Scientific Investigations Report 2007–5158

Version 4.0, March 10, 2008

Methods for Estimating Magnitude and Frequency 

of Peak Flows for Natural Streams in Utah

U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the 

UTAH DEPARTMENT OF TRANSPORTATION AND THE UTAH DEPARTMENT OF NATURAL RESOURCES, 

DIVISIONS OF WATER RIGHTS AND WATER RESOURCES
Cover photo: South Ash Creek at I-15 near Pintura, Utah, looking upstream (north), January 11, 

2005. Photo by Dale E. Wilberg, U.S. Geological Survey.
Methods for Estimating Magnitude and 

Frequency of Peak Flows for Natural Streams 

in Utah

By Terry A. Kenney, Chris D. Wilkowske, and Shane J. Wright

U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the

UTAH DEPARTMENT OF TRANSPORTATION AND THE UTAH DEPARTMENT OF NATURAL 

RESOURCES,DIVISIONS OF WATER RIGHTS AND WATER RESOURCE

Scientific Investigations Report 2007–5158

Version 4.0, March 10, 2008 
U.S. Department of the Interior

DIRK KEMPTHORNE, Secretary 

U.S. Geological Survey

Mark D. Myers, Director

Reston, Virginia: 2007

For additional information write to:

U.S. Geological Survey

Director, USGS Utah Water Science Center

2329 W. Orton Circle

Salt Lake City, UT 84119–2047

Email: GS-W-UTpublic-info@usgs.gov 

URL: http://ut.water.usgs.gov/

For more information about the USGS and its products:

Telephone: 1-888-ASK-USGS

World Wide Web: http://www.usgs.gov/

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

U.S. Government.

 Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Scientific Investigations Report 2007–5158
iii

Contents

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

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

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

Acknowledgments................................................................................................................................1

Previous Studies ...................................................................................................................................2

Description of Utah...............................................................................................................................2

Flooding in Utah..............................................................................................................................................2

Envelope Curves....................................................................................................................................4

Computation of Peak Flow from Gaged Sites............................................................................................5

Methods for Estimating Frequency of Peak Flows at Gaged Sites ......................................................5

Frequency of Peak Flows at Gaged Sites ........................................................................................6

Frequency of Peak Flows at Ungaged Sites that are Near Gaged Sites on the 

Same Stream............................................................................................................................6

Regional Regression Method for Estimating Frequency of Peak Flows for Ungaged Sites .............8

Geohydrologic Regionalization of Utah ............................................................................................9

Basin and Climatic Characteristics ...................................................................................................9

Regional Regression Analysis ............................................................................................................9

Regional Regression Results ............................................................................................................12

Weighting Peak-Flow Estimates from Gaging Stations with Regional Regression 

Estimates .......................................................................................................................16

Limitations of Regional Regression Equations...............................................................................16

StreamStats Web-Based Computer Program ........................................................................................18

Summary........................................................................................................................................................18

References Cited..........................................................................................................................................19

Figures

1. Location of streamflow-gaging stations in Utah and bordering states used in 

regional regression analysis.......................................................................................................3

2. Maximum instantaneous natural peak flows for any site in Utah plotted with 

Crippen and Bue’s (1977) envelope curves for regions 13, 14, and 16, and the Costa

 (1987) envelope curve of maximum rainfall-runoff floods of the United States ................4

3. Map showing flood-region boundaries within the conterminous United States...............5

4. Generalized skew map for Utah (modified from Perica and Stayner, 2004)........................7

5. Example of streamflow-gaging stations with (a) an adequate fit and (b) a poor 

fit to the log-Pearson Type III distribution ................................................................................8

6. Geohydrologic regions of Utah used in regional regression analysis ..............................10

7. Other regions of Utah used to define geohydrologic regions, including (a) climatic

regions of Utah, (b) physiographic regions of Utah and (c) flood regions of the 

southwestern United States ....................................................................................................11

8. Residuals for 50-year recurrence-interval regression equation for region 4 ..................14

9. Leverage values and limit for 100-year recurrence-interval regression equation 

for region 2. .................................................................................................................................18
iv

Tables

1. Previous flood-frequency studies for Utah. .............................................................................2

2. Determined exponent a for each region...................................................................................8

3. Basin physiographic and climatic characteristics. ..............................................................11

4. Data sources used to compute basin physiographic and climatic characteristics. ......12

5. Predictive regression equations and their associated uncertainty in estimating 

peak flows for natural streams in Utah...................................................................................13

6. Range and average errors associated with regional regression equations for 

each recurrence interval. ........................................................................................................15

7. Leverage limits for regional regression equations, the number of streamflowgaging stations with leverage values that exceeded the limit that were retained 

in the equation development, and the maximum leverage value for those stations.......17

8. Range of predictor variables computed for streamflow-gaging stations used in 

the development of the regression equations. ......................................................................18

Appendix

 Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah 

and bordering states used in regional regression analysis. ...............................................21

Conversion Factors and Datums

Multiply By To obtain

Length

inch (in) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2

) 2.590 square kilometer (km2) 

Flow rate

cubic foot per second (ft3

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

inch per year (in/yr) 25.4 millimeter per year (mm/yr)

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).
Abstract

Estimates of the magnitude and frequency of peak 

streamflows is critical for the safe and cost-effective design 

of hydraulic structures and stream crossings, and accurate 

delineation of flood plains. Engineers, planners, resource 

managers, and scientists need accurate estimates of peak-flow 

return frequencies for locations on streams with and without 

streamflow-gaging stations. The 2-, 5-, 10-, 25-, 50-, 100-, 

200-, and 500-year recurrence-interval flows were estimated 

for 344 unregulated U.S. Geological Survey streamflowgaging stations in Utah and nearby in bordering states. 

These data along with 23 basin and climatic characteristics 

computed for each station were used to develop regional 

peak-flow frequency and magnitude regression equations for 

7 geohydrologic regions of Utah. These regression equations 

can be used to estimate the magnitude and frequency of peak 

flows for natural streams in Utah within the presented range 

of predictor variables. Uncertainty, presented as the average 

standard error of prediction, was computed for each developed 

equation. Equations developed using data from more than 35 

gaging stations had standard errors of prediction that ranged 

from 35 to 108 percent, and errors for equations developed 

using data from less than 35 gaging stations ranged from 50 to 

357 percent. 

Introduction

Reliable estimates of peak streamflow are needed 

by engineers, land-use planners, resource managers, and 

scientists. The magnitude and frequency of peak flows are 

required for safe and cost-effective design of near-stream or 

instream structures, flood-plain delineation, and flood-hazard 

assessment. These types of data are readily available for 

streams with streamflow-gaging stations; however, data often 

are needed at locations lacking such stations. Techniques such 

as multiple-linear regression allow estimates of peak flows at 

ungaged locations to be obtained through defined statistical 

associations between physical characteristics and peakflow data obtained from gaged sites. The U.S. Geological 

Survey (USGS), in cooperation with the Utah Department of 

Transportation and the Utah Department of Natural Resources, 

Divisions of Water Rights and Water Resources, completed 

this study to develop new regional regression equations 

for the State of Utah. The regional regression equations 

presented were developed by using annual peak flow-data 

from streamflow-gaging stations in Utah and bordering states 

through water year 2005. 

Purpose and Scope

This report documents the development of regional 

regression equations that can be used to estimate peak 

flows at the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year 

recurrence intervals at ungaged sites in Utah. Methods for 

estimating peak-flow magnitude and frequency for gaged sites 

and at locations near gage sites are presented. A technique 

is discussed for weighting peak flows determined from 

both regional regression equations and gage data using the 

equivalent years of record metric and the number of years of 

annual peak record. Limitations associated with the regional 

regression equations are outlined, including the assessment 

of prediction errors and determination of ungaged sites 

applicable to the models. Finally, StreamStats, a USGS webbased computer program that allows for the application of the 

developed regression equations in an efficient and accurate 

manner, is introduced.

Acknowledgments

The authors would like to acknowledge the efforts of 

the dedicated hydrographers, past and present, from the 

Utah Water Science Center and surrounding Water Science 

Centers that are and have been responsible for the collection, 

computation, and analysis of streamflow data, particularly 

peak-flow data, used in this report. Special thanks go to 

Kenny Eng of the USGS who provided statistical expertise and 

a computer program that improved the efficiency of applying 

the generalized least-squares techniques of Stedinger and 

Tasker (1985) and Tasker and Stedinger (1989). 

Methods for Estimating Magnitude and Frequency of Peak 

Flows for Natural Streams in Utah 

By Terry A. Kenney, Chris D. Wilkowske, and Shane J. Wright
Previous Studies

Many previous studies in Utah have examined floodfrequency relations (table 1). The index-flood method was 

used in the earlier studies of Patterson and Somers (1966) and 

Butler and others (1966). The first multiple-linear regression 

study of regional flood frequency for Utah was completed by 

Butler and Cruff (1971). Since 1971, more than five multiplelinear regression studies have been completed. Aside from 

Fields (1975), which examined the relation between channel 

geometry characteristics and flood frequency, these studies 

used basin characteristics to develop regional equations to 

predict peak-flow frequency. Thomas and others (1997) 

developed regional regression equations for the entire 

southwestern United States, including Utah, from streamflowgaging station data through 1986. Regression equations for 

the Virgin River basin were developed in Perica and Grenney 

(2003), and regression equations were developed for the 

Weber River basin in Perica and Stayner (2004).

Description of Utah

Located within both the Colorado River Basin and the 

Great Basin, Utah possesses a wide variety of physiographic 

characteristics. The landscape is diverse and includes high 

alpine regions, expansive arid desert, and vast slickrock 

canyonlands. The major drainage basins in Utah are the 

Green River basin, Colorado River Basin, Virgin River basin, 

Sevier River basin, and the Great Basin (Great Salt Lake) (fig. 

1). Land-surface elevations range from 13,528 ft at Kings 

Peak in the Uinta Mountains of northeastern Utah, to about 

2,000 ft near Beaver Dam Wash in southwestern Utah. The 

spatial variability in precipitation is quite large. More than 60 

in/yr of precipitation, mostly as snow, falls in the mountains 

of the northern part of Utah, while the annual precipitation 

in the Great Salt Lake Desert is about 5 in (Daly and others, 

1994). Average annual temperatures vary throughout the 

state as a function of both elevation and latitude. The diverse 

physiographic and climatic conditions throughout Utah create 

a unique flood-hydrology.

Flooding in Utah

Floods and, to a similar degree, annual peak flows, result 

from three atmospheric conditions that produce substantial 

precipitation. Mountain snowpack, which accumulates from 

late fall through the spring, is generated by west-to-eastmoving Pacific frontal systems (U.S. Geological Survey, 

1991). Storms associated with upper-level low-pressure 

systems, which generally occur in the spring and early fall, 

often are widespread and slow moving (U.S. Geological 

Survey, 1991). Monsoonal thunderstorms, common in late 

summer, are precipitation events of short duration and high 

intensity. 

Table 1. Previous flood-frequency studies for Utah.

Year Study Authors Method

1966 Magnitude and frequency of floods in the United 

States, Part 9. Colorado River Basin

Patterson and Somers Index-flood

1966 Magnitude and frequency of floods in the United 

States, Part 10. The Great Basin

Butler and others Index-flood

1971 Floods of Utah, magnitude and frequency characteristics through 1969Butler and Cruff Ordinary least squares multiple regression basin 

and climate

1975 Estimating streamflow characteristics for streams in 

Utah using selected channel-geometry parameters

Fields Ordinary least squares multiple regression channel geometry

1976 Estimating runoff volumes and flood hydrographs 

in the Colorado River Basin, Southern Utah

Eychaner Ordinary least squares multiple regression basin 

and climate

1983 Methods for estimating peak discharge and flood 

boundaries of streams in Utah

Thomas and Lindskov Ordinary least squares multiple regression basin 

and climate

1985 Manual for estimating selected streamflow characteristics of natural-flow streams in the Colorado 

River Basin in Utah

Christenson and others Ordinary least squares multiple regression basin 

and climate

1997 Methods for estimating magnitude and frequency of 

floods in the Southwestern United States

Thomas and others Generalized least squares multiple regression 

basin and climate

2003 Regional flood frequency analysis for selected 

basins in Utah Part I: Virgin River basin

Perica and Grenney Ordinary least squares multiple regression basin 

and climate

2004 Regional flood frequency analysis for selected 

basins in Utah Part II: Weber River basin

Perica and Stayner Ordinary least squares multiple regression basin 

and climate

2 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
Co lora d o R i v e r

G re e n R iv e r

E s cal a n te R iv er

S a n Ju a n R iv er

R i e

Dir t y D ev i l Ri v e r

Pric e Riv e r

S trawberry Riv er

314

119 208

334

355

354 353 352

351

350

347

346 348 318

349

322

324 323

331

327

319

287

286

285

284

282

280 283

281

316

317 320

205

204

206 207

278

314

308 310 304

301

309

307

306

221

222

215

276

277

229

228

227

224

226 220

268 223

251

253

254

255

256

257 258

259 264

265

267

266

263

273

272 271

225

270

269 181

184

183 182

203

202

201

275

274

186 185 191190

197

189

188

187

262

196 261

260 195

194

193

192

244

245 250

243

242 241

155

240

165

164

148

147

142

154

249 248

247

246 175

153

152

151 149 150

139

180

178

179

141

140

137138

136 156

146 157 145 143

144

158

159

160

162

161 163

232

134

135

128

133

124

127 126 125

132

131 129130

21 17

19

1 18 20

22

23

24

26

2527

57

28

29 30

59

60

58

53

54

56 55

61

168 167

166

77

75

76 78

80

79

81 82

174

177 173

171

170 169

198

200

91

8485

86 88 87

89 90

67

68

62 69 70

74

66 65

63

71

72

73

64

52

46 47

49

48

45 104

103 51 31

50

231 230

305

303

302

333 328

329

176

252

279

ea r River

Virgin v r

Colorado

Gaging station and map ID.

0 20 40 60 80 100 Miles EXPLANATION

0 20 40 60 80 100 Kilometers

37°5'

42°10'

113°55'

New Mexico

Nevada

108°50'

Utah

Arizona

Idaho

38

Great

Salt

Lake

Wyoming

120

342 344

343

340

345 326 325

339 330

341

321

121

123

122

315

313

311

312

292

293

289

291 290

288

300

217

219

218

216

209

296 295

210 211

213

214

212

238

238

239

16

15

14

13

12

11

10

5

6

3 2 4

83

172

199

92

108

94 93

95

99

98 97

96

105

44

43

42

41

40

38

39

101

102

7

32

36

37

34

33

35 100

117

118 116

115

114

113

111

109

106

107

8

9

299

298 297

294

236

233

234

235

112

335

336

337 338 332

330

Co lora d o R i v e r

G re e n R iv e r

E s cal a n te R iv er

S a n Ju a n R iv er

R i e

Dir t y D ev i l Ri v e r

Pric e Riv e r

S trawberry Riv er

314

119 208

334

355

354 353 352

351

350

347

346 348 318

349

322

324 323

331

327

319

287

286

285

284

282

280 283

281

316

317 320

205

204

206 207

278

314

308 310 304

301

309

307

306

221

222

215

276

277

229

228

227

224

226 220

268 223

251

253

254

255

256

257 258

259 264

265

267

266

263

273

272 271

225

270

269 181

184

183 182

203

202

201

275

274

186 185 191190

197

189

188

187

262

196 261

260 195

194

193

192

244

245 250

243

242 241

155

240

165

164

148

147

142

154

249 248

247

246 175

153 152

151 149 150

139

180

178

179

141

140

137138

136 156

146 157 145 143

144

158

159

160

162

161 163

232

134

135

128

133

124

127 126 125

132

131 129130

21 17

19

1 18 20

22

23

24

26

2527

57

28

29 30

59

60

58

53

54

56 55

61

168 167

166

77

75

76 78

80

79

81 82

174

177 173

171

170 169

198

200

91

8485

86 88 87

89 90

67

68

62 69 70

74

66 65

63

71

72

73

64

52

46 47

49

48

45 104

103 51 31

50

231 230

305

303

302

333 328

329

176

252

279

311

Figure 1. Location of streamflow-gaging stations in Utah and bordering states used in regional regression analysis.

