U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2010–5012

Prepared in cooperation with the Alabama Department of Transportation

Magnitude and Frequency of Floods for Urban Streams

in Alabama, 2007
Cover.  Flooded tributary to Jenkins Creek at Montgomery, Alabama, May 7, 2009 (photograph taken by T.S. Hedgecock, USGS).
Magnitude and Frequency of Floods for Urban Streams 

in Alabama, 2007

By T.S. Hedgecock and K.G. Lee

Prepared in cooperation with the Alabama Department of Transportation

Scientific Investigations Report 2010–5012

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2010

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Suggested citation:

Hedgecock, T.S., and Lee, K.G., 2010, Magnitude and frequency of floods for urban streams in Alabama, 2007: 

U.S. Geological Survey Scientific Investigations Report 2010–5012, 17 p.

(Also available online at http://pubs.usgs.gov/sir/2010/5012/)

ISBN 978 1 4113 2836 5
iii

Contents

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

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

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

Previous Studies ...................................................................................................................................1

Description of the Study Area ............................................................................................................1

Flood Data Used in the Analysis..................................................................................................................2

Flood Magnitude and Frequency at Gaging Stations ..............................................................................9

Urban Flood-Frequency Analysis................................................................................................................9

Accuracy and Limitations of Flood-Frequency Estimates ...........................................................12

Use of Flood-Frequency Relations...................................................................................................13

Gaged Sites.................................................................................................................................13

Comparison of Results with Previous Alabama Study Results ...................................................14

Summary........................................................................................................................................................16

References ...................................................................................................................................................16

Figures

1–2. Maps showing locations of—

1. Physiographic provinces in Alabama...............................................................................2

2. Cities with urban streamgaging stations that were used in the study .......................3

3–5. Maps showing locations of urban streamgaging stations in the vicinity of—

3. Birmingham, Alabama.........................................................................................................4

4. Huntsville, Alabama.............................................................................................................5

5. Mobile, Alabama..................................................................................................................6

6–8. Maps showing locations of urban streamgaging stations at—

6. Mill Branch at Columbus, Georgia....................................................................................7

7. Elevenmile Creek near Pensacola, Florida......................................................................8

8. Gordon Creek at Hattiesburg, Mississippi.......................................................................8

9. Map showing locations of the four flood regions in Alabama............................................13

Tables

1. T-year recurrence intervals with corresponding annual exceedance probabilities 

and P-percent chance exceedance for flood-frequency flow estimates...........................9

2. Peak flows for selected exceedance probabilities at urban streamgaging stations 

used in Alabama urban regression analyses.........................................................................10

3. Regional flood-frequency relations for urban streams in Alabama...................................12

4. Accuracy of regional flood-frequency relations for urban streams in Alabama.............13

5. Variance of prediction values for urban streamgaging stations used in Alabama 

urban regression analyses........................................................................................................15
iv

Conversion Factors

Inch/Pound to SI

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) 

acre 0.00405 square kilometer (km2

)

Flow rate

cubic foot per second (ft3

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

Hydraulic gradient

foot per mile (ft/mi) 0.1894 meter per kilometer (m/km)

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

(NAVD 88).

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

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

Methods of estimating flood magnitudes for exceedance 

probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent have 

been developed for urban streams in Alabama that are not 

significantly affected by dams, flood detention structures, 

hurricane storm surge, or substantial tidal fluctuations. 

Regression relations were developed using generalized 

least-squares regression techniques to estimate flood 

magnitude and frequency on ungaged streams as a function 

of the basin drainage area and percentage of basin developed. 

These methods are based on flood-frequency characteristics 

for 20 streamgaging stations in Alabama and 3 streamgaging 

stations in adjacent States having 10 or more years of record 

through September 2007. 

Introduction

The magnitude and frequency of floods are important factors in the design of bridges, culverts, highway embankments, 

dams, and other structures near streams and rivers. Flood-plain 

management plans and flood-insurance rates also require 

information on the magnitude and frequency of floods.

The Alabama Department of Transportation needs 

accurate flood-frequency information to efficiently design 

drainage structures in Alabama. To meet this need, the U.S. 

Geological Survey (USGS), in cooperation with the Alabama 

Department of Transportation, conducted a study to update 

previous urban flood-frequency reports on the basis of 

peak-flow data collected through September 2007 from urban 

streamgaging stations. 

Purpose and Scope

The information in this report updates previously 

published urban flood-frequency information for Alabama by 

providing methods of estimating the magnitude and frequency 

of floods at ungaged urban streams and provides frequency 

estimates of peak flow using peak-flow data collected through 

September 2007 at urban streamgaging stations. Included in 

this report are equations for estimating the magnitude of floods 

having exceedance probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 

0.2 percent for ungaged and unregulated urban streams and 

methods for estimating the magnitude and frequency of floods 

at or near urban gaging stations.

Previous Studies

Magnitude and frequency of floods in Alabama have been 

described by Pierce (1954), Speer and Gamble (1964), Gamble 

(1965), Barnes and Golden (1966), Hains (1973), Olin (1985), 

Atkins (1996), and Hedgecock and Feaster (2007). Magnitude 

and frequency of floods for rural streams with small drainage 

areas have been described by Olin and Bingham (1977) 

and Hedgecock (2004), and for urban streams by Olin and 

Bingham (1982).

Description of the Study Area

The study area includes all of Alabama, which covers an 

area of about 51,600 square miles (mi2 ), in five physiographic 

provinces—Coastal Plain, Piedmont, Valley and Ridge, 

Appalachian Plateaus, and Interior Lowland Plateaus (fig. 1). 

The area north of the Fall Line, which delineates the contact 

of the Coastal Plain with the other provinces, has a diverse 

topography with land-surface elevations ranging from 200 to 

2,400 feet (ft) above the North American Vertical Datum of 

1988 (NAVD 88). In the Coastal Plain, elevations range from 

0 to 1,000 ft above NAVD 88 in the northwestern part of the 

State. The land surface generally slopes to the south and west.

Average annual precipitation ranges from about 48 inches 

in central and west-central Alabama to about 68 inches near 

the Gulf of Mexico and averages about 57 inches statewide 

(National Oceanic and Atmospheric Administration, 2002). 

Rainfall in Alabama generally is associated with the movement of warm and cold fronts across the State from November 

through April and isolated summer thunderstorms from May 

through October. Occasionally, tropical storms or hurricanes 

that enter the State along the gulf coast produce unusually 

heavy amounts of rainfall (U.S. Geological Survey, 1986).

Magnitude and Frequency of Floods for Urban Streams 

in Alabama, 2007

By T.S. Hedgecock and K.G. Lee
2 Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007 

Figure 1. Locations of physiographic provinces in Alabama.

