Prepared in cooperation with the Alabama Department of Transportation

Clear-Water Contraction Scour at Selected Bridge

Sites in the Black Prairie Belt of the Coastal Plain

in Alabama, 2006

Scientific Investigations Report 2007–5260

Clear-Water Contraction Scour at Selected 

Bridge Sites in the Black Prairie Belt of the 

Coastal Plain in Alabama, 2006

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

Prepared in cooperation with the Alabama Department of Transportation

Scientific Investigations Report 2007–5260

U.S. Department of the Interior

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

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

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

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Suggested citation:

Lee, K.G., and Hedgecock, T.S., 2008, Clear-water contraction scour at selected bridge sites in the Black Prairie Belt of 

the Coastal Plain in Alabama, 2006: U.S. Geological Survey Scientific Investigations Report 2007–5260, 56 p.

(available online at http://pubs.water.usgs.gov/sir2007-5260).
iii

Contents

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

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

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

Acknowledgments................................................................................................................................2

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

Previous Investigations........................................................................................................................5

Theoretical Bridge Scour.............................................................................................................................6

Contraction Scour.................................................................................................................................6

Theoretical Live-Bed Contraction Scour.................................................................................6

Theoretical Clear-Water Contraction Scour...........................................................................8

Pier Scour...............................................................................................................................................9

Site Selection..................................................................................................................................................9

Data Assumptions........................................................................................................................................11

Justification for the Assumption of Clear-Water Scour...............................................................11

Justification for the Assumption of Large Flood Flows ................................................................12

Historical Floods.........................................................................................................................12

Flood of 1929 ......................................................................................................................15

Floods of 1951 ....................................................................................................................15

Flood of 1955 ......................................................................................................................15

Floods of 1961 ....................................................................................................................15

Floods of 1964 ....................................................................................................................18

Floods of 1979 ....................................................................................................................18

Floods of 1990 ....................................................................................................................21

Risk Analysis...............................................................................................................................23

Justification for the Assumption of Equilibrium-Scour Conditions ............................................24

Approach.......................................................................................................................................................25

Estimation of Hydrologic Data ..........................................................................................................26

Estimation of Hydraulic Data ............................................................................................................26

Measurement of Actual Scour Depths ...........................................................................................27

Computation of Theoretical Scour Depths .....................................................................................28

Comparison of Actual and Theoretical Scour Depths..................................................................28

Variables Influencing Clear-Water Contraction Scour..........................................................................29

Median Grain Size...............................................................................................................................29

Velocity Variables ...............................................................................................................................30

Channel-Contraction Ratio................................................................................................................35

Hydraulic Ratios..................................................................................................................................37

Contraction Ratios ..............................................................................................................................39

Depth Variables...................................................................................................................................40

Other Variables....................................................................................................................................40

Development of the Alabama Clear-Water Contraction Scour Envelope Curves.............................43

Application of the Alabama Contraction-Scour Envelope Curves ......................................................43

Summary........................................................................................................................................................46

References Cited..........................................................................................................................................46
iv

Appendix A. Alabama bridge-scour study sites and reference numbers for figure 7..................49

Appendix B. Photographs of selected Alabama bridge-scour study sites.....................................51

Figures

1. Map showing location of physiographic provinces in Alabama ..........................................3

2. Map showing location of study area and major rivers in Alabama .....................................4

3. Graph showing frequency of streambed slopes for the 25 selected bridge sites 

in the bridge-scour database in the Black Prairie Belt of Alabama ....................................5

4. Graph showing frequency of drainage area for the 25 selected bridge sites 

in the bridge-scour database in the Black Prairie Belt of Alabama ....................................5

5. Sketch showing schematic diagram of a contracted reach.................................................7

6. Sketch showing typical bridge cross section for a well-defined channel 

and relief bridge showing areas of clear-water scour...........................................................8

7. Map showing location of study area and bridge-scour study sites in Alabama. ............10

8. Graph showing frequency of clear-water contraction-scour depths for the 

37 scour data points in the bridge-scour database in the Black Prairie Belt 

of Alabama...................................................................................................................................11

9. Map showing maximum recurrence interval of streamflow-gaging stations 

located in the study area in Alabama......................................................................................14

10. Map showing areal extent of major floods—March 1929, February–March 1961, 

March–April 1973, and March–April 1979—in Alabama .....................................................15

11. Map showing significant floods affecting streamflow gaging stations located 

in the study area in Alabama ....................................................................................................16

12. Isohyetal map of the Southeastern States showing storm rainfall, 

February 17–26, 1961 ..................................................................................................................17

13. Isohyetal map of the Southeastern States showing storm rainfall, 

February 23–26, 1961 ..................................................................................................................17

14. Map of flood area; location of flood-determination points and isohyets 

for April 6–8, 1964, floods in Alabama .....................................................................................19

15. Isohyetal map of the Southeastern States showing storm rainfall, 

April 11–14, 1979..........................................................................................................................20

16. Map showing areas affected by heavy rainfall—Alabama, Georgia, 

and Florida—in February and March 1990.............................................................................21

17. Map showing location of lines of equal recurrence intervals for February 1990 peak 

discharges for unregulated and unurbanized streams in Alabama and Georgia............22

18. Map showing location of lines of equal recurrence intervals for March 1990 peak 

discharges for unregulated and unurbanized streams in Alabama, Georgia, 

and Florida ...................................................................................................................................23

19. Graph showing frequency of bridge ages and the probability of occurrence 

for the 50-year recurrence interval flood for the bridge-scour database 

in the Black Prairie Belt of Alabama .......................................................................................24

20. Sketch showing schematic diagram of cross-section locations used in the 

Water-Surface Profile (WSPRO) model ..................................................................................27

21. Graph of relation of observed clear-water contraction-scour depth and 

theoretical clear-water contraction-scour depth for the 50-year flood............................28

22. Graph showing relation of observed clear-water contraction-scour depths 

to the median grain size at selected sites in the Black Prairie Belt of the 

Coastal Plain of Alabama ..........................................................................................................31
v