Flooding in Utah 3
Peak streamflows for most streams in northern and 

eastern Utah are dominated by snowmelt runoff. The 

snowmelt runoff period typically is between April and late 

June, with peaks occurring in late May and early June. Rapid 

melting of exceptionally large snowpacks can lead to statewide 

flooding, as was the case in 1983. The largest and most 

damaging floods in Utah generally are associated with rain 

that falls on melting snow, and the most common flooding in 

Utah comes in the form of flash floods related to heavy local 

precipitation (Wilkowske and others, 2006).

Envelope Curves

Envelope curves allow for a method of estimating 

potential maximum floodflows in a given geographic area. 

These curves are developed by plotting the largest peak flow 

for all gage sites against drainage area. With streamflow 

record length considered to be long enough to capture 

maximum peak flows at some of the stations in the dataset, a 

limiting relation between drainage area and peak flow can be 

interpreted. Physiographic and atmospheric characteristics 

are the determining factors of a maximum floodflow, and 

therefore different locales possess different envelopes of 

drainage area and streamflow. A number of studies have 

examined this relation for different geographic areas for 

which envelope curves were developed (Creager, 1939; Hoyt 

and Langbein, 1955; Matthai, 1969; Crippen and Bue, 1977; 

Jensen and others, 1978; Crippen, 1982; and Costa, 1987). 

For perspective, the maximum instantaneous natural 

peak flows for any site in Utah stored in the USGS National 

Water Information System (NWIS) database are plotted along 

with three envelope curves developed in Crippen and Bue 

(1977) and an envelope curve developed in Costa (1987) (fig. 

2). Crippen and Bue (1977) defined 17 flood regions for the 

conterminous United States, and most of Utah is contained 

within region 14 (fig. 3). However, much of the western part 

of the state falls into region 16, and some of the northeastern 

part of the state is in region 13. Regions 13 and 16 contain 

DRAINAGE AREA, IN SQUARE MILES

1 10 100 1,000 10,000

100

1,000

10,000

100,000

1,000,000

DISCHARGE, IN CUBIC FEET PER SECOND

Peak flows, Utah streams

Crippen and Bue region 13

Crippen and Bue region 14

Crippen and Bue region 16

Maximum rainfall-runoff floods

 of the United States (Costa, 1987) 

Figure 2. Maximum instantaneous natural peak flows for any site in Utah plotted with Crippen and Bue’s (1977) envelope curves 

for regions 13, 14, and 16, and the Costa (1987) envelope curve of maximum rainfall-runoff floods of the United States. 

4 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
portions of Idaho, Wyoming, Montana, Washington, Nevada, 

California, and Arizona and are shown to not represent the 

drainage area and peak-flow limits for Utah. The curve for 

region 14, which encompasses much of Utah and parts of 

Colorado, New Mexico, and Arizona appears to be valid for 

Utah streams. Maximum natural peak flows for streams in 

Utah are well below the envelope curve of the United States 

(Costa, 1987).

Computation of Peak Flow from

Gaged Sites

 For more than 100 years, the USGS has been publishing 

the annual peak flow at streamflow-gaging stations. The 

annual peak flow at a gaging station is the largest computed 

streamflow that occurred during a single water year (October 

1-September 30), typically computed by applying the highest 

recorded water-surface elevation, or gage-height, to the active 

stage-discharge rating for that particular streamflow-gaging 

station. Annual peak-flow data are available for continuous 

streamflow-gaging stations where daily-mean flows are 

computed, as well as stations that only record maximum 

water-surface elevations, or gage-heights, commonly referred 

to as crest-stage streamflow-gaging stations. For the United 

States, these data are stored in the USGS NWIS database and 

are available on the world wide web at http://nwis.waterdata.

usgs.gov/usa/nwis/peak. Peak-flow data have proven extremely 

useful for a variety of engineering design, water-resource 

management, and hydrologic science applications. 

Methods for Estimating

Frequency of Peak Flows at

Gaged Sites

 Commonly, the annual peak-flow dataset for a 

single streamflow-gaging station is used to estimate 

return frequencies or recurrence intervals of specific peak 

streamflows for that site. By fitting the recorded annual 

peak flows to a probability distribution, traditionally 

the log-Pearson Type III (LPIII), probability-based flow 

1

4

5 2

3

7

6

8

15

17

11

13

12

14

16

10

9

EXPLANATION

Regional boundry 

Digital base from U.S. Geological Survey 

10 Region 

1:2,000,000,1970 

Albers equal-area projection based on 

standard parallels 29.5 and 45.5 degrees

0 250 500 750 MILES 

0 250 500 750 KILOMETERS 

Figure 3. Map showing flood-region boundaries within the conterminous United States (modified from Crippen and Bue, 1977).

Methods for Estimating Frequency of Peak Flows at Gaged Sites 5
recurrence intervals, such as the 100-year peak streamflow, 

can be estimated. Bulletin 17B (U.S. Interagency Advisory 

Committee on Water Data, 1982) outlines this most common 

method of determining the frequency of peak flows at 

streamflow-gaging stations. The methods outlined in Bulletin 

17B are specific to natural streamflow conditions and should 

not be applied to watersheds affected by reservoir regulation, 

urbanization, or other conditions that may affect the natural 

runoff-streamflow relation. Recurrence-interval flows at 

streamflow-gaging stations provide the basis for developing 

regional flood-frequency regression equations. 

Frequency of Peak Flows at Gaged Sites 

 USGS streamflow-gaging stations in Utah and nearby in 

surrounding states were examined to determined if they meet 

criteria established in Bulletin 17B (U.S. Interagency Advisory 

Committee on Water Data, 1982). Selected gaging-station 

data were not affected by regulation or urbanization and 

possessed a minimum of 10 annual peaks. Historic data from 

gaging stations currently regulated by reservoirs that possessed 

10 or more annual peaks prior to reservoir construction also 

were selected. For any station, no more than 25 percent of the 

annual peaks could be reported as below the defined gage base 

flow or 0 ft3

/s. A total of 355 streamflow-gaging stations were 

selected for this analysis (fig. 1). The peak-flow data from 

these stations consist of a mixed population of rainfall- and 

snowmelt-related events. 

The 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year 

recurrence-interval flows (appendix 1) were determined for the 

selected stations following the techniques outlined in Bulletin 

17B. As previously mentioned, flows for specific recurrence 

intervals are obtained by fitting the annual peak-flow record 

from a station to a LPIII distribution. Recurrence intervals 

in years and exceedance probabilities are mathematical 

inverses. For example, a flow with an exceedance probability 

of 0.10 has a recurrence interval of 10 years (1/0.10 = 10) 

(Berenbrock, 2002). A 10-year peak flow has a 1 in 10 

probability of occurring in a single year. The equation for 

fitting the LPIII distribution to a series of annual peak flows 

takes the form (U.S. Interagency Advisory Committee on 

Water Data, 1982):

logQ X KS T = + (1)

where:

QT is T-year peak flow, in cubic feet per second, where T 

is recurrence interval;

X is mean of the log-transformed annual peak flow,

K is frequency factor dependent on the recurrence 

interval and the skew coefficient of the log-transformed 

annual peak flow, and

S is standard deviation of the log-transformed annual 

peak flow.

As shown by equation 1, the skew of the annual peak 

flow, contained in K, is a critical component in fitting the 

distribution. Because the skew computed from the station 

record is sensitive to extreme events it is recommended to 

weight this skew, often termed station skew, with a skew 

computed from nearby sites, termed generalized skew (U.S. 

Interagency Advisory Committee on Water Data, 1982). 

Perica and Stayner (2004) developed a generalized skew map 

for the state of Utah that used stations with at least 30 years of 

record (fig. 4). Site-specific skews were plotted on a map, and 

a gridded skew map was developed by using linear and bicubic 

interpolation techniques. From the gridded map, Perica 

and Stayner (2004) developed a generalized skew contour 

map. For this study, generalized skew values used in the 

weighted skew computations for each station were obtained 

by interpolating between contours contained on this map. For 

the purposes of this report, the contours were extended into 

adjoining states to obtain generalized skew values for stations 

not located in Utah. 

For all stations, the LPIII fits to the systematic annual 

peak-flow record were graphically examined. Most stations 

fit the distribution adequately. However, 11 of the selected 

stations did not. For stations with poor fits, recurrenceinterval flows were not determined, and these stations were 

dropped from the analysis. Generally, stations with poor fits 

to the LPIII distribution contained short periods of record 

and a high variability in the annual peak series. The average 

period of record for the sites that fit poorly was 14 years, and 

the average standard deviation of the logarithms of annual 

peak flow was 1.00. The remaining stations had an average 

period of record of 26 years, and an average standard deviation 

of 0.37. An example of a station that fit well and one that fit 

poorly to the LPIII distribution is shown in figure 5. 

Frequency of Peak Flows at Ungaged Sites that 

are Near Gaged Sites on the Same Stream

Frequency of peak flows can be estimated at different 

locations on a stream containing a gage by using a ratio of 

drainage area for the ungaged and gaged sites. If the drainagearea ratio of the two locations falls between 1.5 and 0.5, there 

is no significant tributary inflow occurring between either site, 

and both basins are physically and climatically similar, then 

peak flows can be estimated by using the equation (Guimaraes 

and Bohman, 1992; Stamey and Hess, 1993): 

QT(u) = QT(g) (DAu / DAg)

a (2)

where:

QT(u) is T-year peak flow for ungaged site, in cubic feet per 

second, where T is recurrence interval,

QT(g) is T-year peak flow for gaged site, in cubic feet per 

second,

DAu is drainage area for the ungaged site,

6 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
37°5'

42°10'

113°55' 108°50'

EXPLANATION

0

0 .50

-0 .2 5

-0 .50

-0.7 5

-0 .50

0

-0 .2 5

0 .2 5

0 .50

-0 .2 5

0

0

0 .2 5

0

-0 .2 5

0 .2 5

0 .2 5 0

0

-0 .2 5

-0 .2 5

Green River

Moab

Saint George

Cedar City

Provo

Salt Lake City

Ogden

Logan

0.25

Vernal

Line showing equal skew value—Dashed 

 where approximately located. 

 Contour interval 0.25 

0.25

0 20 40 60 80 100 Miles

0 20 40 60 80 100 Kilometers

Figure 4. Generalized skew map for Utah (modified from Perica and Stayner, 2004). 

Methods for Estimating Frequency of Peak Flows at Gaged Sites 7
DAg is drainage area for the gaged site, and

a is an exponent for the drainage area for each 

hydrologic region (table 2).

The exponent 

a was determined 

by regressing the 

logarithms of each 

T-year flow (T = 2, 5, 

10, 25, 50, 100, 200, 

and 500) against the 

logarithms of drainage 

area for each region. 

The exponent a for each 

region is the average of 

the coefficients for the 

logarithm of drainage 

area for all T-year flows (table 2).

If an ungaged site is located between two gaged sites 

on the same stream, the following equation can be used 

(Berenbrock, 2002):

(QT(g1) (DAg2 – DAu) + QT(g2) (DAu – DAg1)) QT(u) = (DAg2 – DAg1)

(3)

where:

QT(u) is T-year peak flow for ungaged site between gaged 

sites, in cubic feet per second, where T is recurrence 

interval,

QT(g1) is T-year peak flow for upstream gaged site, in cubic 

feet per second,

QT(g2) is T-year peak flow for downstream gaged site, in 

cubic feet per second,

DAu is drainage area for the ungaged site,

DAg1 is drainage area for the upstream gaged site, and

DAg2 is drainage area for the downstream gaged site.

Regional Regression Method for

Estimating Frequency of Peak 

Flows for Ungaged Sites

Peak streamflow data, and therefore estimates of 

specific recurrence-interval flows, are not directly available 

for streams without established streamflow-gaging stations. 

The concept of expanding the utility of gaged-site data for 

use at ungaged locations with similar physiographic and 

climatic characteristics is not new, and several methods have 

been examined and tested during the past 50 years. The 

method of choice for the past 30 years has been statistically 

based regional equations that predict peak streamflow. For 

this method, a study area is divided into regions of similar 

physiographic and climatic characteristics. Multiple-linear 

regression techniques are applied to determine coefficients 

for statistically significant predictors of peak streamflow. For 

every region, regression models or equations are developed for 

each desired recurrence-interval flow such as the 2-, 5-, 10-, 

25-, 50-, 100-, 200-, and 500-year peak flow. As previously 

discussed, for Utah there have been a number of studies that 

have developed regional regression equations to predict peak 

flows. The previous effort that encompassed the entire state of 

Utah used data through water year 1986 (Thomas and others, 

1997). This study used annual peak-flow data collected 

through water year 2005 to develop regional regression 

equations. Since the past statewide effort, the available 

dataset has been extended by 19 years, and computational 

102

100 99.5 98 95 90 80 70 50 30 20 10 5 2 1 0.5 0.2

103

104

Bulletin 17B frequency

Peaks from systematic record

Frequency of systematic record

95-percent confidence limits

ANNUAL EXCEEDANCE PROBABILITY, IN PERCENT ANNUAL EXCEEDANCE PROBABILITY, IN PERCENT

ANNUAL PEAK DISCHARGE, 

IN CUBIC FEET PER SECOND

ANNUAL PEAK DISCHARGE, 

IN CUBIC FEET PER SECOND

Station—09292500

10-1

1

100 99.5 98 95 90 80 70 50 30 20 10 5 2 1 0.5 0.2

103

102

104

105

10

106

Bulletin 17B frequency

Peaks from systematic record

Frequency of systematic record

95-percent confidence limits

Station—09415050

A B

Figure 5. Example of streamflow-gaging stations with (a) an adequate fit and (b) a poor fit to the log-Pearson Type III 

distribution.

Table 2. Determined exponent a

for each region.

Region Exponent a

1 0.49

2 .51

3 .21

4 .84

5 .53

6 .31

7 .45

8 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
techniques, including Geographic Information Systems (GIS) 

and statistical algorithms, have advanced considerably. GIS 

allows for the computation of complex basin characteristics, 

previously very difficult to compute, that can be statistically 

examined as predictors of peak flows. 

Geohydrologic Regionalization of Utah 

In an effort to define best-fit regression equations based 

upon basin physiographic and climatic characteristics, seven 

distinct geohydrologic regions for Utah were defined (fig. 6). 

