Modeling Water Temperature in the 

Yakima River, Washington, from Roza 

Diversion Dam to Prosser Dam, 2005-06

Prepared in cooperation with the Bureau of Reclamation

Scientific Investigations Report 2008–5070

U.S. Department of the Interior

U.S. Geological Survey
Cover: Photograph of the Yakima River near Wapato, Washington. (Photograph taken 

by M. Eleno, U.S. Geological Survey, Tacoma, Washington, 2005.)
Modeling Water Temperature in the 

Yakima River, Washington, from Roza

Diversion Dam to Prosser Dam, 2005–06

By Frank D. Voss, Christopher A. Curran, and Mark C. Mastin

Prepared in cooperation with the Bureau of Reclamation

Scientific Investigations Report 2008-5070

U.S. Department of the Interior

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

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2008

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reproduce any copyrighted materials contained within this report.

Suggested citation:

Voss, F.D., Curran, C.A., and Mastin, M.C., 2008, Modeling water temperature in the Yakima River, Washington, from 

Roza Diversion Dam to Prosser dam, 2005–06: U.S. Geological Survey Scientific Investigations Report 2008-5070, 

42 p.
iii

Contents

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

Introduction.....................................................................................................................................................1

Purpose and Scope ..............................................................................................................................1

Description of Study Area ...................................................................................................................2

Development of Water-Temperature Model ............................................................................................3

Description of Stream Network Temperature Model .....................................................................3

Model Structure for the Yakima River...............................................................................................5

Input Data...............................................................................................................................................6

Meteorology..................................................................................................................................6

Hydrology ....................................................................................................................................14

Roza Diversion Dam to Parker, Washington ................................................................14

Parker to Grandview, Washington.................................................................................15

Grandview to Prosser, Washington ...............................................................................15

Water Temperature ...................................................................................................................17

Stream Geometry.......................................................................................................................19

Shading........................................................................................................................................19

Water-Temperature Model Calibration and Testing ..............................................................................21

Sensitivity Analysis......................................................................................................................................30

Limitations of Water-Temperature Model................................................................................................31

Summary........................................................................................................................................................32

Acknowledgments.......................................................................................................................................32

References Cited..........................................................................................................................................32

Appendix A. Example of Input File to the EDT Analytical Model......................................................35

Appendix B. Method for Deriving Daily Mean Flow for Sites Used to Define Flow for the 

Roza-Prosser Reach Water-Temperature Model .....................................................................36

Appendix C. Regression Equations Used to Estimate Water Temperature for Each 

Surface-Water Source of the Roza–Prosser Reach, Washington.........................................38

Appendix D. Example of the Shading Effects Field Sheet .................................................................39

Appendix E. Regression Equations Used to Estimate Daily Mean Water Temperature in 

Outflow from Five Reservoirs in the Yakima River Basin.........................................................40

Appendix F. Daily Maximum, Mean, and Minimum Water Temperature for Sites in the 

Yakima River Basin, Washington ................................................................................................41
iv

Figures

Figure 1. Map showing location of Yakima River basin and study area, Washington ......... 2

Figure 2. Diagram showing energy fluxes simulated for solution of the stream energy

balance by the SNTEMP model............................................................ 4

Figure 3. Map showing extent of the five SNTEMP models used to simulate water

temperature in the Roza–Prosser Reach, Washington ................................. 5

Figure 4. Diagram showing difference between the SNTEMP branch and point source

model configurations........................................................................ 6

Figure 5. Diagram showing model structure showing flows to and from the Roza–Prosser

Reach, Washington ........................................................................ 7

Figure 6. Map showing sites where simulated water temperatures are output from the

model, Roza–Prosser Reach, Washington................................................ 8

Figure 7. Map showing location of AgriMet weather station (Harrah, Washington) and 

four U.S. Geological Survey weather stations at Roza, Parker, Granger, and 

Prosser, Washington ........................................................................ 9

Figure 8. Boxplots showing monthly distributions of solar radiation, daily mean air

temperature, daily mean relative humidity, and daily mean wind speed at the

AgriMet weather station (Harrah, Washington), January 1, 1988, through

October 30, 2006 ........................................................................... 10

Figure 9. Scatter plots of measured air temperature, solar radiation, and relative humidity

at the AgriMet weather station (Harrah,) and four USGS weather stations (Roza,

Parker, Granger, and Prosser), Roza–Prosser Reach, Washington, July 4 through

September 30, 2006 ........................................................................ 11

Figure 10. Map showing locations of Bureau of Reclamation Hydromet sites and U.S.

Geological Survey sites used to estimate flow to and from the Roza–Prosser

Reach, Yakima River, Washington ......................................................... 16

Figure 11. Map showing locations where shade parameters were measured by the U.S.

Geological Survey, Roza–Prosser Reach, Washington, October 2006 ............... 20

Figure 12. Map showing locations of sites where mean and maximum daily water

temperature used for model calibration and testing were measured,

Roza–Prosser Reach, Washington ...................................................... 22

Figure 13. Boxplots showing monthly distributions of solar radiation, air temperature,

relative humidity, and wind speed measured at the AgriMet weather station

(Harrah), Roza–Prosser Reach, Washington, April through October 31, 2005 ...... 23

Figure 14. Graphs showing simulated and measured daily mean water temperature at

Bureau of Reclamation gaging stations at Parker and Grandview, Roza–Prosser

Reach, Washington, April 1 to October 31, 2005 ....................................... 24
v

Tables

Table 1. Population estimates for cities and towns adjacent to the Roza–Prosser 

Reach, Washington ........................................................................ 3

Table 2. Modules of the Stream Network Temperature Model and description of the 

functionality associated with each module ............................................. 4

Table 3. Bureau of Reclamation Hydromet gaging stations used to estimate flow in the 

Yakima River mainstem from Roza Diversion Dam to Prosser Dam, Washington ... 14

Table 4. U.S. Geological Survey surface-water sites measured for flow, velocity, and 

water temperature in the Yakima River mainstem from Roza Diversion Dam to 

Prosser Dam, Washington, and joining creeks, diversions, wasteways, and 

drains, September 14–16, 2005 ............................................................ 15

Table 5. Data sources used to develop regression equations for the Yakima River 

above Roza Diversion Dam and the Naches River where the river joins the 

Roza–Prosser Reach, Washington ...................................................... 17

Table 6. Inflowing laterals to the Roza–Prosser Reach, Washington, where regression 

equations were developed to estimate water temperature ........................... 18

Table 7. Goodness-of-fit statistics for the final calibration simulation, Roza–Prosser 

Reach, Washington ........................................................................ 24

Table 8. Goodness-of-fit statistics for testing simulations, Roza–Prosser Reach, 

Washington ................................................................................. 24

Table 9. Monthly goodness-of-fit statistics for testing simulations, Roza-Prosser Reach, 

Washington ................................................................................. 29

Table 10. Results of sensitivity analysis, Roza–Prosser Reach, Washington .................. 30

Figure 15. Graphs showing simulated and measured daily maximum water temperature at

three Bureau of Reclamation TidbiT sites near Parker, Granger, and Mabton,

Washington, May 15 to October 31, 2005 ................................................ 25

Figure 16. Boxplots showing monthly distributions of solar radiation, air temperature,

relative humidity, and wind speed measured at the AgriMet weather station

(Harrah), Roza–Prosser Reach, Washington, April 1 to October 31, 2006 ............ 26

Figure 17. Graphs showing tested simulated and measured daily mean water temperature

at Bureau of Reclamation gaging stations at Parker and Grandview, Washington,

April 1 to October 31, 2006 .................................................................. 27

Figure 18. Graphs showing tested simulated and measured daily maximum water

temperature at three TidbiT sites, Washington, April 1 to October 22, 2006 ......... 28

Figures—Continued
vi

Conversion Factors and Datums

Conversion Factors

Multiply By To obtain

centimeter (cm) 0.3937 inch (in.)

cubic centimeter per second (cm3

/s) 3.531 cubic foot per second (ft3/s)

cubic meter per second (m3

/s) 35.31 cubic foot per second (ft3/s)

cubic meter per second (m3

/s) 22.83 million gallons per day (Mgal/d) 

joule (J) 0.0000002 kilowatt hour (kWh)

cubic hectometer (hm3

) 810.7 acre-foot (acre-ft)

kilometer (km) 0.6214 mile (mi)

meter (m) 3.281 foot (ft) 

meter (m) 1.094 yard (yd) 

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

square meter (m2

) 0.0002471 acre 

square kilometer (km2

) 0.3861 square mile (mi2

)

Datums

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

(NAVD 88).

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

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

A mechanistic water-temperature model was constructed 

by the U.S. Geological Survey for use by the Bureau of 

Reclamation for studying the effect of potential water 

management decisions on water temperature in the Yakima 

River between Roza and Prosser, Washington. Flow and 

water temperature data for model input were obtained from 

the Bureau of Reclamation Hydromet database and from 

measurements collected by the U.S. Geological Survey during 

field trips in autumn 2005. Shading data for the model were 

collected by the U.S. Geological Survey in autumn 2006. 

The model was calibrated with data collected from April 1 

through October 31, 2005, and tested with data collected from 

April 1 through October 31, 2006. Sensitivity analysis results 

showed that for the parameters tested, daily maximum water 

temperature was most sensitive to changes in air temperature 

and solar radiation. Root mean squared error for the five sites 

used for model calibration ranged from 1.3 to 1.9 degrees 

Celsius (°C) and mean error ranged from –1.3 to 1.6°C. The 

root mean squared error for the five sites used for testing 

simulation ranged from 1.6 to 2.2°C and mean error ranged 

from 0.1 to 1.3°C.

The accuracy of the stream temperatures estimated by 

the model is limited by four errors (model error, data error, 

parameter error, and user error).

Introduction

The Bureau of Reclamation tries to maintain river 

conditions conducive to salmon recovery while also regulating 

flows in the Yakima River to meet urban and agricultural 

water allocation demands in the Yakima River basin. The 

Bureau of Reclamation is considering water management 

plans that could potentially change the amount and timing of 

flows in the Yakima River. For example, the Yakima Basin 

Storage Project (known as the Black Rock Project) involves 

the construction of a new reservoir about 48 km east of 

Yakima, Washington. Under this project, the reservoir would 

have a maximum capacity of 1,973 hm3

 and be filled by water 

pumped from the Columbia River. Between 616 to 986 hm3

of water from the reservoir would be delivered directly to 

irrigation canals supplying the Yakima River basin, thereby, 

freeing up an equivalent volume of water from the Yakima 

River for enhancing fish and wildlife habitat. The Bureau 

of Reclamation plans to use the Ecosystem Diagnosis and 

Treatment (EDT) method described at http://www.mobrand.

com/MBI/edt.html to estimate results of the enhancements 

to habitat quality and quantity from water management 

alternatives such as the Black Rock Project. The EDT 

analytical model is a major component of the EDT method 

and is used to analyze environmental information. 

Daily maximum water temperature is a necessary input 

for the EDT analytical model. In this cooperative study with 

the Bureau of Reclamation, the U.S. Geological Survey 

(USGS) used a water-temperature model to generate simulated 

daily maximum water temperature data for the Yakima River 

mainstem between the Roza Diversion Dam and the Prosser 

Dam (Roza–Prosser Reach) (fig. 1) for input into the EDT 

analytical model. 

Purpose and Scope

The purpose of this report is to document a watertemperature model for simulating daily maximum water 

temperatures along the Roza–Prosser Reach for any given 

year from April 1 through October 31. This is the approximate 

time range when water is diverted from the river to irrigate 

agricultural areas. The model is intended to assess general 

trends in daily maximum water temperature that may occur 

when different proposed water management alternatives are 

used. The model is not intended to simulate daily maximum 

water temperature with an accuracy of 1.0°C or less on any 

given day. 