23. Graph showing relation of observed clear-water contraction-scour depths 

to the bridge velocity at selected sites in the Black Prairie Belt of the 

Coastal Plain of Alabama ..........................................................................................................32

24. Definition sketch of variables used to compute (A) velocity index and (B) channel 

contraction ratio, eccentricity, and flow index for a single bridge opening.....................33

25. Definition sketch of variables used to compute (A) velocity index and (B) channel 

contraction ratio, eccentricity, and flow index for a multiple bridge opening .................34

26. Graph showing relation of observed clear-water contraction-scour depths 

to the average approach velocity at selected sites in the Black Prairie Belt 

of the Coastal Plain of Alabama ...............................................................................................35

27. Graph showing relation of observed clear-water contraction-scour depths 

to the velocity index at selected sites in the Black Prairie Belt of the 

Coastal Plain of Alabama ..........................................................................................................36

28. Graph showing relation of observed clear-water contraction-scour depths 

to the channel-contraction ratio at selected sites in the Black Prairie Belt 

of the Coastal Plain of Alabama ...............................................................................................36

29. Graph showing relation of observed clear-water contraction-scour depths 

to the width-to-depth ratio at selected sites in the Black Prairie Belt of the 

Coastal Plain of Alabama ..........................................................................................................37

30. Graph showing relation of observed clear-water contraction-scour depths 

to the conveyance-to-depth ratio at selected sites in the Black Prairie Belt 

of the Coastal Plain of Alabama ...............................................................................................37

31. Graph showing relation of observed clear-water contraction-scour depths 

to eccentricity at selected sites in the Black Prairie Belt of the Coastal Plain 

of Alabama...................................................................................................................................38

32. Graph showing relation of observed clear-water contraction-scour depths 

to the flow index at selected sites in the Black Prairie Belt of the Coastal Plain 

of Alabama...................................................................................................................................38

33. Graph showing relation of observed clear-water contraction-scour depths 

to the geometric-contraction ratio of widths at selected sites in the 

Black Prairie Belt of the Coastal Plain of Alabama...............................................................39

34. Graph showing relation of observed clear-water contraction-scour depths 

to the geometric-contraction ratio of areas at selected sites in the 

Black Prairie Belt of the Coastal Plain of Alabama...............................................................39

35. Graph showing relation of observed clear-water contraction-scour depths 

to the geometric-contraction ratio of conveyance at selected sites in the 

Black Prairie Belt of the Coastal Plain of Alabama...............................................................40

36. Graph showing relation of observed clear-water contraction-scour depths 

to the average depth in the bridge opening at selected sites in the 

Black Prairie Belt of the Coastal Plain of Alabama...............................................................41

37. Graph showing relation of observed clear-water contraction-scour depths 

to the average depth in the approach section at selected sites in the 

Black Prairie Belt of the Coastal Plain of Alabama...............................................................41

38. Graph showing relation of observed clear-water contraction-scour depths 

to the Froude number at selected sites in the Black Prairie Belt of the 

Coastal Plain of Alabama ..........................................................................................................41

39. Graph showing relation of observed clear-water contraction-scour depths 

to submergence at selected sites in the Black Prairie Belt of the Coastal Plain 

of Alabama...................................................................................................................................42

40. Graph showing relation of observed clear-water contraction-scour depths to 

head at selected sites in the Black Prairie Belt of the Coastal Plain of Alabama...........42
vi

41. Graph showing relation of observed clear-water contraction-scour depths to 

backwater at selected sites in the Black Prairie Belt of the Coastal Plain 

of Alabama...................................................................................................................................42

42. Graph showing envelope curve of observed clear-water contraction-scour 

depths based on the velocity index at selected sites in the Black Prairie Belt 

of the Coastal Plain of Alabama ...............................................................................................44

43. Graph showing envelope curve of observed clear-water contraction-scour 

depths based on the channel-contraction ratio at selected sites in the 

Black Prairie Belt of the Coastal Plain of Alabama...............................................................45

Tables

1. Approximate recurrence interval for selected flood years at selected 

streamflow-gaging stations in the study area in Alabama..................................................13

2–5. Peak discharges, dates, and approximate recurrence intervals for selected 

streamflow-gaging stations in the study area in Alabama for the:

2. 1961 Floods .........................................................................................................................18

3. 1964 Floods .........................................................................................................................19

4. 1979 Floods .........................................................................................................................20

5. 1990 Floods .........................................................................................................................22

6. Percent risk for the occurrence of the 50-year recurrence-interval flow 

for selected bridge ages............................................................................................................23

7. Comparison of the effect that median grain size has on clear-water 

contraction scour .......................................................................................................................30
vii

Conversion Factors and Datums

Multiply By To obtain

Length

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square foot (ft2

) 0.0929 square meter (m2)

square mile (mi2

) 2.590 square kilometer (km2) 

Flow rate

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

cubic foot per second (ft3

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

cubic foot per second per square 

mile [(ft3

/s)/mi2]

 0.01093 cubic meter per second per 

square kilometer [(m3/s)/km2]

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.

Abbreviations and Acronyms:

 ALDOT Alabama Department of Transportation

 EFA Erosion Function Apparatus

 FHWA Federal Highway Administration

 ft/ft foot per foot

 HEC-18 Hydraulic Engineering Circular-18

 mm millimeter

 N/m2 Newton per square meter

 SAS Statistical Analysis System

 STATSGO State Soil Geographic database

 USGS U.S. Geological Survey

 WSPRO Water-Surface Profile

 < less than

 ≤	 	 less than or equal to

	 	 >	 	 greater than

	 	 ≥	 	 greater than or equal to

Abstract

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

Alabama Department of Transportation, made observations of 

clear-water contraction scour at 25 bridge sites in the Black 

Prairie Belt of the Coastal Plain of Alabama. These bridge 

sites consisted of 54 hydraulic structures, of which 37 have 

measurable scour holes. Observed scour depths ranged from 

1.4 to 10.4 feet. Theoretical clear-water contraction-scour 

depths were computed for each bridge and compared with 

observed scour. This comparison showed that theoretical 

scour depths, in general, exceeded the observed scour depths 

by about 475 percent. Variables determined to be important 

in developing scour in laboratory studies along with several 

other hydraulic variables were investigated to understand 

their influence within the Alabama field data. The strongest 

explanatory variables for clear-water contraction scour were 

channel-contraction ratio and velocity index. Envelope curves 

were developed relating both of these explanatory variables to 

observed scour. These envelope curves provide useful tools for 

assessing reasonable ranges of scour depth in the Black Prairie 

Belt of Alabama.