The regions were determined on the basis of the following 

factors: (1) statistically significant groupings of basin 

and climatic characteristics of streamflow-gaging stations 

using cluster analysis techniques; (2) statewide landscape 

features; (3) defined climatic regions (fig. 7a); (4) defined 

physiographic provinces (fig. 7b); (5) previously defined 

flood regions (Thomas and others, 1997) (fig. 7c); and (6) 

scientific judgment based upon general hydrologic knowledge 

of the area. The seven regions were divided along hydrologic 

boundaries except for a portion of the divisions between 

regions 3 and 5, 3 and 7, and 2 and 4. These nonhydrologic 

divisions agreed with the general definition of the surrounding 

regions taking into account the factors discussed above. The 

location of streamflow-gaging stations used in the definition 

of the regions is shown on figure 1. Regions 1, 2, 4, and 5 are 

generally related to the two major mountain ranges in Utah, 

the Wasatch and Uinta Mountains. The north slope of the 

Uinta Mountains and most of the upper Bear River basin are 

contained in region 1. The northern and central parts of the 

Wasatch Mountains define regions 2 and 5 respectively. The 

south slope of the Uinta Mountains, including the Uinta Basin, 

makes up region 4. Region 3 includes the western part of the 

state, most of which is contained within the arid Basin and 

Range physiographic province. Region 6, the largest defined, 

encompasses most of the Colorado Plateau, and the Virgin 

River basin is mostly contained in region 7. 

Basin and Climatic Characteristics

Twenty-one basin characteristics and two climatic 

characteristics were computed for each streamflow-gaging 

station by using GIS techniques. Conceptually, each of 

these characteristics has an influence upon the magnitude 

and frequency of peak streamflow. Geospatial algorithms, 

developed using Arc Macro Language programs written 

for ArcGIS (Environmental Systems Research Institute, 

Inc., 1999), were used in the computation of the basin 

characteristics. The values generated for each characteristic 

are directly dependent upon the algorithm, dataset, and 

spatial scale(s) used in their computation. As described 

below, the quantified uncertainties associated with the 

regression equations developed in this study are associated 

with the methods used to compute basin characteristics. 

For the uncertainties to be valid, the predictor variables 

in the equations should be computed using the same 

algorithms, datasets, and spatial scales. A list of the 

computed characteristics, the corresponding units, and the 

datasets they were computed from are contained in table 3. 

Descriptions of the datasets used are contained in table 4. Of 

the 23 characteristics examined for statistical significance in 

predicting the 8 recurrence interval flows, 5 were included in 

one or more of the final sets of regional equations.

Regional Regression Analysis

The regional regression method, as presented in this 

report, regresses basin and climatic characteristics computed 

for each streamflow-gaging station previously selected 

against the desired recurrence-interval flows for stations in 

each region. Stations determined to fit poorly to the LPIII 

distribution were not used in the analysis. For all seven 

regions, equations for the eight selected recurrence-interval 

flows were developed. Statistical outliers in the peak-flow 

data and the basin and climatic characteristics were screened. 

All peak-flow data were transformed to base-10 logarithms. 

Normality in the basin and climatic characteristic data 

was examined, and for most characteristics normality was 

enhanced through a transformation to base-10 logarithms. For 

characteristics represented as percentages, such as percent of 

basin defined as herbaceous upland (Vogelmann and others, 

1998), a value of 1 percent was added prior to transformation 

to prevent null values associated with an attempt to take a 

logarithm of 0. Elevations were first divided by 1,000 in an 

effort to obtain smaller, more-convenient coefficient values. 

An iterative stepwise regression approach was used 

in an exploratory capacity to test several combinations of 

basin and climatic characteristics for each region. Different 

combinations of basin and climatic characteristics were 

necessary because of the presence of multi-colinearity and 

(or) high correlation between some characteristics. The 

stepwise regressions were done using traditional weighted 

least-squares (WLS) technique. In an effort to mimic some 

of the weighting associated with the generalized least-squares 

(GLS) regression technique discussed below, weights for 

each station were computed by dividing total years of peak 

flow for the station by the maximum years of peak flow for 

a single station in that region. For each stepwise equation a 

variety of statistical metrics were evaluated to determine the 

most explanatory variables to further examine with the GLS 

regression technique.

GLS regression technique was applied by a program 

based on methods described by Stedinger and Tasker (1985) 

and Tasker and Stedinger (1989) to achieve the final regression 

models. For regional peak-flow frequency analyses, GLS 

regression is generally chosen over conventional least-squares 

regression techniques for its ability to account for cross 

correlation between sites, differences in station record length, 

and variability in peak flows at gaging stations. Traditional 

ordinary least-squares techniques assume independence, 

Regional Regression Method for Estimating Frequency of Peak Flows for Ungaged Sites 9
Great

Salt

Lake

Lake Powell

Utah

Lake

Colorado

River

Juan

San

River

Salt Lake City

1

2

3

4

5

6

7

37°5'

42°10'

113°55' 108°50'

0 20 40 60 80 100 Miles

0 20 40 60 80 100 Kilometers

Figure 6. Geohydrologic regions of Utah used in regional regression analysis. 

10 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
!

5

6

7

2

4

3

1

Logan

Ogden

Provo Vernal

Moab

Green River

Salt Lake City

Cedar City

Saint George

A

Middle Rocky

Mountains

Colorado

Plateau Basin and Range 

Colorado Plateau 

Transition

Basin and Range

B

7

4

9

8

6

3

!

Logan

Ogden

Provo Vernal

Moab

Green River

Salt Lake City

Cedar City

Saint George

C

 Number is climate region Number is flood region

Figure 7. Other regions of Utah used to define geohydrologic regions, including (a) climatic regions of Utah (modified 

from National Oceanic and Atmospheric Administration, 1994), (b) physiographic regions of Utah (modified from Utah 

Geological Survey, 2007) and (c) flood regions of the southwestern United States (modified from Thomas and others, 

1997). 

Table 3. Basin physiographic and climatic characteristics.

[NED, National Elevation Dataset; NLCD, National Land Cover Dataset; PRISM, Parameter-Elevation Regressions on Independent Slopes Model; NOAA, 

National Oceanic and Atmospheric Administration]

Characteristic Unit Datasets used

Area square miles Watershed polygon generated by the StreamStats process

Perimeter length miles Watershed polygon generated by the StreamStats process 

Relief feet 10-meter NED

Relative relief feet per mile 10-meter NED

Elevation feet 10-meter NED

Maximum basin elevation feet 10-meter NED

Minimum basin elevation feet 10-meter NED

High elevation index-percent of area with elevation greater 

than 6,000 feet

percent 10-meter NED

Average basin slope percent 10-meter NED

Percent of basin with slope greater than 30 percent percent 10-meter NED

Percent of basin with slope greater than 30 percent and facing 

north

percent 10-meter NED

Elevation of basin at outlet feet 10-meter NED

Percent of area covered by forest percent NLCD 1992

Percent of area covered by agriculture percent NLCD 1992

Percent of area covered by barren land percent NLCD 1992

Percent of area covered by developed land percent NLCD 1992

Percent of area covered by shrubland percent NLCD 1992

Percent of area covered by herbaceous upland percent NLCD 1992

Percent of area covered by wetland percent NLCD 1992

Percent of area covered by woody land percent NLCD 1992

Mean annual precipitation (basin wide average) inches PRISM

24-hour storm total with 2-year return frequency, averaged 

throughout basin

inches NOAA-Atlas141

, NOAA-Atlas 22

1

 Used for Utah, Nevada, Arizona, and New Mexico

2

 Used for Idaho, Wyoming, and Colorado

Regional Regression Method for Estimating Frequency of Peak Flows for Ungaged Sites 11
ignoring cross correlations, between response variables. Peak 

flows between stations within a region often are correlated 

because of the widespread atmospheric conditions that they 

are the result of, and common years of record. Even though 

the response variables for the regression models developed 

in this study are recurrence interval flows derived from curve 

fitting, GLS technique examines the series of annual peaks at 

all stations as well as the geographic distance between stations 

to help determine the degree of potential correlation between 

sites. GLS regression technique utilizes weighting matrices 

that are populated from a “best fit” mathematical relation 

between sample cross-correlation coefficients and distance 

between sites for site pairs with long periods (typically 30 

years) of concurrent record (Tasker and Stedinger, 1989). 

Sites with correlated concurrent peak flows, as estimated by 

using the relation between correlation and distance between 

sites, are given less weight. Variability in the series of annual 

peak flows for each station is evaluated by using the standard 

deviation of the population and predictor variables of the 

station. In GLS regression technique, the standard deviation 

of the annual peak series and the input predictor variables 

of all sites are regressed. From this regression, standard 

deviations are computed to obtain unbiased estimates of 

standard deviation for each station which is used to assign 

weights that account for variability. Generally speaking, 

unless weights are developed to account for differences in 

time-sampling errors and their cross correlations, traditional 

ordinary least-squares techniques will assume equal sampling 

error. Time-sampling error is assumed to be less with longer 

station record. GLS regression technique accounts for this by 

giving more weight to stations with longer periods of record. 

Regional Regression Results

GLS regression equations for the 2-, 5-, 10-, 25-, 50-,

 100-, 200-, and 500-year recurrence-interval flows were 

developed for all seven regions (table 5). As can be seen, for 

each region the same set of predictor variables was used in 

all eight equations. This was done in an effort to provide a 

consistent frequency curve for any location within a specific 

region. The use of different variables for different recurrenceinterval flows allows the potential for flow to decrease 

with increasing frequency, a violation in the definition of a 

peak streamflow frequency curve (Asquith and Thompson, 

2005). In taking this approach, the variables chosen for each 

region were those that, on average, best predicted the eight 

recurrence-interval flows. Drainage area (DRNAREA) was 

used in all equations, mean basin elevation (ELEV) was 

included in three regions, and the variables mean annual 

precipitation (PRECIP), average basin slope (BSLDEM10M), 

and percent of basin defined as herbaceous upland 

(HERBUPLND) were each used in the equations for one 

region. Past peak-flow regression equations for Utah have not 

included the predictor variables mean basin slope or percent of 

basin defined as herbaceous upland. A graph of residuals for 

the 50-year flow regression equation for region 4 is shown in 

figure 8. Ideally for valid unbiased regression equations, it is 

desired that residuals be distributed randomly about the zero 

line without any discernable pattern. Graphs of the residuals 

were examined for all developed equations.

A measure of the average error the regression equation 

will yield is the average variance of prediction (Stedinger and 

Tasker, 1985; Tasker and Stedinger, 1989), AVP. Modified for 

GLS regression, AVP is given by: 

Table 4. Data sources used to compute basin physiographic and climatic characteristics. 

Dataset name Source description

10-meter National Elevation Dataset (NED) U.S. Geological Survey, 1999, National elevation dataset: U.S. Geological Survey 

Fact Sheet 148-99, accessed July 12, 2007, at 

http://erg.usgs.gov/isb/pubs/factsheets/fs14899.html

National Land Cover Dataset 1992 (NLCD 1992) Vogelmann, J.E., Sohl, T.L., Campbell, P.V., and Shaw, D.M., 1998, Regional land 

cover characterization using Landsat Thematic Mapper data and ancillary data 

sources: Environmental Monitoring and Assessment, v. 51, p. 415-428, accessed 

July 12, 2007, at http://landcover.usgs.gov/natllandcover.php

Precipitation frequency atlas of the United States 

(National Oceanic and Atmospheric Administration 

Atlas 14)

Bonnin, G., Martin, D., Parzybok, T., Lin, B., Riley, D., and Yekta, M., 2006, 

Precipitation frequency atlas of the United States: National Weather Service, 

National Oceanic and Atmospheric Administration Atlas 14, vol. 1, version 4.0, 

accessed July 12, 2007, at http://hdsc.nws.noaa.gov/hdsc/pfds/docs/NA14Vol1.pdf

Precipitation frequency atlas of the United States 

(National Oceanic and Atmospheric Administration 

Atlas 2)

Miller, J.F., Frederick, R.H., and Tracy, R.J., 1973, Precipitation-frequency atlas of 

the Western United States: National Weather Service, National Oceanic and Atmospheric Administration Atlas 2, 11 vols., accessed July 12, 2007, at http://nws.

noaa.gov/ohd/hdsc/noaaatlas2.htm

Parameter-elevation Regressions on Independent 

Slopes Model climate mapping system (PRISM) 

Total precipitation (30-year average, 1971-2000)

Daly, Christopher, Nielson, R.P., and Phillips, D.L., 1994, A statistical-topographic 

model for mapping climatological precipitation over mountainous terrain: Journal of Applied Meteorology, v. 33, no. 2, p. 140-158, accessed July 12, 2007, at 

http://prism.oregonstate.edu/products

12 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
Table 5. Predictive regression equations and their associated uncertainty in estimating peak flows for natural streams in Utah—

Continued.

Regression equation for 

given recurrence interval 

(2- to 500-year)

Average 

standard 

error of 

prediction, 

in percent

Model 

error, in 

percent

Equivalent 

years of 

record

Region 1 (equation based on data from 46 streamflow-gaging stations)

PK2 = 1.52 DRNAREA0.677 1.39(ELEV/1,000) 62 59 0.97

PK5 = 5.49 DRNAREA0.614 1.30(ELEV/1,000) 54 52 1.49

PK10 = 10.3 DRNAREA0.5811.25(ELEV/1,000) 53 51 2.00

PK25 = 19.7 DRNAREA0.547 1.21(ELEV/1,000) 55 52 2.59

PK50 = 29.4 DRNAREA0.524 1.19(ELEV/1,000) 57 55 2.92

PK100 = 40.4 DRNAREA0.512 1.17(ELEV/1,000) 58 55 3.34

PK200 = 58.3 DRNAREA0.483 1.15(ELEV/1,000) 63 60 3.35

PK500 = 85.4 DRNAREA0.457 1.13(ELEV/1,000) 68 64 3.50

Region 2 (equation based on data from 32 streamflow-gaging stations)

PK2 = 0.585 DRNAREA0.847 1.07PRECIP 71 66 .91

PK5 = 1.56 DRNAREA0.747 1.07PRECIP 58 54 1.62

PK10 = 2.51 DRNAREA0.703 1.06PRECIP 53 50 2.46

PK25 = 4.00 DRNAREA0.661 1.06PRECIP 51 47 3.70

PK50 = 5.36 DRNAREA0.635 1.06PRECIP 50 46 4.59

PK100 = 6.92 DRNAREA0.613 1.06PRECIP 50 46 5.38

PK200 = 8.79 DRNAREA0.592 1

1.055PRECIP 51 47 6.06

PK500 = 12.0 DRNAREA0.555 1.05PRECIP 52 48 6.84

Region 3 (equation based on data from 14 streamflow-gaging stations)

PK2 = 14.5 DRNAREA0.328 357 295 .60

PK5 = 47.6 DRNAREA0.287 194 168 1.40

PK10 = 83.7 DRNAREA0.289 152 132 2.49

PK25 = 148 DRNAREA0.298 130 113 4.21

PK50 = 215 DRNAREA0.302 128 110 5.28

PK100 = 300 DRNAREA0.303 136 116 5.89

PK200 = 411 DRNAREA0.301 150 126 6.13

PK500 = 599 DRNAREA0.299 177 147 6.10

Region 4 (equation based on data from 42 streamflow-gaging stations)