Modeling Water Temperature in the Yakima River, 

Washington, from Roza Diversion Dam to Prosser Dam, 

2005–06

By Frank D. Voss, Christopher A. Curran, and Mark C. Mastin
2 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

Figure 1. Location of Yakima River basin and study area, Washington.

wa19_0153_drainage_fig01

82 

22

22

97 

97

97

12

12

82

82

240

24

410

240

90 

90 

90 

24

410

12

97

12 

241

82 

82 12 

Location of figure 3

YAKAMA INDIAN RESERVATION

KITTITAS COUNTY 

YAKIMA COUNTY 

COUNTY 

BENTON COUNTY

KLICKITAT

COUNTY

YAKIMA

EXPLANATION

Boundary of Yakima

 River basin

Canal

Roza

Sunnyside Canal

Main Canal

Extension

Kennewick

Main Canal

Marion Drain

North 

Branch 

Canal 

Kittitas Main Canal

Bumping 

Lake N Fk 

S Fk

S Fk 

N Fk 

S Fk 

N Fk 

N Fk 

Cle Elum River

Swauk Creek

Caribou Cr

Coleman Cr

Naneum

Cr

Cooke Cr

Crow Creek

Bumping River

American River

Rattlesnake Cr

Little Rattlesnake Cr

Nile Creek

Manastash

Badger Creek

Lmuma Cr

Ahtanum Creek 

Oak Creek

Tieton River

Wide Hollow Cr

Wenas Creek

Selah Creek

North Fork

Dry Creek

Simcoe Creek

Agency Creek

Creek

Toppenish

Corral Cr

RIVER

Spring Cr

Logy Creek

Satus

Creek

Mule Dry

Creek

Cle 

Elum 

Lake 

Rimrock 

Lake 

Kachess Lake 

Keechelus Lake 

Lake 

Wallula 

Priest 

Rapids 

Lake 

Teanaway River Reecer Cr

Wilson Creek

Park Cr

Taneum Creek

Umtanum Creek

Little Naches River

Cr

Cowiche Creek

Cowiche Creek

River

Naches

Snipes Cr

Sulphur Cr Wasteway

Cherry 

Cr 

S Fk

N Fk

YAKIMA

YAKIMA

RIVER

Cle Elum 

Parker 

Wapato 

Ellensburg

Umtanum 

Kittitas

Thrall 

Toppenish 

Moxee City Union Gap 

Yakima 

Selah 

Naches 

Sunnyside Richland 

Kiona 

Kennewick Prosser 

Grandview 

Mabton 

Satus 

Zillah 

Granger 

Roza 

Easton 

Teanaway 

Tieton Rimrock 

Snoqualmie

Pass

Van Epps 

Pass 

Esmeralda

Peaks

KITTITAS

VALLEY

M A N A S T A S H

KACHESS RIDGE

R I D G E

UNION GAP

CLEMAN 

MOUNTAIN 

TEANAWAY

NORTH RIDGE

U M T A N U M

R I D G E

Deception

Pass

YAKIMA 

 VALLEY 

AHTANUM RIDGE

COWICHE MTN

AMERICAN RIDGE

CLE ELUM

RIDGE

RIDGE

TOPPENISH RIDGE

R A T T L E S N A K E H I L L S

Y A K I M A R I D G E

H O R S E

H E A V E N

H I L L S

C

A

S C A

D E R

A

N

G

E

W E N AT C H E E

M O U N TA I N S

Gilbert

Peak

121°

47°

47°

30'

46° 

121°30' 120°30' 120° 119°30'

46°

30'

0 5 10 20 30 40 MILES

0 5 10 20 30 40 KILOMETERS

Yakima

River

basin

WASHINGTON

 COLUMBIA

 RIVER

Prosser

Dam

 Roza Diversion

Dam

The objectives of the project were to (1) collect 

discharge, water-temperature, and related data along the Roza–

Prosser Reach of the Yakima River; (2) develop methods for 

estimating water temperatures at the Roza Diversion Dam on 

the Yakima River and at a point on the lower Naches River; 

(3) apply an existing process-based water-temperature model 

to the Roza–Prosser Reach to simulate daily maximum water 

temperature; and (4) document the model.

The USGS was supported in this work through a 

scientific and financial partnership with the Bureau of 

Reclamation.

Description of Study Area

The Yakima River is located in south-central Washington 

and is a tributary of the Columbia River (fig. 1). The Yakima 

River originates in the central Cascade Range near Snoqualmie 

Pass (at an elevation of about 914 m) and flows 354 km 

southeast out of the Cascade Range and onto the Columbia 

Plateau. The Yakima River then flows into the Columbia River 

near Richland (at an elevation of 104 m), draining a total 

drainage basin area of 15,941 km2. 
Development of Water-Temperature Model 3

Table 1. Population estimates for cities and towns adjacent to 

the Roza–Prosser Reach, Washington. 

[U.S. Census Bureau, 2000. Cities and towns ordered from upstream to 

downstream]

Cities and towns Population estimate

Selah 6,310

Yakima (city) 71,845

Yakima (metro area) 229,094

Moxee 821

Union Gap 5,621

Wapato 4,582

Zillah 2,198

Toppenish 8,946

Granger 2,530

Sunnyside 13,905

Satus 746

Mabton 1,905

Grandview 8,377

Prosser 5,138

Precipitation in the Yakima River basin varies 

substantially with elevation and season. The high elevations at 

the crest of the Cascade Range in the western part of the basin 

normally receive more than 305 cm of annual precipitation 

(mostly as snow); whereas, low elevations in the rain shadow 

of the mountains only receive 18 cm of annual precipitation. 

Most of the precipitation occurs during the late autumn, 

winter, and early spring seasons; the summers typically are 

dry. Peak river discharge under natural conditions generally 

occurs during late spring and early summer because of 

snowmelt. The Bureau of Reclamation manages six lakes 

and reservoirs (with a total active storage capacity of about 

1,233 hm3) to retain the spring and summer snowmelt from the 

mountains and to deliver water to agriculture in the lowlands 

between April and October (Kent, 2004). 

The Yakima River basin contains a diverse range of land 

cover types. About 30 percent of the basin is forested, mostly 

in the western mountains; 50 percent is rangeland, where 

sagebrush and bunch grass are the dominant vegetation; and 

20 percent is agricultural, mostly irrigated land along the main 

valley of the Yakima River (Kent, 2004). 

The study area for this project is the Yakima River 

mainstem extending from the Roza Diversion Dam located 

at river kilometer (RKM) 214 to the Prosser Dam located 

at RKM 74. From the Roza Diversion Dam, the Yakima 

River flows in a general southeasterly course past Selah, 

Washington, to the city of Yakima where the river is joined by 

the Naches River, then flows past a series of towns including 

Moxee City, Union Gap, Wapato, Zillah, Toppenish, Granger, 

Sunnyside, Satus, Mabton, Grandview, and finally Prosser. 

(For populations of these towns, see table 1.) The river forms 

the eastern boundary of the 5,260 km2

 Yakama Reservation 

(population 31,799), which occupies 23 percent of the 

southwestern section of the Yakima River basin. The main 

roads running alongside the river are State Route 82 to the 

north and State Routes 97 and 22 to the south.

Development of Water-Temperature 

Model 

Description of Stream Network Temperature 

Model

The Stream Network Temperature model (SNTEMP) 

is a mechanistic, one-dimensional heat transport model that 

simulates the daily mean and maximum water temperatures 

as a function of stream distance and environmental heat 

flux. The model was developed in the early 1980s for the 

U.S. Department of Agriculture, Soil Conservation Service 

(Theurer and others, 1984) and has since been used in studies 

to analyze the effects of reservoir discharge timing, release 

temperature, and release volume (or some combination of 

all three) on downstream water temperatures (Bartholow, 

2000). The DOS-based SNTEMP (Version 2.0) was used 

to develop the water-temperature model for this study. The 

USGS supports and distributes SNTEMP and offers an online 

course on how to use the model at http://www.fort.usgs.gov/

Products/Training/IF312.asp. The SNTEMP software used for 

this study was obtained online from the USGS Fort Collins 

Science Center at http://www.fort.usgs.gov/Products/Software/

SNTEMP/. The user’s manual (Theurer and others, 1984) 

contains equations used by the model and describes how to 

construct model input files. In addition, answers to frequently 

asked questions about SNTEMP are provided at URL http://

www.fort.usgs.gov/products/Publications/4037/4037.asp

The SNTEMP model is composed of the six modules 

listed in table 2. This table also includes a description of the 

functionality associated with each module.

The heat flux module forms the core of the SNTEMP 

model (Theurer and others, 1984). Processes that affect the 

amount of heat entering or leaving a stream are represented by 

the following equation:

Net heat flux = solar radiation + atmospheric radiation

+ vegetative and topographic radiation 

+ evaporation + convection + conduction 

+ fluid friction - water's back radiation

(1)

The processes represented by the heat flux equation are 

shown in figure 2. (Energy fluxes directed at the water body 

are positive and those directed away from the water body are 

negative.)

The SNTEMP model has several advantages. These 

advantages include (1) the capability to simulate stream 

networks of any size or order, and (2) the capability to use a 

simulation time step ranging from 1 month to 1 day. SNTEMP 

documentation states that the model is capable of simulating 

mean water temperatures to within 0.5°C of measured mean 

water temperatures given representational data for a user 

selected time step. The model also uses readily available input 

data and is well documented (Bartholow, 2000).
4 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

Table 2. Modules of the Stream Network Temperature Model 

and description of the functionality associated with each module. 

Module Functionality

Heat flux Calculates incoming and outgoing energy 

fluxes

Heat transport Calculates daily mean and maximum water 

temperatures as a function of stream 

distance

Solar Calculates solar radiation penetrating the 

water as a function of latitude, time of 

year, and meteorological conditions

Shade Calculates interception of solar radiation due 

to topography and riparian vegetation

Meteorological 

correction

Calculates changes in air temperature, 

relative humidity, and atmospheric 

pressure as a function of watershed 

elevation

Regression Smooths water temperature data and 

estimates missing water temperature 

values

Figure 2. Energy fluxes simulated for solution of the stream energy balance by the SNTEMP model.

Solar radiation

Incoming

flow and

temperature

Shading

Atmospheric

radiation

Water's back

radiation

Evaporation

Convection

Topographic

radiation

Conduction

Fluid

friction

Streambed

conduction

Modified from Theurer and others, 1984

HDR Engineering, Inc., as part of a study for the State 

of Idaho Department of Environmental Quality compared 

several water-temperature models (SNTEMP, Heat Source, 

Basin Temp, CE-QUAL-W2, CE-QUAL-RIV1, RMA-11, 

MIKE-11, and hybrid model combinations) and selected 

SNTEMP to simulate water temperature in the Lochsa River in 

north-central Idaho based on the criteria that the model should 

(1) simulate daily maximum stream temperature, (2) be peerreviewed and used within the scientific community, (3) not 

require an inordinate amount of time for data collection, and 

(4) have documentation that is easy to follow and reasonably 

available technical support (HDR Engineering Inc., 2002). 

The SNTEMP model also has limitations. SNTEMP 

uses a regression equation to estimate daily maximum air 

temperature, which is used to calculate daily maximum 

water temperature. The effect of regression equation error 

on simulation results is discussed in section, “Limitations 

of Water-Temperature Model”. Technical staff is no longer 

available as of February 2006 to answer users’ questions about 

the theory and application of the model. One important fact is 

that the SNTEMP model does not simulate hydrologyflow 

data and initial water temperatures are required for all input 

locations. 
Development of Water-Temperature Model 5

Model Structure for the Yakima River

Five SNTEMP modeled reaches were linked in a series 

(fig. 3) to simulate daily maximum water temperatures at any 

given location on the Roza–Prosser Reach, which was required 

for generating input data for the EDT analytical model. 

The equations used in SNTEMP required the length of the 

modeled reach to approximately equal the distance that 

a “parcel” of water travels in the reach for the selected 

simulation time step. For example, if the selected time step is 

1 week, then the length of the reach being modeled would be 

the distance that water would travel in 1 week; if the selected 

Prosser

Dam

Roza

Dam

i

YAKAMA 

INDIAN

RESERVATION

US

97

US

97

SR

22

SR

22

I

82 US

12

I

82

US

12

SR

241

SR

241

SR

24

SR

24

SR

24

SR

240

I

82

US

97

SR

821

US

12

US

12

SR

22

SR

22

0 5 10 15 KILOMETERS

0 5 10 15 MILES Section 1

Section 2

Section 3

Section 4

Section 5

46°40'

46°30'

46°20'

46°10'

120°30' 120°20' 120°10' 120° 119°50' 119°40'

Moxee

Union Gap

Terrace

Heights

Selah

Yakima

Wapato

Parker

Harrah

Zillah

Granger

Toppenish

Satus

Sunnyside

Mabton

Grandview

Prosser

End point of sections

River and stream

Canal and ditch

River kilometer—Measured upstream

 of confluence

Start of model

EXPLANATION

Creek

Toppenish

Marion Drain

Dry Creek

Satus

Creek

Mule Dry

Creek

Wenas Cr.

Lmuma

Creek

Selah

Creek

Canal

Roza

Sunnyside

Canal

YAKIMA

RIVER

Sulphur

Creek Wasteway

Spring

Creek

RK 75

RKM 175

RKM 200

RKM 213

RKM 175

RKM 150

RKM 125

RKM 100

Figure 3. Extent of the five SNTEMP models used to simulate water temperature in the Roza–Prosser Reach, Washington.
6 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

wa19-0153_fig04

Branch model configuration:

 Use when water temperatures

 in tributaries are simulated

Point source model configuration:

 Use when water temperatures

 in tributaries are known

Tributary

Tributary

Tributary Tributary

Mainstem Mainstem

Figure 4. Difference between the SNTEMP branch and point 

source model configurations.

time step is 1 day, then the length of the reach would be the 

distance that the water would travel in 1 day. The travel time 

for the Roza–Prosser Reach was determined to be 5 days 

using water velocity measurements collected by the USGS 

during field trips in September 2005; therefore, five modeled 

reaches were necessary to run the model using a daily time 

step. Because the SNTEMP model is not designed to be linked 

in series, the USGS linked the modeled reaches by developing 

software to transform output data from an upstream modeled 

reach into input for the next downstream modeled reach. The 

end points for the modeled reaches are shown in figure 3.

The model developed for this study did not use the 

branch configuration (fig. 4) typical for most stream networks 

because water temperatures were not simulated for tributaries 

entering the Roza–Prosser Reach. Instead, the Roza–Prosser 

Reach was represented as a single channel. Streams, drains, 

and wasteways carrying water to the Roza–Prosser Reach were 

designated as point sources; whereas, canals carrying water 

from the Roza–Prosser Reach were designated as diversions. 

The water-temperature model requires input of water 

temperature and flow data for every point source and diversion 

for every day of the entire simulation period. The structure 

of the model for the Roza–Prosser Reach with all point 

sources and diversions is shown in figure 5. The vertical line 

in figure 5 represents the Roza–Prosser Reach. Entities listed 

left of the vertical line are adding water to the Roza–Prosser 

Reach; whereas, sites listed to the right of the vertical line are 

entities diverting water from the Roza–Prosser Reach. 

Simulated daily maximum water temperature from 

SNTEMP was generated for locations that correspond to 

the input locations for the EDT analytical model (fig. 6). An 

example of the output file generated for input into the EDT 

analytical model is shown in appendix A.

Input Data

SNTEMP model was designed to use data that are 

relatively easy to gather from maps and Federal data sources 

(Bartholow, 2000). Because SNTEMP is a steady-state model 

and uses a daily time step, the model requires daily mean data 

as input.