Introduction 

During 2005, the Nation’s roads experienced an all-time 

high in vehicle miles traveled. The U.S. Department of 

Transportation, Federal Highway Administration (FHWA) 

documented 3 trillion vehicle miles of travel. A vital part 

of the road system is safe and functional bridges. Statistics 

show that 28 percent of the Nation’s highways are considered 

deficient (Road Information Program, 2002). 

Safety of the Nation’s bridges became a major concern in 

the late 1960s when the structural failure of the Silver Bridge, 

connecting U.S. Highway 35 over the Ohio River, fatally 

injured 46 people (National Transportation Safety Board, 

1971). Following this event, an amendment was added to the 

Federal Highway Act of 1968 that required the establishment 

of the National Bridge Inspection Program. This program 

was later expanded to investigate failure due to scour after 

the collapse of two major bridges occurred during 1987 and 

1989. The failure of the Schoharie Creek Bridge in New York 

State and the Hatchie River Bridge in Tennessee claimed 18 

lives (National Transportation Safety Board, 1988; 1990). On 

recommendation of the National Transportation Safety Board, 

the FHWA initiated a national program during 1988 to assess 

the susceptibility of existing and future bridges to scour. This 

assessment includes the computation of theoretical scour 

depths, monitoring channel migration, and countermeasures 

to prevent bridge failure due to scour. In earlier years, the 

proper research and analytical tools necessary to compute 

theoretical scour were not available. To address the issue, the 

FHWA published Hydraulic Engineering Circulars (HEC)-18 

and -20 (Richardson and others, 1991; Lagasse and others, 

1991). Hydraulic Engineering Circular-18 provides theoretical 

equations for predicting contraction-scour and local scour 

depths. Each state was mandated to do qualitative (level 1) and 

quantitative (level 2) analyses, using these equations. Since 

1995, there has been a decrease in the percent of deficient 

bridges (Road Information Program, 2002). This decrease 

may be attributed to better inspection policies, technological 

advances in materials, and more stringent design guidelines. 

Forty-eight percent of the Nation’s bridges were built 

during the period from 1950–1980 (Road Information 

Program, 2002). As a result, a large number of existing bridges 

are getting close to the end of their life span. In order to find 

the most cost-effective methods for replacement or repair of 

these bridges, current techniques are being reevaluated for 

more efficient methods. At this time, new bridge construction 

and countermeasures for existing bridges are designed on 

the basis of the theoretical scour equations presented in 

HEC-18. Research has indicated that these equations often 

provide conservative estimates of scour and in some instances 

severely overpredict scour depths (Norman, 1975; Holnbeck 

and others, 1993; Brabets, 1995; Fischer, 1995). Mueller and 

Wagner (2005) provided a comparison of published literature 

and field data. Their findings suggest that the accuracy of the 

contraction-scour equations greatly depends on the degree of 

contraction, flow distribution, configuration of the approach, 

and how well the hydraulic model represents the true flow 

distribution (Mueller and Wagner, 2005). 

Clear-Water Contraction Scour at Selected Bridge Sites 

in the Black Prairie Belt of the Coastal Plain in Alabama, 

2006 

By K.G. Lee and T.S. Hedgecock
2 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Alabama is among many states that have substantial 

roadway construction needs and limited funding. According 

to statistics published during 2005, Alabama’s road system 

accommodated about 59 billion vehicle miles of travel (U.S. 

Department of Transportation Federal Highway Administration, 2006), and the census has projected a steady increase in 

Alabama’s population, which will likely result in greater road 

traffic. With increases in traffic, there is a high demand for 

bridges to be functional and safe. Many of Alabama’s bridges 

are approaching the end of their 50-year expected life span. 

About $50 million is spent annually for repair and replacement 

of bridges in the State of Alabama (Government Performance 

Project, 2005).

To address the concern of economic feasibility of 

new bridge construction and countermeasures for existing 

structures, alternative methods for computing theoretical scour 

depths have been explored in other states. Methods of relating 

hydraulic properties to measured scour depths are outlined 

by Benedict (2003) in Clear-Water Abutment and Contraction Scour in the Coastal Plain and Piedmont Provinces of 

South Carolina, 1996–99. That study and a following study 

(Benedict and Caldwell, 2005) were successful in developing 

correlations that are useful in the assessment of clear-water 

scour.

The U.S. Geological Survey (USGS), in cooperation 

with the Alabama Department of Transportation (ALDOT), 

initiated a study, using a similar approach, to investigate 

alternative methods for computing clear-water contractionscour depths in the cohesive soils located in the Black Prairie 

Belt of the Coastal Plain of Alabama (fig. 1).

Purpose and Scope

This report describes (1) techniques used to collect 

clear-water contraction scour data at 25 bridge sites 

(37 hydraulic structures) in the Black Prairie Belt of the 

Coastal Plain of Alabama, (2) a comparison of theoretical 

clear-water contraction-scour depths with observed scour 

depths, (3) selected relations within the field data, (4) envelope 

curves that may be used to estimate ranges of anticipated 

clear-water contraction scour for bridges in the Black Prairie 

Belt of the Coastal Plain of Alabama, and (5) pier-scour 

observations and insights for bridges in the Black Prairie Belt 

of the Coastal Plain of Alabama.

Acknowledgments

The assistance of Mr. Tom Flournoy, ALDOT Bridge 

Hydraulics Engineer, and Mr. Eric Christy, ALDOT Assistant 

State Maintenance Engineer, is greatly appreciated. The 

Testing Division of the ALDOT Bureau of Materials and Test 

also was instrumental in providing grain-size distribution 

analyses for all of the sites included in this study. Also, special 

thanks are given to Mr. Benjamin Dewit and Miss Britane 

Bell, engineering students at Auburn University, for their 

contributions to this study. 

