. In Fourier analysis, a function f(x), 

which is periodic in x, is represented as an 

infinite series of sine and cosine functions 

(Oxford University Press, 2010, p. 332).

Grain shear stress A component of shear 

stress that acts on individual sediment particles (Julien, 2010, p. 184).

Incipient motion The threshold condition 

when the hydrodynamic moments of force 

acting on a single particle balance the resisting moments of force (Julien, 2010, p. 146).

Natural logarithm Logarithm is the power 

to which a number, called the base, must be 

raised to give another number. Any number y 

can be written in the form of y = xn where n 

is then the logarithm to the base x of y, that is, 

n = logxy. Natural logarithms are to the base 

e = 2.71828 and are written logey or more 

commonly in this report lny (Oxford University Press, 2010, p. 486).

Rouse number Ratio of the sediment properties to the hydraulic characteristics of the flow 

(Julien, 2010, p. 231)

Seasonality Seasonal variations in evapotranspiration rates, precipitation volume, 

or type that results in seasonal variations in 

discharge. Many surface-water concentrations (sediment and water chemistry) show 

strong seasonal patterns due to the seasonal 

variations in discharge (Helsel and Hirsch, 

2002, p. 337).

ADCP Acoustic Doppler Current Profiler; 

An instrument that obtains profiles of water 

velocity by transmitting sound of known frequency into the water and measuring the Doppler shift of reflections from scatterers, which 

are assumed to be passively moving with the 

water (Teledyne RD Instruments, 2006).

Antecedent conditions Preceding conditions 

or conditions found prior to an event (American Geological Institute, 1976, p. 16).

Boundary shear stress Density of water 

multiplied by the shear velocity squared or the 

shear stress along channel margin (streambed 

and banks) (Julien, 2010, p. 117).

Critical shear stress The lowest required 

value of shear stress applied by flowing water 

to initiate motion of individual particles of 

specified size (diameter) along the bed of a 

stream (Osterkamp, 2008, p. 14).

Coefficient of determination Proportional reduction in the squared error of the 

response variable (Ott and Longnecker, 

2001, p. 646).

Decimal years A mathematical manipulation of a calendar date which represents the 

date as the sum of the year and decimal portion of the year.

d50 Particle diameter, as determined from a 

size-distribution analysis, in which 50 percent 

of the sediment sample, by weight or count, 

is finer than the total sample weight or count 

(Osterkamp, 2008, p. 42).

Effective discharge The increment of 

discharge that transports the largest fraction 

of the annual sediment load over a period of 

years (Andrews, 1980, p. 311). 

Entrainment The process by flowing 

water or air, or by the mixing of water or 

air between opposing currents, of mobilizing sediment by picking up particles 

and transporting them in suspension, as 

suspended load, and along the channel or 

other surface of transfer, as bed (or traction) load; rates of hydrologic entrainment 

depend on stream power (the product of 

discharge and water-surface slope) and the 
82 Sediment Characteristics and Transport Conditions, Upper Colorado River, Colorado and Utah, 1965–2007

Sediment transport flux The rate at which a dry 

weight of sediment passes a section of a stream 

in a given time (Osterkamp, 2008, p. 39). 

Shear stress That portion of stress acting 

tangentially as a tearing action (as opposed 

to that portion that acts as a normal stress) to 

a plane or surface; thus, a sediment particle 

resting on a channel bed is affected by the 

shear stress created by water moving on the 

bed (Osterkamp, 2008, p. 40).

Shields parameter Dimensionless shear 

stress, is defined as the ratio of fluid forces 

acting on a non-cohesive sediment particle 

and the submerged weight of the particle 

(Julien, 2010, p. 146). 

Slope coefficient The expected change in 

the response variable for a unit increase in 

the explanatory variable associated with the 

slope coefficient when all other explanatory 

variables are held constant (Ott and Longnecker, 2001, p. 621). Examples of explanatory variables from this report include time, 

streamflow, and the seasonality variables. 

Temporal trends Whether the probability 

distribution from which a series of observations of a random variable has arisen has 

changed over time (Helsel and Hirsch, 2002, 

p. 324).

Two-dimensional stream model Model that 

solves for flow properties for two-dimensional 

elements (downstream and cross-stream directions), rather than for entire cross-sections as 

does a one-dimensional model. This produces 

a spatially distributed grid of data points 

where the downstream and cross-stream 

components of the governing equations of 

open-channel flow are solved separately, 

which assumes that the flow components in 

the vertical direction are negligible (Wilcox, 

2007, p. 555; Langley, 2005, p. 4).
Williams and others—Sediment Characteristics and Transport Conditions, Colorado and Utah, 1965–2007—Scientific Investigations Report 2012–5195