Average annual runoff varies from approximately 12 to 

40 inches (National Oceanic and Atmospheric Administration, 

2002). Runoff typically is greatest during February through 

April and least when rainfall decreases during September 

through November.

Flood Data Used in the Analysis

 This study is based on peak-flow data collected through 

September 2007 at 23 urban gaging stations having 10 or 

more years of record. Of these 23 stations, 20 were located in 

Alabama, and 3 were located in the adjacent States of Florida, 

Georgia, and Mississippi near the Alabama State boundary. 

The gaging stations in Alabama were located in or near the 

cities of Birmingham, Huntsville, and Mobile (figs. 2–5). 

Stations in adjacent States were located in Columbus, Georgia; 

Pensacola, Florida; and Hattiesburg, Mississippi (figs. 2, 

6–8). The period of record for gaging stations used in this 

study ranged from 11 to 38 years, with an average record 

length of 17 years. Only gaging stations with well-defined 

ratings (stage-to-flow relation) were used in this study. Some 

gaging-station ratings were improved and extended using a 

one-dimensional step-backwater model (Shearman, 1990) and 

a culvert analysis program (Fulford, 1998). The peak-flow 

records used in the study were not significantly affected by 

0 50 MILES

0 50 KILOMETERS

Base from U.S. Geological Survey digital data,

1:100,000, Universal Transverse Mercator Projection, 

Zone 16.

35

34

33

32

31

88 87 86 85

LAUDERDALE

LAWRENCE

MARION WINSTON

LAMAR FAYETTE WALKER

CULLMAN

BLOUNT

ETOWAH

CHEROKEE

ST. CLAIR CALHOUN

JEFFERSON

TUSCALOOSA

PICKENS SHELBY CLAY

COOSA

CHILTON

BIBB

HALE

PERRY

DALLAS

AUTAUGA

LOWNDES MONTGOMERY

BUTLER

ELMORE

LEE

RUSSELL

BARBOUR

HENRY

DALE

COFFEE

GENEVA COVINGTON

ESCAMBIA

CONECUH

MONROE

WILCOX

CLARKE

CHOCTAW

WASHINGTON

MOBILE

BALDWIN

HOUSTON

PIKE

CRENSHAW

MACON

BULLOCK

MARENGO

GREENE

SUMTER

TALLAPOOSA

RANDOLPH

CHAMBERS

TALLADEGA

CLEBURNE

COLBERT

FRANKLIN

LIMESTONE

MADISON JACKSON

MORGAN MARSHALL DEKALB

MISSISSIPPI

GEORGIA

FLORIDA

TENNESSEE

Gulf of Mexico

Interior Lowland

Plateaus

Appalachian

 Plateaus

Valley 

 and 

Ridge

Piedmont

Coastal Plain

Fall Line
Flood Data Used in the Analysis 3

dams, flood detention structures, hurricane storm surge, or 

substantial tidal fluctuations. Only gaging stations located in 

basins having a fairly constant percentage of development for 

the period of gaging record were used in this study. Development could be any manmade structure, paving, or clearing of 

land that would increase the runoff potential in a local area. 

Stations having more than a 50-percent increase in development during the gaging period (Sauer and others,1983) were 

not used in this study. Basin development and changes in basin 

development were assessed from inspection of topographical 

maps and aerial photographs of various vintages throughout 

the gaging period. Several sites located in or near Birmingham, Alabama, on Village, Valley, Fivemile, and Shades 

Creeks were not used in this study because of one or more 

of the following: (1) the existence of a substantial amount 

of detention storage, (2) substantial increases (greater than 

50 percent) in development that occurred during the gaging 

period, or (3) poorly defined stage-to-flow relation for the site. 

Figure 2. Locations of cities with urban streamgaging stations used in the study.

MOBILE BALDWIN

LEE

CLARKE

PIKE

DALLAS

HALE

BIBB

CLAY

JACKSON

MONROE

WILCOX

PERRY

DALE

SUMTER

PICKENS SHELBY

BUTLER

TUSCALOOSA

JEFFERSON

WALKER

COOSA

MARENGO

COFFEE

CHOCTAW

DE KALB

BARBOUR

MARION

ESCAMBIA

CONECUH

COVINGTON

HENRY

LAMAR

GREENE

MADISON

CHILTON

ELMORE

BLOUNT

MACON

WASHINGTON

CULLMAN

FAYETTE

RUSSELL

ST CLAIR

LOWNDES

GENEVA

COLBERT

BULLOCK

MORGAN LAWRENCE

FRANKLIN

WINSTON

ETOWAH

CALHOUN

AUTAUGA

HOUSTON

CHEROKEE

MARSHALL

LAUDERDALE

CLEBURNE

CHAMBERS

TALLADEGA

TALLAPOOSA

MONTGOMERY

RANDOLPH

CRENSHAW

LIMESTONE

Pensacola

Columbus

Birmingham

Huntsville

Mobile

Hattiesburg

88 89

35

87 86 85

34°

33°

32°

31°

30°

Base from U.S. Geological Survey digital data,

1:100,000, Universal Transverse Mercator Projection, 

Zone 16.

0 50 MILES

0 50 KILOMETERS

FLORIDA

GEORGIA

MISSISSIPPI

TENNESSEE

Gulf of Mexico
4 Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007 

Figure 3. Locations of urban streamgaging stations in the vicinity of Birmingham, Alabama.

#

#

#

#

Black Warrior River

Locust Fork

Turkey Creek

Fivemile Creek

Valley Creek

SHELBY

WALKER

JEFFERSON

ST. CLAIR

TUSCALOOSA

BLOUNT

TALLADEGA

BIBB

02455980

02423400

02423397

02423130

0 3 6 MILES

0 3.9 7.8 KILOMETERS

Figure 3. Location of urban stations in the vicinity of Birmingham, Alabama.

Birmingham

Valley Creek

Mud Creek

Shades Creek

Cahaba River

LittleCahaba River

Cahaba River

Cahaba River

#

02423400 Streamgaging

 station and number

EXPLANATION

Study area

8715’

33

45’

33

30’

33

15’

86

45’ 86 87 30’ 
Flood Data Used in the Analysis 5

Figure 4. Locations of urban streamgaging stations in the vicinity of Huntsville, Alabama. Figure 4. Location of urban stations in the vicinity of Huntsville, Alabama.