Description of Study Area

The physiography of Alabama is divided into five 

regions: Coastal Plain, Appalachian Plateaus, Piedmont, 

Valley and Ridge, and Interior Lowland Plateaus (fig. 1). 

The largest physiographic region in Alabama is the Coastal 

Plain. The Coastal Plain covers about 59 percent of the State’s 

51,600 square miles (mi2) of area. This region is subdivided 

into four subregions called districts. Based on previous 

unpublished scour assessments, the Black Prairie Belt district, 

located in the upper half of the Coastal Plain, was determined 

to be the area of greatest concern for accurate bridge-scour 

determinations.

The Black Prairie Belt extends from Russell County, 

Alabama, through east-central Mississippi and thins out north 

of the Tennessee State line. A prairie is defined as a large area 

of undulating valley covered by coarse grasses and minimal 

trees. The Black Prairie Belt is composed of sedimentary soils 

of Cretaceous age. In this area, Selma chalk is overlain with 

rich black soil that is characterized as consolidated and highly 

cohesive clay that contains significant amounts of organic 

matter (Fenneman, 1938). 

The crescent-shaped Black Prairie Belt occupies about 

4,300 mi2 in Alabama, ranging from 35 to 46 miles (mi) in 

width (Rankin, 1974). The Black Prairie Belt extends through 

13 counties in Alabama: Bullock, Dallas, Greene, Hale, 

Lowndes, Macon, Marengo, Montgomery, Perry, Pickens, 

Russell, Sumter, and Wilcox. The major streams in Alabama’s 

portion of the Black Prairie Belt are the Black Warrior, 

Alabama, and Tombigbee Rivers (Fenneman, 1938). The 

Tombigbee River flows southeastward and joins the Black 

Warrior at Demopolis and turns in a southwestward direction 

as it flows through the western portion of the Black Prairie 

Belt. The confluence of the Coosa and Tallapoosa Rivers form 

the Alabama River (fig. 2). The elevation between streams in 

some areas is minimal and provides little topographic relief. 

The Black Prairie Belt is often described as a peneplain, 

indicating relief has been shaped through erosion. The average 

elevation of Alabama’s portion of the Black Prairie Belt is 

225 feet (ft) (U.S. Geological Survey, 2006).

The study area was determined by compiling several 

maps. Depending on the source, date, and detail of the map, 

the extent of the Black Prairie Belt boundary varies. To 

determine the most extensive study area, general soils maps 

were compared with the physiographic provinces. These maps 

were overlain with the State Soil Geographic (STATSGO) 

database. The STATSGO database is a generalization of a 

detailed soil survey that provides a representation of soil 

patterns in a landscape (National Resource Conservation 

Service, 2006). The soil patterns of the Black Prairie Belt 

were selected, and the study area was defined. The resulting 

study area (fig. 2) was determined to be 6,150 mi2 in area and 
Abstract 3

Figure 1. Location of physiographic provinces in Alabama.

LEE

BALDWIN MOBILE

CLARKE

PIKE

BIBB

HALE

DALLAS

CLAY

JACKSON

PERRY

WILCOX

MONROE

DALE

SUMTER

SHELBY

PICKENS

BUTLER

TUSCALOOSA

W JEFFERSON ALKER

COFFEE

COOSA

BARBOUR

DE KALB

MARENGO

CHOCTAW

ESCAMBIA

MARION

COVINGTON

CONECUH

GREENE

CHILTON

LAMAR

HENRY

MADISON

BLOUNT

ELMORE

MACON

WASHINGTON

FAYETTE

CULLMAN

RUSSELL

ST CLAIR

GENEVA

COLBERT

LOWNDES

BULLOCK

TALLADEGA

FRANKLIN LAWRENCE

MORGAN

WINSTON

CALHOUN

ETOWAH

AUTAUGA

TALLAPOOSA

HOUSTON

CHEROKEE

MARSHALL

LAUDERDALE

CLEBURNE

RANDOLPH

MONTGOMERY

CHAMBERS

LIMESTONE

CRENSHAW

89°0'W 88°0'W 87°0'W 86°0'W 85°0'W

30°0'N

31°0'N

32°0'N

33°0'N

34°0'N

35°0'N

0 75 150 KILOMETERS

0 60 120 MILES

EXPLANATION

Black Prairie Belt

Physiographic provinces

Interior Lowland

 Plateaus

Appalachian

 Plateaus

Valley 

 and 

Ridge

Piedmont

Coastal Plain

Fall Line

Modified from Miller, 1990

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA
4 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure 2. Location of study area and major rivers in Alabama.

M o bile River

Alabama River

Tomb igbe e River

Alabama River

Coosa River

Mulberry F ork

Tennessee River

Tom bi gbeeRiver

Demopolis

Black Warrior River

Locust For k

LEE

BALDWIN MOBILE

CLARKE

PIKE

BIBB

HALE

DALLAS

CLAY

JACKSON

PERRY

WILCOX

MONROE

DALE

SUMTER

SHELBY PICKENS

BUTLER

TUSCALOOSA

JEFFERSON

WALKER

COFFEE

COOSA

BARBOUR

DE KALB

MARENGO

CHOCTAW

ESCAMBIA

MARION

COVINGTON

CONECUH

GREENE

CHILTON

LAMAR

HENRY

MADISON

BLOUNT

ELMORE

MACON

WASHINGTON

FAYETTE

CULLMAN

RUSSELL

ST CLAIR

GENEVA

COLBERT

LOWNDES BULLOCK

TALLADEGA

FRANKLIN

LAWRENCE

MORGAN

WINSTON

CALHOUN

ETOWAH

AUTAUGA

TALLAPOOSA

HOUSTON

CHEROKEE

MARSHALL

LAUDERDALE

CLEBURNE

RANDOLPH

MONTGOMERY

CHAMBERS

LIMESTONE

CRENSHAW

York

Epes

Elba

Cuba

Eutaw

Selma Browns

Minter

Linden

Geiger

Tuskegee

Kimbrough

Livingston

Montgomery Lowndesboro

Pickensville

89°0'W 88°0'W 87°0'W 86°0'W 85°0'W

30°0'N

31°0'N

32°0'N

33°0'N

34°0'N

35°0'N

0 75 150 KILOMETERS

0 60 120 MILES

EXPLANATION

Study area

River or shoreline

Towns

Tallapoosa River

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA
Abstract 5

 The bridge sites were visited and the current field 

conditions documented. A detailed summary of each bridge 

included measurement of the existing hydraulic structure, 

verification of previous floodplain surveys, measurement of 

high-water marks, selection of Manning’s roughness coefficients, and observations of land use in the drainage basin. 