Meteorology

SNTEMP model requires daily mean values for air 

temperature, relative humidity, wind speed, and solar 

radiation or percent cloud cover for each day of the simulation 

period. Precipitation data are not used because the model 

does not simulate flows. The AgriMet weather station in 

Harrah, Washington (fig. 7) was used to obtain values for 

mean air temperature, relative humidity, wind speed, and 

solar radiation, which were used for calibration and testing 

simulations. The weather data were downloaded from the 

web site http://www.usbr.gov/pn/agrimet/webarcread.html

for the station code HRHW. Data for these four meteorology 

parameters from January 1, 1988, through October 31, 

2006, are shown in figure 8. The boxplots illustrate general 

weather patterns for the Roza–Prosser Reach; namely, relative 

humidity is inversely related to air temperature and solar 

radiation. The boxplot for wind speed shows that wind speed 

is fairly constant throughout the simulation period.

Solar radiation, daily mean air temperature, and daily 

mean relative humidity data from July 4 through September 

30, 2006, were collected at four USGS weather stations at 

Roza, Parker, Granger, and Prosser, Washington. (fig. 7). 

These weather data were compared to weather data from the 

AgriMet weather station (Harrah, Washington) to determine 

whether data from the AgriMet station represented conditions 

near the river. If the data did not represent these conditions, 

then appropriate adjustments to the data were needed before 

the data were used as input to the model. Scatter plots 

showing these comparisons are shown in figure 9. Correlation 

coefficients for the weather data from the AgriMet weather 

station at Harrah, Washington, and data from the four USGS 

weather stations were 0.97 or greater for daily mean air 

temperature (fig. 9A), 0.94 or greater for solar radiation 

(fig. 9B), and 0.83 or greater for relative humidity (fig. 9C). 

The high correlations provide evidence that the weather data 

from the AgriMet weather station at Harrah, Washington, is 

representative of weather conditions along the Roza–Prosser 

Reach, and adjustments were not made to the AgriMet weather 

data before using the data for model input.
Development of Water-Temperature Model 7

WA19_0153_Voss_fig_05

INFLOW OUTFLOW

Start of section 1 213.18

206.99

206.53

204.45

204.05

195.74

194.46

192.86

192.82

192.24

192.08

189.63

189.60

180.25

179.88

179.20

178.62

Start of section 2 174.91

173.71

163.61

161.40

151.44

144.82

143.00

142.60

Start of section 3 142.40

142.38

136.91

136.30

135.61

135.25

132.29

124.92

117.66

Start of section 4 114.16

113.67

113.22

108.94

104.77

101.63

Start of section 5 99.57

99.36

98.07

96.24

91.23

83.75

77.09

76.77

76.62

74.59

Yakima River Mainstem

Selah Creek at Canyon Road Crossing, near Pomona

Wenas Creek near mouth on Reclamation land, near Selah

Golf Course and Selah Sewage Outflow Creek near Selah

NRYW – Naches River near Yakima

BICW Moxee Drain at Birchfield Road

(RZCW-ROZW) Roza Wasteway No. 2 (at Reclamation)

Wide Hollow Creek near mouth

Union Gap Canal Wasteway

AUGW – Ahtanum Creek at Union Gap Station

Roza Canal Wasteway No. 3

Lateral 1 near the Donald-Wapato Road, near Wapato

Roza Canal Wasteway No. 4

Roza-Sunnyside Joint Drain No. 19.9

Roza-Sunnyside Joint Drain No. 20.8

East Toppenish Drain at Wilson Road, Station No. 12505350

DID No. 27 Drain at mouth

Sub-Drain No. 35 at Parton Road, Station No. 12505410

Granger Drain at Sheep Barns, Station No. 12505460

Marion Drain at Indian Church Road at Granger, Station No. 12505510

Toppenish Creek at Indian Church Road, Station No. 12507508

Coulee Drain near Satus Road Crossing

DID No.16 Drain

Satus Creek at Satus (at gage), Station No. 12508620

South Drain near Satus, Station No. 12508630

Satus No. 2 Drain

DID No. 7 Drain 

Satus No. 3 Drain

SUCW – Sulphur Creek at Holiday Road, near Sunnyside

Satus Drain 303 + Mabton West Wasteway at Highway 22

DID Drain 31 (Frazier Drain at Chase-Frasier Road)

Joint DID No. 2 Drain 

Outlet for DID No. 10

Drain near Grandview-Prosser Hwy. 8/24-2B

Roza-Sunnyside Joint Drain 

SEXW Selah-Moxee Canal

Taylor Ditch at Harrison Road Bridge, near Selah

Moxee Canal

Hubbard Canal

UNGW – Union Gap Canal

Richartz Ditch

RSCW – New Reservation Canal

SNCW – Sunnyside Canal

Snipes and Allen Ditch Diversion

CHCW – Chandler – Prosser Power Plant

Model end

River distance,

in kilometers

Model Start

Figure 5. Model structure showing flows to and from the Roza–Prosser Reach, Washington.
8 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

wa19-0153_fig06

0 5 10 15 KILOMETERS

0 5 10 15 MILES

US

97

US

97

SR

22

SR

22

I

82

US

12

I

82

US

12

SR

241

SR

241

SR

24

SR

24

SR

24

SR

240

I

82

US

97

SR

821

US

12

US

12

SR

22

SR

22

46°40'

46°30'

46°20'

46°10'

120°30' 120°20' 120°10' 120° 119°50' 119°40'

Moxee

Union Gap

Terrace

Heights

Selah

Roza

Yakima

Wapato

Harrah

Zillah

Granger

Toppenish

Satus

Sunnyside

Mabton

Grandview

Prosser

EXPLANATION

Sites where simulated water temperatures

 are output from the model

Parker

 YAKIMA

RIVER

Figure 6. Sites where simulated water temperatures are output from the model, Roza–Prosser Reach, Washington.
Development of Water-Temperature Model 9

wa19-0153_fig07

US

97

US

97

SR

22

SR

22

I

82

US

12

I

82

US

12

SR

241

SR

241

SR

24

SR

24

SR

24

SR

240

I

82

US

97

SR

821

US

12

US

12

SR

22

SR

22

0 5 10 15 KILOMETERS

0 5 10 15 MILES

46°40'

46°30'

46°20'

46°10'

120°30' 120°20' 120°10' 120° 119°50' 119°40'

Moxee

Union Gap

Terrace

Heights

Selah

Roza

Yakima

Wapato

Zillah

Granger

Toppenish

Satus

Sunnyside

Mabton

Grandview

Prosser

Parker

Roza

Parker

Granger

Prosser

Harrah

AgriMet

EXPLANATION

U.S. Geological Survey

Weather stations

AgriMet 

 YAKIMA

RIVER

Figure 7. Location of AgriMet weather station (Harrah, Washington) and four U.S. Geological Survey weather stations at 

Roza, Parker, Granger, and Prosser, Washington.
10 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

wa19-0153_fig08

100

0

300

200

400

-10

0

20

-20

10

30

SOLAR RADIATION AIR TEMPERATURE

NovOctSeptAugJulyJune

Simulation period

MayAprMarFebJan Dec NovOctSeptAugJulyJuneMayAprMarFebJan Dec

DAILY MEAN SOLAR RADIATION, IN WATTS PER SQUARE METER

 DAILY MEAN AIR TEMPERATURE, IN DEGREES CELCIUS

0

0.8

0.6

0.4

0.2

1.0

4

6

5

7

0

2

1

3

RELATIVE HUMIDITY WIND SPEED

NovOctSeptAugJulyJuneMayAprMarFebJan Dec NovOctSeptAugJulyJuneMayAprMarFebJan Dec DAILY MEAN WIND SPEED, IN METERS PER SECOND

DAILY MEAN RELATIVE HUMIDITY (DECIMAL PERCENT)

50th Median

75th

25th

10th

Minimum

 reporting limit

Percentage of analyses

 equal to or less than

 indicated values

90th

Figure 8. Monthly distributions of solar radiation, daily mean air temperature, daily mean relative humidity, and daily mean 

wind speed at the AgriMet weather station (Harrah, Washington), January 1, 1988, through October 30, 2006. 
Development of Water-Temperature Model 11

WA19_0153_Voss_fig_09A DAILY MEAN AIR TEMPERATURE AT HARRAH, WA , IN DEGREES CELSIUS

DAILY MEAN AIR TEMPERATURE, IN DEGREES CELSIUS

5

10

15

20

25

30

35

5

10

15

20

25

30

35

5

10

15

20

25

30

35

5

10

15

20

25

30

35

5 10 15 20 25 30 35 5 10 15 20 25 30 35

A. AIR TEMPERATURE

Parker

 Correlation coefficient = 0.978

Granger

 Correlation coefficient = 0.985

Prosser

 Correlation coefficient = 0.986

Roza

Correlation coefficient = 0.978

Figure 9. Measured air temperature, solar radiation, and relative humidity at the AgriMet weather station (Harrah,) 

and four USGS weather stations (Roza, Parker, Granger, and Prosser), Roza–Prosser Reach, Washington, July 4 through 

September 30, 2006.
12 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

WA19_0153_Voss_fig_9B

0

50

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350 400 0 50 100 150 200 250 300 350 400

0

50

100

150

200

250

300

350

400

0

50

100

150

200

250

300

350

400

0

50

100

150

200

250

300

350

400

DAILY MEAN SOLAR RADIATION, FOR A 24 HOUR PERIOD, AT HARRAH, WA, IN WATTS PER SQUARE METER

DAILY MEAN SOLAR RADIATION, IN WATTS PER SQUARE METER

Correlation coefficient = 0.952

Roza

Parker

 Correlation coefficient = 0.983

Granger

 Correlation coefficient = 0.975

Prosser

 Correlation coefficient = 0.949

B. SOLAR RADIATION

Figure 9.—Continued.
Development of Water-Temperature Model 13

WA19_0153_Voss_fig_9C

20

30

40

50

60

70

80

90

20

30

40

50

60

70

80

90

20

30

40

50

60

70

80

90

20

30

40

50

60

70

80

90

20 30 40 50 60 70 80 90 20 30 40 50 60 70 80 90

DAILY MEAN RELATIVE HUMIDITY, IN PERCENT

DAILY MEAN RELATIVE HUMIDITY FOR HARRAH, WA, IN PERCENT

C. RELATIVE HUMIDITY

Roza Parker

 Correlation coefficient = 0.857

Granger

 Correlation coefficient = 0.830

Prosser

 Correlation coefficient = 0.835

Correlation coefficient = 0.839

Figure 9.—Continued.
14 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

Hydrology

SNTEMP model does not simulate hydrology. Therefore, 

before the model could be run, flow data needed to be 

determined at all locations where flow enters or leaves the 

Roza–Prosser Reach for each time step during the simulation 

period. Flow data were obtained from two sources: Hydromet 

gaging stations maintained by the Bureau of Reclamation and 

field measurements collected in September 2005 by the USGS. 

Average daily flow data for model calibration and 

testing were downloaded for 15 gages from the Bureau of 

Reclamation’s Yakima Project Hydromet System Web page 

at http://www.usbr.gov/pn/hydromet/yakima/index.html. The 

Hydromet system is a network of automated hydrologic and 

meteorological monitoring stations located throughout the 

Pacific Northwest. Remote data collection platforms transmit 

water and environmental data by using point-to-point radio 

or satellite communications to provide near-real-time water 

management capability. The sites used to supply data to the 

model are listed in table 3.

From September 14 through September 16, 2005, the 

USGS measured flows in the Roza–Prosser Reach and at more 

than 40 joining creeks, diversions, wasteways, and drains, 

which are referred to as laterals. Sites used to estimate flows 

for the water-temperature model are listed in table 4, and the 

locations of the sites are shown in figure 10.

A database table was developed to include columns for 

flow and water temperature for each of the 15 Hydromet 

gaging stations and for the laterals sampled by the USGS. 

Data for the 15 Hydromet gaging stations were then imported 

into this database table. The flow to and from the Roza–

Prosser Reach from ungaged laterals was calculated using the 

following methods:

Roza Diversion Dam to Parker, Washington 

•	 Flow in ungaged diversions was assigned a 

proportion of the flow at the nearest gaging station. 

This proportion of flow was based on USGS field 

measurements collected in September 2005. For 

example, if flow in an ungaged diversion was 10 

percent of the flow from the nearest gaged diversion, 

then the ungaged flow would always be set to 10 

percent of the flow from the gaged diversion for 

each day of the simulation period. The equations for 

estimating flow in the ungaged diversions are included 

in appendix B.

•	 Flow for ungaged laterals that added water to the 

Roza–Prosser Reach was estimated by subtracting 

all gaged inflow from outflow for the Roza–Prosser 

Reach. The difference in flow was assumed to be the 

total inflow from ungaged laterals. 

•	 A percentage of the difference in flow was assigned 

to each ungaged lateral based on proportions of flow 

measured during USGS field trips in September 2005. 

For example, if measurements showed that flow in 

a lateral was 10 percent of the total inflow to the 

Roza–Prosser Reach on the day of the measurement, 

then the ungaged lateral was assigned 10 percent 

of the difference between inflow and outflow to the 

Roza–Prosser Reach for each day of the simulation 

period. The equations used to assign flow in ungaged 

inflowing laterals are included in appendix B.

Table 3. Bureau of Reclamation Hydromet gaging stations used to estimate flow in the Yakima River 

mainstem from Roza Diversion Dam to Prosser Dam, Washington.