0 2.5 5 MILES

0 3.3 6.6 KILOMETERS

GILES

LIMESTONE MADISON

JACKSON

MORGAN

LINCOLN FRANKLIN

#

03575700 Streamgaging

 station and number

EXPLANATION

Study area

8645’ 8630’ 86 87 15’ 

35

3445’

34

30’

Limestone Creek

Bradford

Indian Beaverdam

McDonald

Huntsville

Tennessee

Spring

Flint

River

Branch

Broglan Br

Creek

Pinhook Cr

Hurricane

Creek

Aldridge Creek

Creek

Dry Cr

Creek

Briar

Fork

Flint

Flint

Flint

Big

Cove

Creek

River

River

River

Creek

Dallas Br

Fagan

River

Cr

#

##

# #

# #

#

#

#

#

# #

0357587090

03575980

0357526200

03575700

0357568980 0357568650

0357587400

0357586650

03575950

0357587728 0357591500

03575933

03575890

Huntsville
6 Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007 

Figure 5. Locations of urban streamgaging stations in the vicinity of Mobile, Alabama.

#

#

#

02480002

02471078

02471065

Figure 5. Location of urban stations in the vicinity of Mobile, Alabama.

WASHINGTON

GREENE

GEORGE

JACKSON

MOBILE

BALDWIN

Mobile

Bennett Creek

Hamilton

Chickasaw

Big Creek

Big

Fowl

West Fowl Montlimar Cr

Mobile River

Mobile River

Puppy

Middle

Middle

River

River

Cedar Bayou

Escatawpa

Creek

Creek

Creek

Sara

River

Cr

Creek

River

River

0 3 6 MILES

0 3.9 7.8 KILOMETERS

#

02471078 Streamgaging

 station and number

Study area

EXPLANATION

8830’

31

3045’

30

30’

30

15’

88

15’ 88
Flood Data Used in the Analysis 7

Figure 6. Location of the urban streamgaging station at Mill Branch at Columbus, Georgia.

#

02341544

0 2 4 MILES

0 2.3 4.6 KILOMETERS

Figure 6. Location of Mill Branch at Columbus, Georgia

LEE

HARRIS

TALBOT

CHATTAHOOCHEE

MUSCOGEE

RUSSELL

Bull Creek

Chattahoochee River

Upatoi Creek

Mill Br

Columbus

#

02341544 Streamgaging

 station and number

Study area

EXPLANATION

8615’

32

40’

32

30’

32

20’

84 85 45’ 
8 Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007 

Figure 7. Location of the urban streamgaging station at 

Elevenmile Creek near Pensacola, Florida.

Figure 8. Location of the urban streamgaging station at 

Gordon Creek at Hattiesburg, Mississippi.

#

02376115

0 3 6 MILES

0 4.5 9 KILOMETERS

Figure 7. Location of Elevenmile Creek near Pensacola, Florida.

ESCAMBIA

ESCAMBIA

BALDWIN

SANTA ROSA

#

02376115 Streamgaging

 station and number

Study area

EXPLANATION

Perdido River

Elevenmile

Perdido River

Escambia

Brushy Creek

Barren

Pine

Canoe

Escambia

 Cr

Big

Creek

Creek

River

Cr

Pensacola

8745’

31

3045’

30

30’

87

30’ 8715’

#02473047

0 2.5 5 MILES

0 4 8 KILOMETERS

COVINGTON JONES

LAMAR

FORREST

PERRY

STONE

Bouie River

Leaf River

Leaf River

Black Creek

Gordon Cr

Black Creek

Creek

Little

Black Creek

Chaney 

Hattiesburg

#

02473047 Streamgaging

 station and number

Study area

Figure 8. Location of Gordon Creek at

Hattiesburg, Mississippi

EXPLANATION

8930’

31

30’

31

15’

31

8915’ 89
Urban Flood-Frequency Analysis 9

1Water year is the period October 1 through September 30 and is identified 

by the year in which the period ends. For example, the 2007 water year began 

on October 1, 2006, and ended at midnight on September 30, 2007.

Table 1. T-year recurrence intervals with corresponding 

annual exceedance probabilities and P-percent chance 

exceedances for flood-frequency flow estimates.

T-year recurrence 

interval

Annual exceedance 

probability

P-percent chance 

exceedance

2 0.50 50

5 0.20 20

10 0.10 10

25 0.40 5

50 0.02 2

100 0.01 1

200 0.005 0.5

500 0.002 0.2

(1)

Flood Magnitude and Frequency at 

Gaging Stations

A flood-frequency relation is the relation of peak flow to 

probability of exceedance. Probability of exceedance refers 

to the chance that a given peak flow will be exceeded in any 

one year. For example, a 1-percent chance exceedance flood 

corresponds to the flow magnitude that has a probability of 

0.01 of being equaled or exceeded in any given year (table 1). 

A frequency analysis of annual peak-flow data at a gaging 

station provides an estimate of the flood magnitude and 

frequency at that specific stream site. Flood-frequency flows 

in previous USGS reports were expressed as T-year floods on 

the basis of the recurrence interval for that flood quantile (for 

example, the “100-year flood”). The use of recurrence-interval 

terminology is now discouraged because it sometimes causes 

confusion to the general public (Gotvald and others, 2009). 

The term is sometimes interpreted to imply that there are set 

time intervals between floods of a particular magnitude, when 

in fact floods are random processes that are best understood 

using probabilistic terms.

The terminology associated with flood-frequency 

estimates is undergoing a shift away from the T-year recurrence interval flood to the P-percent chance exceedance 

flood (Gotvald and others, 2009). The use of percent chance 

exceedance flood conveys the probability, or odds, of a flood 

of a given magnitude being equaled or exceeded in any given 

year. T-year recurrence intervals with corresponding annual 

exceedance probabilities and P-percent chance exceedances 

are given in table 1.

The flood-frequency relation for a stream having 10 or 

more years of streamgaging record can be defined by fitting 

a theoretical frequency distribution to the logarithms of 

water-year 1 peak flows (largest instantaneous flow for each 

year). The Interagency Advisory Committee on Water Data 

(1982) identified fitting a Pearson Type III distribution to 

the logarithms of water-year peak flows as the recommended, 

consistent method for determining flood magnitudes 

and frequencies. 

Commonly referred to as the log-Pearson Type III frequency analysis, this technique generally is accepted by most 

Federal and State agencies. Water-year peak flows for each 

gaging station used in this study were fitted to the log-Pearson 

Type III distribution (Interagency Advisory Committee on 

Water Data, 1982). Flood magnitudes having exceedance 

probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent were 

computed for each station by using the following equation:

log , Q M K S p x p x = +

where

Qpis the P-percent chance exceedance flow, in 

cubic feet per second;

Mx is the mean of the logarithms of the wateryear peak flows;

	 K

p is a Pearson Type III factor for a coefficient 

of skewness (G) computed from the 

logarithms of the water-year peak flows 

and a selected probability p; and

	 Sx is the standard deviation of the logarithms of 

the water-year peak flows.