These measurements and observations were notated and used 

in hydrologic and hydraulic computations. 

Other field data measurements included depth of existing 

scour holes and estimates of soil classification. The properties 

computed from the hydraulic model and the soil classification 

were used as input variables in the theoretical scour equations 

presented in HEC-18. Contraction and local scour were 

computed for the 100- and 500-year recurrence interval flood 

discharges, unless significant roadway overtopping occurred. 

In the case of roadway overtopping, the recurrence interval 

Figure 3. Frequency of streambed slopes for the 25 selected bridge sites in the 

bridge-scour database in the Black Prairie Belt of Alabama.

has a range in elevation from 23 to 664 ft (U.S. Geological 

Survey, 2006). The study area includes a small buffer around 

the designated Black Prairie Belt district to include areas with 

similar soil characteristics. 

Within the study area, more than 325 bridge sites 

were visited in efforts to locate the 25 having the deepest 

observed-scour holes. Of the 25 sites selected, more than half 

have multiple hydraulic structures. The selected sites have a 

total of 54 hydraulic structures, of which 37 have measurable 

scour holes that were included in the study. The Black Prairie 

Belt is well known for its fertile soil and crop production. The 

sites selected for the database have a mixture of grasslands 

and wooded areas in the floodplain. Several of the sites were 

swamps with poorly defined channels. The only scour holes 

considered for the database were those located in areas where 

clear-water scour normally occurs. Clear-water scour usually 

occurs in the overbank areas of a bridge opening or under a 

relief bridge. Of the 37 scour data points, 

24 were found under relief structures and 

13 under main channel structures.

Streambed slopes calculated for these 

sites range from 0.0003 to 0.0035 foot per 

foot (ft/ft). A histogram (fig. 3) of the slopes 

in this area shows that the minimum and 

maximum values are outliers, and most of 

the sites have a slope that ranges from 0.0005 

to 0.002 ft/ft. The drainage area of the sites 

ranges from 2.8 to 607 mi2 with most of the 

sites between 10 and 50 mi2 (fig. 4). Most 

(80 percent) of the sites are located in flood 

region 3 of Magnitude and Frequency of 

Floods in Alabama, (Atkins, 1996). The 

equations for this region produce the highest 

runoff per square mile in the State. 

Previous Investigations 

The Alabama Department of Transportation is responsible for evaluating about 

14,100 bridges in Alabama for scour (U.S. 

Department of Transportation Federal Highway Administration, 2003). During 2004, 

ALDOT estimated that about 25 percent of 

those bridge sites still needed scour assessments (Eric Christie, ALDOT Assistant State 

Maintenance Engineer, oral commun., 2004). 

The USGS, in cooperation with ALDOT, 

investigated scour at select remaining sites 

in Alabama. During the level 2 phase of 

scour assessment, the USGS conducted 145 

hydrologic and hydraulic analyses at several 

locations throughout the State. A qualitative 

and quantitative study was conducted at each 

bridge site.

Figure 4. Frequency of drainage area for the 25 selected bridge sites in the bridgescour database in the Black Prairie Belt of Alabama.

0

1

2

3

4

5

6

7

8

0 to

0.00025

0.00025

to 0.0005

0.0005 to

0.00075

0.00075

to 0.001

0.001 to

0.0015

0.0015 to

0.002

0.002 to

0.0025

0.0025 to

0.003

0.003 to

0.0035

0.0035 to

0.004

STREAMBED SLOPE, IN FOOT PER FOOT

FREQUENCY OF OCCURRENCE 0

1

2

3

4

5

6

7

8

9

0 to10 10 to 25 25 to 50 50 to 75 75 to 100 100 to 200 200 to 400 400 to 600 600 to 800

DRAINAGE AREA, IN SQUARE MILES

FREQUENCY OF OCCURRENCE
6 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

flood discharge that produced the highest velocity in the 

bridge was used for the analysis.

The calculated theoretical scour depths were compared 

by ALDOT to the bridge foundations to assess the susceptibility of the structures to failure due to scour. This assessment 

was used for determining countermeasures and selecting 

which structures are scour critical. Additionally, the theoretical 

scour depths were compiled into a database and compared 

to the field-measured scour depths. Because a detailed flood 

history was not available at the level 2 sites, only general 

conclusions could be made from this comparison. For most 

of the sites investigated, the theoretical scour computations 

were found to be excessive. One area of great concern was 

the Black Prairie Belt. Of the 145 sites investigated, 18 were 

located in the Black Prairie Belt. The soils of this district are 

characterized as consolidated highly cohesive clay. Drainage 

area and streambed slopes for these sites range from 1.2 to 

94.6 mi2

 and 0.0007 to 0.0083 ft/ft, respectively. Typically, 

the computed clear-water contraction-scour depths for these 

sites were extreme, and engineering judgment was applied to 

provide a realistic scour depth. The deepest contraction-scour 

hole observed in the Black Prairie Belt was about 2.5 ft. The 

computed theoretical scour depth at this site for the 100-year 

flood was 5.2 times deeper than the observed scour. The 

average age of these bridges is 15 years old with maximum 

and minimum age of 56 and 1 year(s), respectively. Although 

the comparison of the theoretical and measured scour depths 

in the level 2 analysis was limited by the lack of flood 

histories at the selected sites, the general trends indicated that 

an alternative approach was needed to determine more realistic 

scour-depth predictions in cases where unrealistic depths 

result from HEC-18 computations. This conclusion served as a 

basis for the initialization of the current study.