[Locations of gaging stations are shown in figure 10. NA, not applicable]

Station name Station identification River kilometer

Yakima River below Roza Dam RBDW 213.18

Roza Canal at Headworks RZCW NA

Selah Moxee Canal SEXW 206.99

Naches River near Yakima NRYW 194.46

Union Gap Canal UNGW 192.24

Moxee Drain at Birchfield Road BICW 189.63

Ahtanum Creek at Union Gap AUGW 179.20

Roza Canal at 11.0 mile ROZW NA

New Reservation Canal RSCW 178.62

Sunnyside Canal SNCW 173.71

Yakima River near Parker PARW 173.37

Sulpher Creek at Holiday Road, near Sunnyside SUCW 99.36

Yakima River at Euclid Road Bridge, near Grandview YGVW 89.77

Chandler–Prosser Power Canal CHCW 76.62

Yakima River near Prosser YRPW 74.64
Development of Water-Temperature Model 15

Table 4. U.S. Geological Survey surface-water sites measured for flow, velocity, and water temperature in the 

Yakima River mainstem from Roza Diversion Dam to Prosser Dam, Washington, and joining creeks, diversions, 

wasteways, and drains, September 14–16, 2005.

[Locations of surface-water sites are shown in figure 10. Inflow is flow from a lateral to the Roza-Prosser Reach. Outflow is flow from 

the Roza-Prosser Reach to a lateral. Abbreviations: Reclamation, Bureau of Reclamation; m3/s, cubic meter per second] 

Site description Inflow/Outflow Flow 

(m3

/s)

River 

kilometer

Selah Creek at Canyon Road crossing, near Pomona Inflow 0.00 206.53

Wenas Creek near mouth on Reclamation land, near Selah Inflow .05 204.45

Taylor Ditch at Harrison Road Bridge, near Selah Outflow .11 204.05

Golf course and Selah Sewage Outflow Creek near Selah Inflow .30 195.74

Moxee Canal Outflow .09 192.86

Hubbard and Moxee Canals Outflow .33 192.82

Richartz Ditch Outflow .00 192.08

Wide Hollow Creek near mouth Inflow .99 180.25

Union Gap Canal Wasteway Inflow .17 179.88

Roza Canal Wasteway No. 3 Inflow .19 163.61

Snipes and Allen Ditch Diversion Outflow .28 161.40

Lateral 1 near the Donald-Wapato Road, near Wapato Inflow .18 151.44

Roza Canal Wasteway No. 4 Inflow .04 144.82

Roza-Sunnyside Joint Drain No. 19.9 Inflow .01 143.00

Roza-Sunnyside Joint Drain No. 20.8 Inflow .02 142.60

East Toppenish Drain at Wilson Road Station No. 12505350 Inflow .65 142.38

DID Drain No 27 at mouth Inflow .03 136.91

Sub-Drain No. 35 at Parton Road Station No. 12505410 Inflow 1.17 136.30

Granger Drain at Sheep Barns Station No. 12505460 Inflow .64 135.61

Marion Drain at Indian Church Road at Granger, Station No. 12505510 Inflow .43 135.25

Toppenish Creek at Indian Church Road, Station No. 12507508 Inflow 1.22 132.29

Coulee Drain near Satus Road Crossing Inflow .36 124.92

DID No. 16 Drain Inflow .40 117.66

Satus Creek at Satus (at gage), Station No. 12508620 Inflow 1.53 113.67

South Drain near Satus, Station No. 12508630 Inflow 1.31 113.22

Satus No. 2 Drain Inflow .00 108.94

DID No. 7 Drain Inflow .09 104.77

Satus No. 3 Drain Inflow .42 101.63

Satus Drain 303 + Mabton West Wasteway at Highway 22 Inflow 1.24 98.07

DID Drain 31 (Frazier Drain at Chase-Frasier Road) Inflow .48 96.24

Joint DID No. 2 Drain Inflow .51 91.23

Outlet for DID No. 10 Inflow .10 83.75

Drain near Grandview-Prosser Highway 8/24-2B Inflow .01 77.09

Roza-Sunnyside Joint Drain Inflow .09 76.77

Parker to Grandview, Washington

There are no diversions for this section of the Roza–

Prosser Reach. Inflow from April through September is mostly 

water used for irrigation returning to the Roza–Prosser Reach 

through laterals. 

•	 Flow measured at the Yakima River near Parker 

Hydromet gaging station (PARW) was subtracted from 

the flow measured at the Yakima River at Euclid Road, 

near Grandview Hydromet gaging station (YGVW). 

The difference in flow was assumed to be the total 

inflow from ungaged laterals. 

•	 A percentage of the difference in flow was assigned to 

each ungaged inflowing lateral based on proportions of 

flow measured during USGS field trips in September 

2005. The equations used to assign flow in ungaged 

inflowing laterals are included in appendix B.

Grandview to Prosser, Washington

There is one gaged diversion for this section of the 

Roza–Prosser Reach. Inflow from April through September is 

mostly water used for irrigation returning to the reach through 

laterals.
16 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

wa19-0153_fig10

RDR

RZCW

RBDW

SEXW

NRYW

BICW

UNGW

ROZW

RSCW 

AUGW

SNCW

PARW

YGVW

YRPW

SR

22

SR

22

I

82

US

12

I

82

US

12

SR

241

SR

241

SR

24

SR

24

SR

24

SR

240

I

82

US

97

SR

821

US

12

US

12

SR

22

US

97

US

97

0 5 10 15 KILOMETERS

0 5 10 15 MILES

46°40'

46°30'

46°20'

46°10'

120°30' 120°20' 120°10' 120° 119°50' 119°40'

Moxee

Union Gap

Terrace

Heights

Selah

Roza

Yakima

Wapato

Harrah

Zillah

Granger

Toppenish

Satus

Sunnyside

Mabton

Grandview

Prosser

Parker

EXPLANATION

Bureau of Reclamation sites

 with identification 

U.S. Geological Survey sites

Creek

Diversion

Drain

Wasteway

RBDW

Satus Creek at Satus (at gage), Station No. 12508620

South Drain near Satus, Station No. 12508630

Satus No. 2 Drain

Satus No. 3 Drain

Satus Drain 303 + Mabton West Wasteway at Highway 22

Joint DID No. 2 Drain

Outlet for DID No. 10

Drain near Grandview-Prosser Highway 8/24-2B

Roza-Sunnyside Joint Drain

Lateral 1 near the DonaldWapato Road near Wapato 

Selah Creek at Canyon Road Crossing, near Pomona

Wenas Creek near mouth on Reclamation land, near Selah

Taylor Ditch at Harrison Road Bridge, near Selah

Golf Course and Selah Sewage Outflow Creek near Selah

Hubbard and Moxee Canals

Moxee Canal

Richartz Ditch

Roza Wasteway No. 2 (at Reclamation)

Wide Hollow Creek near mouth

Union Gap Canal Wasteway

Roza Canal Wasteway No. 3

Snipes and Allen Ditch Diversion

Roza Canal Wasteway No. 4

Roza-Sunnyside Joint Drain 19.9

Roza-Sunnyside Joint Drain 20.8

East Toppenish Drain at Wilson Road Station No.12505350

DID Drain 27 at mouth

Sub-Drain No. 35 at Parton Road, Station No. 12505410

Granger Drain at Sheep Barns, Station No. 12505460

Marion Drain at Indian Church Road, at Granger, Station No. 12505510

Toppenish Creek at Indian Church Road, Station 12507508

Coulee Drain near Satus Road Crossing

DID 16 Drain

DID Drain 31

DID No.7 Drain

CHCW

YAKIMA

SUCW RIVER

Figure 10. Locations of Bureau of Reclamation Hydromet sites and U.S. Geological Survey sites used to estimate flow to and 

from the Roza–Prosser Reach, Yakima River, Washington.
Development of Water-Temperature Model 17

•	 Flow measured at the YGVW Hydromet gaging station 

(Grandview) was subtracted from the flow measured at 

the YRPW Hydromet gaging station (Prosser) minus 

the flow measured at the Hydromet gaging station 

for the Chandler Canal (CHCW). The difference in 

flow was assumed to be the total inflow from ungaged 

laterals. 

•	 A percentage of the difference in flow was assigned to 

each ungaged inflowing lateral based on proportions 

of flow measured during the USGS field trips in 

September 200 The equations used to assign flow in 

ungaged inflowing laterals are included in appendix B. 

Ground water flowing to and from a river affects water 

temperature (Poole and Berman, 2001) and is an important 

process, but difficult to measure. The SNTEMP model sets 

ground-water flow equal to the difference between inflow 

and outflow. For example, if flow into the model is 20 m3

/s

and the outflow from the model is 21 m3/s, then the model 

will add 1 m3/s as ground-water inflow. The model sets the 

temperature of the ground water equal to the mean annual air 

temperature for the simulation period, unless the user specifies 

another value. Ground-water temperature was set to 11.2oC 

for calibration and testing simulations based on the calculated 

average daily mean air temperature at the AgriMet weather 

station (Harrah) from January 1, 1988, through December 31, 

2005. SNTEMP adds ground water to a model as a distributed 

flow, meaning that flow in a reach was added equally 

throughout the reach of the entire model instead of being 

discharged at a specific location. 

Water Temperature

Water temperature, as with flow, must be determined for 

all inflows before the SNTEMP model can be run. However, 

consistent water-temperature data for flows into the Roza–

Prosser Reach were not available, and methods needed to be 

developed for estimating inflow water temperatures. Water 

temperatures leaving the Roza–Prosser Reach do not need 

to be calculated because those temperatures do not affect 

the temperature of the Roza–Prosser Reach, and outflow 

water temperatures are not used in other calculations. Two 

methods were developed by the USGS to estimate the water 

temperature of flows entering the Roza–Prosser Reach: (1) 

regression equations to estimate water temperatures for rivers 

entering the Roza–Prosser Reach (namely the upper Yakima 

River above Roza Diversion Dam and the Naches River 

where the river joins the Roza–Prosser Reach just north of 

Yakima) and (2) a set of regression equations to estimate water 

temperature for all streams, wasteways, and drains entering the 

length of the Roza–Prosser Reach.

To develop the regression equations for the Yakima River 

above Roza Diversion Dam and the Naches River where the 

river joins the Roza–Prosser Reach, existing datasets were 

required for water temperature (response variable) at both 

locations as well as for other parameters used to explain 

the variations in water temperature over time (explanatory 

variables). Daily records of average water temperature at 

both locations were obtained from the Bureau of Reclamation 

Hydromet database (table 5).

The primary dataset used to derive explanatory variables 

for Roza Diversion Dam and Naches River regressions was 

obtained from the National Climate Data Center (NCDC). 

Specifically, the daily mean air temperature recorded at 

Yakima Air Terminal (Site ID: YKM) was used. Previous 

studies have concluded that in the absence of other data, mean 

air temperature (above freezing) can explain most variations 

in water temperature (Bartholow, 1989). For the Naches River 

regression, river discharge recorded at the Naches River at 

Yakima gaging station also was used. Because the model 

alternatives were seasonal and limited to the 7-month period 

April 1 through October 31, only data collected during this 

period were used to develop the regression equations. 

Regression equations were derived by using S-PLUS 

statistical software (Insightful Corp., 2002). Ordinary leastsquares (OLS) linear regression as well as linear robust 

(least trimmed squares, LTS) and nonlinear methods were 

considered. Initially, a regression equation was developed 

to estimate water temperature, using only daily mean air 

temperature as an explanatory variable. Residual plots for 

these regressions (residual versus fit) showed slight curvature 

(heteroscadasticity) that resulted in a relation between 

residuals and the explanatory variable that was not desirable 

and likely the result of seasonality. To incorporate the effect 

Table 5. Data sources used to develop regression equations for the Yakima River above Roza Diversion Dam and the Naches River 

where the river joins the Roza–Prosser Reach, Washington.

[Locations of sites are shown in figure 10. Reclamation, Bureau of Reclamation; oC, degrees Celsius; m3/s, cubic meter per second]

Site Site 

identification Source Parameter Type of data Period of record

Roza Reservoir RDR Reclamation-Hydromet Water temperature (oC) Daily mean April 1999 to present

Naches River at Yakima NRYW Reclamation-Hydromet Water temperature (oC) Daily mean August 1987 to July 2004

Naches River at Yakima NRYW Reclamation-Hydromet Flow (m3

/s) Daily mean October 1981 to present

Yakima air terminal YKM National Climate Data Center Air temperature (oC) Daily mean March 1909 to present
18 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

of seasonality, regressions were examined using 3-, 7-, 15-, 

30-, and 45-day moving averages of air temperature and a 

time-dependent parameter based on a function of Julian day. 

In the case of the Naches River regression, river flow also 

was added. Then a stepwise regression technique was used 

to select variables that best explain the data variance, thereby 

reducing the total number of variables. An evaluation of multicolinearity between variables (Helsel and Hirsch, 1995) also 

was performed and further reduced the number of variables.

The resulting linear regression equations for estimating 

water temperature at Roza Diversion Dam and Naches River at 

Yakima are:

2

2

 RDR = 4.0 + AT45dav*0.2991 + AT*0.3448; (2)

 = 0.80, N=1605, Std. Err. = 1.6 (°C)

 NRYW = 2.4 + AT45dav*0.4635 + AT*0.2992 (3)

 - 0.002*Q;

 

R

R = 0.90, N = 2302, Std. Err. = 1.4 (°C),

where

RDR and

NRYW are water temperature (o C) at Roza Diversion 

Dam and Naches River at Yakima,

 respectively,

AT45dav is the simple 45-day moving average of daily 

mean air temperature (o C) at the Yakima

Air Terminal,

AT is the daily mean air temperature at the same

location, and

Q is the discharge (cubic meters per second) at the 

Naches River at Yakima gaging station.

Explanatory variables need not be independent of 

each other (Helsel and Hirsch, 1995), and although the 

explanatory variables AT45dav and AT are derivations of the 

same parameter, these variables are only modestly correlated 

(r = 0.65).

The proportion of variability (R2) explained by using 

robust LTS or nonlinear regression methods did not increase 

appreciably, nor was there a substantial decrease in standard 

error; therefore these methods were not used. 