PK2 = 0.083 DRNAREA0.822 2.720.656 (ELEV/1,000) - 0.039 BSLDEM10M 49 46 1.35

PK5 = 0.359 DRNAREA0.816 2.720.537 (ELEV/1,000) - 0.035 BSLDEM10M 37 35 2.60

PK10 = 0.753 DRNAREA0.811 2.720.500 (ELEV/1,000) - 0.032 BSLDEM10M 35 32 3.84

PK25 = 1.64 DRNAREA0.804 2.720.414 (ELEV/1,000) - 0.030 BSLDEM10M 35 32 5.07

PK50 = 2.68 DRNAREA0.798 2.720.373 (ELEV/1,000) - 0.028 BSLDEM10M 37 34 5.56

PK100 = 4.18 DRNAREA0.792 2.720.334 (ELEV/1,000) - 0.023 BSLDEM10M 39 36 5.72

PK200 = 6.29 DRNAREA0.786 2.720.299 (ELEV/1,000) - 0.021 BSLDEM10M 43 39 5.69

PK500 = 10.5 DRNAREA0.778 2.720.256 (ELEV/1,000) - 0.018 BSLDEM10M 47 43 5.47

Region 5 (equation based on data from 35 streamflow-gaging stations)

PK2 = 4.32 DRNAREA0.623 (HERBUPLND+1)0.503 99 92 1.08

PK5 = 11.7 DRNAREA0.575 (HERBUPLND+1)0.425 60 54 3.27

PK10 = 18.4 DRNAREA0.555 (HERBUPLND+1)0.388 50 45 6.11

PK25 = 28.8 DRNAREA0.538 (HERBUPLND+1)0.352 49 43 8.91

PK50 = 38.4 DRNAREA0.536 (HERBUPLND+1)0.331 53 47 9.35

PK100 = 50.2 DRNAREA0.515 (HERBUPLND+1)0.316 61 53 8.79

PK200 = 64.7 DRNAREA0.504 (HERBUPLND+1)0.300 71 62 7.99

PK500 = 88.3 DRNAREA0.489 (HERBUPLND+1)0.285 86 76 7.05

Region 6 (equation based on data from 99 streamflow-gaging stations)

PK2 = 4,150 DRNAREA0.553 (ELEV/1,000)-2.45 108 106 1.44

PK5 = 13,100 DRNAREA0.479 (ELEV/1,000)-2.44 80 78 3.01

PK10 = 24,700 DRNAREA0.444 (ELEV/1,000)-2.47 70 68 5.06

PK25 = 49,500 DRNAREA0.411 (ELEV/1,000)-2.51 62 60 8.43

Table 5. Predictive regression equations and their associated uncertainty in estimating peak flows for natural streams in Utah.

[PK, Peak flow, number following PK represents recurrence interval, in years; DRNAREA, drainage area, in square miles; ELEV, mean basin elevation, in feet; 

PRECIP, mean annual precipitation, in inches; BSLDEM10M, average basin slope, in percent; HERBUPLND, area covered by herbaceous upland, in percent]

Regional Regression Method for Estimating Frequency of Peak Flows for Ungaged Sites 13

1

 Value not rounded for accuracy purposes.
0 1,000 2,000 3,000 4,000 5,000 6,000 7,000

-2,000

-1,000

0

1,000

2,000

3,000

4,000

PREDICTED DISCHARGE, IN CUBIC FEET PER SECOND

RESIDUAL DISCHARGE, IN CUBIC FEET

 PER SECOND

Figure 8. Residuals for 50-year recurrence-interval regression equation for region 4. 

Table 5. Predictive regression equations and their associated uncertainty in estimating peak flows for natural streams in Utah—

Continued.

Regression equation for 

given recurrence interval 

(2- to 500-year)

Average 

standard 

error of 

prediction, 

in percent

Model 

error, in 

percent

Equivalent 

years of 

record

Region 6 (equation based on data from 99 streamflow-gaging stations)—Continued

PK50 = 77,400 DRNAREA0.391 (ELEV/1,000)-2.54 60 58 10.95

PK100 = 115,000 DRNAREA0.391 (ELEV/1,000)-2.58 61 58 12.97

PK200 = 166,000 DRNAREA0.361 (ELEV/1,000)-2.61 62 60 14.42

PK500 = 258,000 DRNAREA0.344 (ELEV/1,000)-2.65 66 63 15.40

Region 7 (equation based on data from 25 streamflow-gaging stations)

PK2 = 18.4 DRNAREA0.630 76 71 2.71

PK5 = 67.4 DRNAREA0.539 95 88 2.46

PK10 = 134 DRNAREA0.487 110 102 2.62

PK25 = 278 DRNAREA0.429 132 121 2.85

PK50 = 446 DRNAREA0.390 149 136 2.99

PK100 = 683 DRNAREA0.355 166 151 3.13

PK200 = 1,010 DRNAREA0.321 185 167 3.23

PK500 = 1,620 DRNAREA0.280 211 189 3.35

14 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
AVP

n i

T

i

T

i

n

= +

æ

è

ç

ç

çç

ö

ø

÷

÷

÷

÷ ( ) - -

=

sd å 2 1 1

1

1 x X L X x (4)

where:

AVP is the average variance of prediction, 

sd

2 is the model error variance,

n is the number of stations in the regression model,

xi is the vector containing the basin attributes of the i

th

station augmented by a value of one,

X is the matrix of all basin attributes at all stations in 

the regression augmented by a column of ones, 

Λ is the GLS weighting matrix (Tasker and Stedinger, 

1989), 

T superscript indicates taking the transpose of a matrix, 

and the -1 superscript indicates taking the inverse of a 

matrix.

The AVP is comprised of model error variance and timesampling error. Model error variance represents the inherent 

error associated with the model such as the representation of 

non log-linear behavior with log-linear regression methods, or 

the inability to explain all observed variance with the selected 

predictor variables. Time-sampling error, computed as the 

difference between the AVP and model error variance, is an 

indication of the amount of error associated with sample size. 

Theoretically, time-sampling error should decrease with more 

data from gaging stations of similar characteristics 

 A more commonly used metric, the average standard 

error of prediction in percent, Sp, as computed from the AVP 

is given by (Aitchison and Brown (1957), modified for use of 

common logarithms): 

S e p

AVP

= - é

ë

ê

ê

ù

û

ú

ú

( ) 100 1 10

0 5 2 ln.

(5)

where:

Sp is the average standard error of prediction, in percent, 

and

AVP is the average variance of prediction.

The average standard error of prediction in percent, and 

the model error variance in percent for all developed equations 

are contained in table 5. Equations for region 4 had the 

smallest values, while region 3 had the largest. Generally, 

standard errors of prediction were lowest for equations based 

upon data from more than 35 gaging stations. Equations for 

regions 3 and 7 were based on data from 14 and 25 gaging 

stations, respectively. As would be expected, equations 

from these regions show the largest time-sampling errors, on 

average 19.7 percent. Equations for region 6 were based on 

data from 99 gaging stations and had the smallest average 

time-sampling error of 2.46 percent. The range and average 

standard error of prediction, model error, and time sampling 

Table 6. Range and average errors associated with regional 

regression equations for each recurrence interval. 

Recurrence 

interval,

in years

Average 

error, 

in percent

Minimum 

error, 

in percent

Maximum 

error,

 in percent

Average standard error of prediction

2 117 48.8 357

5 82.7 37.2 194

10 74.7 34.6 152

25 73.3 35.0 132

50 76.4 36.7 149

100 81.7 39.4 166

200 89.2 42.6 185

500 101 47.4 211

Model error variance 

2 105 45.9 295

5 75.6 34.7 168

10 68.6 32.1 132

25 66.8 32.2 121

50 69.5 33.7 136

100 73.6 36.1 151

200 80.0 39.0 167

500 90.0 43.4 189

Time-sampling error

2 12.3 2.58 62.0

5 7.02 2.15 26.3

10 6.13 2.06 19.6

25 6.49 2.15 17.4

50 6.97 2.30 18.1

100 8.04 2.48 20.2

200 9.18 2.69 23.5

500 11.1 2.98 29.9

error associated with each recurrence interval are shown in 

table 6.

When developing multiple-linear regression models, it 

is important to consider whether an observation, in this case 

peak-flow and basin-characteristic data from a single gaging 

station, potentially has a large impact on the coefficient(s) of 

the model. A measure of this potential impact can be obtained 

by using the leverage statistic (Tasker and Stedinger, 1989), 

which is computed for each observation independent of the 

model by using the equation:

( ) 1 1 1 − − − Λ= Λ T T XXXXh (6)

where: 

h is the matrix containing leverage values for all 

stations, 

X is the matrix of all basin attributes at all stations in 

the regression augmented by a column of ones, and

Λ is the GLS weighting matrix (Tasker and Stedinger, 

1989). 

Regional Regression Method for Estimating Frequency of Peak Flows for Ungaged Sites 15
As shown, a leverage matrix is constructed from the input 

predictor variables, basin climatic characteristics, and the GLS 

weighting matrix mentioned above. An indicator of the level 

at which a large impact to the model from a single observation 

would be expected is the leverage threshold, or limit, given by 

the equation:

n

h

h

n

i

∑ ii

= = 1

limit

2

(7)

where: 

hlimit is the leverage threshold,

hii are the main diagonal components of the h matrix 

from equation 6, and 

n is the number of stations in the regression model, 

A graph of leverage values with the leverage limit for the 

100-year peak-flow regression equation for region 2 is shown 

in figure 9. To assess the stability of the models by using the 

leverage statistic, stations with leverage values that exceeded 

the leverage limit were identified. These stations were then 

removed from the dataset and the equation was re-formulated. 

Equations were considered stable and the impact minimal if 

the coefficient(s) changed by less than 20 percent. In these 

cases, stations were retained in the analysis and the original 

equation was used. If the coefficient(s) changed by more 

than 20 percent, these stations were removed and the new 

equation was used. In order to maintain a maximum number 

of observations available for each regional set of equations 

and avoid over-tuning the calibration procedure, this leverage 

assessment process was iterated only once. The leverage 

limits for each equation, the number of stations with leverage 

values that exceeded the limit that were retained in the 

equation development, and the maximum leverage value for 

those stations are contained in table 7. 

Weighting Peak-Flow Estimates from Gaging 

Stations with Regional Regression Estimates

A method for weighting flood-frequency estimates for a 

gaged location obtained from the annual peak flow series and 

regional regression equations is outlined in Bulletin 17B (U.S. 

Interagency Advisory Committee on Water Data, 1982). The 

weighting method assumes that flood-frequency estimates 

determined from the systematic annual peaks for a streamflowgaging station are independent from estimates obtained for 

the station from regression equations (Ries and Crouse, 2002). 

The weighting is determined by the number of years of peak 

record and the equivalent years of record metric (Hardison, 

1971) associated with the regression equation (table 5). The 

computed equivalent years of record is a representation of 

the number of years of record that would be required at any 

ungaged site in the region to achieve comparable accuracy of 

the given regression equation. Equivalent years of record for 

each regression equation were computed from the equation 

(modified from Hardison, 1971):

EQ = spred

2 [1 + kT

g + 0.5kT

2

(1 + 0.75g2)] / AVP0.5 (8)

where:

EQ is the equivalent years of record,

spred is the average of predicted standard deviations for 

each station used in regional regression equation estimated 

from a regression between standard deviations of the annual 

peak series for each station and the predictor variables used 

in the regression equation for each station,

kT is the log-Pearson type III deviate for T-year 

recurrence interval,

g is the average of weighted skew values from 

frequency analysis for each station used in regional 

regression equation, and

AVP is the average variance of prediction of the regression 

equation.

Weighted flood-frequency estimates can be computed as 

(Ries and Crouse, 2002)

log

log log

( )

( ) ( ) Q

N Q EQ Q

N EQ T G w

T G s T G r

= ( ) +

+

(9)

where:

QT(G)w is the weighted T-year peak flow estimate, in 

cubic feet per second, where T is recurrence 

interval,

QT(G)s is the T-year peak flow estimate derived from 

the systematic flood peaks, 

QT(G)r is the T-year peak flow estimate derived from 

the regression equation,

N is the number of years of peak record, and

EQ is the equivalent years of record associated with 

the regression equation.

Limitations of Regional Regression Equations

The applications of the regional regression equations 

presented in this report have certain limitations. Recurrenceinterval flows estimated by using the regression equations 

are considered to be associated with natural atmospheric and 

physiographic conditions and not representative of conditions 

created through anthropogenic means. The annual time 

series of peak flows used in the development of the equations 

were not affected by regulation, or urbanization, and peaks 

associated with dam failures were not included in the analysis. 

The utility of the equations is related to the datasets used in 

their construction. The range of predictor variable values for 

the gaging stations used to develop the regression equations 

16 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
Table 7. Leverage limits for regional regression equations, the number of streamflow-gaging stations with leverage values that 

exceeded the limit that were retained in the equation development, and the maximum leverage value for those stations.

Recurrence 

interval, 

in years

Leverage 

statistic limit

Number of 

sites used in 

analysis that 

exceed limit

Maximum 

leverage value

Recurrence 

interval, 

in years

Leverage 

statistic limit

Number of 

sites used in 

analysis that 

exceed limit

Maximum 

leverage value

Region 1 Region 5

2 0.130 2 0.160 2 0.171 1 0.193

5 .130 3 .155 5 .171 3 .187

10 .130 3 .151 10 .171 4 .198

25 .130 3 .147 25 .171 4 .210

50 .130 3 .147 50 .171 4 .211

100 .130 3 .149 100 .171 4 .210

200 .130 3 .148 200 .171 4 .208

500 .130 3 .149 500 .171 4 .204

Region 2 Region 6

2 .188 1 .210 2 .061 4 .067

5 .188 1 .213 5 .061 4 .063

10 .188 2 .215 10 .061 2 .062

25 .188 2 .218 25 .061 2 .065

50 .188 2 .219 50 .061 3 .067

100 .188 2 .220 100 .061 5 .069

200 .188 2 .221 200 .061 5 .069

500 .188 2 .222 500 .061 5 .069

Region 3 Region 7

2 .286 1 .362 2 .160 1 .266

5 .286 1 .368 5 .160 1 .266

10 .286 1 .375 10 .160 1 .265

25 .286 1 .385 25 .160 1 .265

50 .286 1 .390 50 .160 1 .265

100 .286 1 .393 100 .160 1 .265

200 .286 1 .395 200 .160 1 .265

500 .286 1 .396 500 .160 1 .265

Region 4

2 .190 3 .246

5 .190 3 .251

10 .190 3 .255

25 .190 3 .258

50 .190 4 .260

100 .190 4 .261

200 .190 4 .262

500 .190 4 .262

is contained in table 8. The equations, and associated errors, 

are valid for these ranges of predictor-variable values. 

Computation of the predictor variables was done by using 

specified GIS algorithms on datasets and at scales previously 

discussed. These same computational procedures using the 

same digital datasets at the same scales should be adhered to in 

order to stay consistent with the quantified uncertainty of the 

equations. It is understood that certain engineering, scientific, 

and management problems may require the application of 

the methods presented in this report outside of the prescribed 

ranges and with predictor-variable values computed by means 

other than those outlined. For these instances, the quantified 

errors of the equations are not valid. Consideration of the 

limitations presented requires proper application of hydrologic 

judgment by the end user of the equations of this report. 