Theoretical Bridge Scour 

Scour is the removal of material from channel and 

overbank areas due to erosive forces of fluid flow. There are 

several forms of bridge scour including long-term degradation, 

general scour, contraction scour, local scour, and scour due 

to the lateral migration of channels. Long-term degradation 

reflects changes in the bed elevation due to natural processes 

or human activities. This type of scour is not inclusive of 

changes near the bridge due to flood events. Degradation is 

reflective of the lack of stability of the stream for the entire 

basin. The assessment of basin equilibrium usually is made 

based on historic information and evaluation of the reach 

above and below the bridge. General scour is based on the 

conditions near the bridge. General scour may be a result 

of superelevated flow caused by flow around a bend, or the 

contraction of flow as a result of hydraulic structures and 

roadway embankments. Contraction scour is a type of general 

scour that occurs when the stream encounters a reduction 

in flow area because of natural constrictions or manmade 

encroachments. Local sour is related to the obstruction of 

flow due to obstacles in the bridge. Lateral scour is caused by 

the horizontal movement of a stream’s channel. Meandering 

streams may shift horizontally, changing the eccentricity of 

the bridge. This dynamic behavior can change how the bridge 

functions and compromise its structural stability. 

Currently, analytical and empirical methods are used to 

compute theoretical scour depths associated with contraction 

and local scour. These depths are estimated by using equations 

presented in HEC-18. The equations were developed through 

flume studies using movable-bed physical models. Laboratory 

experiments provide the opportunity to examine scour in a 

controlled setting. The results, however, may not be fully 

applicable to the complex conditions found in the field. 

Contraction Scour

Contraction scour occurs when a stream encounters a 

reduction in flow area. Bridges and their associated highway 

embankments serve as a constriction that forces the streamflow through the bridge opening. This causes an increase in 

velocity and a decrease in flow depth near the bridge. When 

the applied bed shear stress is greater than the critical shear 

stress for the bed sediments, there is an initiation of motion 

and bed material is transported downstream. The theoretical 

contraction-scour equations were developed on the basis of 

conservation of sediment transport. There are two types of 

contraction scour, live bed and clear water, depending on the 

sediment and flow characteristics upstream. 

Theoretical Live-Bed Contraction Scour

Live-bed scour occurs when bed material upstream from 

the bridge is transported into the region of scour. This type of 

scour is cyclic, with periods of scour and fill. As the depth of 

the scour hole progresses with the hydrograph rise, the flow 

area increases. This action decreases the average velocity 

and shear stress and, therefore, decreases the amount of 

scoured bed material transported out of the scour hole. As the 

hydrograph recedes, the scour hole tends to refill with sediment. Once the sediment transport into and out of the scour 

hole becomes equal, the hole reaches equilibrium and attains 

its maximum depth for the given flow conditions. Live-bed 

equilibrium scour depth for a contracted reach (fig. 5) is a 

function of the width, flow, and flow depth at the contracted 

section and upstream from the contracted section. The depth of 

live-bed scour in a contracted section can be computed using a 

modified version of Laursen’s 1960 equation (Richardson and 

Davis, 2001), which is defined as:

1

2

1

7

6

1

2

1

2

k

W

W

Q

Q

y

y































 = and

2 1 y y y s = −

(1)

,
Theoretical Bridge Scour 7

where

y2 is the average flow depth in the main channel 

at the contracted section, in feet;

y1 is the average flow depth in the upstream main 

channel, in feet;

Q1 is the flow in the upstream main channel 

transporting sediment, in cubic feet per 

second;

Q2 is the flow in the main channel at the 

contracted section, in cubic feet per 

second;

W1 is the top width of the upstream main channel, 

in feet;

W2 is the top width of the main channel at the 

contracted section, in feet;

k1 is an exponent determined from V*/ω and the 

tables in HEC-18 (Richardson and Davis, 

2001);

ys is the average live-bed contraction-scour 

depth, in feet;

ω is the fall velocity of the median bed material 

D50 , in feet per second; and

V* is the shear velocity in the upstream main 

channel, in feet per second, which is 

defined as

where

g is the acceleration of gravity, in feet per 

square second; and

S1 is the energy grade line of the main channel, 

in foot per foot.

In the absence of real-time monitoring, live-bed scour 

depths are difficult to determine after a flood event. In 

contrast, clear-water scour holes do not refill with sediment 

and historic maximum scour depths can be easily measured 

after flood events. Therefore, the data collected for this study 

were limited to clear-water contraction scour. 

Figure 5. Schematic diagram of a contracted reach.

1

2 1 1 V gy S ( ), ∗ =

Roadway

Approach or start

 of contraction

Exit or end of 

 expansion

Contracted section
8 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Theoretical Clear-Water Contraction Scour

Equilibrium clear-water contraction scour depths can 

be slightly larger than equilibrium live-bed contraction-scour 

depths. Clear-water contraction scour was the primary area of 

focus for this study. Scour holes created in clear-water zones 

are not filled during the recession of the hydrograph due to 

the lack of sediment transport from upstream. In some cases, 

sediment is transported from the upstream bed but remains 

suspended through the bridge opening. The lack of sediment 

transport typically is associated with well-vegetated overbanks, armored streambeds, cohesive bed materials, coarse 

bed materials, and riprapped channels. Clear-water contraction 

scour usually is found in the overbank region of a bridge or 

under relief structures (fig. 6). The obstruction of overbank 

flow by roadway embankments causes flow acceleration 

through the bridge and the removal of bed material. Current 

analytical methods for computing clear-water contraction 

scour are based on equations outlined in HEC-18 (Richardson 

and Davis, 2001) and developed by Laursen (1963). These 

equations were used in this study to compute theoretical 

clear-water contraction scour and are defined as follows:

Figure 6. Typical bridge cross section for a well-defined channel and relief bridge showing areas of 

clear-water scour (from Benedict, 2003).
Site Selection 9

 and (2)

where

y2 is the average equilibrium flow depth in the 

contracted section after the contraction 

scour, in feet;

Q is the discharge through the bridge or on 

the set-back overbank area at the bridge 

associated with the width W, in cubic feet 

per second;

Dm is the diameter of the smallest 

nontransportable particle in the bed 

material in the contracted section, in feet, 

and is defined as ;

D50 is the median diameter of bed material, in 

feet;

W is the width of the contracted section less pier 

widths, in feet;

ys is the average scour depth in the contracted 

section, in feet;

y1 is the average depth of flow in the contracted 

section prior to contraction scour, in feet; 

and

Ku is a constant value of 0.0077 for English units.