The flood magnitudes for gaging stations for the previously identified exceedance probabilities are listed in table 2. 

Frequency estimates were not computed for urban stations 

located in basins having large increases in the amounts of 

development during the gaging period.

Urban Flood-Frequency Analysis

The flood magnitudes obtained from station frequency 

curves were related to basin characteristics by using 

generalized least squares (GLS) multiple-regression analysis. 

Stedinger and Tasker (1985, 1986) have shown that GLS 

regression analysis can provide more accurate estimates of 

regression coefficients, better estimates of the accuracy of the 

regression coefficients, and better estimates of the regression 

model error than ordinary least squares (OLS) regression 

analysis. OLS regression analysis does not account for the 

errors associated with estimates of flood magnitude varying 

with length of observed record, nor does it account for the 

cross-correlation of concurrent peak-flow data among sites. 

GLS regression analysis accounts for these errors by using 
10 Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007 Table 2. Peak flows for selected exceedance probabilities at urban streamgaging stations used in Alabama urban regression analyses.—Continued [mi2, square miles; top line for each station entry is the log-Pearson Type III peak flow and bottom line is the weighted-average or best-estimate peak flow] Station number Station name Drainage area (mi2

)

Percent 

developed 

Period of 

record

(years)

Peak flow, in cubic feet per second, for indicated percent exceedance probability

50 20 10 4 2 1 0.5 0.2

02423130 Cahaba River at Trussville, 

AL

19.7 13.6 18 2,180

2,060

3,5103,570

4,5404,650

6,0206,320

7,2506,950

8,5807,970

10,000

9,010

12,20010,400

02423397 Little Cahaba River below 

Leeds, AL

17.0 30.3 12 2,060

2,990

2,9703,900

3,8204,920

5,2106,410

6,5407,440

8,1608,460

10,200

9,500

13,50010,900

02423400 Little Cahaba River near 

Jefferson Park, AL

24.4 26.3 15 1,780

2,280

3,0904,370

4,2005,910

5,9107,690

7,4208,990

9,150

10,200

11,10011,500

14,20013,300

02455980 Turkey Creek at sewage plant 

near Pinson, AL

27.4 25.9 19 2,920

3,000

5,7105,550

7,8607,240

10,800

9,170

13,10010,500

15,40012,000

17,80013,200

21,00015,000

02471065 Montlimar Creek at U.S. 

Highway 90 at Mobile, AL

7.28 82.5 14 2,570

2,340

3,7603,470

4,5004,200

5,3505,030

5,9305,610

6,470

6,200

6,9806,800

7,6107,620

02471078 Fowl River at Half-Mile Road 

near Laurendine, AL

16.5 21.1 13 1,590

1,720

3,6003,790

5,5405,030

8,7706,840

11,800

8,330

15,50010,000

19,800

11,900

26,70014,800

02480002 Hamilton Creek at Snow Road 

near Semmes, AL

8.22 21.3 17 930

1,150

1,9102,200

2,7202,900

3,9403,750

4,9604,370

6,0705,010

7,2805,660

9,0406,560

0357526200 Big Cove Creek at Dug Hill 

Road near Huntsville, AL

4.89 16.1 11 1,150

906

2,1701,630

2,9102,090

3,8902,640

4,6403,030

5,3803,450

6,1203,890

7,1004,480

0357568650 Aldridge Creek at Toney 

Drive at Huntsville, AL

1.41 78.7 12 680

687

1,3001,170

1,8401,480

2,6901,910

3,4402,270

4,3002,680

5,2803,130

6,8003,800

0357568980 Aldridge Creek at Sherwood 

Drive at Huntsville, AL

8.10 42.5 13 1,290

1,540

2,3902,700

3,3003,490

4,6604,410

5,8305,090

7,1305,780

8,5706,480

10,700

7,440

03575700 Aldridge Creek near Farley, 

AL

14.1 50.5 23 1,980

2,220

3,3703,850

4,4204,990

5,8406,350

6,9807,360

8,1608,340

9,400

9,350

11,100

10,700

0357586650 Fagan Creek at Adams Street 

at Huntsville, AL

3.44 58.4 11 1,150

1,130

2,3402,030

3,3702,550

4,9303,280

6,2803,880

7,8004,560

9,4805,300

12,000

6,360

0357587090 West Fork Pinhook Creek 

at Blue Springs Road at Huntsville, AL

2.28 36.7 12 840

781

1,2301,190

1,5001,460

1,8301,810

2,0802,080

2,3402,350

2,5902,640

2,9303,040

0357587400 Pinhook Creek at Mastin Lake 

Road at Huntsville, AL

8.5 34.3 11 1,730

1,660

2,6202,680

3,1803,340

3,8404,140

4,3104,740

4,7405,330

5,1605,960

5,6806,800

0357587728 Dallas Branch at Coleman 

Street at Huntsville, AL

2.99 67.2 23 685

751

1,0701,270

1,5701,770

2,6702,600

4,0403,420

6,1604,530

9,4306,040

16,700

8,880

03575890 Pinhook Creek at Clinton 

Avenue at Huntsville, AL

22.6 51.0 23 4,120

3,990

5,7205,770

6,7306,980

7,9708,430

8,8609,530

9,720

10,600

10,600

11,700

11,700

13,100
Urban Flood-Frequency Analysis

11

Table 2. Peak flows for selected exceedance probabilities at urban streamgaging stations used in Alabama urban regression analyses.—Continued[mi2, square miles; top line for each station entry is the log-Pearson Type III peak flow and bottom line is the weighted-average or best-estimate peak flow]

Station 

number Station name

Drainage

area

(mi2)

Percent 

developed 

Period of 

record

(years)

Peak flow, in cubic feet per second, for indicated percent exceedance probability