StreamStats Web-Based

Computer Program

 StreamStats is a web-based tool developed by the USGS 

that integrates published streamflow-gaging station data and 

regional regression equations with a web-based GIS (Ries and 

Regional Regression Method for Estimating Frequency of Peak Flows for Ungaged Sites 17
others, 2004). StreamStats allows a user to obtain a variety of 

streamflow statistics and basin characteristics by selecting a 

location on a map interface. Published data can be obtained 

if the user selects the location of a USGS streamflow-gaging 

station. If the location of interest does not have a gaging 

station, StreamStats will apply published regression equations 

for that location and estimate the associated streamflow 

statistics. The methods used in computing the predictor 

variables used in the development of the regression equations 

is preserved in the StreamStats application. StreamStats can 

be accessed on the World Wide Web at http://water.usgs.gov/

osw/streamstats/. To use StreamStats for the application of the 

equations described in this report, navigate within the above 

StreamStats website to the state application for Utah. 

Summary

Engineers, planners, resource managers, and scientists 

use estimates of the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 

500-year recurrence-interval flows for a variety of design, 

planning, and management purposes. Flooding in Utah can 

be caused by runoff from exceptional snowpacks; widespread, 

slow-moving low-pressure weather systems; and high-intensity 

monsoonal thunderstorms of short duration. Even though 

these are distinct atmospheric conditions, a well-defined limit 

of the relation between drainage area and peak flow in Utah 

is evident in the Crippen and Bue (1977) region 14 envelope 

curve. The USGS NWIS database for Utah and surrounding 

states was examined for streamflow-gaging stations with 10 

or more years of natural peak-flow data in order to estimate 

the return frequencies of specific streamflows. The 2-, 5-, 10-, 

25-, 50-, 100-, 200-, and 500-year recurrence-interval flows 

were estimated for 344 unregulated USGS gaging stations 

in Utah and bordering states. In an effort to expand this 

extensive dataset to similar streams without gaging stations, 

regional regression equations were developed. Seven distinct 

geohydrologic regions were determined by using a variety 

of physiographic, climatic, and hydrologic characteristics. 

Twenty-three physiographic and climatic characteristics 

were computed for the 344 gaging stations. Combinations of 

these characteristics were statistically examined as predictors 

of the different recurrence-interval flows in each region. 

Final equations were developed by using GLS regression 

technique that accounts for cross correlation between sites, 

annual peak-flow record length, and annual peak-flow 

variability. Recurrence-interval flows were determined to 

be either solely a function of drainage area, or a function of 

drainage area and one or two other variables. Equations for 

three regions included mean basin elevation. Mean annual 

precipitation, average basin slope, and percent of basin defined 

as herbaceous upland (Vogelmann and others, 1998) were each 

used in the equations for one region. Equations developed 

from more than 35 gaging stations had standard errors of 

prediction that ranged from 35 to 108 percent, and errors for 

equations developed from less than 35 

gaging stations ranged from 50 to 357 

percent. On the basis of the standard 

error of prediction, the equations for 

region 4 have the least uncertainty, 

and the equations for regions 3 and 

7 have the greatest. The limitations 

presented in this report should be 

considered for any application of the 

developed regression equations.

0 200 400 600 800 1,000

0

0.05

0.10

0.15

0.20

0.25

LEVERAGE VALUES

OBSERVED DISCHARGE, IN CUBIC FEET PER SECOND

LEVERAGE LIMIT 0.188

Figure 9. Leverage values and limit for 100-year recurrenceinterval regression equation for region 2. 

Table 8. Range of predictor variables computed for streamflow-gaging stations used in 

the development of the regression equations.

[—, variable not used in equations]

Region

Drainage 

area, 

in square 

miles

Elevation, 

in feet

Precipitation, 

 in inches

Average 

area

 slope, 

percent 

Area 

covered by 

herbaceous

upland, percent

1 3.62-390 6,420-10,500 — — —

2 2.14-84.1 — 16.5-53.7 — —

3 5.72-66.5 — — — —

4 2.95-667 8,130-10,900 — 9.67-40.3 —

5 .91-629 — — — 2.14-15.6

6 .87-532 4,300-9,380 — — —

7 5.43-1,670 — — — —

18 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
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20 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis—Continued.

Map 

ID

Gaging 

station 

number

Gaging station name

Peak flow, in cubic feet per second, for given recurrence interval, in years

2 5 10 25 50 100 200 500

Number of 

annual 

peak flows

Region 1

3

1 09217900 BLACKS FORK NEAR ROBERTSON, WYOMING 1,600 2,080 2,360 2,670 2,880 3,080 3,260 3,480 35

2 09218500 BLACKS FORK NEAR MILLBURNE, WYOMING 1,460 1,830 2,070 2,370 2,600 2,820 3,040 3,340 31

3 09220000 EAST FORK OF SMITHS FORK NEAR ROBERTSON, 

WYOMING

499 742 930 1,200 1,430 1,680 1,960 2,380 40

4 09220500 WEST FORK OF SMITH FORK NEAR ROBERTSON, 

WYOMING

438 703 911 1,210 1,470 1,750 2,060 2,510 42

5 09221680 MUD SPRING HOLLOW NEAR CHURCH BUTTE, NR 

LYMAN, WYOMING

56.6 190 360 713 1,110 1,660 2,390 3,740 20

6 09221700 MUD SPRING HOLLOW NEAR LYMAN, WYOMING 90.5 179 260 391 512 657 827 1,100 13

7 09223000 HAMS FORK BELOW POLE CREEK, NEAR FRONTIER, WYOMING745 1,140 1,400 1,720 1,950 2,190 2,410 2,710 53

8 09223500 HAMS FORK NEAR FRONTIER, WYOMING 1,140 1,620 1,920 2,290 2,560 2,820 3,070 3,410 27

9 09224000 HAMS FORK AT DIAMONDVILLE, WYOMING 1,420 2,210 2,770 3,490 4,040 4,600 5,160 5,930 18

2

10 09224800 MEADOW SPRINGS WASH TRIB NEAR GREEN 

RIVER, WYOMING

32.6 96.2 157 250 328 412 499 619 18

1

11 09224810 BLACKS FORK TRIBUTARY NO 2 NEAR GREEN 

RIVER, WYOMING

Nd Nd Nd Nd Nd Nd Nd Nd 17

3

12 09224820 BLACKS FORK TRIBUTARY NO 3 NEAR GREEN 

RIVER, WYOMING

19 71 142 295 475 728 1,080 1,730 20

4

13 09224840 BLACKS FORK TRIBUTARY NO 4 NEAR GREEN 

RIVER, WYOMING

11 24.1 36.1 55.2 72.3 92 115 149 17

4

14 09224980 SUMMERS DRY CREEK NEAR GREEN RIVER, 

WYOMING

675 2,250 4,350 8,990 14,500 22,600 34,100 56,700 17

15 09225200 SQUAW HOLLOW NEAR BURNTFORK, WYOMING 104 229 349 550 739 966 1,240 1,670 20

4

16 09225300 GREEN RIVER TRIBUTARY NO 2 NEAR BURNTFORK, WYOMING238 746 1,340 2,480 3,680 5,230 7,190 10,500 21

17 09226000 HENRYS FORK NEAR LONETREE, WYOMING 574 894 1,150 1,540 1,880 2,250 2,680 3,340 30

2

18 09226500 MIDDLE FORK BEAVER CREEK NEAR LONETREE, 

WYOMING

308 487 621 806 956 1,110 1,280 1,530 22

2

19 09227500 WEST FORK BEAVER CREEK NEAR LONETREE, 

WYOMING

164 252 320 416 496 583 679 819 14

4

20 09228500 BURNT FORK NEAR BURNTFORK, WYOMING 279 505 715 1,070 1,410 1,820 2,330 3,190 32

1

21 09229450 HENRYS FORK TRIBUTARY NEAR MANILA, UTAH Nd Nd Nd Nd Nd Nd Nd Nd 10

3

22 10010400 EAST FK BEAR RIVER NR EVANSTON, WYOMING 561 688 762 847 904 958 1,010 1,070 13

23 10011500 BEAR RIVER NEAR UTAH-WYOMING STATE LINE 1,840 2,380 2,690 3,040 3,280 3,500 3,710 3,970 63

4

24 10012000 MILL CREEK AT UTAH-WYOMING STATE LINE 390 544 643 764 851 936 1,020 1,130 19

25 10014000 BEAR RIVER ABOVE SULPHUR CREEK, NR EVANSTON, WYOMING1,910 2,350 2,600 2,900 3,100 3,290 3,480 3,710 10

26 10015700 SULPHUR CR.AB.RES.BL.LA CHAPELLE CR.NR 

EVANSTON,WY

328 543 707 936 1,120 1,320 1,530 1,830 39

27 10016000 SULPHUR CREEK NEAR EVANSTON, WYOMING 515 783 962 1,190 1,350 1,520 1,680 1,890 17

4

28 10019000 BEAR RIVER NEAR EVANSTON, WYOMING 1,950 2,580 2,950 3,380 3,670 3,940 4,190 4,510 43

29 10019700 WHITNEY CANYON CREEK NEAR EVANSTON, 

WYOMING

45 84.1 115 160 196 235 277 337 17

30 10021000 WOODRUFF CREEK NEAR WOODRUFF, UTAH 242 358 426 502 553 598 640 689 27

31 10023000 BIG CREEK NEAR RANDOLPH, UTAH 57.3 110 149 198 235 271 306 350 45

32 10032000 SMITHS FORK NEAR BORDER, WYOMING 896 1,270 1,510 1,810 2,020 2,220 2,420 2,680 64

33 10040000 THOMAS FORK NEAR GENEVA, IDAHO 145 249 327 435 522 613 709 844 12

34 10040500 SALT CREEK NEAR GENEVA, IDAHO 162 293 393 529 637 748 863 1,020 12

35 10041000 THOMAS FORK NEAR WYOMING-IDAHO STATE 

LINE

395 805 1,140 1,620 2,020 2,440 2,880 3,510 43

36 10042500 THOMAS FORK NR RAYMOND, IDAHO 438 797 1,060 1,420 1,690 1,970 2,250 2,630 10

37 10069000 GEORGETOWN CREEK NR GEORGETOWN, IDAHO 50.4 67.2 78.6 93.2 104 116 127 143 17

38 10084500 COTTONWOOD CREEK NR CLEVELAND, IDAHO 374 562 689 851 972 1,090 1,220 1,380 48

39 10089500 MINK CREEK NR MINK CREEK IDAHO 356 400 425 452 470 486 502 521 10

2

40 10090800 BATTLE CREEK TRIB NR TREASURETON, IDAHO 45.2 95.7 137 195 243 292 344 415 19

Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis.

[Nd, not determined, see footnote 1] 

Appendix 21

Appendix
Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis—Continued.