An important assumption for the regression equation 

for the Roza Diversion Dam is that water temperature near 

the surface of the reservoir (at the location of the sensor) is 

representative of water temperature in the river immediately 

downstream of the spillway. The water temperature sensor 

was located just west of the gage structure on the dam, about 

46 meters from the edge of the spillway (Q. Kreutler, U.S. 

Bureau of Reclamation, written commun., 2006). Water 

temperature data collected by the USGS between April 1 and 

July 20, 2006, indicated that on average the water temperature 

at the gaging station was within 0.2oC of water temperature in 

the river immediately downstream of the spillway.

Water temperature for inflowing lateral sites was 

estimated by developing regression equations for 11 inflowing 

laterals that had limited measured water temperature data 

available (table 6). Other inflowing laterals to the Roza–

Prosser Reach were then assigned the same water temperature 

as the nearest lateral with a developed regression equation for 

water temperature (see appendix C).

Table 6. Inflowing laterals to the Roza–Prosser Reach, Washington, where regression equations were developed to 

estimate water temperature.

[Locations of sites are shown in figure 10. Ta, daily mean air temperature at Harrah, Wash., in degrees Celsius; Tw, daily mean water 

temperature, in degrees Celsius]

Site description Regression equations R2

Wide Hollow Creek near mouth Tw = (0.5768*Ta) + 20.8 0.9115

Lateral 1 near the Donald-Wapato Road, near Wapato Tw = (1.1037*Ta) + 26.4 .8797

East Toppenish Drain at Wilson Road, Station No. 12505350 Tw = (0.5567*Ta) + 20.6 .8308

Sub-Drain No. 35 at Parton Road, Station No. 12505410 Tw = (0.5074*Ta) + 20.1 .8738

Marion Drain at Indian Church Road, at Granger, Station No. 12505510 Tw = (0.7477*Ta) + 23.1 .8634

Toppenish Creek at Indian Church Road, Station No. 12507508 Tw = (1.0704*Ta) + 22.0 .8769

Coulee Drain near Satus Road Crossing Tw = (0.7312*Ta) + 22.8 .8363

Satus Creek at Satus (at gage), Station No. 12508620 Tw = (0.8225*Ta) + 23.4 .8519

South Drain near Satus, Station No. 12508630 Tw = (0.915*Ta) + 24.5 .8979

DID No. 7 Drain Tw = (0.9929*Ta) + 24.3 .8092

Satus Drain 303 + Mabton West Wasteway at Highway 22 Tw = (1.1977*Ta) + 27.5 .7853
Development of Water-Temperature Model 19

Stream Geometry

Stream geometry data were developed to define 

characteristics of the Roza–Prosser Reach. The SNTEMP 

model requires descriptive data for the model nodes and the 

river sections between the nodes. Model nodes are used in the 

Roza–Prosser Reach to define where model sections begin and 

end, where water enters or leaves the reach, where simulation 

results are output, and where substantial changes occur in 

reach characteristics. Each model node must be assigned a site 

location (distance upstream for some arbitrary downstream 

site), latitude, and elevation, which were derived using a 

Geographic Information System (GIS) in this study. Reaches 

between points require data for the reach azimuth (defined as 

the deviation of a channel from a true north-south axis), the 

river roughness coefficient called Manning’s N, and width of 

the river. Reach properties are set at the starting node and are 

considered constant until these properties are changed at a 

node farther downstream.

A GIS was used to determine the azimuth for sections 

of the Roza–Prosser Reach. A Manning’s N value of 0.04 

(the value for large natural channels) was selected from the 

SNTEMP user’s manual (Table II, page II-3) and was assigned 

to all channels in the Roza–Prosser Reach. The width of a 

river can be set to a constant value or can vary with flow. The 

equation W = aQb

 (where W is stream width in meters, Q is 

flow in cubic meters per second, and a and b are coefficients) 

was used to change the width of reaches as the flow changed. 

The equation coefficients a and b were determined by using 

the results of the Bureau of Reclamation’s HEC-RAS model, 

which estimates channel width for a set of flow conditions 

for hundreds of cross sections along the length of the Roza–

Prosser Reach. The equations derived from the HEC-RAS 

model also represent sections of the reach that had braided 

channels.

Shading

Shading lowers water temperature by reducing the 

amount of solar radiation that enters the water. To test for the 

effect that shading might have on water temperature in the 

Roza–Prosser Reach, a shading survey was conducted by the 

USGS on October 26–28, 2006, at 37 stations, covering a total 

river distance of 62 km.

The shading survey methods used were developed by 

previous researchers (Quigley, 1981; Theurer and others, 

1984) and outlined more recently by Bartholow (1989). 

Parameters measured at each station were date, time, location, 

stream azimuth, stream width, topographic altitude, vegetation 

shade parameters, and incident solar radiation. Location and 

stream azimuth were determined using a standard compass 

and Global Positioning System (GPS). A hand-held LaserAce 

Hypsometer was used to measure stream width, topographic 

altitude, and vegetation shade parameters, including height 

above water surface, crown width, distance from the edge of 

the water, and vegetation density. Vegetation density is partly 

subjective and was determined by estimating the percentage 

of continuity of vegetation (quantity) along the river reach and 

multiplying this by the percentage of incident solar radiation 

filtered through the vegetation (quality). 

Incident solar radiation measurements were made by 

using a hand-held solarimeter. Direct solar radiation was 

measured from the center of the river, exposure measurement 

in sunlight (Eo), and diffuse solar radiation was measured at 

the riverbank, exposure measurement in shade (Ei). Bartholow 

(1989) used both incident solar radiation measurements to 

determine a relative shade quality index:

Shade quality = 1.0 ( / ) − E E i o

In addition to the above measurements, digital 

photographs were taken at each station, and the water 

temperature was measured. 

Two hydrographers collected measurements from a 

5-m jet boat with a 35-horsepower outboard motor. The river 

generally was navigable at the time of the survey, and the boat 

was used to travel between stations, allowing observation of 

various riparian terrain and vegetation.

Weather conditions at the time of the survey were mild, 

dry, and generally clear. The level of sunlight was not constant 

during the survey and changed frequently during the days 

because of intermittent clouds. Following the suggestion 

of Bartholow (1989), shade data mostly were collected 

between 0900 and 1500 hours. The locations where shade 

measurements were collected are shown in figure 11, and an 

example of the field sheet is in appendix D.

For this project, shading data were entered into the model 

for locations where shade was directly measured. Estimates 

of shading at other locations were based on relating shading 

measurements to orthophotographs. Sections of the Roza–

Prosser Reach that appeared similar to measured sections were 

given average values of the measured sections.

Topographic shading was not estimated in the field by 

the USGS because topographic shading is difficult to measure 

and is usually not a factor for large rivers in a floodplain. 

However, the upper regions of the study area are in a canyon 

where topographic shading may contribute to a decrease in 

water temperature. In the future, topographic shading in the 

canyon could potentially be calculated using a GIS and digital 

elevation data, but this calculation was beyond the scope of 

this study.
20 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

wa19-0153_fig11

US

97

US

97

SR

22

SR

22

I

82

US

12

I

82

US

12

SR

241

SR

241

SR

24

SR

24

SR

24

SR

240

I

82

US

97

SR

821

US

12

US

12

SR

22

SR

22

0 5 10 15 KILOMETERS

0 5 10 15 MILES

46°40'

46°30'

46°20'

46°10'

120°30' 120°20' 120°10' 120° 119°50' 119°40'

Moxee

Union Gap

Terrace

Heights

Selah

Roza

Yakima

Wapato

Harrah

Zillah

Granger

Toppenish

Satus

Sunnyside

Mabton

Grandview

Prosser

Parker

EXPLANATION

YAKIMA

RIVER

Locations where shading measured

Figure 11. Locations where shade parameters were measured by the U.S. Geological Survey, Roza–Prosser Reach, 

Washington, October 2006.
Water-Temperature Model Calibration and Testing 21

Water-Temperature Model 

Calibration and Testing

A simulation period from April 1 through October 31, 

2005, was used to calibrate the water-temperature model 

for the Roza–Prosser Reach. Daily mean water temperature 

data used to calibrate the model were obtained for Hydromet 

gaging stations at Parker, and at Grandview. Daily maximum 

water temperature data were obtained for sites maintained by 

the Bureau of Reclamation (fig. 12) where small temperature 

sensors (TidbiTs) were installed. Monthly distributions of 

weather variables measured at the AgriMet weather station 

(Harrah) that were used as model input during the calibration 

period are shown in figure 13. Weather coefficients in 

the SNTEMP program control file, which can be set to 

systematically increase or decrease the magnitude of SNTEMP 

climate input data (air temperature, wind speed, relative 

humidity, and solar radiation) by a user-specified percentage, 

were adjusted to obtain the best agreement between simulated 

and measured water temperature. The best agreement was 

obtained when the coefficients for air temperature, wind speed, 

and relative humidity were set to 1.0 and the coefficient for 

solar radiation set to 0.95. Because adjustments to Manning’s 

N did not produce better agreement between simulated and 

measured water temperatures, Manning’s N was left at the 

original value of 0.04. 

The two statistics used for assessing the goodness-of-fit 

between simulated and measured water temperatures at the 

calibration and testing sites were root mean squared error 

(RMSE) and mean error. RMSE is the standard deviation of 

the simulated water-temperature values about the measured 

water-temperature values. For example, a RMSE value of 

1.4°C for the Mabton site for the calibration simulation period 

indicates that approximately 68 percent of the simulated 

daily maximum water temperatures are within one standard 

deviation (+1.4°C) of the measured daily maximum water 

temperatures at Mabton, 95 percent are within two standard 

deviations (+2.7°C), and 99 percent are within three standard 

deviations (+3.6°C). RMSE is a measure of how accurately 

the model simulates water temperature; the lower the RMSE, 

the more accurate the simulations. The RMSE was calculated 

using the following steps: (1) subtracting simulated from 

measured water temperatures for each day of the period 

of interest (which could be a week, a month, or the entire 

simulation period) and squaring the differences (so that 

negative values do not cancel positive values), (2) sum all 

squared differences and divide by the number of days in the 

period of interest, and (3) take the square root of the value 

calculated in step 2 to get the RMSE. 

Mean error is the average error of a number of 

observations by taking the mean value of the positive and 

negative errors without regard to sign. Therefore, mean 

error can be positive or negative and is an indicator of bias 

in simulation results. For example, if the mean error for the 

TidbiT site at Mabton is –0.8oC, then on average, the model 

simulated daily maximum water temperatures that were 0.8oC 

lower than the measured daily maximum water temperature at 

Mabton. Ideally, mean error should be zero, meaning that the 

model over-simulates and under-simulates water temperature 

equally and, therefore, has no bias. Possible reasons for bias 

in the calibration and testing simulations are discussed in 

section, “Limitations of Water-Temperature Model”. Mean 

error is calculated by subtracting the measured daily (mean 

or maximum) water temperature from the simulated daily 

(mean or maximum) water temperature for the period of 

interest, summing the differences, and then dividing the 

summed differences by the number of days in the period 

of interest. Table 7 shows the goodness-of-fit statistics for 

the five calibration sites of the final calibration simulation. 

Simulated and measured daily mean water temperatures for 

the calibration period at two Hydromet gaging stations are 

shown in figure 14. Simulated and measured daily maximum 

water temperatures at three TidbiT sites maintained by Bureau 

of Reclamation are shown in figure 15.

A simulation period from April 1 through October 31, 

2006, was used to test the water-temperature model for the 

Roza–Prosser Reach. Daily mean water temperature data for 

testing were obtained from Hydromet gaging stations at Parker 

and Grandview, Washington, which were the same sites used 

to obtain data for the calibration simulation. Daily maximum 

water temperature data were obtained for three TidbiT sites 

maintained by the Bureau of Reclamation (fig. 12). The 

Mabton TidbiT site also was used to obtain data for the 

calibration simulations; however, data from TidbiT sites at 

Harlin Landing and Wapato were used only for the testing 

simulation. Monthly distributions of weather variables used as 

model input during the testing period measured at the AgriMet 

weather station (Harrah) are shown in figure 16. Model 

parameters were not adjusted for the testing simulation. 