50 20 10 4 2 1 0.5 0.2

0357591500 Broglan Branch at Oakwood 

Avenue at Huntsville, AL

1.47 97.2 11 930

886

1,2501,190

1,4901,430

1,8401,750

2,1201,990

2,4402,250

2,7802,500

3,3002,880

03575933 Broglan Branch at Clinton 

Avenue at Huntsville, AL

9.50 57.8 16 1,930

1,980

3,0103,290

4,1904,240

6,4805,740

9,0207,100

12,500

8,760

17,40010,800

26,90014,300

03575950 Huntsville Springs Branch at 

Johnson Road at Huntsville, AL

43.2 43.3 16 5,360

5,230

8,4508,580

11,000

10,300

14,80013,800

18,20015,600

22,00017,600

26,40019,500

33,20022,200

03575980 McDonald Creek at Patton 

Road near Huntsville, AL

10.1 49.3 23 1,750

1,820

2,4402,780

3,0003,620

3,8404,740

4,5805,600

5,4106,450

6,3607,250

7,8208,390

02341544 Mill Branch at Chalbena Road 

at Columbus, GA

1.58 45.2 20 580

590

790840

930

1,030

1,1001,270

1,2301,460

1,350

1,650

1,6001,810

1,9602,130

02376115 Elevenmile Creek near 

Pensacola, FL

28.5 32.6 20 2,420

2,620

4,9305,550

7,2207,440

10,90010,100

14,40012,400

18,40014,800

23,20017,700

30,70021,800

02473047 Gordon Creek at Hattiesburg, 

MS

8.83 59.5 38 2,970

2,845

4,0003,850

4,7004,540

5,6005,410

6,2806,060

6,9706,740

7,6807,420

8,6408,380
12 Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007 

a weighting matrix so that sites are weighted proportionally 

according to standard errors and cross-correlation of the 

annual peak-flow estimates. Equations resulting from these 

analyses can be used to estimate flood magnitudes at ungaged 

sites. Basin characteristics were calculated in 2008 for each 

gaging station using geographic information system (GIS) 

coverages and distance and area measurement tools included 

in the Terrain Navigator ProTM Version 8.5 software package. 

The following basin characteristics were tested for significance in the GLS regression analysis:

• contributing drainage area (A), in square miles, 

upstream from the gaging station;

• main channel slope (S), in feet per mile, between points 

10 and 85 percent of the distance from the gaging station to the basin divide;

• main channel length (L), in miles, between the gaging 

station and the basin divide;

• lag-time factor (T), defined by the ratio L/S0.5 with L

and S as defined above;

• impervious area (IA), in percent, percentage of the 

total contributing drainage area covered by impervious 

surfaces;

• percent developed (PD), in percent, percentage of the 

total contributing drainage area covered by any form of 

development; and

• width-to-length ratio (W/L), dimensionless, the average 

basin width to basin length. The average basin width 

(W) is the drainage area (A) divided by the main channel length (L). This ratio is essentially a basin shape 

factor. 

Exploratory multiple regression analyses were performed 

relating the station frequency curves to basin characteristics 

using OLS regression techniques. Results of the analyses 

indicated that contributing drainage area, main channel slope, 

impervious area, and percent developed were the four explanatory variables having the greatest statistical significance 

in relation to peak flows predicted at the streamgaging 

stations. Each of these basin characteristics was used in GLS 

regression analyses. 

Initial GLS regression analyses were performed for all of 

the gaging stations included in the study, and multiple combinations of the four explanatory variables previously listed 

were used. Four different regression scenarios were explored: 

(1) drainage area and impervious area, (2) drainage area and 

percent developed, (3) scenario 1 plus main channel slope, 

and (4) scenario 2 plus main channel slope. These regressions 

were used in the development of statewide urban regression 

equations. Statewide urban regression equations that included 

drainage area and percent developed as the explanatory 

variables had standard errors of prediction that were lower 

than any of the standard errors produced from equations that 

included the other combinations of variables. Consequently, 

the statewide regression equations that included drainage 

area and percent developed as the explanatory variables were 

used as the final predictive equations for estimating urban 

peak flows. Analyses of these variables indicate a fairly 

constant influence of the drainage area term (exponent/slope 

not changing significantly) with increasing flood magnitude, 

while the percent developed term has decreasing influence 

with increasing flood magnitude (exponent/slope decreases 

significantly). The decrease of significance of the percent 

development at the higher flood magnitudes is expected as 

soils become saturated and runoff becomes more similar to 

that occurring in rural basins. The urban regression equations 

are summarized in table 3. 

Table 3. Regional flood-frequency relations for 

urban streams in Alabama.

[Note: Associated mean standard errors of estimate, mean 

standard errors of prediction, and mean variance of prediction 

are listed in table 4. Q, flood flow, in cubic feet per second; A, 

contributing drainage area, in square miles; PD, percentage of 

basin developed]

Exceedance 

probability

(percent)

Urban regression 

equations

50 Q = 95 A 0.648PD 0.407

20 Q = 226 A 0.670PD 0.298

10 Q = 306 A 0.675PD 0.276

4 Q = 417 A 0.670PD 0.253

2 Q = 513 A 0.663PD 0.237

1 Q = 618 A 0.656PD 0.223

0.5 Q = 733 A 0.650PD 0.210

0.2 Q = 897 A 0.642PD 0.196

Accuracy and Limitations of 

Flood-Frequency Estimates

The accuracy of a flood-frequency relation traditionally 

has been expressed in two ways—the mean standard error of 

estimate (SEE) or as mean standard error of prediction (SEP). 

The SEE is a measure of how well the regression equation fits 

the data used to derive the relation and is often referred to 

as the model error. The SEE is the standard deviation of the 

differences between station data and the corresponding values 

computed from the regression equation. The SEE ranged from 

a minimum of 17 percent (10-percent exceedance flood) to 

a maximum of 31 percent (0.2-percent exceedance flood; 

table 4). The SEP is a measure of how well the regression 

relation estimates flood magnitudes when applied to ungaged 

basins. The SEp is the square root of the mean square error 

of prediction, MSEp. The MSEp is the sum of two components—the mean square error resulting from the model and 
Urban Flood-Frequency Analysis 13

the sampling mean square error, which results 

from estimating the model parameters from 

samples of the population. The SEp ranged from 

a minimum of 21 percent (20- and 10-percent 

exceedance floods) to a maximum of 38 percent 

(0.2-percent exceedance flood). Another 

measure of the uncertainty in a regression 

equation estimate for a site is the variance of 

prediction, Vp. The Vp is the sum of the model 

error variance and sampling error variance. 

The mean variance of prediction, MVP, can be 

computed for n number of stations to determine 

the average accuracy of prediction, assuming 

that the explanatory variables for the gaging 

stations in a regression analysis are representative of all stations in the region. The SEE , SEp , 

and MVP for the regression relations are listed 

in table 4.

The regression relations are applicable for 

ungaged urban basins having drainage areas 

ranging from 1 to 43 mi2

 and basin development ranging from 20 to 100 percent. The 

equations should not be used for basins having 

less than 20-percent development or where 

dams, flood-detention structures, hurricane 

storm surge, or substantial tidal fluctuations 

have a significant effect on peak flows. Sites in 

basins having less than 20-percent development 

should be considered as rural sites. The user 

is cautioned not to use the urban equations for 

streams located in flood region 3 (fig. 9). Flood 

region 3 has impervious chalk and marl, which 

produce high flood runoff. No stations in flood 

region 3 were used to develop the urban equations; therefore, flood region 3 rural equations 

(Hedgecock and Feaster, 2007) should be used 

for urban sites located in this region.