Map 

ID

Gaging 

station 

number

Gaging station name

Peak flow, in cubic feet per second, for given recurrence interval, in years

2 5 10 25 50 100 200 500

Number of 

annual 

peak flows

Region 1—Continued

41 10093000 CUB RIVER NR PRESTON, IDAHO 595 718 791 875 933 988 1,040 1,110 44

42 10096000 CUB RIVER AB MAPLE CREEK NR FRANKLIN, 

IDAHO

558 623 661 703 731 758 783 814 13

43 10099000 HIGH CREEK NEAR RICHMOND, UTAH 214 335 418 524 603 681 760 864 22

44 10102300 SUMMIT CREEK ABV DIVERSIONS NR SMITHFIELD, UTAH147 212 252 300 334 366 397 435 18

45 10104700 LITTLE BEAR R BL DAVENPORT CREEK NR. AVON, 

UTAH

435 742 970 1,280 1,520 1,770 2,030 2,390 32

46 10104900 EAST FK LT BEAR RIV AB RES. NR AVON, UTAH 497 697 823 974 1,080 1,180 1,280 1,410 23

47 10105000 EAST FORK LITTLE BEAR R NR AVON UT 320 525 674 873 1,030 1,190 1,360 1,590 13

4

48 10105900 LITTLE BEAR RIVER AT PARADISE, UTAH 577 1,260 1,900 2,980 3,990 5,210 6,660 8,990 13

49 10106000 LITTLE BEAR RIVER NEAR PARADISE, UTAH 717 1,100 1,390 1,800 2,140 2,500 2,890 3,460 50

50 10109001 COMBINED FLOW LOGAN R AB ST D AND LO HP 

AND SM C N LO UT

1,110 1,480 1,690 1,940 2,100 2,260 2,400 2,580 83

51 10111700 BLACKSMITH F B MILL CREEK NR HYRUM, UTAH 141 207 251 306 346 385 424 475 11

52 10113500 BLACKSMITH FORK AB UP & L CO.’S DAM NR 

HYRUM, UTAH

448 805 1,070 1,440 1,730 2,030 2,340 2,770 88

53 10128200 SOUTH FORK WEBER RIVER NEAR OAKLEY, UTAH 197 226 242 261 273 284 295 308 10

54 10128500 WEBER RIVER NEAR OAKLEY, UTAH 1,810 2,430 2,800 3,220 3,510 3,780 4,030 4,340 101

1

55 10129350 CRANDALL CREEK NEAR PEOA, UTAH Nd Nd Nd Nd Nd Nd Nd Nd 10

56 10130000 SILVER CREEK NEAR WANSHIP, UTAH 122 236 326 453 556 665 779 939 14

57 10130700 EAST FORK CHALK CREEK NEAR COALVILLE, 

UTAH

291 369 417 474 514 552 589 637 10

58 10131000 CHALK CREEK AT COALVILLE, UTAH 512 848 1,070 1,340 1,530 1,720 1,890 2,110 80

59 10132500 LOST CREEK NEAR CROYDEN, UTAH 237 415 547 726 867 1,010 1,160 1,370 28

60 10133000 LOST CREEK AT DEVILS SLIDE, UTAH 600 1,030 1,320 1,680 1,930 2,180 2,420 2,730 13

Region 2

4

61 10133700 THREEMILE CREEK NEAR PARK CITY, UTAH 10.3 14.9 18.1 22.4 25.8 29.3 33 38.1 13

62 10135000 HARDSCRABBLE CREEK NEAR PORTERVILLE, 

UTAH

247 364 435 515 570 619 665 721 29

4

63 10137500 SOUTH FORK OGDEN RIVER NEAR HUNTSVILLE, 

UTAH

794 1,250 1,540 1,880 2,110 2,330 2,530 2,780 45

64 10137680 NORTH FORK OGDEN RIVER NEAR EDEN, UTAH 91.3 120 137 158 173 188 202 220 11

65 10137780 MIDDLE FK OGDEN RIVER AB DIV NR HUNTSVILLE, UTAH458 561 623 696 748 797 845 907 11

66 10139300 WHEELER CREEK NEAR HUNTSVILLE, UTAH 105 225 327 481 611 753 908 1,130 37

67 10141400 HOWARD SLOUGH AT HOOPER, UTAH 175 231 265 303 330 354 378 407 13

68 10141500 HOLMES CREEK NEAR KAYSVILLE, UTAH 18.9 34.4 46.8 64.7 79.5 95.5 113 138 18

69 10142000 FARMINGTON CR ABV DIV NR FARMINGTON, 

UTAH

154 253 327 428 508 592 680 804 34

70 10142500 RICKS C AB DIVERSIONS, NR CENTERVILLE, UTAH 20.1 46.3 71.8 115 155 203 261 353 18

71 10143000 PARRISH C AB DIVERSIONS NR CENTERVILLE, 

UTAH

13.9 24.1 31.2 40.2 46.9 53.4 59.8 68.1 20

72 10143500 CENTERVILLE CREEK ABV DIV NR CENTERVILLE, 

UTAH

14.3 27.4 38.8 56.7 72.7 91.1 112 145 38

4

73 10144000 STONE CREEK ABOVE DIVERSION NEAR BOUNTIFUL, UTAH30 106 211 445 726 1,140 1,720 2,870 17

74 10145000 MILL C AT MUELLER PARK, NR BOUNTIFUL, UTAH 43.9 82.1 112 156 191 229 269 326 20

75 10155400 SPRING CREEK NEAR HEBER CITY, UTAH 107 182 242 328 401 480 566 693 10

76 10156000 SNAKE CREEK NEAR CHARLESTON, UTAH 86.1 108 122 138 150 162 173 188 22

77 10158500 ROUND VALLEY CREEK NEAR WALLSBURG, UTAH 116 155 180 212 235 259 282 314 12

78 10160000 DEER CREEK NEAR WILDWOOD, UTAH 61.2 87.5 104 123 137 150 163 179 11

79 10160800 NO FK PROVO RIV AT WILDWOOD UTAH 106 148 176 213 240 268 297 336 10

80 10161500 SOUTH FORK PROVO R AT VIVIAN PARK, UTAH 50.6 81.9 108 146 179 217 261 326 52

81 10164500 AMERICAN FK AB UPPER POWERPLANT NR 

AMERICAN FK, UTAH

330 482 575 685 761 832 900 984 69

82 10165500 DRY CREEK NEAR ALPINE, UTAH 201 279 332 401 453 506 561 635 23

4

83 10166430 WEST CANYON CREEK NEAR CEDAR FORT, UTAH 30.2 86.1 156 304 477 725 1,070 1,760 30

3

84 10167500 LITTLE COTTONWOOD CREEK NR SALT LAKE 

CITY, UTAH

387 513 594 696 771 846 921 1,020 51

22 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis—Continued.

Map 

ID

Gaging 

station 

number

Gaging station name

Peak flow, in cubic feet per second, for given recurrence interval, in years

2 5 10 25 50 100 200 500

Number of 

annual 

peak flows

Region 2—Continued

85 10168500 BIG COTTONWOOD CR NR SALT LAKE CITY UTAH 377 498 578 679 755 831 908 1,010 60

86 10170000 MILL CREEK NEAR SALT LAKE CITY, UTAH 49.9 74.5 91.1 112 128 143 159 180 63

87 10171500 PARLEYS CREEK NEAR SALT LAKE CITY, UTAH 122 191 237 296 339 382 425 481 18

88 10172000 EMIGRATION CREEK NEAR SALT LAKE CITY, UTAH 25.2 45.7 62.5 87.4 109 132 159 198 57

89 10172200 RED BUTTE CREEK AT FORT DOUGLAS, NEAR SLC, 

UTAH

15.6 32.4 47.2 70.1 90.4 113 139 178 42

90 10172500 CITY CREEK NEAR SALT LAKE CITY, UTAH 64.4 98 121 150 171 193 214 243 72

3

91 10172640 LEE CREEK NEAR MAGNA, UTAH 45.6 74.6 95.5 123 144 166 189 219 11

4

92 10172700 VERNON CREEK NEAR VERNON, UTAH 20.7 71.1 142 307 515 831 1,300 2,280 46

1

93 10172740 RUSH VALLEY TRIBUTARY NEAR FAIRFIELD, UTAH Nd Nd Nd Nd Nd Nd Nd Nd 11

4

94 10172760 CLOVER CREEK NEAR CLOVER, UTAH 13.7 34.3 55.1 91 126 167 218 299 15

95 10172765 CLOVER CREEK ABOVE BIG HOLLOW, NEAR CLOVER, UTAH16.2 29.5 40 55 67.3 80.6 94.8 115 17

96 10172790 SETTLEMENT CANYON NR TOOELE, UTAH 20.9 62.6 108 189 269 366 483 670 11

97 10172791 SETTLEMENT CREEK ABOVE RESERVOIR NEAR 

TOOELE, UTAH

17.9 41 62.1 95.4 125 158 196 253 10

98 10172800 SOUTH WILLOW CREEK NEAR GRANTSVILLE, 

UTAH

32.5 57 76.2 103 125 149 175 211 45

99 10172805 NORTH WILLOW CREEK NR GRANTSVILLE, UTAH 25.6 54 80.6 124 165 214 272 365 13

Region 3

4

100 10119000 LITTLE MALAD RIVER AB ELKHORN RES NR 

MALAD CITY ID

108 257 431 786 1,190 1,760 2,570 4,130 15

101 10122500 DEVIL CREEK AB CAMPBELL CREEK NR MALAD 

CITY ID

63.9 109 146 202 250 304 365 458 15

102 10125000 DEEP CREEK BL FIRST CREEK NR MALAD CITY ID 53.9 94.9 129 182 228 281 341 433 12

103 10126180 SULPHUR CREEK NR. CORINNE, UTAH 175 235 273 320 355 389 423 468 40

2

104 10127100 BLACK SLOUGH NEAR BRIGHAM CITY, UTAH 184 258 307 367 411 454 497 555 12

4

105 10172835 SKULL VALLEY TRIBUTARY NR DELLE, UTAH .1 .8 3.2 12.7 30.2 64.7 128 287 11

106 10172870 TROUT CREEK NEAR CALLAO, UTAH 47 86.8 117 157 188 219 252 295 10

1

107 10172885 GR SALT LAKE DESERT TR NO.2 NR DUGWAY, 

UTAH

Nd Nd Nd Nd Nd Nd Nd Nd 15

4

108 10172890 GOVERNMENT CREEK NEAR DUGWAY, UTAH 10.2 116 402 1,500 3,470 7,350 14,500 33,000 10

4

109 10172895 DEEP CREEK NEAR IBAPAH, UTAH 97.1 244 399 677 956 1,310 1,740 2,480 12

110 10172900 BAR CREEK NEAR IBAPAH, UTAH 68.9 374 860 2,010 3,400 5,390 8,120 13,100 15

4

111 10172902 DEAD CEDAR WASH NR WENDOVER, UTAH 2.8 237 1,820 13,100 42,100 112,000 262,000 679,000 14

112 10172909 BURNT C NR SHORES, NV 1.1 7.9 23.6 80.4 183 392 801 1,950 10

1

113 10172913 LORAY WASH TR NR COBRE, NV Nd Nd Nd Nd Nd Nd Nd Nd 11

114 10172920 COTTON CREEK NEAR GROUSE CREEK, UTAH 3.3 16.6 41.8 120 245 480 905 2,010 32

1

115 10172925 GR ST LAKE DESERT TR NO 3 NR PARK VALLEY, 

UTAH

Nd Nd Nd Nd Nd Nd Nd Nd 23

116 10172940 DOVE CREEK NEAR PARK VALLEY, UTAH 8.9 35.1 78.2 196 370 669 1,180 2,400 17

4

117 10172970 ROCK CREEK NR HOLBROOK ID 170 595 1,200 2,640 4,500 7,350 11,700 20,800 18

3

118 10172990 BLUE SPRING CREEK NR SNOWVILLE, UTAH 96.5 375 756 1,590 2,560 3,930 5,800 9,280 18

119 10240600 BIG WASH NEAR WILFORD, UTAH 159 334 486 718 920 1,150 1,400 1,770 21

120 10242440 COTTONWOOD CREEK NR ENTERPRISE, UTAH 147 395 668 1,180 1,700 2,380 3,240 4,720 18

121 10242460 ESCALANTE VALLEY TR NR PANACA, NV 20.5 120 278 636 1,050 1,610 2,340 3,590 18

122 10243240 BAKER C AT NARROWS, NR BAKER, NV 74.7 137 188 260 321 387 458 561 28

123 10243260 LEHMAN CREEK NEAR BAKER, NV 26.2 53.9 80 123 165 214 274 371 16

Region 4

124 09235600 POT CREEK ABOVE DIVERSIONS, NEAR VERNAL, 

UTAH

62.4 126 182 271 351 444 549 712 35

3

125 09264000 ASHLEY C BELOW TROUT C NR VERNAL, UTAH 433 561 637 724 784 840 893 959 11

2

126 09264500 SOUTH FORK ASHLEY C NR VERNAL, UTAH 313 414 474 544 592 638 682 737 12

127 09265300 ASHLEY CREEK ABOVE RED PINE CREEK NR 

VERNAL, UTAH

1,260 2,260 3,100 4,350 5,430 6,630 7,990 10,000 10

128 09266500 ASHLEY CREEK NEAR VERNAL, UTAH 1,110 1,690 2,060 2,510 2,830 3,130 3,430 3,800 93

129 09268000 DRY FORK ABOVE SINKS, NEAR DRY FORK, UTAH 526 745 887 1,060 1,190 1,310 1,440 1,600 37

130 09268500 NORTH FORK OF DRY FORK NEAR DRY FORK, 

UTAH

76.2 116 143 178 204 231 258 294 44

Appendix 23
Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis—Continued.

Map 

ID

Gaging 

station 

number

Gaging station name

Peak flow, in cubic feet per second, for given recurrence interval, in years

2 5 10 25 50 100 200 500

Number of 

annual 

peak flows

Region 4—Continued

131 09268900 BROWNIE CANYON ABOVE SINKS, NR DRY FORK, 

UTAH

187 281 342 418 473 526 579 648 29

132 09269000 EAST FORK OF DRY FORK NEAR DRY FORK, UTAH 129 191 229 272 301 329 354 385 18

133 09270000 DRY FORK BELOW SPRINGS NEAR DRY FORK, 

UTAH

526 761 914 1,100 1,240 1,370 1,500 1,670 22

134 09270500 DRY FORK AT MOUTH NEAR DRY FORK, UTAH 487 964 1,310 1,760 2,090 2,400 2,710 3,100 35

135 09271000 ASHLEY C, SIGN OF THE MAINE, NR VERNAL, 

UTAH

1,390 2,030 2,460 2,990 3,390 3,780 4,180 4,700 31

136 09273000 DUCHESNE R AT PROVO R TRAIL NR HANNA, UTAH 697 882 994 1,130 1,220 1,310 1,390 1,500 21

3

137 09273500 HADES CREEK NEAR HANNA, UTAH 74.3 108 129 156 174 193 210 233 19

138 09274000 DUCHESNE RIVER (N.FORK) NEAR HANNA, UTAH 1,220 1,430 1,540 1,670 1,750 1,830 1,900 1,980 10

139 09275000 W F DUCHESNE RIVER BL DRY HOLLOW NR 

HANNA, UTAH

456 678 820 994 1,120 1,240 1,350 1,500 26

140 09275500 WEST FORK DUCHESNE RIVER NEAR HANNA, 

UTAH

461 623 715 818 886 948 1,000 1,070 41

4

141 09276000 WOLF CREEK ABOVE RHOADES CANYON NEAR 

HANNA, UTAH

49.9 73.2 88.3 107 120 133 146 163 38

142 09277500 DUCHESNE RIVER NEAR TABIONA, UTAH 1,400 1,830 2,080 2,350 2,530 2,690 2,850 3,030 35

143 09277800 ROCK CREEK ABOVE SOUTH FORK, NEAR HANNA, 

UTAH

1,650 2,160 2,460 2,790 3,010 3,220 3,410 3,640 19

144 09278000 SOUTH FORK ROCK CREEK NEAR HANNA,UTAH 93.1 138 167 203 228 253 277 307 38

145 09278500 ROCK CREEK NEAR HANNA, UTAH 1,720 2,180 2,430 2,700 2,870 3,030 3,170 3,330 34

146 09279000 ROCK CREEK NEAR MOUNTAIN HOME, UTAH 1,620 2,060 2,320 2,610 2,800 2,990 3,160 3,370 50

147 09279100 ROCK CREEK NEAR TALMAGE, UTAH 1,570 1,940 2,150 2,390 2,540 2,690 2,820 2,980 24

148 09279500 DUCHESNE RIVER AT DUCHESNE, UTAH 2,760 3,540 3,950 4,390 4,670 4,920 5,130 5,390 36

3

149 09280400 HOBBLE CREEK AT DANIELS SUMMIT NEAR 

WALLSBURG UT

69.6 102 123 149 167 185 203 226 21

150 09286100 RED CREEK ABOVE RESERVOIR, NEAR FRUITLAND, UTAH

51.3 122 189 299 399 516 651 859 12

151 09287000 CURRANT C BL RED LEDGE HOLLOW NR FRUITLAND, UTAH259 464 619 833 1,000 1,180 1,360 1,620 32

152 09287500 WATER HOLLOW NR FRUITLAND, UTAH 28 60 90.7 143 192 253 326 446 26

153 09288000 CURRANT CREEK NEAR FRUITLAND, UTAH 314 500 644 848 1,020 1,200 1,400 1,690 47

154 09288150 W F AVINTAQUIN CREEK NR FRUITLAND, UTAH 282 661 1,050 1,750 2,450 3,340 4,450 6,330 22

3

155 09288900 SOWERS CREEK NEAR DUCHESNE, UTAH 54.5 161 283 517 762 1,080 1,490 2,180 22

156 09289500 LAKE FORK RIVER AB MOON LAKE, NR MOUNTAIN HOME, UTAH1,340 1,870 2,200 2,580 2,850 3,110 3,360 3,670 57

157 09292500 YELLOWSTONE RIVER NEAR ALTONAH, UTAH 1,050 1,550 1,870 2,250 2,520 2,770 3,010 3,320 61

158 09296000 UINTA R ABOVE CLOVER C NEAR NEOLA UTAH 1,300 1,840 2,180 2,610 2,930 3,230 3,540 3,940 10

159 09296800 UINTA R BLW POWERPLANT DIVERSION, NR 

NEOLA, UTAH

1,300 2,520 3,490 4,890 6,030 7,250 8,540 10,400 15

160 09297000 UINTA RIVER NEAR NEOLA, UTAH 1,400 2,090 2,580 3,230 3,740 4,280 4,840 5,610 57

161 09298000 FARM CREEK NEAR WHITEROCKS, UTAH 87.6 174 240 329 398 468 539 634 31

162 09298500 WHITEROCKS R AB PARADISE C N WHITEROCKS 

UTAH

1,100 1,580 1,880 2,240 2,500 2,740 2,970 3,260 10

163 09299500 WHITEROCKS RIVER NEAR WHITEROCKS, UTAH 1,100 1,730 2,130 2,620 2,970 3,310 3,630 4,030 86

164 09300500 UINTAH RIVER AT FORT DUCHESNE, UTAH 1,270 2,690 3,850 5,520 6,870 8,300 9,800 11,900 28

4

165 09301500 UINTA RIVER AT RANDLETT, UTAH 1,090 3,270 5,480 9,060 12,200 15,800 19,700 25,400 17

166 10153500 PROVO RIVER NEAR KAMAS, UTAH 503 632 711 804 870 933 994 1,070 20

167 10153800 NORTH FORK PROVO RIVER NEAR KAMAS, UTAH 395 546 638 748 824 897 967 1,060 33

168 10154000 SHINGLE CREEK NEAR KAMAS, UTAH 178 203 218 235 247 258 269 282 10

Region 5

169 10145500 SALT CREEK NEAR NEPHI, UTAH 283 460 596 791 952 1,130 1,320 1,600 12

170 10146000 SALT CREEK AT NEPHI, UTAH 190 332 446 613 752 906 1,070 1,320 30

171 10146400 CURRANT CREEK NEAR MONA, UTAH 163 322 446 616 750 887 1,030 1,220 27

4

172 10146900 UTAH LAKE TRIBUTARY NEAR ELBERTA, UTAH 180 712 1,390 2,720 4,120 5900 8,110 11,800 12

173 10147000 SUMMIT CREEK NEAR SANTAQUIN, UTAH 73.2 123 157 203 237 271 305 351 19

2

174 10147500 PAYSON CREEK ABV DIVERSIONS, NEAR PAYSON, 

UTAH

140 258 351 480 585 695 811 973 15

175 10148200 TIE FORK NEAR SOLDIER SUMMIT, UTAH 23.1 80 165 379 670 1,140 1,900 3,600 33

4

176 10148300 DAIRY FORK NEAR THISTLE, UTAH 152 393 670 1,220 1,830 2,670 3,800 5,910 14

24 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis—Continued.