The goodness-of-fit statistics for the testing simulation 

at two Hydromet gaging stations and three TidbiT sites are 

shown in table 8. Graphs of simulated and measured daily 

mean water temperature for the calibration period at two 

Hydromet gages are shown in figure 17. Graphs of simulated 

and measured daily maximum water temperatures at three 

TidbiT sites maintained by the Bureau of Reclamation are 

shown in figure 18. 
22 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

wa19-0153_fig12

YAKIMA

RIVER

US

97

US

97

SR

22

SR

22

I

82

US

12

I

82

US

12

SR

241

SR

241

SR

24

SR

24

SR

24

SR

240

I

82

US

97

SR

821

US

12

US

12

SR

22

SR

22

0 5 10 15 KILOMETERS

0 5 10 15 MILES

46°40'

46°30'

46°20'

46°10'

120°30' 120°20' 120°10' 120° 119°50' 119°40'

Moxee

Union Gap

Terrace

Heights

Selah

Roza

Yakima

Wapato

Harrah

Zillah

Granger

Toppenish

Satus

Sunnyside

Mabton

Grandview

Prosser

EXPLANATION

Sites where daily water temperature 

 was measured 

Mean

Maximum

Parker

Harlin Landing

2006 testing site

Wapato, WA

2006 testing site

Parker

2005 calibration site 

Parker (PARW)

2005 calibration site

and 2006 testing site 

Granger

2005 calibration site 

Mabton

2005 calibration site

and 2006 testing site 

Grandview

(YGVW)

2005 calibration site

and 2006 testing site 

Figure 12. Locations of sites where mean and maximum daily water temperature used for model calibration and testing 

were measured, Roza–Prosser Reach, Washington. 
Water-Temperature Model Calibration and Testing 23

Figure 13. Monthly distributions of solar radiation, air temperature, relative humidity, and wind speed measured at the 

AgriMet weather station (Harrah), Roza–Prosser Reach, Washington, April through October 31, 2005.

wa19-0153_fig13

100

0

300

200

400

-10

0

20

-20

10

30

OctSeptAugJulyJuneMayApr

DAILY MEAN SOLAR RADIATION, IN WATTS PER SQUARE METER DAILY MEAN AIR TEMPERATURE, IN DEGREES CELSIUS

0

0.8

0.6

0.4

0.2

1.0

4

5

0

2

1

3

OctSeptAug

2005

2005

2005

2005

JulyJuneMayApr

OctSeptAugJulyJuneMayApr OctSeptAugJulyJuneMayApr DAILY MEAN WIND SPEED, IN METERS PER SECOND DAILY MEAN RELATIVE HUMIDITY (DECIMAL PERCENT)

50th Median

75th

25th

10th

Minimum

 reporting limit

Percentage of analyses

 equal to or less than

 indicated values

90th

SOLAR RADIATION

AIR TEMPERATURE

RELATIVE HUMIDITY

WIND SPEED
24 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

WA19_0153_Voss_fig_14

30

25

20

15

10

5

0

30

25

20

15

10

5

0

APR MAY JUNE JULY AUG SEPT OCT

Reclamation gage near Parker, WA

Reclamation gage near Grandview, WA

Simulated (April 1 to October 31, 2005)

Measured (April 1 to October 31, 2005)

SIMULATED AND MEASURED DAILY MEAN WATER TEMPERATURE, IN DEGREES CELSIUS 

2005

Figure 14. Simulated and measured daily mean water temperature at Bureau of Reclamation gaging stations at Parker and 

Grandview, Roza–Prosser Reach, Washington, April 1 to October 31, 2005.

Table 7. Goodness-of-fit statistics for the final calibration 

simulation, Roza–Prosser Reach, Washington.

[Abbreviations: RMSE, root mean square error; oC, degrees Celsius; 

Reclamation, Bureau of Reclamation]

Site description RMSE 

(oC)

Mean error 

(oC)

Sites where daily mean water temperatures were measured

Hydromet gage at Parker (station identification–

PARW)

1.7 -1.3

Hydromet gage at Grandview (station 

identification–YGVW)

1.5 .7

Sites where daily maximum water temperatures were measured

Reclamation TidbiT near Parker 1.9 1.6

Reclamation TidbiT near Granger 1.4 -.4

Reclamation TidbiT near Mabton 1.3 -.8

Table 8. Goodness-of-fit statistics for testing simulations, 

Roza–Prosser Reach, Washington.

[Abbreviations: RMSE, root mean square error; oC, degrees Celsius; 

Reclamation, Bureau of Reclamation]

Site description RMSE 

(oC)

Mean error 

(oC)

Sites where daily mean water temperatures were measured

Hydromet gage at Parker (station 

identification–PARW)

1.6 0.7

Hydromet gage at Grandview (station 

identification–YGVW)

2.0 1.2

Sites where daily maximum water temperatures were measured

Reclamation TidbiT near Harlin 2.2 1.2

Reclamation TidbiT near Wapato 1.8 1.3

Reclamation TidbiT near Mabton 1.9 .1
Water-Temperature Model Calibration and Testing 25

WA19_0153_Voss_fig_15

2005

30

25

20

15

10

5

0

30

25

20

15

10

5

0

30

25

20

15

10

5

0

APR MAY JUNE JULY AUG SEPT OCT

SIMULATED AND MEASURED DAILY MAXIMUM WATER TEMPERATURE, IN DEGREES CELSIUS 

Reclamation TidbiT site near Parker, WA

Reclamation TidbiT site near Granger, WA

Reclamation TidbiT site near Mabton, WA

Simulated (May 19 to October 31, 2005)

Measured (May 19 to October 31, 2005)

Figure 15. Simulated and measured daily maximum water temperature at three Bureau of Reclamation TidbiT sites near 

Parker, Granger, and Mabton, Washington, May 15 to October 31, 2005.
26 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

wa19-0153_fig16

100

0

300

200

400

-10

0

20

-20

10

30

40

OctSeptAugJulyJuneMayApr

DAILY MEAN SOLAR RADIATION, IN WATTS PER SQUARE METER DAILY MEAN AIR TEMPERATURE, IN DEGREES CELSIUS

0

0.8

0.6

0.4

0.2

1.0

4

6

5

0

2

1

3

OctSeptAug

2005

2005

2005

2005

JulyJuneMayApr

OctSeptAugJulyJuneMayApr

OctSeptAugJulyJuneMayApr

DAILY MEAN WIND SPEED, IN METERS PER SECOND DAILY MEAN RELATIVE HUMIDITY (DECIMAL PERCENT)

50th Median

75th

25th

10th

Minimum

 reporting limit

Percentage of analyses

 equal to or less than

 indicated values

90th

SOLAR RADIATION

AIR TEMPERATURE

RELATIVE HUMIDITY

WIND SPEED

Figure 16. Monthly distributions of solar radiation, air temperature, relative humidity, and wind speed measured at the 

AgriMet weather station (Harrah), Roza–Prosser Reach, Washington, April 1 to October 31, 2006.
Water-Temperature Model Calibration and Testing 27

The graphs in figures 17 and 18 show that the Roza–

Prosser Reach model simulates seasonal patterns in measured 

daily mean and maximum water temperatures at the testing 

sites indicating that flows generally are characterized correctly 

and the model is responding correctly to meteorological 

inputs. The RMSE for the testing simulation sites ranged 

from 1.6 to 2.2°C and mean error ranged from –1.3 to 

1.6°C; whereas, RMSE for the calibration simulation sites 

range from 1.3 to 1.9°C and mean error ranged from 0.1 to 

1.3°C, showing that the model is capable of simulating water 

temperature for growing seasons with differing flow and 

climate conditions with generally the same degree of accuracy.

Monthly RMSE and mean error values were calculated 

for the testing sites to investigate seasonal patterns in 

simulation error. Statistics were not generated for October 

because data for October from the TidbiT site contained 

errors. Monthly goodness-of-fit statistics for the testing sites 

are shown in table 9. 

The mean error shows a general seasonal pattern where 

the model over-predicts water temperature from April 

through June of the simulation period and obtains greater 

accuracy or under-predicts water temperature from July 

through September (table 9). The seasonal pattern in error 

also can be seen in figures 17 and 18. This seasonal bias 

may indicate model sensitivity to air temperature, possibly 

caused by underestimating flow in the system resulting in less 

thermal buffering; overestimating stream width resulting in 

overexposure to solar radiation and air temperature input; or 

incorrect model-section lengths, resulting in errors in climate 

input. Errors and the effect on simulation results are discussed 

in section, “Limitations of Water-Temperature Model”.

Figure 17. Tested simulated and measured daily mean water temperature at Bureau of Reclamation gaging stations at Parker 

and Grandview, Washington, April 1 to October 31, 2006.

30

25

20

15

10

5

0

30

25

20

15

10

5

0

APR MAY JUNE JULY

2006

AUG SEPT OCT

Reclamation gage near Parker, WA

Reclamation gage near Grandview, WA

Simulated (April 1 to October 31, 2006)

Measured (April 1 to October 31, 2006)

SIMULATED AND MEASURED DAILY MEAN WATER TEMPERATURE, IN DEGREES CELSIUS 
28 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

WA19_0153_Voss_fig_18

2006

30

25

20

15

10

5

0

30

25

20

15

10

5

0

30

25

20

15

10

5

0

APR MAY JUNE JULY AUG SEPT OCT

SIMULATED AND MEASURED DAILY MAXIMUM WATER TEMPERATURE, IN DEGREES CELSIUS 

Reclamation TidbiT site near Harlin, WA

Reclamation TidbiT site near Wapato, WA

Reclamation TidbiT site near Mabton, WA

Simulated (April 1 to October 22, 2006)

Measured (April 1 to October 22, 2006)

Figure 18. Tested simulated and measured daily maximum water temperature at three TidbiT sites, Washington, April 1 to 

October 22, 2006.
Water-Temperature Model Calibration and Testing 29

Table 9. Monthly goodness-of-fit statistics for testing simulations, Roza-Prosser Reach, Washington. 

Testing 

period

Water temperature, in degrees Celsius

Parker Grandview Harlin Landing Wapato Mabton

Mean Mean Mean Maximum Mean Maximum Mean Maximum

Mean Error

April through 

September

0.7 1.2 1.9 0.8 1.1 1.3 0.3 0.1

April 1.9 2.0 2.4 1.2 2.0 2.1 1.7 1.6

May 1.3 2.0 2.7 1.5 1.4 1.8 1.5 1.4

June 1.4 2.2 2.5 1.1 1.6 1.8 1.7 1.6

July 1.3 .8 4.4 3.5 2.2 2.1 -.8 -1.1

August -.4 .4 .5 -.9 .4 .3 -1.2 -1.5

September -1.3 .1 -.8 -1.9 -.8 -.5 -.9 -1.5

Root Mean Square Error

April through 

September

1.6 2.0 2.8 2.2 1.7 1.8 1.8 1.9

April 2.1 2.5 2.6 1.6 2.1 2.3 2.2 2.1

May 1.4 2.2 2.8 1.9 1.5 1.9 1.7 1.7

June 1.5 2.5 2.6 1.6 1.7 2.0 2.0 2.0

July 1.6 1.7 4.6 3.7 2.3 2.2 1.6 1.7

August 1.0 1.2 1.4 1.8 1.1 .9 1.6 1.9

September 1.5 1.7 1.3 2.1 1.3 1.2 1.6 1.9
30 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

Table 10. Results of sensitivity analysis, Roza–Prosser Reach, Washington.

[Irrigation season = April 1 to October 31, 2005; July = July 1 through July 31, 2005. All values are in percent. Abbreviations: Reclamation, Bureau of 

Reclamation; YGVW, Yakima River at Euclid Road Bridge, near Grandview; °C, degrees Celsius; Wm-2, Watts per square meter; m/s, meter per second; m, 

meter]

Parameter or variable

Percent 

change to 

input value

Resulting percent change in maximum water 

temperature at sites

Resulting percent change in mean 

water temperature at site

Reclamation Tidbit site 

near Granger

Reclamation Tidbit site 

near Mabton

Hydromet gage at Grandview 

(station identification – YGVW)

Irrigation 

season July Irrigation season July Irrigation season July

Daily mean air temperature (°C) + 5 + 1.71 2.02 1.72 1.95 2.03 2.47

- 5 - 1.67 -2.02 -1.69 -1.95 -2.00 -2.06

Daily mean solar radiation (Wm-2) + 5 + 1.31 1.62 1.40 1.56 1.22 1.65

- 5 - 1.31 -1.21 -1.41 -1.56 -1.23 -1.23

Relative humidity (percent) + 5 + .61 .81 .62 .78 .76 .82

- 5 - .61 -.40 -.63 -.39 -.77 -.82

Wind speed (m/s) + 5 + .24 .00 -.26 -.39 -.28 -.41

Channel width (m) + 10 .00 .00 .21 .39 .18 .41

- 10 .00 .00 -.22 -.39 -.19 .00

Sensitivity Analysis

A series of simulations were conducted to determine the 

relative effect of selected input variables and model parameters 

on simulated water temperatures. One input variable or model 

parameter in the calibrated Roza–Prosser Reach model was 

changed for each simulation by a percentage, although all 

other variables and parameters were held constant. As shown 

in table 10, the resulting percentage of change in daily mean 

water temperature for the simulation period was measured and 

recorded for one Hydromet site (Grandview) and two TidbiT 

sites maintained by Bureau of Reclamation. The period for the 

sensitivity simulations was from April 1 through October 31, 

2005, and used weather data from the AgriMet weather station 

(Harrah). Simulations for July were run to determine seasonal 

patterns of sensitivity.

Daily maximum and mean water temperatures for the 

Roza–Prosser Reach model were most sensitive to daily mean 

air temperature. Daily maximum water temperatures were 

more sensitive than daily mean water temperatures to solar 

radiation, and both simulated daily maximum and daily mean 

water temperatures were more sensitive to solar radiation than 

to relative humidity.
Limitations of Water-Temperature Model 31

Limitations of Water-Temperature 

Model

The accuracy of the water temperatures estimated by the 

SNTEMP model is limited by four types of error: model, data, 

parameter, and user errors.

Model error occurs when the equations used to represent 

physical processes are flawed or incomplete. This happens in 

all models in varying degrees because a model by definition 

is a simplified version of a real system. Model error can 

result from the use of an improper equation, use of the wrong 

numerical method to represent the equation, and calculation 

errors in the computer code that might make a model overly 

sensitive to certain input parameters. A potentially significant 

source of model error in SNTEMP is the method used to 

calculate daily maximum water temperature (Bartholow, 

2000). The form of the equation used to calculate daily 

maximum water temperature (Theurer and others, 1984, 

equation II(116)) is the same as that used for daily mean water 

temperature (Theurer and others, 1984, equation II(115)). 

However, because of limitations in the model computer 

code, daily maximum air temperature cannot be used in 

place of the daily mean air temperature. Instead, a regression 

equation that includes relative humidity, wind speed, and 

solar radiation is used to predict the daily maximum air 

temperature, which is used as input into equation II(116). 

The coefficients for the regression equation (Theurer and 

others, 1984, table II.3 page II-32) are based on measurements 

collected throughout the country. A method exists to estimate 

regression coefficients by using local weather data (Bartholow, 

2000). This was attempted by using data from the AgriMet 

weather station (Harrah). However, when the results from 

the regression equation were compared against measured 

data, the local coefficients did not predict daily maximum air 

temperature as well as the coefficients from table II.3 in the 

User’s Manual (Theurer and others, 1984). 