Use of Flood-Frequency Relations

Regional flood-frequency equations or relations can 

be used to estimate flood magnitudes at ungaged sites or to 

improve estimates at gaged sites. Methods are presented in the 

following section that describe procedures for use in obtaining 

these estimates.

Gaged Sites

Flood estimates at gaged sites for a selected exceedance 

probability can be determined best by weighting the regional 

and station flood estimates for the specified exceedance 

probability using the variance of prediction for each of the 

two estimates. The variance of prediction can be thought of as 

a measure of the uncertainty in either the gaging-station flow 

estimate or the regional regression results. If the two estimates 

Table 4. Accuracy of regional flood-frequency relations 

for urban streams in Alabama.

Exceedance 

probability 

(percent)

Mean 

standard 

error of 

estimate 

(percent)

Mean 

standard 

error of 

prediction 

(percent)

Mean 

variance of 

prediction 

(log units)

50 22 26 0.0120

20 18 21 0.0085

10 17 21 0.0082

4 19 24 0.0102

2 21 26 0.0128

1 24 30 0.0160

0.5 27 33 0.0197

0.2 31 38 0.0254

Figure 9. Locations of the four flood regions in Alabama.

0 50 MILES

0 50 KILOMETERS

Base from U.S. Geological Survey digital data,

1:100,000, Universal Transverse Mercator Projection, 

Zone 16.

35

34

33

32

31

88 87 86 85

LAUDERDALE

LAWRENCE

MARION WINSTON

LAMAR FAYETTE WALKER

CULLMAN

BLOUNT

ETOWAH

CHEROKEE

ST. CLAIR CALHOUN

JEFFERSON

TUSCALOOSA

PICKENS SHELBY CLAY

COOSA

CHILTON

BIBB

HALE

PERRY

DALLAS

AUTAUGA

LOWNDES MONTGOMERY

BUTLER

ELMORE

LEE

RUSSELL

BARBOUR

HENRY

DALE

COFFEE

GENEVA COVINGTON

ESCAMBIA

CONECUH

MONROE

WILCOX

CLARKE

CHOCTAW

WASHINGTON

MOBILE

BALDWIN

HOUSTON

PIKE

CRENSHAW

MACON

BULLOCK

MARENGO

GREENE

SUMTER

TALLAPOOSA

RANDOLPH

CHAMBERS

TALLADEGA

CLEBURNE

COLBERT

FRANKLIN

LIMESTONE

MADISON JACKSON

MORGAN MARSHALL DEKALB

MISSISSIPPI

GEORGIA

FLORIDA

TENNESSEE

Gulf of Mexico

REGION 1

REGION 2

REGION 3

REGION 4
14 Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007 

can be assumed to be independent and are weighted in inverse 

proportion to the associated variances, the variance of the 

weighted estimate will be less than the variance of either of 

the independent estimates. 

The variance of prediction corresponding to the gagingstation flow estimate from the log-Pearson Type III analysis 

is computed using the asymptotic formula given in Cohn and 

others (2001) with the addition of the mean-squared error of 

generalized skew (Griffis and others, 2004). This variance 

varies as a function of the length of record and the fitted 

log-Pearson Type III distribution parameters (mean, standard 

deviation, and station skew). The variance of prediction values 

for the gaging-station flow estimates for the 23 gaging stations 

used in urban regression analyses are shown in table 5. The 

variance of prediction from the regression equations is a 

function of the regression equations and the values of the independent variables used to develop the flow estimate from the 

regression equations. Once the variances have been computed, 

the two independent flow estimates can be weighted using the 

following equation: 

where

QP(g)w is the weighted estimate of peak flow for any 

P-percent chance exceedance for a gaged 

station, in cubic feet per second;

	 Vp,P(g)r is the variance of prediction at the gaged 

station derived from the regression 

equation for the selected P-percent chance 

exceedance (from table 4), in log units;

	 QP(g)s is the estimate of peak flow at the gaged 

station from the log-Pearson Type III 

analysis for the selected P-percent chance 

exceedance, in cubic feet per second;

	 Vp,P(g)s is the variance of prediction at the gaged 

station from the log-Pearson Type III 

analysis for the selected P-percent chance 

exceedance (from table 5), in log units; and 

	 QP(g)r is the peak-flow estimate for the P-percent 

chance exceedance at the gaged station 

derived from the applicable regression 

equation (from table 3), in cubic feet 

per second.

When the variance of prediction corresponding to one 

of the estimates is high, the uncertainty also is high, so the 

weight for that estimate is relatively small. Conversely, when 

the variance of prediction is low, the uncertainty also is low, so 

the weight is correspondingly large. The variance of prediction 

associated with the weighted estimate, V

p, P(g)w , is computed 

using the following equation:

, ( ) , ( )

, ( ) , ( ) , ( )

, p P g s p P g r

p P g w

p P g s p P g r

V V

V

V V = +

where variables are as previously defined.

Flood magnitudes obtained from station frequency 

curves were weighted using equation 2 and the variance of 

prediction values from tables 4 and 5. The weighted values 

(best estimate) shown in table 2 for each of the 23 stations are 

for design purposes at gaged sites. The variance of prediction 

values associated with the weighted estimates are shown in 

table 5. 

Comparison of Results with Previous Alabama 

Study Results

Equations were developed for urban streams in Alabama 

(Olin and Bingham, 1982) using multiple regression analyses 

of flood magnitudes obtained from synthetic flow data 

generated with a calibrated rainfall-runoff model and basin 

characteristics for 23 urban gaging stations. The regression 

analyses indicated that drainage area size and percentage of 

the basin occupied by impervious materials were the most 

significant basin characteristics affecting flood frequency and 

magnitude of urban streams.

The results of this study indicate that a different combination of two explanatory variables best correlate to flood peaks 

that occur on urban streams today. Drainage area and percent 

developed provided the best correlation for the data used in 

the analysis. Both the 1982 and 2009 equations were applied 

to the current dataset (drainage area and associated impervious 

area or percent developed) used for this study. Results indicate 

that the 2009 equations predict higher peak flows than the 

1982 equations for 21 out of 23 stations (1-percent exceedance flow). For these 21 stations, the average increase in the 

predicted peak flow was about 18 percent. For the two stations 

having a lower predicted peak flow, the average reduction of 

flow was about 3 percent (1-percent exceedance flow). 