Map 

ID

Gaging 

station 

number

Gaging station name

Peak flow, in cubic feet per second, for given recurrence interval, in years

2 5 10 25 50 100 200 500

Number of 

annual 

peak flows

Region 5—Continued

177 10148400 NEBO CREEK NEAR THISTLE, UTAH 109 208 294 430 553 695 858 1,110 10

178 10148500 SPANISH FORK AT THISTLE, UTAH 513 773 961 1,210 1,420 1,630 1,850 2,160 60

179 10150500 SPANISH FORK AT CASTILLA, UTAH 726 1,170 1,490 1,930 2,270 2,630 3,010 3,540 16

180 10152500 HOBBLE CR NR SPRINGVILLE UTAH 258 468 629 852 1,030 1,220 1,410 1,680 43

181 10187300 OTTER CREEK NEAR KOOSHAREM, UTAH 56.9 79.1 92.2 107 117 126 134 144 18

182 10194200 CLEAR CREEK ABOVE DIVERSIONS, NEAR SEVIER, 

UTAH

235 427 573 775 936 1,100 1,280 1520 47

183 10195000 CLEAR CREEK AT SEVIER, UTAH 202 320 405 517 604 694 786 913 32

184 10204200 MILL CREEK NEAR GLENWOOD, UTAH 1.9 18.4 56.7 180 374 708 1,260 2,490 11

185 10205030 SALINA CREEK NEAR EMERY, UTAH 152 305 433 626 791 974 1,170 1,470 42

186 10205070 COTTONWOOD CREEK NEAR SALINA, UTAH 24.9 101 220 517 912 1,540 2,510 4,590 10

2

187 10205100 SHEEP CREEK NEAR SALINA, UTAH 4.3 8.7 12.5 18.4 23.6 29.5 36.1 46.1 12

3

188 10205200 WEST FORK SHEEP CREEK NEAR SALINA, UTAH 3.7 8.1 11.8 17.3 21.9 26.9 32.3 39.9 12

189 10205300 SHEEP CREEK AT MOUTH NEAR SALINA, UTAH 11.7 23.4 32.9 46.6 58 70.1 83.1 102 12

190 10205700 SALINA CREEK ABOVE DIVERSION NEAR SALINA, 

UTAH

553 924 1,240 1,730 2,170 2,690 3,280 4,230 16

191 10206000 SALINA CREEK AT SALINA, UTAH 445 854 1,200 1,730 2,190 2,710 3,290 4,160 26

192 10208500 OAK CREEK NR. FAIRVIEW, UTAH 145 283 413 632 842 1,100 1,410 1,930 25

193 10210000 PLEASANT CREEK NEAR MOUNT PLEASANT, UTAH 150 277 391 575 746 949 1,190 1,580 21

194 10211000 TWIN CREEK NEAR MOUNT PLEASANT, UTAH 66.8 132 195 304 413 549 719 1,010 12

195 10215700 OAK CREEK NEAR SPRING CITY, UTAH 91 150 195 260 314 373 438 532 25

3

196 10215900 MANTI CREEK BLW DUGWAY CREEK, NR MANTI, 

UTAH

319 466 567 698 798 900 1,000 1,140 37

197 10216400 TWELVEMILE CREEK NEAR MAYFIELD, UTAH 262 468 650 944 1,220 1,540 1,920 2,540 21

3

198 10219200 CHICKEN CREEK NEAR LEVAN, UTAH 45.7 132 230 420 619 880 1,220 1,800 33

199 10220300 TINTIC WASH TR NEAR NEPHI, UTAH 64.3 158 254 423 589 794 1,050 1,460 14

3

200 10224100 OAK CREEK ABOVE LITTLE CREEK, NEAR OAK 

CITY, UTAH

18.8 42.1 64.9 104 142 189 246 339 31

201 10232500 CHALK CREEK NEAR FILLMORE UTAH 235 424 589 852 1,090 1,370 1,700 2,230 29

202 10233000 MEADOW CREEK NEAR MEADOW UTAH 52 104 150 222 285 358 440 566 11

203 10233500 CORN CREEK NEAR KANOSH, UTAH. 134 364 615 1,080 1,550 2,160 2,920 4,220 17

204 10234500 BEAVER RIVER NEAR BEAVER, UTAH 353 611 793 1,030 1,200 1,370 1,540 1,760 92

205 10235000 SOUTH CREEK NEAR BEAVER, UTAH 32.6 79.6 126 203 275 361 461 619 12

206 10236000 NORTH FORK NORTH CREEK NEAR BEAVER, UTAH 39.8 76.6 107 150 186 225 267 328 18

2

207 10236500 SOUTH FORK NORTH CREEK NEAR BEAVER, UTAH 176 469 767 1,280 1,760 2,330 3,010 4,080 11

208 10237500 INDIAN CREEK NEAR BEAVER, UTAH 33.1 70 104 161 213 275 349 466 13

Region 6

209 09106200 LEWIS WASH NEAR GRAND JUNCTION, CO. 59 113 158 225 283 347 418 524 10

210 09152650 LEACH CREEK AT DURHAM, CO. 218 356 462 612 736 870 1,020 1,230 11

211 09152900 ADOBE CREEK NEAR FRUITA, CO. 131 180 212 251 279 307 335 372 11

212 09153400 WEST SALT CREEK NEAR MACK, CO. 513 1,140 1,710 2,580 3,340 4,190 5,130 6,530 10

213 09163310 EAST SALT CREEK NEAR MACK, CO. 442 1,330 2,310 4,100 5,880 8,080 10,800 15,100 9

214 09163490 SALT CREEK NEAR MACK, CO. 778 1,300 1,680 2,200 2,610 3,030 3,480 4,100 10

215 09163700 CISCO WASH NEAR CISCO, UTAH 1,670 3,210 4,470 6,300 7,830 9,490 11,300 13,900 15

216 09168100 DISAPPOINTMENT CREEK NEAR DOVE CREEK, CO. 1,180 2,570 3,890 6,110 8,210 10,700 13,800 18,600 29

217 09174500 COTTONWOOD CREEK NEAR NUCLA, CO. 123 236 328 459 568 684 808 985 10

218 09175800 DEAD HORSE CREEK NEAR NATURITA, CO. 151 546 1,040 2,010 3,050 4,390 6,090 8,990 11

1

219 09175900 DRY CREEK NEAR NATURITA, CO. Nd Nd Nd Nd Nd Nd Nd Nd 12

3

220 09177500 TAYLOR CREEK NEAR GATEWAY, CO. 111 264 408 644 859 1,110 1,400 1,840 23

221 09181000 ONION CREEK NEAR MOAB, UTAH 730 1,390 1,920 2,660 3,270 3,910 4,600 5,560 13

2

222 09182000 CASTLE CREEK ABOVE DIVERSIONS, NEAR MOAB, 

UTAH

9.3 19 27.2 39 48.9 59.5 71 87.4 24

223 09182600 SALT WASH NEAR THOMPSON, UTAH 263 714 1,220 2,180 3,200 4,520 6,240 9,240 15

2

224 09183000 COURTHOUSE WASH NEAR MOAB, UTAH 2,090 4,590 7,090 11,500 15,800 21,300 28,100 39,600 31

225 09183500 MILL CREEK AT SHELEY TUNNEL, NEAR MOAB, 

UTAH

185 405 622 998 1,360 1,820 2,370 3,300 23

226 09184000 MILL CREEK NEAR MOAB, UTAH 687 1,810 3,010 5,170 7,340 10,100 13,400 19,100 47

227 09185200 KANE SPRINGS CANYON NEAR MOAB, UTAH 529 842 1,070 1,370 1,610 1,850 2,110 2,460 15

228 09185500 HATCH WASH NEAR LA SAL, UTAH 493 1,210 1,970 3,340 4,720 6,470 8,660 12,400 22

229 09187000 COTTONWOOD CREEK NEAR MONTICELLO, UTAH 378 1,260 2,380 4,700 7,330 10,900 15,800 24,800 17

Appendix 25
Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis—Continued.

Map 

ID

Gaging 

station 

number

Gaging station name

Peak flow, in cubic feet per second, for given recurrence interval, in years

2 5 10 25 50 100 200 500

Number of 

annual 

peak flows

Region 6—Continued

230 09263700 CLIFF CREEK NEAR JENSEN, UTAH 163 745 1,550 3,210 5,000 7,340 10,300 15,200 15

231 09263800 COW WASH NEAR JENSEN, UTAH 298 800 1,320 2,230 3,110 4,180 5,450 7,510 14

232 09271800 HALFWAY HOLLOW TRIB. NEAR LAPOINT, UTAH 89.8 300 538 968 1,390 1,890 2,490 3,440 15

233 09306235 CORRAL GULCH BELOW WATER GULCH, NR 

RANGELY, CO.