Pier Scour

Pier scour is a result of flow obstruction within the 

bridge, associated with the bridge piers. The obstruction of 

flow changes the natural streamlines and causes the formation 

of vortices. Theses vortices are referred to as horseshoe 

vortices and wake vortices. As water stacks up and is accelerated around the upstream face of the pier, a horseshoe vortex is 

formed. This downward acceleration results in the removal of 

bed material around the pier. Wake vortices act in the vertical 

direction and are formed downstream from the pier. Both types 

of vortices contribute to the removal of bed material and the 

deepening of the scour hole. The depth of the hole continues 

to increase until equilibrium is reached. In the case of live-bed 

pier scour, equilibrium conditions are achieved when sediment 

transport into and out of the scour hole is balanced. In the case 

of clear-water pier scour, scouring continues until the stress 

resulting from the vortices is no longer great enough to exceed 

the critical shear stress of the sediment. Theoretical pier-scour 

depth can be calculated using the following equation suggested in HEC-18 (Richardson and Davis, 2001).

where

ys is the theoretical pier-scour depth, in feet;

a is the pier width, in feet;

K1 is the dimensionless correction factor for pier 

nose shape;

K2 is the dimensionless correction factor for 

angle of attack for flow;

K3 is the dimensionless correction factor for bed 

condition;

K4 is the dimensionless correction factor for bed 

armoring;

y1 is the approach flow depth, in feet; and

Fr1 is the Froude number directly upstream from 

the pier and defined as

where

V1 is the mean velocity directly upstream from 

the pier, in feet per second; and

g is the acceleration of gravity, in feet per 

square second.

Site Selection 

The study area (fig. 2) was used as the basis for selecting 

sites for field reconnaissance. The sites selected for investigation are stream crossings having older, multiple-span bridges 

with the potential for scour holes. Crossings with culverts, 

single-span bridges, and bridges over major rivers were 

eliminated. A total of 325 sites were investigated for use in the 

scour database. Of the 325 sites, 16 were railroad structures. 

The only railroad structures considered for the database were 

those constructed similar to highway structures. 

Each site was investigated for the presence of scour holes, 

and the age and condition of the structure were documented. 

A field dilatancy test was performed on the soil near the 

bridge to determine if the soil was primarily clay or silt. A 

list was compiled of the sites that had significant scour holes 

and showed characteristics of the soils indicative of the Black 

Prairie Belt. 

After all field reconnaissance was completed the database 

was reduced to 25 stream crossings (fig. 7). The 25 sites 

were a combination of stream crossings on county (12), State 

(8), and U.S. highways (3), and railroad stream crossings 

(2). More than half of the crossings have multiple structures 

giving the database a total of 54 hydraulic structures. Of the 

54 structures, 40 had measurable scour holes. On further 

inspection, it was determined that the natural occurrence of 

three of the holes was questionable. One site was thought to 

have undocumented maintenance. Research of the second hole 

indicated that the channel had been rerouted, and the measured 

scour hole was a combination of scour and the old channel. 

The third hole was eliminated because it was thought to be 

3 / 7

2 / 3 2

2

2















 = D W

K Q

y

m

u

2 1 y y y s = − (3)

50 1.25 D D m =

(4)

0.35

1 0.43

1234 1 2.0 s y y K K K K Fr

a a

  =    

1

1

1

V Fr

gy =

,

,

,
10 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 Figure 7. Location of study area and bridge-scour study sites in Alabama (refer to Appendix 1 to identify bridge with corresponding number). HALE PERRYDALLAS LOWNDES MONTGOMERY BUTLER LEE RUSSELL WILCOX MACON BULLOCK MARENGO GREENE PICKENS SUMTER EXPLANATION Study area Site and site number (see Appendix A) LOCATION OF STUDY AREA IN ALABAMA

6

21

20

22

19

23

7

18

4

13 12 5

25

24

9

8

10

16

15

17 2

14

3

11

1

6

Sougahatchee Cr.

Uchee

Uchee

Little

Creek

Uphapee

Cr.

Creek

Line

Bughall Cr.

Creek

Catoma

Pintlalla

Big

Alabama

Swamp

River

Creek

Creek

Alabama River

Cedar Cr.

Cahaba

Bogue Chitto Creek

R.

Cahaba River

Pine

Barron

Creek

Turkey

Creek

Horse

Chickasaw

Cr.

Creek

Bogue

Big

Big

Brush

Prairie

Tombigbee

Alamuchee River

Cr.

Sucarnoochee

River

River

Bodka

Lubbub

Noxubee

Tombigbee

Cr.

River

Creek

Sipsey

Black Warrior

River

River

Creek

Creek Oakmulgee

Persimmon

Pigeon

Creek

Creek

0 25 50 KILOMETERS

0 25 50 MILES

88 87 86 85

3332
Data Assumptions 11

created from the effects of drift being caught on the piers. The 

remaining 37 scour holes, with depths ranging from 1.4 to 

10.4 ft, were determined to represent unaltered natural scour. 

Figure 8 shows that most of the data points are concentrated 

between scour depths of 2 and 6 ft. 

Justification for the Assumption 

of Clear-Water Scour

Scour created by clear-water conditions provides a 

permanent record of maximum historic scour unless altered 

by human activity. The first assumption is 

that the scour data collected are reflective 

of unaltered, clear-water conditions. The 

occurrence of clear-water or live-bed scour 

is theoretically determined by comparing 

the critical velocity of given sediment to 

the mean velocity in the upstream reach. If 

the upstream mean velocity is less than the 

critical velocity, the upstream velocity is not 

large enough to cause movement of the bed 

material, and the reach is considered to have 

clear-water transport.