A second comparison was made for hypothetical sites 

having drainage areas of 1, 5, 10, 25, and 40 mi2

. For each 

of these drainage areas, values of 20-, 40-, 60-, 80-, and 

99-percent developed were applied to both the 1982 and 2009 

equations. Because the explanatory variables are not the same, 

a direct comparison could not be made. Regression techniques 

were used to relate impervious area to percent developed using 

the current dataset. Results of these regressions indicate that 

percent developed correlates to about 3.75 times the computed 

impervious area. Using this factor, an approximate comparison 

was made between the 1982 and 2009 equations. 

Experimentation with the 1982 and 2009 urban equations 

has generally shown that higher peak flows are predicted 

by the 2009 equations for sites having drainage areas less 

than 25 mi2

 and impervious areas less than 25 percent 

(94-percent developed). This was true for the 50-percent to 

, ( ) ( ) , ( ) ( )

( ) , ( ) , ( )

log log log , p P g r P g s p P g s P g r

P g w

p P g s p P g r

V Q V Q Q V V+ = +

(2)

(3)
Urban Flood-Frequency Analysis

15

Table 5. Variance of prediction values for urban streamgaging stations used in Alabama urban regression analyses.[USGS, U.S. Geological Survey; G, computed from the Bulletin 17B analysis of the streamgaging station; W, weighted using equation 3]

USGS

station

number

Variance of prediction, in log units

50-percent chance 

exceedance

20-percent chance 

exceedance

10-percent chance 

exceedance

4-percent chance 

exceedance

2-percent chance

 exceedance

1-percent chance 

exceedance

0.5-percent chance 

exceedance

0.2-percent chance 

exceedance

G W G W G W G W G W G W G W G W

02423130 0.0038 0.0022 0.0048 0.0020 0.0070 0.0024 0.0126 0.0034 0.0191 0.0042 0.0277 0.0056 0.0384 0.0069 0.0561 0.0092

02423397 0.0040 0.0019 0.0063 0.0023 0.0119 0.0027 0.0319 0.0040 0.0600 0.0049 0.1010 0.0066 0.1562 0.0080 0.2527 0.0106

02423400 0.0060 0.0028 0.0080 0.0025 0.0122 0.0027 0.0228 0.0038 0.0352 0.0046 0.0515 0.0062 0.0720 0.0076 0.1058 0.0100

02455980 0.0087 0.0033 0.0078 0.0024 0.0092 0.0026 0.0152 0.0035 0.0232 0.0044 0.0481 0.0062 0.0488 0.0072 0.0726 0.0096

02471065 0.0040 0.0023 0.0034 0.0017 0.0038 0.0018 0.0064 0.0027 0.0101 0.0035 0.0152 0.0048 0.0217 0.0061 0.0325 0.0082

02471078 0.0160 0.0040 0.0189 0.0030 0.0264 0.0031 0.0456 0.0042 0.0682 0.0050 0.0983 0.0066 0.1360 0.0080 0.1980 0.0105

02480002 0.0101 0.0035 0.0105 0.0026 0.0133 0.0028 0.0219 0.0038 0.0325 0.0046 0.0470 0.0061 0.0653 0.0075 0.0957 0.0099

0357526200 0.0135 0.0038 0.0117 0.0027 0.0136 0.0028 0.0226 0.0038 0.0350 0.0046 0.0523 0.0062 0.0745 0.0076 0.1113 0.0101

0357568650 0.0108 0.0036 0.0133 0.0028 0.0190 0.0030 0.0335 0.0040 0.0503 0.0048 0.0726 0.0064 0.1005 0.0078 0.1464 0.0103

0357568980 0.0091 0.0034 0.0107 0.0027 0.0148 0.0029 0.0255 0.0039 0.0381 0.0047 0.0549 0.0063 0.0759 0.0076 0.1105 0.0100

03575700 0.0040 0.0023 0.0043 0.0019 0.0056 0.0022 0.0093 0.0031 0.0139 0.0039 0.0200 0.0052 0.0277 0.0065 0.0405 0.0087

0357586650 0.0148 0.0039 0.0163 0.0029 0.0216 0.0030 0.0362 0.0041 0.0537 0.0049 0.0771 0.0065 0.1068 0.0078 0.1557 0.0103

0357587090 0.0039 0.0022 0.0042 0.0019 0.0056 0.0022 0.0094 0.0031 0.0135 0.0038 0.0194 0.0052 0.0269 0.0064 0.0392 0.0086

0357587400 0.0059 0.0028 0.0051 0.0021 0.0058 0.0022 0.0097 0.0031 0.0151 0.0040 0.0227 0.0054 0.0324 0.0067 0.0484 0.0090

0357587728 0.0047 0.0025 0.0145 0.0028 0.0175 0.0029 0.055 0.0042 0.1304 0.0051 0.2615 0.0069 0.4576 0.0083 0.8283 0.0109

03575890 0.0015 0.0012 0.0016 0.0011 0.0020 0.0013 0.0034 0.0019 0.0050 0.0026 0.0072 0.0036 0.0101 0.0046 0.0148 0.0063

0357591500 0.0023 0.0016 0.0035 0.0017 0.0061 0.0022 0.0133 0.0034 0.0223 0.0043 0.0346 0.0059 0.0504 0.0072 0.0770 0.0097

03575933 0.0056 0.0027 0.0102 0.0026 0.0166 0.0029 0.0516 0.0042 0.1090 0.0051 0.1994 0.0068 0.3272 0.0083 0.5591 0.0108

03575950 0.0037 0.0022 0.0053 0.0021 0.0088 0.0025 0.0176 0.0036 0.0281 0.0045 0.0421 0.0060 0.0599 0.0074 0.0895 0.0098

03575980 0.0014 0.0011 0.0022 0.0014 0.0041 0.0019 0.0094 0.0031 0.0161 0.0040 0.0275 0.0056 0.0376 0.0069 0.0583 0.0093

02341544 0.0015 0.0012 0.0017 0.0012 0.0023 0.0014 0.0039 0.0021 0.0058 0.0028 0.0083 0.0038 0.0115 0.0049 0.0168 0.0067

02376115 0.0076 0.0031 0.0095 0.0026 0.0138 0.0028 0.0245 0.0039 0.0370 0.0047 0.0535 0.0062 0.0742 0.0076 0.1082 0.0100

02473047 0.0007 0.0006 0.0009 0.0007 0.0013 0.0009 0.0046 0.0015 0.0035 0.0021 0.0050 0.0029 0.0069 0.0038 0.0101 0.0053
16 Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007 

1-percent exceedance probabilities. For larger sites (up to 

43 mi2) that have impervious areas greater than 25 percent 

(94-percent developed), the 1982 equations typically predict 

slightly higher flows (for 50-percent to 1-percent exceedance 

probabilities). 