14.1 69.1 157 374 652 1,070 1,680 2,900 14

234 09306240 BOX ELDER GULCH NEAR RANGELY, CO. 14.7 57.7 118 254 418 655 987 1,630 11

235 09306242 CORRAL GULCH NEAR RANGELY, CO. 32.5 126 257 552 908 1,420 2,150 3,550 32

236 09306255 YELLOW CREEK NEAR WHITE RIVER, CO. 96.8 355 727 1,600 2,720 4,441 6,930 12,100 27

237 09306800 BITTER CREEK NEAR BONANZA, UTAH 108 443 934 2,080 3,510 5,630 8,700 14,800 19

238 09307500 WILLOW CREEK ABOVE DIVERSIONS NEAR 

OURAY, UTAH

231 466 704 1,130 1,570 2,130 2,860 4,130 27

4

239 09308000 WILLOW CREEK NEAR OURAY, UTAH 629 1,850 3,200 5,650 8,100 11,100 14,900 21,000 26

4

240 09308200 PLEASANT VALLEY WASH TRIB. NEAR MYTON, 

UTAH

88.2 997 3,120 9,590 18,900 33,500 55,400 98,300 11

241 09308500 MINNIE MAUD CREEK NR MYTON, UTAH 107 356 655 1,240 1,850 2,650 3,650 5,370 35

242 09309000 MINNIE MAUD C AT NUTTER RANCH NR MYTON, 

UTAH

481 843 1,110 1,450 1,720 1,990 2,260 2,620 23

243 09309100 GATE CANYON NEAR MYTON, UTAH 175 726 1,420 2,760 4,110 5,790 7,800 11,000 12

244 09310500 FISH CREEK ABOVE RESERVOIR, NEAR SCOFIELD, 

UTAH

517 826 1,040 1,300 1,500 1,700 1,890 2,140 68

245 09310700 MUD CRK BL WINTER QUARTERS CYN AT SCOFIELD, UTAH99.3 186 259 371 468 577 700 886 23

246 09312500 WHITE RIVER NEAR SOLDIER SUMMIT, UTAH 171 303 413 578 722 884 1,070 1,340 28

247 09312600 WHITE R BL TABBYUNE CRK NR SOLDIER SUMMIT, 

UTAH

193 386 552 808 1,030 1,280 1,570 2,000 38

248 09312700 BEAVER CREEK NEAR SOLDIER SUMMIT, UTAH 41.7 82.9 119 177 229 289 358 465 29

249 09312800 WILLOW CREEK NEAR CASTLE GATE, UTAH 216 387 538 779 999 1,260 1,560 2,050 27

250 09313500 PRICE RIVER NEAR HELPER, UTAH 2,270 4,300 6,160 9,230 12,100 15,600 19,900 26,800 19

251 09314200 MILLER CREEK NEAR PRICE, UTAH 1,370 3,380 5,400 8,890 12,200 16,300 21,200 29,100 13

252 09314280 DESERT SEEP WASH NEAR WELLINGTON, UTAH 501 886 1,200 1,680 2,100 2,560 3,080 3,860 15

253 09314400 COLEMAN WASH NEAR WOODSIDE, UTAH 254 607 948 1,520 2,050 2,670 3,400 4,560 10

254 09315150 SALERATUS WASH TRIB. NR WOODSIDE, UTAH 804 2,240 3,820 6,730 9,680 13,400 18,100 25,900 15

255 09315200 SALERATUS WASH TRIB NO 2 NR WOODSIDE, UTAH 974 2,530 4,030 6,480 8,700 11,200 14,100 18,400 15

256 09315400 SALERATUS WASH ABOVE C. WASH NR. GREEN 

RIVER, UTAH

3,040 5,960 8,640 13,000 17,100 22,100 27,900 37,400 10

257 09315500 SALERATUS WASH AT GREEN RIVER, UTAH 2,440 4,750 6,710 9,650 12,200 15,000 18,100 22,800 22

3

258 09315900 BROWNS WASH TRIB. NR. GREEN RIVER, UTAH 206 608 1,070 1,970 2,920 4,170 5,780 8,590 15

259 09316000 BROWNS WASH NEAR GREEN RIVER, UTAH 1,780 3,750 5,480 8,160 10,500 13,200 16,100 20,600 19

260 09318000 HUNTINGTON CREEK NR HUNTINGTON, UTAH 802 1,300 1,650 2,120 2,490 2,860 3,250 3,770 71

261 09324500 COTTONWOOD CREEK NEAR ORANGEVILLE, UTAH 1,450 2,150 2,620 3,220 3,670 4,110 4,560 5,150 23

262 09326500 FERRON CREEK (UPPER STATI 784 1,310 1,750 2,410 2,980 3,620 4,350 5,460 70

3

263 09327600 FERRON CREEK TRIB. NEAR FERRON, UTAH 106 338 623 1,210 1,860 2,750 3,940 6,100 12

264 09328300 SIDS DRAW NEAR CASTLE DAL 438 1,190 1,960 3,310 4,590 6,140 7,970 10,900 15

265 09328600 GEORGES DRAW NEAR HANKSVILLE, UTAH 216 592 998 1,730 2,470 3,400 4,530 6,430 14

266 09328700 TEMPLE WASH NEAR HANKSVILLE, UTAH 130 400 714 1,320 1,950 2,780 3,820 5,630 10

267 09328720 OLD WOMAN WASH NEAR HANKSVILLE, UTAH 263 936 1,730 3,200 4,680 6,490 8,670 12,100 10

268 09328900 CRESENT WASH NEAR CRESENT JUNCTION, UTAH 418 1,110 1,930 3,590 5,440 7,990 11,500 18,000 10

2

269 09329050 SEVEN MILE CREEK NEAR FISH LAKE, UTAH 184 271 323 381 419 455 487 525 34

270 09329900 PINE CREEK NEAR BICKNELL, UTAH 81.9 237 390 641 865 1,120 1,400 1,810 16

271 09330120 SULPHUR CREEK NEAR FRUITA, UTAH 548 1,230 1,820 2,680 3,410 4,190 5,020 6,200 16

272 09330200 PLEASANT CREEK AT NOTOM, UTAH 270 822 1,400 2,390 3,300 4,370 5,580 7,410 14

3

273 09330300 NEILSON WASH NEAR CAINEVILLE, UTAH 988 2,390 3,630 5,510 7,100 8,830 10,700 13,300 15

274 09330500 MUDDY CREEK NEAR EMERY, UTAH 459 976 1,480 2,360 3,230 4,300 5,630 7,860 62

275 09331500 IVIE CREEK ABOVE DIVERSIONS NR EMERY, UTAH 189 402 589 876 1,130 1,410 1,720 2,190 24

276 09333900 BUTLER CANYON NEAR HITE, UTAH 415 748 1,010 1,400 1,720 2,060 2,440 2,980 16

277 09334000 NORTH WASH NEAR HANKSVILLE (HITE), UTAH 1,190 3,080 4,980 8,250 11,400 15,100 19,500 26,500 21

1

278 09334400 FRY CANYON NEAR HITE, UTAH Nd Nd Nd Nd Nd Nd Nd Nd 15

279 09334500 WHITE CANYON NEAR HANKSVILLE UTAH 2,200 4,260 5,980 8,550 10,700 13,200 15,900 19,900 20

280 09336000 BIRCH CREEK NEAR ESCALANTE, UTAH 425 1,030 1,620 2,570 3,450 4,470 5,640 7,440 17

281 09336400 UPPER VALLEY CREEK NEAR ESCALANTE, UTAH 739 1,600 2,400 3,730 4,970 6,450 8,200 1,1000 16

3

282 09337000 PINE CREEK NEAR ESCALANTE, UTAH 177 371 536 784 994 1,230 1,480 1,850 53

283 09337500 ESCALANTE RIVER NEAR ESCALANTE, UTAH 815 1,690 2,420 3,470 4,350 5,290 6,290 7,710 50

26 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah
Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis—Continued.

Map 

ID

Gaging 

station 

number

Gaging station name

Peak flow, in cubic feet per second, for given recurrence interval, in years

2 5 10 25 50 100 200 500

Number of 

annual 

peak flows

Region 6—Continued

2

284 09338000 EAST FORK BOULDER CREEK NEAR BOULDER, 

UTAH

203 304 369 447 502 556 607 672 20

2

285 09338500 EAST FORK DEER CREEK NEAR BOULDER, UTAH 21.5 65.9 117 217 321 456 628 924 20

286 09338900 DEER CREEK NEAR BOULDER, UTAH 498 1,500 2,520 4,210 5,740 7,480 9,420 12,300 20

287 09339200 TWENTYMILE WASH NR ESCALANTE, UTAH 1,680 3,010 4,030 5,440 6,570 7,760 9,020 10,800 10

288 09366500 LA PLATA RIVER AT COLORADO-NEW MEXICO 

STATE LINE

655 1,370 2,040 3,140 4,180 5,430 6,910 9,300 85

3

289 09367530 LOCKE ARROYO NR. KIRTLAND, NM 105 249 395 651 902 1,210 1,590 2,220 35

290 09367550 STEVENS ARROYO NR KIRTLAND, NM 131 467 915 1,890 3,030 4,640 6,860 11,100 21

291 09367561 SHUMWAY ARROYO NEAR WATERFLOW, NM 178 776 1,710 4,040 7,110 11,900 19,100 34,200 16

292 09367980 RATTLESNAKE ARROYO NR SHIPROCK, NM 141 563 1,230 2,970 5,370 9,320 15,700 29,900 17

3

293 09368020 MALPAIS ARROYO NR SHIPROCK, NM 109 276 460 808 1,170 1,660 2,280 3,390 19

2

294 09371000 MANCOS RIVER NEAR TOWAOC, CO. 1,090 2,010 2,770 3,910 4,890 5,980 7,190 9,000 71

1

295 09371300 MCELMO CREEK TRIBUTARY NEAR CORTEZ, CO. Nd Nd Nd Nd Nd Nd Nd Nd 11

296 09371420 MCELMO CREEK ABOVE ALKALI CANYON, NR 

CORTEZ, CO.

599 748 839 949 1,030 1,100 1,170 1,270 14

297 09371500 MCELMO CREEK NEAR CORTEZ, CO. 807 1,610 2,390 3,750 5,090 6,770 8,850 12,400 22

298 09371520 MCELMO CREEK ABOVE TRAIL CANYON NEAR 

CORTEZ, CO

473 1,110 1,770 3,010 4,280 5,940 8,060 11,800 12

299 09371700 MCELMO CREEK BELOW CORTEZ, CO. 733 1,180 1,530 2,020 2,430 2,880 3,360 4,070 11

300 09372000 MCELMO CREEK NEAR COLORADO-UTAH STATE 

LINE

909 1,570 2,090 2,830 3,450 4,120 4,850 5,920 55

4

301 09372200 MCELMO CREEK NEAR BLUFF, UTAH 644 1,790 3,220 6,290 9,930 15,200 22,800 37,900 13

302 09378170 SOUTH CREEK ABOVE RESERVOIR NEAR MONTICELLO, UTAH44 92.4 137 209 275 353 444 587 20

303 09378200 MONTEZUMA CREEK AT GOLF COURSE AT MONTICELLO, UTAH

25.1 96.7 204 465 806 1,340 2,150 3,850 13

4

304 09378600 MONTEZUMA CREEK NEAR BLUFF, UTAH 1,220 3,640 6,860 14,200 23,400 37,300 58,100 102,000 15

2

305 09378630 RECAPTURE CREEK NEAR BLANDING, UTAH 13.7 37.2 62.4 108 153 210 280 396 40

306 09378650 RECAPTURE CR BL JOHNSON CR NR 

BLANDING,UT.

114 327 564 1,000 1,460 2,030 2,750 3,970 17

307 09378700 COTTONWOOD WASH NR BLANDING UTAH 1,060 2,720 4,640 8,460 12,700 18,500 26,400 41,100 29

4

308 09378720 COTTONWOOD WASH AT BLUFF, UTAH 1,150 4,360 9,380 22,400 40,600 70,600 119,000 230,000 10

309 09378950 COMB WASH NEAR BLANDING, UTAH 737 1,430 2,090 3,210 4,300 5,630 7,260 9,990 10

310 09379000 COMB WASH NEAR BLUFF, UTAH 1,800 3,150 4,350 6,270 8,050 10,200 12,700 16,800 10

311 09379030 BLACK MOUNTAIN WASH NEAR CHINLE, ARIZ. 722 1,670 2,580 4,110 5,530 7,240 9,240 12,400 15

3

312 09379060 LUKACHUKAI CREEK TRIBUTARY NEAR LUKACHUKAI, AZ13.1 51.5 105 221 358 552 817 1,310 14

4

313 09379100 LONG HOUSE WASH NEAR KAYENTA, ARIZ. 177 1,160 3,000 8,080 15,200 26,500 43,800 79,900 15

314 09379300 LIME CREEK NEAR MEXICAN HAT, UTAH 1,620 4,120 6,730 11,400 16,000 21,800 28,900 40,800 15

315 09379560 EL CAPITAN WASH NEAR KAYENTA, ARIZ. 461 944 1,410 2180 2,930 3,850 4,960 6,800 14

316 09379800 COYOTE CREEK NEAR KANAB, UTAH 1,400 2,740 3,880 5,590 7,060 8,690 10,500 13,200 14

317 09379820 BUCK TANK DRAW NEAR KANAB, UTAH 9.7 70.2 207 675 1,480 3,020 5,890 13,400 10

318 09381100 HENRIEVILLE CREEK AT HENRIEVILLE, UTAH 873 2,070 3,320 5,550 7,790 10,600 14,200 20,300 16

319 09381500 PARIA RIVER NEAR CANNONVILLE, UTAH 2,710 4,780 6,430 8,860 10,900 13,100 15,600 19,200 25

4

320 09381800 PARIA RIVER NEAR KANAB, UTAH 2,570 5,210 7,610 11,400 14,900 19,000 23,800 31,300 17

4

321 09382000 PARIA RIVER AT LEES FERRY, AZ 3,120 6,350 9,020 12,900 16,200 19,700 23,500 28,900 82

322 09403500 KANAB C NR GLENDALE UT 623 1,430 2,140 3,180 4,060 5,000 6,010 7,430 16

323 09403600 KANAB CREEK NEAR KANAB, UTAH 368 1,010 1,630 2,640 3,520 4,520 5,620 7,220 37

324 09403700 JOHNSON WASH NEAR KANAB, UTAH 1,010 2,060 2,860 3,930 4,740 5,550 6,360 7,410 16

4

325 09403780 KANAB CREEK NR FREDONIA, ARIZ. 893 1,790 2,570 3,770 4,810 5,980 7,300 9,280 16

3

326 09403800 BITTER SEEPS WASH TRIB NEAR FREDONIA, ARIZ. 134 566 1,160 2,410 3,820 5,730 8,220 12,600 14

Region 7

327 09404450 EAST FORK VIRGIN RIVER NEAR GLENDALE, UTAH 101 232 362 586 804 1,070 1,400 1,930 38

328 09404500 MINERAL GULCH NEAR MT. CARMEL, UTAH 202 1,040 2,330 5,290 8,800 13,700 20,300 32,300 14

329 09404700 EAST FK VIRGIN RIVER NR MOUNT CARMEL JUNCTION, UTAH519 1,100 1,600 2,350 2,990 3,690 4,460 5,570 11

330 09404900 EAST FORK VIRGIN RIVER NEAR SPRINGDALE, 

UTAH

872 2,410 4,000 6,790 9,460 12,700 16,500 22,600 14

331 09405420 N FK VIRGIN R BLW BULLOCH CANYON NR GLENDALE, UTAH

207 410 598 910 1,200 1,560 1,980 2,670 11

Appendix 27
Appendix. Peak flows at selected recurrence intervals for streamflow-gaging stations in Utah and bordering states used in regional 

regression analysis—Continued.

Map 

ID

Gaging 

station 

number

Gaging station name

Peak flow, in cubic feet per second, for given recurrence interval, in years

2 5 10 25 50 100 200 500

Number of 

annual 

peak flows

Region 7—Continued

332 09405500 NORTH FORK VIRGIN RIVER NEAR SPRINGDALE, 

UTAH

1,710 3,170 4,340 6020 7,410 8,900 10,500 12,800 82

4

333 09406000 VIRGIN RIVER AT VIRGIN, UTAH 3,690 6,870 9,550 13,600 17,200 21,200 25,700 32,400 89

334 09406300 KANARRA CREEK AT KANARRAVILLE, UTAH 141 367 608 1,040 1,480 2,030 2,720 3,880 23

335 09406700 SOUTH ASH CREEK BELOW MILL CREEK NEAR 

PINTURA, UTAH

199 549 926 1,610 2,280 3,120 4,160 5,860 16

336 09406800 SOUTH ASH CREEK NEAR PINTURA, UTAH 193 468 740 1,200 1,640 2,170 2,790 3,790 14

337 09407200 ASH CR BLW WEST FIELD DITCH AT TOQUERVILLE, 

UTAH

264 828 1,490 2,770 4,110 5,860 8,080 11,900 10

338 09408000 LEEDS CREEK NEAR LEEDS, UTAH 161 724 1,590 3,670 6,300 10,200 16,000 27,400 42

4

339 09408150 VIRGIN RIVER NEAR HURRICANE, UTAH 6,000 11,000 14,900 20,400 25,000 29,800 35,000 42,300 19

3

340 09408200 FORT PIERCE WASH NR ST. GEORGE, UTAH 2,240 4,650 6,740 9,950 12,700 15,900 19,400 24,600 11

341 09408400 SANTA CLARA RIVER NEAR PINE VALLEY, UTAH 68.7 156 244 395 544 727 951 1,320 46

342 09409500 MOODY WASH NEAR VEYO, UTAH 210 802 1,600 3,310 5,280 8,000 11,700 18,400 15

343 09410000 SANTA CLARA RIVER AB WINSOR DAM NR SANTA 

CLARA, UTAH

944 2,390 3,840 6,340 8,740 11,600 15,100 20,600 30

344 09413900 BEAVER DAM WASH NEAR ENTERPRISE, UTAH 278 1350 2,880 6,140 9,750 14,500 20,600 30,900 14

1

345 09415050 BIG BEND WASH TRIB NEAR LITTLEFIELD, ARIZONANd Nd Nd Nd Nd Nd Nd Nd 26

346 10173450 MAMMOTH CREEK ABV WEST HATCH DITCH, 

NEAR HATCH, UTAH

401 562 660 773 851 925 994 1,080 40

347 10174500 SEVIER RIVER AT HATCH, UTAH 566 883 1,110 1,410 1,640 1,880 2,120 2,460 81

4

348 10183900 EAST FORK SEVIER RIVER NEAR RUBYS INN, UTAH 101 176 240 340 430 533 653 840 34

349 10185000 ANTIMONY CREEK NEAR ANTIMONY, UTAH 239 417 527 652 733 805 870 944 21

350 10241300 FREMONT WASH NEAR PARAGONAH, UTAH 105 199 275 384 474 570 673 821 16

351 10241400 LITTLE CREEK NEAR PARAGONAH, UTAH 36.7 126 244 502 806 1,240 1,850 3,010 21

352 10241430 RED CREEK NEAR PARAGONAH, UTAH 14.4 24.9 33.1 44.7 54.2 64.5 75.5 91.4 11

353 10241470 CENTER CREEK ABV PAROWAN CREEK, NEAR 

PAROWAN, UTAH

57.9 142 231 392 554 759 1,020 1,460 23

354 10241600 SUMMIT CREEK NEAR SUMMIT, UTAH 69.3 218 409 820 1,300 1,990 2,970 4,850 23

355 10242000 COAL CREEK NEAR CEDAR CITY, UTAH 743 1,590 2,340 3,510 4,540 5,710 7,030 9,010 75

1

Annual peak series plotted poorly to log Pearson Type III distribution, peak-flow recurrence intervals not determined, not used in analysis. 

2

Leverage statistic exceeded limit and removed from analysis.

3

Leverage statistic exceeded limit but remained in analysis.

4

Peak-flow recurrence interval discharge(s) and/or basin characteristics determined to be outliers, not used in analysis.

28 Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah

Kenney, Wilkowske, and Wright—Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah—SIR 2007–5158