Data error occurs when the input data used in the model 

do not accurately represent actual conditions. Input data for 

the Roza–Prosser Reach contained data errors because much 

of the input data were estimated. 

Input flow data contain data errors for at least four 

reasons:

1. Flow estimates in all ungaged laterals (for example. 

streams, canals, drains, returns) were based on flow 

measurements from one USGS September 2005 seepage 

run. The proportion of flow in the laterals measured in 

September 2005 generally was assumed to be the same 

throughout the growing season but the actual proportion 

of flow varies over the growing season and adds error to 

water temperature estimates on any given day. 

2. All flow estimates for the model were based on daily 

flow measurements made at 13 gages maintained by 

the Bureau of Reclamation. Data errors at these gages 

(especially during large runoff events) add data error to 

flow estimates. 

3. Ground-water flow to or from a reach is based on 

estimated surface-water flows. When inflow to a reach 

is less than outflow, SNTEMP adds ground water to 

maintain the water balance in the reach. Therefore, errors 

in surface-water flow estimates are related to errors in 

ground-water estimates. The work required to characterize 

ground-water exchange more accurately in the Roza–

Prosser Reach was beyond the scope of this project. 

(4) Data error may occur because inflow to the Yakima 

River mainstem from holding ponds and oxbow lakes may not 

be accurately represented. The exchange between those bodies 

of water is not well understood. Therefore, greater data error 

could occur during low-flow conditions in the mainstem when 

inflow from ponds and oxbow lakes may be proportionally 

higher. Characterizing the flow exchange between the 

mainstem and adjacent ponds and lakes also was beyond the 

scope of this study. 

Input water temperatures contain data errors because 

these data were generated using regression equations, which 

are approximations of actual conditions. Data also were not 

available to develop a regression equation for every inflowing 

lateral. Many laterals were assigned water temperature values 

from a nearby lateral (with a developed regression equation), 

which increases data error. 

Input meteorology data contain data errors because 

actual conditions along the mainstem vary from conditions at 

the AgriMet weather station at Harrah. Differences between 

meteorological data at Harrah and at four USGS weather 

stations along the mainstem are discussed in the section, 

“Meteorology”. 

Parameter error occurs when variables adjusted to 

calibrate a model are set to values that do not represent actual 

conditions. For example, Manning’s N can be adjusted to 

improve the agreement between measured and simulated water 

temperatures, but instead of obtaining a better representation 

of the system, the adjustment might be concealing poorly 

represented processes in the model that caused the poor 

agreement. 

User error can occur when the user makes a mistake. This 

can happen when a user assumes a condition exists when in 

fact it does not or when a user makes a programming error or 

enters incorrect data.
32 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

Summary

Water temperatures in the Roza–Prosser Reach affect 

aquatic habitat and the viability of native fish populations. 

However, water demand for increasing population and 

agriculture in the Yakima River basin has caused the Bureau 

of Reclamation to consider water-allocation management 

plans that could potentially alter water temperatures in the 

Roza–Prosser Reach. A mechanistic water-temperature 

model was constructed by the U.S. Geological Survey 

(USGS) for use by the Bureau of Reclamation to study the 

relative effects that various water-management plans might 

have on water temperature during a growing season (April 

1 through October 31). The DOS-based Stream Network 

Temperature model (SNTEMP version 2.0) was selected 

for the simulation because input data for the model were 

readily available, and the model has been successfully used 

in water temperature studies since the mid-1980s. Five 

SNTEMP modeled reaches were linked in series to simulate 

the daily maximum water temperatures at locations selected 

by the Bureau of Reclamation for input into the Ecosystem 

Diagnosis and Treatment analytical model. Meteorological 

data for model input were collected from an AgriMet 

weather station (Harrah). Streamflow data collected from 

15 Bureau of Reclamation Hydromet gaging stations and 

field measurements collected by the USGS in September 

2005 were used to estimate flow in the Roza–Prosser Reach. 

Regression equations were used to estimate water temperature 

data for flow entering the Roza–Prosser Reach from the upper 

Yakima River upstream of the Roza Dam and the Naches 

River and for all inflowing laterals under current operating 

conditions. Shading data for model input were collected by 

the USGS in October 2006. The model was calibrated using 

a simulation period, April 1 through October 31, 2005, and 

tested using a simulation period, April 1 through October 31, 

2006. A sensitivity analysis indicated that daily maximum 

water temperatures are most influenced by daily mean air 

temperature and solar radiation. 

Graphs comparing daily simulated and measured 

water temperatures at calibration and testing sites show that 

the model simulated seasonal patterns of measured water 

temperature. Root mean squared error (RMSE) for the five 

sites used for model calibration ranged from 1.3 to 1.9 degrees 

Celsius (°C), and mean error ranged from –1.3 to 1.6°C. For 

the five sites used for testing simulation, the RMSE ranged 

from 1.6 to 2.2°C, and mean error ranged from 0.1 to 1.3°C. 

Similar RMSE and mean error for the calibration and testing 

simulations indicate the model simulated differing flow and 

climate conditions with the same level of accuracy and that 

the model is suitable for studying the effect of potential water 

management decisions on water temperature in the Roza–

Prosser Reach.

Acknowledgments

The authors gratefully acknowledge John Bartholow from 

the USGS Fort Collins Science Center for generously sharing 

his knowledge of the SNTEMP model. From the USGS 

Tacoma Science Center, we would like to thank Lonna Frans 

and Joseph Jones for their statistical analyses, Karen Payne for 

her field work, and John Vaccaro for his technical guidance. 

From the Bureau of Reclamation, we would like to thank Joel 

Hubble, Roger Sonnichsen, and Dave King for their help and 

cooperation.

References Cited

Bartholow, J.M., 1989, Stream temperature investigations—

Field and analytic methods: U.S. Fish and Wildlife Service, 

Biological Report, v. 89, no. 17, 139 p.

Bartholow, J.M., 2000, The stream segment and stream 

network temperature models—A self-study course: U.S. 

Geological Survey Open-File Report 99-112, 276 p.

HDR Engineering Inc., 2002, Water temperature of Lochsa 

River and selected tributaries (QRP00023) – final report, 55 

p., accessed March 12, 2008, at http://www.deq.state.id.us/

water/data_reports/surface_water/water_bodies/lochsa_

river_temp_cs.pdf

Helsel, D.R., and Hirsch, R.M., 1995, Statistical methods in 

water resources: Studies in Environmental Science, New 

York, Elsevier, v. 49, 529 p.

Insightful Corporation, 2002, S-PLUS, v. 6.1, for Windows 

[computer software], Professional Edition: Insightful 

Corporation.
References Cited 33

Kent, C.A., 2004, Water resource planning in the Yakima 

River Basin—Development versus Sustainability: Yearbook 

of the Association of Pacific Coast Geographers, v. 66, p. 

27-60.

Poole, G.C., and Berman, C.H., 2001, An ecological 

perspective on in-stream temperature—Natural heat 

dynamics and mechanisms of human-caused thermal 

degradation: Environmental Management, v. 27, no. 6, p. 

787-802.

Quigley, T.M., 1981, Estimating contribution of overstory 

vegetation to stream surface shade: Wildlife Society 

Bulletin, v. 9, no. 1, p. 22-27.

Systat Software, Inc. SYSTAT 10.2, Statistics I. Point 

Richmond, Calif.: Systat Software, Inc; 2002.

Theurer, F.D., Voos, K.A., and Miller, W.J., 1984, Instream 

water-temperature model—Instream flow information Paper 

16: U.S. Fish and Wildlife Service, FWS/OBS-84/15, 335 p.

U.S. Census Bureau, 2000, Census 2000 data for the state of 

Washington, accessed June 5, 2006, at 

http://www.census.gov/census2000/states/wa.html
34 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

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Appendix A 35

Appendix A. Example of Input File to the EDT Analytical Model

The following is an example of the output file format 

that will be generated from the Roza-Prosser Reach 

water-temperature model for input to the EDT analytical 

model. The first column is the identifier code for the 

output site, the second column is the output data code 

(MAX_WATER_TEMP_C is daily maximum simulated water 

temperature in degrees Celsius [°C]), the third column is the 

date (in Afrikaans date format), and the fourth column is the 

simulated daily maximum water temperature in °C.

H-2C MAX_WATER_TEMP_C 1984/04/01 12.02

H-2C MAX_WATER_TEMP_C 1984/04/02 12.62

H-2C MAX_WATER_TEMP_C 1984/04/03 11.91

H-2C MAX_WATER_TEMP_C 1984/04/04 11.03

H-2C MAX_WATER_TEMP_C 1984/04/05 11.46

H-2C MAX_WATER_TEMP_C 1984/04/06 12.72

H-2C MAX_WATER_TEMP_C 1984/04/07 11.25

H-2C MAX_WATER_TEMP_C 1984/04/08 12.29
36 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

Appendix B. Method for Deriving Daily Mean Flow for Sites Used to Define 

Flow for the Roza-Prosser Reach Water-Temperature Model

Tables B1 and B2 show methods used to derive values for 

daily mean flow for sites used to define flow for the Roza–

Prosser Reach water-temperature model. Sites at Hydromet 

gaging stations used daily mean flow measurements from 

those stations. Sites between Hydromet stations were assigned 

a percentage of the difference in flow between the stations. 

The assigned percentages were based on flow measurements 

made by the USGS during field trips in September 2005. 

Table B1. Method used to assign daily mean flow to sites used to define flow for the Roza–Prosser Reach water-temperature model.

[Flow calculation abbreviations are listed in table B2; SUM1 = All inflow between Roza Dam and Parker, Washington, minus flow to diversions. 

Abbreviations: Reclamation, Bureau of Reclamation; NA, not applicable]

Location Flow calculation Decimal percent 

used in calculations

Yakima River below Roza Dam, near Roza Used daily values measured at RBDW NA

Selah-Moxee Canal Used daily values measured at SEXW NA

Selah Creek at Canyon Road Crossing, near Pomona Set daily values equal to percent of PARW - (SUM1) 0.003

Wenas Creek near mouth on Reclamation land, near Selah Set daily values equal to percent of PARW - (SUM1) .031

Taylor Ditch at Harrison Road Bridge, near Selah Set daily values equal to percent of SEXW .080

Golf Course and Selah Sewage Outflow Creek, near Selah Set daily values equal to percent of PARW - (SUM1) .197

Naches River near North Yakima, near mouth at 

Reclamation gaging site 12499900 

Used daily values measured at NRYW NA

Moxee Canal Set daily values equal to percent of UNGW .050

Hubbard Canal Set daily values equal to percent of UNGW .200

Union Gap Canal Set daily values measured at UNGW NA

Richartz Ditch Set daily values equal to percent of UNGW .000

Roza Wasteway No. 2 (at Reclamation) Set daily values equal to RZCW-ROZW NA

Moxee Drain at Thrope Road Use daily values measured at BICW NA

Wide Hollow Creek near mouth Set daily values equal to percent of PARW - (SUM1) .658

Ahtanum Creek at Union Gap, Station No. 12502500 Use daily values measured at AUGW NA

Union Gap Canal Wasteway Set daily values equal to percent of PARW - (SUM1) .111

New Reservation Canal Headworks (Wapato Canal) Use daily values measured at RSCW NA

Sunnyside Canal near Parker Use daily values measured at SNCW NA

Yakima River at Parker, Station No. 1250500 Use daily values measured at PARW NA

Roza Canal Wasteway No. 3 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0174

Snipes and Allen Ditch Diversion Set daily values equal to percent of SEXW .2065

Lateral 1 near the Donald-Wapato Road, near Wapato Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0161

Roza Canal Wasteway No. 4 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0039

Roza-Sunnyside Joint Drain 19.9 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0011

Roza-Sunnyside Joint Drain 20.8 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0017

East Toppenish Drain at Wilson Road, Station No 12505350 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0592

DID Drain 27 at mouth Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0026

Sub-Drain No. 35 at Parton Road, Station No. 12505410 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.1073

Granger Drain at Sheep Barns, Station No. 12505460? Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0584

Marion Drain at Indian Church Road, at Granger, Station No. 

12505510

Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0392

Coulee Drain near Satus Road Crossing (2 Drains?) Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0327
Appendix B 37

Location Flow calculation Decimal percent 

used in calculations

Toppenish Creek at Indian Church Road, Station 12507508 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

0.1122

DID 16 Drain Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0364

Satus Creek at Satus (at gage), Station No. 12508620 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.1402

South Drain near Satus, Station No. 12508630 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.1205

Satus No. 2 Drain Set daily values equal to percent of 

(YGVW-SUCW)-PARW

0.00

DID No. 7 Drain Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0085

Satus No. 3 Drain Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.039

Sulphur Creek Wasteway Use daily values measured at SUCW NA

Satus Drain 303 + Mabton West Wasteway at Highway 22 Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.1135

DID Drain 31 (Frazier Drain at Chase-Frasier Road) Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0436

Joint DID 2 Drain Set daily values equal to percent of 

(YGVW-SUCW)-PARW

.0465

Outlet for DID No. 10 Set daily values equal to percent of 

(YRPW+CHCW)-YGVW

.5075

Drain near Grandview-Prosser Highway 8/24-2B Set daily values equal to percent of 

(YRPW+CHCW)-YGVW

.0374

Roza-Sunnyside Joint Drain Set daily values equal to percent of 

(YRPW+CHCW)-YGVW

.4551

Chandler Canal at Prosser Dam, Station No. 12509499 Use daily values measured at CHCW NA

Yakima River at Prosser Use daily values measured at YRPW NA

Table B1. Method used to assign daily mean flow to sites used to define flow for the Roza-Prosser Reach water-temperature 

model.—Continued

[Flow calculation abbreviations are listed in table B2; SUM1 = All inflow between Roza Dam and Parker, Washington, minus flow to diversions. 