Summary

Flood flows for selected exceedance probabilities of 

50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent were determined for 

20 streamgaging stations on urban streams in Alabama using 

the log-Pearson Type III frequency distribution. The data for 

these sites in Alabama and three additional stations in parts of 

the adjacent States of Florida, Georgia, and Mississippi were 

used to develop flood-frequency relations that can be used to 

estimate flood flows for exceedance probabilities of 50, 20, 10, 

4, 2, 1, 0.5, and 0.2 percent for ungaged, unregulated urban 

streams in Alabama. 

Multiple-regression techniques were used to develop 

predictive equations relating peak flow to one or more 

drainage-basin characteristics. Contributing drainage area, 

main channel slope, impervious area, and percent developed 

were the four explanatory variables having the greatest 

statistical significance in relation to peak flows predicted at the 

streamflow-gaging stations. Each of these basin characteristics 

was used in generalized least squares regression analyses. 

Drainage area and percent developed were determined to be 

the most significant variables for use in predicting flood flows 

for urban streams in Alabama. Generalized least-squares 

regression methods were used to define the final regression 

coefficients used in the predictive equations and the model and 

prediction errors. 

The flood-frequency relations can be applied to streams 

in Alabama whose flood-peak flows are not significantly 

affected by dams, flood detention structures, hurricane storm 

surge, or substantial tidal fluctuations. These regression 

relations are applicable for ungaged urban basins having drainage areas ranging from 1 to 43 mi2

 and basin development 

ranging from 20 to 100 percent. Methods are presented in the 

report for determining flood flows for selected exceedance 

probabilities on ungaged and gaged streams. 

References 

Atkins, J.B., 1996, Magnitude and frequency of floods in Alabama: U.S. Geological Survey Water-Resources Investigations Report 95–4199, 234 p.

Barnes, H.H., Jr., and Golden, H.G., 1966, Magnitude and 

frequency of floods in the United States, Part 2–B, South 

Atlantic slope and eastern Gulf of Mexico basins, Ogeechee 

River to Pearl River: U.S. Geological Survey Water-Supply 

Paper 1674, 409 p.

Cohn, T.A., Lane, W.L., and Stedinger, J.R., 2001, Confidence 

intervals for Expected Moments Algorithm flood quantile 

estimates: Water Resources Research, v. 37, no. 6, 

p. 1695–1706.

Fulford, J.M., 1998, User’s guide to the U.S. Geological 

Survey Culvert Analysis Program, version 97–08: 

U.S. Geological Survey Water-Resources Investigations 

Report 98–4166, 68 p.

Gamble, C.R., 1965, Magnitude and frequency of floods 

in Alabama: Alabama Highway Department HPR Report 

No. 5, 42 p.

Gotvald, A.J., Feaster, T.D., and Weaver, J.C., 2009, Magnitude and frequency of rural floods in the southeastern 

United States, 2006—Volume 1, Georgia: U.S. Geological 

Survey Scientific Investigations Report 2009–5043, 120 p.

Griffis, V.W., Stedinger, J.R., and Cohn, T.A., 2004, Log 

Pearson type 3 quantile estimators with regional skew 

information and low outlier adjustments: Water Resources 

Research, v. 40, W07503, doi:10.1029/2003WR002697.

Hains, C.F., 1973, Floods in Alabama, magnitude and frequency: Alabama Highway Department Special Report, 

174 p.

Hedgecock, T.S., 2004, Magnitude and frequency of floods 

on small rural streams in Alabama: U.S. Geological Survey 

Scientific Investigations Report 2004–5135, 10 p.

Hedgecock, T.S., and Feaster, T.D., 2007, Magnitude and frequency of floods in Alabama, 2003: U.S. Geological Survey 

Scientific Investigations Report 2007–5204, 28 p., + app.

Interagency Advisory Committee on Water Data, 1982, Guidelines for determining flood-flow frequency: Bulletin 17B, 

183 p.

National Oceanic and Atmospheric Administration, 2002, 

Monthly station normals of temperature, precipitation, and 

heating and cooling degree days 1971–2000: National Environmental Satellite, Data, and Information Service; National 

Climatic Data Center, Climatography of the United States 

No. 81, 26 p. (available online at http://nsstc.uah.edu/aosc/

files/ALnorm.pdf).

Olin, D.A., 1985, Magnitude and frequency of floods in Alabama: U.S. Geological Survey Water-Resources Investigations Report 84–4191, 105 p., 1 pl.

Olin, D.A., and Bingham, R.H., 1977, Flood frequency of 

small streams in Alabama: Alabama Highway Department, 

HPR Report No. 83, 44 p.

Olin, D.A., and Bingham, R.H., 1982, Synthesized flood frequency of urban streams in Alabama: U.S. Geological Survey Water-Resources Investigations Report 82–683, 35 p.
References 17

Pierce, L.B., 1954, Floods in Alabama, magnitude and frequency: U.S. Geological Survey Circular 342, 105 p.

Sauer, V.B., Thomas, W.O., Stricker, V.A., and Wilson, K.V., 

1983, Flood characteristics of urban watersheds in the 

United States: U.S. Geological Survey Water-Supply 

Paper 2207, 63 p.

Shearman, J.O., 1990, User’s manual for WSPRO—A 

computer model for water surface profile computation: 

U.S. Department of Transportation, no. FHWA-IP-89-027, 

177 p.

Speer, P.R., and Gamble, C.R., 1964, Magnitude and frequency of floods in the United States, Part 3–B, Cumberland and Tennessee River basins: U.S. Geological Survey 

Water-Supply Paper 1676, 340 p.

Stedinger, J.R., and Tasker, G.D., 1985, Regional hydrologic 

analysis 1. Ordinary, weighted and generalized least squares 

compared: Water Resources Research, v. 21, no. 9, 

p. 1421–1432.

Stedinger, J.R., and Tasker, G.D., 1986, Correction to 

“Regional hydrologic analysis 1. Ordinary, weighted and 

generalized least squares compared”: Water Resources 

Research, v. 22, no. 5, p. 844.

U.S. Geological Survey, 1986, National water summary 

1985—Hydrologic events and surface-water resources: 

U.S. Geological Survey Water-Supply Paper 2300, 506 p.

Printed on recycled paper

Hedgecock and Lee—Magnitude and Frequency of Floods for Urban Streams in Alabama, 2007—Scientific Investigations Report 2010–5012