Abbreviations: Reclamation, Bureau of Reclamation; NA, not applicable]

Table B2. U.S. Bureau of Reclamation gaging stations used in 

calculations for the Roza–Prosser Reach water-temperature model.

[Data obtained from Hydromet database]

Station 

identification Station description

RBDW Yakima River below Roza Dam

RZCW Roza Canal at Headworks

SEXW Selah Moxee Canal

NRYW Naches River near Yakima

UNGW Union Gap Canal

BICW Moxee Drain at Birchfield Road

AUGW Ahtanum Creek at Union Gap

ROZW Roza Canal at 11.0 mile

RSCW New Reservation Canal

SNCW Sunnyside Canal

PARW Yakima River near Parker

SUCW Sulpher Creek at Holiday Road, near Sunnyside

YGVW Yakima River at Euclid Road Bridge, near Grandview

CHCW Chandler–Prosser Power Canal

YRPW Yakima River near Prosser
38 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

Appendix C. Regression Equations Used to Estimate Water Temperature for 

Each Surface-Water Source of the Roza–Prosser Reach, Washington.

Table C1. Regression equations used to estimate water temperature for each surface-water source of the Roza–Prosser Reach, 

Washington.

[Abbreviations: NA, Water temperature is not assigned to diversions; Tw, daily mean water temperature in degrees Celsius; m3/s, cubic meter per second]

Location Water temperature calculation

Yakima River below Roza Dam, near Roza Tw = 4.0+ 0.2991*(45-day moving average of daily mean air temperature) 

+ 0.3448*(daily mean average of air temperature)

Selah-Moxee Canal NA

Selah Creek at Canyon Road Crossing, near Pomona Tw = Tw at Wide Hollow Creek near mouth 

Wenas Creek near mouth on Reclamation land, near Selah Tw = Tw at Wide Hollow Creek near mouth 

Taylor Ditch at Harrison Road Bridge, near Selah Tw = Tw at Wide Hollow Creek near mouth 

Golf Course and Selah Sewage Outflow Creek near Selah Tw = Tw at Wide Hollow Creek near mouth 

Naches River near North Yakima, near mouth at Reclamation 

gaging station 12499900 

Tw = 2.4 + 0.4635*(45-day moving average of daily mean air temperature) 

+ 0.2992*(daily mean average of air temperature) – 0.002*(flow (m3

/s) at 

the Naches River at Yakima gaging station)

Moxee Canal NA

Hubbard Canal NA

Union Gap Canal NA

Richartz Ditch Tw = Tw at Wide Hollow Creek near Mouth 

Roza Wasteway No. 2 (at Reclamation) Tw = Tw at Wide Hollow Creek near Mouth 

Moxee Drain at Thrope Road Tw = Tw at Wide Hollow Creek near Mouth 

Wide Hollow Creek near mouth Tw = (0.5768*daily mean air temperature) + 20.8

Ahtanum Creek at Union Gap, Station No. 12502500 Tw = Tw at Wide Hollow Creek near Mouth 

Union Gap Canal Wasteway Tw = Tw at Wide Hollow Creek near Mouth 

New Reservation Canal Headworks (Wapato Canal) NA

Sunnyside Canal near Parker NA

Yakima River at Parker, Station No. 1250500 NA

Roza Canal Wasteway No. 3 Tw = Tw at Lateral 1 near the Donald-Wapato Road near Wapato

Snipes and Allen Ditch Diversion NA

Lateral 1 near the Donald-Wapato Road, near Wapato Tw = (1.1037*daily mean air temperature) + 26.4

Roza Canal Wasteway No. 4 Tw = Tw at Lateral 1 near the Donald-Wapato Road near Wapato

Roza-Sunnyside Joint Drain 19.9 Tw = Tw at Lateral 1 near the Donald-Wapato Road near Wapato

Roza-Sunnyside Joint Drain 20.8 Tw = Tw at Lateral 1 near the Donald-Wapato Road near Wapato

East Toppenish Drain at Wilson Road, Station No 12505350 Tw = (0.5567*daily mean air temperature) + 20.6

DID Drain 27 at mouth Tw = Tw at Sub-Drain No. 35 at Parton Road, Station No. 12505410

Sub-Drain No. 35 at Parton Road, Station No. 12505410 Tw = (0.5074*daily mean air temperature) + 20.1

Granger Drain at Sheep Barns, Station No. 12505460 Tw = Tw at Sub-Drain No. 35 at Parton Road, Station No. 12505410

Marion Drain at Indian Church Road, at Granger, 

Station No. 12505510

Tw = (0.7477*daily mean air temperature) + 23.1

Coulee Drain near Satus Road Crossing Tw = (0.7312*daily mean air temperature) + 22.8

Toppenish Creek at Indian Church Road, Station 12507508 Tw = (1.0704*daily mean air temperature) + 22.0

DID 16 Drain Tw = Tw at Coulee Drain near Satus Road Crossing

Satus Creek at Satus (at gage), Station No. 12508620 Tw = (0.8225*daily mean air temperature) + 23.4

South Drain near Satus, Station No. 12508630 Tw = (0.915*daily mean air temperature) + 24.5

Satus No. 2 Drain Tw = Tw at South Drain near Satus, Station No. 12508630

DID No. 7 Drain Tw = (0.9929*daily mean air temperature) + 24.3

Satus No. 3 Drain Tw = Tw at DID No. 7 Drain 

Sulphur Creek Wasteway Tw = Tw at DID No. 7 Drain 

Satus Drain 303 + Mabton West Wasteway at Highway 22 Tw = (1.1977*daily mean air temperature) + 27.5

DID Drain 31 (Frazier Drain at Chase-Frasier Road) Tw = Tw at Satus Drain 303 + Mabton West Wasteway at Highway 22

Joint DID 2 Drain Tw = Tw at Satus Drain 303 + Mabton West Wasteway at Highway 22

Outlet for DID No. 10 Tw = Tw at Satus Drain 303 + Mabton West Wasteway at Highway 22

Drain near Grandview-Prosser Highway 8/24-2B Tw = Tw at Satus Drain 303 + Mabton West Wasteway at Highway 22

Roza-Sunnyside Joint Drain Tw = Tw at Satus Drain 303 + Mabton West Wasteway at Highway 22

Chandler Canal at Prosser Dam, Station No. 12509499 NA

Yakima River at Prosser NA
Appendix D 39

Appendix D. Example of the Shading Effects Field Sheet. 

Shading Effects Field Sheet

Location______________________________________________

______________________________________________

Date: _________ Time: _______ Hydrographer(s) _____________

GPS Coordinates: N ____° ____’ _____” accuracy +/-_______ft

(at center of river) W____° ____’ _____”

Stream Azimulth (-90° to 90°) ______° Magnetic or True North?

Stream Width _____________ft

 West Bank East Bank

Topographic Altitude __________° __________°

Vegetation height (Vh) __________ft __________ft

Vegetation crown (Vc) __________ft __________ft

Vegetation offset (Vo) __________ft __________ft

Vegetation density (Vd) __________% __________%

Maximum light __________Fc __________Fc

Shaded light __________Fc __________Fc

Remarks________________________________________________
40 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

Appendix E. Regression Equations Used to Estimate Daily Mean Water 

Temperature in Outflow from Five Reservoirs in the Yakima River Basin

The following section shows regression equations that 

were used to estimate daily mean water temperature in outflow 

from five reservoirs in the Yakima River basin. The equations 

were originally intended for generating input to the Roza–

Prosser Reach water-temperature model but were not included 

in the final version of the model. The equations are included 

here for documentation purposes. 

Regression equations were examined by using S-PLUS 

(Insightful Corp., 2002) and TableCurve 3D (Systat Software, 

Inc., 2002) for the purpose of estimating stream water 

temperatures downstream of five reservoirs. The process of 

variable selection for the regressions was identical to the 

process used in Roza Dam and Naches River regression 

development.

Bumping: (Linear Robust LTS, S-PLUS)

BUM = -1.809 + AT * 0.1449 + AT45dav * 0.7177

Robust multiple R2 = 0.89, Scale estimate of residual = 1.5 (°C), N = 1620

Cle Elum: (Linear Robust LTS, S-PLUS)

CLE = 16.28 + AT * 0.0518 - J’ * 0.09 - Q * 0.004

Robust multiple R2

 = 0.89, Scale estimate of residual = 2.56, N = 1279

Kachess: (Linear OLS, S-PLUS)

KAC = -2.1 + AT * 0.1729 + AT45dav * 0.7995

Multiple R2

 = 0.95, Residual Standard Error = 1.0 (°C), N = 460

Keechelus: (Linear OLS, S-PLUS)

KEE = 3.5 + AT * 0.2028 + AT45dav * 0.4633

Multiple R2

 = 0.91, Residual Standard Error = 1.4 (°C), N = 742

Rimrock: (Linear Robust LTS, S-PLUS)

RIM = 15.85 – AT45dav * 0.1071 – J’ * 0.073 + Q * 0.004

Robust multiple R2

 = 0.98, Scale estimate of residual = 0.90, N = 360

Explanation of variables:

AT = Air temperature at Yakima Air Terminal as provided from NOAA (°C).

AT45dav = 45 day moving average of air temperature at Yakima Air Terminal (°C).

Q = Flow downstream of dam (cubic meters per second). 

J’ = Number of days from warmest average water day (for CleElum J’= ABS(Julian day – 233), for 

Rimrock, J’ = ABS(Julian day – 258).

(°C) = degree Celsius.

N = Number of data sets used in regression development.
Appendix F 41

Appendix F. Daily Maximum, Mean, and Minimum Water Temperature for Sites 

in the Yakima River Basin, Washington 

Table F1. U.S. Geological Survey gaging stations where daily maximum, mean, and minimum water temperature data were collected, 

Yakima River basin, Washington.

[Data are available at http://wa.water.usgs.gov/projects/yakimatemp/data.htm. NAD27, North American Datum of 1927; NAD83, North 

American Datum of 1983]

Gaging station name Gaging station No. Latitude Longitude Datum

Gold Creek above Keechelus Lake near Hyak 12473980 47o 23' 25" 121o 22' 54" NAD27

Box Canyon Creek near Hyak 12473985 47o 21' 32.4" 121o 14' 44.4" NAD83

Cle Elum River above Cle Elum Lake, near Roslyn 12478300 47o 21' 19" 121o 06' 22" NAD27

American River near Nile 12488500 46o 58' 40" 121o 10' 03" NAD27

Tieton River below Oak Creek, near Naches 12493005 46o 43' 39" 120o 8' 35.5" NAD83

Naches River above Divrsion Dam, near Yakima 12498690 46o 37' 56" 120o 35' 15" NAD27

Cowiche Creek near Yakima 12498986 46o 37' 38" 120o 34' 52" NAD83

Wide Hollow Creek near Union Gap 12500447 46o 32' 20" 120o 28' 22" NAD27

Yakima River above Ahtanum Creek, at Union Gap 12500450 46o 32' 04" 120o 27' 58" NAD27

Yakima River near Wapato 12505050 46o 29' 09" 120o 25' 49" NAD27

East Toppenish Drain at Wilson Road, near Toppenish 12505350 46o 22' 04" 120o 15' 00" NAD27

Sub 35 Drain at Connie Road, near Granger 12505410 46o 20' 11" 120o 13' 48" NAD27

Lateral 1 Drain near Wapato 1250547010 46o 27' 45" 120o 24' 31" NAD83

Marion Drain at Indian Church Road and Highway 223 12505510 46o 19' 52" 120o 11' 54" NAD27

Toppenish Creek at Indain Church Road, near Granger 12507508 46o 18' 52" 120o 11' 53" NAD27

Coulee Drain at North Satus Road, near Satus 12507560 46o 17' 49" 120o 08' 42" NAD27

South Drain near Satus 12508630 46o 15' 35" 120o 07' 57" NAD27

Satus Creek below North Drain, near Satus 1250862050 46o 16' 32" 120o 08' 16" NAD27

DID 7 Drain near Mabton 12508670 46o 15' 32" 120o 03' 56" NAD83

Satus Drain 303 near Mabton 12508694 46o 13' 00" 120o 01' 14.5" NAD83

As a part of this project, water temperature data were 

collected at 20 sites within the Yakima River basin. Data 

were collected from May 27, 2005, to December 6, 2006, 

but the actual period of record for individual sites varies 

during this period. The data have been entered into the U.S. 

Geological Survey database (Automated Data Processing 

System, ADAPS) and are available in an Excel spreadsheet at 

the USGS Washington Water Science Center Yakima River 

Temperature Model project website at http://wa.water.usgs.

gov/projects/yakimatemp/data.htm. 

Several sites were located in the upper parts of the 

watershed and were not used in the development of the model, 

but they are included here for possible use in other studies. 

Water temperatures were recorded by Onset StowAway TidbiT 

thermistors or Onset Optic StowAway thermistors set in 

enclosures, usually a 1- x 3-inch PVC pipe, tied to something 

solid on the river bank and placed on the bottom of the riveror creek-channel. Either 30- or 60-minute recording cycles 

were used to log the data. Recorded values were checked with 

field measurements during visits to the gaging station.
42 Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005–06

This page intentionally left blank.
Manuscript approved for publication, April 28, 2008

Prepared by the USGS Publishing Network

Bill Gibbs 

Bob Crist

Debra Grillo

Lyn K. Osburn

Bobbie Jo Richey

Sharon Wahlstrom

For more information concerning the research in this report, contact the 

Washington Water Science Center Director, 

U.S. Geological Survey, 934 Broadway — Suite 300

Tacoma, Washington 98402

http://wa.water.usgs.gov
Voss and others— Modeling Water Temperature, Yakima River, Washington, Roza Diversion Dam to Prosser Dam, 2005–06 —Scientific Investigations Report 2008–5070