Rearranging the basic equation for 

clear-water scour (eq. 2), the critical velocity can be determined. The equation was 

developed using the Shields Diagram to 

determine the relation between critical shear 

stress and the bed-size material, for incipient 

motion of noncohesive beds. The critical

 velocity equation, as outlined in HEC-18 

 (Richardson and Davis, 2001), is presented 

 below:

where 

Vc is the critical velocity above which bed 

material of size D and smaller will be 

transported, in feet per second;

Ku is a constant value of 11.17;

y is the average depth of flow upstream from the 

contraction, in feet; and

D is the particle size, in feet.

There is some concern about the application of the 

critical velocity equation to fine-grained, cohesive soils. The 

equation is highly dependent on the median grain size of 

the bed material. As the size of the bed material decreases, 

the velocity required to initiate motion of the bed material is 

reduced. The critical velocity was calculated for each scour 

data point based on the overbank approach flow depth and 

compared to the average velocity upstream from the bridge. 

Based on this concept, 10 of the scour holes maintained an 

upstream velocity small enough to be considered clear-water 

transport. This was not used as the guideline for determining if 

the sites should be classified as clear-water transport. 

Clear-water scour conditions typically exist for coarsebed material streams, flat gradient streams, armored streambeds, and vegetated channels or overbank areas (Richardson 

and Davis, 2001). The scour database was limited to holes 

Figure 8. Frequency of clear-water contraction-scour depths for the 37 scour data 

points in the bridge-scour database in the Black Prairie Belt of Alabama.

16 13 V Ky D c u = (5) Data Assumptions ,

Currently, laboratory-derived analytical methods are 

used in the estimation of live-bed and clear-water scour 

depths. Limited field tests of these methods indicate that 

they are conservative and at times excessive, especially in 

areas having fine-grained cohesive soils (Benedict, 2003; 

Benedict and Caldwell, 2005; and Mueller and Wagner, 2005). 

Hydraulic Engineering Circular-18 indicates that scour depths 

associated with the current scour-prediction equations must 

be scrutinized and modified if deemed prudent. Engineers, 

however, often do not have sufficient information to make 

such modifications. This study looked at several relations in 

field data to provide tools for assessing the reasonableness of 

predicted scour and guidance on modifying those values if 

need be. In order to accomplish this, several assumptions were 

made about the data collected. The effects of live-bed scour 

are mitigated by sediment transported from the upstream bed, 

and the maximum depths attained during the peak of a flood 

hydrograph are not easily measured. Therefore, the primary 

focus of this study is the assessment of contraction and local 

scour in areas of clear-water transport. The first assumption 

is that the data collected in this investigation are reflective of 

unaltered, clear-water scour. The second assumption is that 

measured scour encompasses scour resulting from a significant 

flood. The final assumption is that the measured scour hole 

has reached its maximum depth and is at equilibrium. 

0

1

2

3

4

5

6

7

8

9

10

1 to 2 2 to 3 3 to 4 4 to 5 5 to 6 6 to 7 7 to 8 8 to 9 9 to 10 10 to 11

CLEAR-WATER CONTRACTION SCOUR DEPTH, IN FEET

FREQUENCY OF OCCURRENCE
12 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

located in the overbank regions and under relief structures. 

The overbank bed material upstream from the bridge is 

secured by the root systems of vegetation The cohesive nature 

of the soil at these sites also limits any bed load transport, 

making clear-water scour conditions a reasonable assumption 

for these sites even though the computed critical velocity for 

noncohesive soils suggests otherwise.

Additionally, it is important that scour measured in this 

study reflects scour unaltered by road maintenance. For all 

sites located on a county route, the respective county engineer 

was contacted. A copy was obtained of the maintenance 

logs, date of construction, and bridge soundings. The date of 

construction was compared to the applicable flood dates, and 

the bridge soundings were inspected for any unusual changes 

in ground elevation. Similar documents were obtained for 

State and U.S routes in addition to any applicable highway 

plans. Inspection of these documents indicated that the scour 

holes existed in their original form and had not been altered. 

Based on field observations, it was determined that the 

scour holes present at the railroad structures were unaltered 

by maintenance. The age of the railroad structures was not 

directly determined. Based on the condition and lifespan of the 

structures, it was assumed that they were at least 75 years old 

or older.

Justification for the Assumption of Large 

Flood Flows 

The scour data points were neither measured during or 

directly after a flood event. Research was used to confirm 

that each bridge had experienced a significant flood and to 

determine the correlation flood associated with the measured 

scour holes. The correlation flood is defined as the largest 

probable flood associated with the hydraulics creating 

the scour hole. The justification of large flood flows was 

accomplished through the use of gage data, flood reports, and 

statistical flood risk analysis. 

Theoretical scour is based on hydraulic properties 

reflective of the 100- and 500-year floods, unless significant 

overtopping occurs. If significant overtopping occurs, the 

bridge is provided relief and velocities are reduced. When 

this is the case, the maximum scour is a result of a lesser 

recurrence interval flood. The ALDOT designs State highway 

crossings based on the criteria of a 50-year flood and county 

road crossings on the 25-year flood. It would be a reasonable 

assumption that most of these roadways are overtopped to a 

certain degree by the 500-year flood, unless the design of the 

structure is not governed by hydraulics. Also, the probability 

of a bridge experiencing multiple 500-year floods during its 

life span is low. Therefore, for this study, a significant flood 

is defined as a 50- to 100-year flood event. Documentation of 

significant flooding and determination of the correlation flood 

was accomplished through the use of historical floods and 

statistical risk analyses. 

Historical Floods 

The significant floods in the study area were researched 

using gage data and flood reports to determine the magnitude 

and the affected areas. The oldest bridge in the database was 

constructed during 1925. This date was the starting point for 

flood research. A primary source of information is the USGS 

streamgaging network. Current and past streamgages, located 

in the study area, were inspected for significant events. A 

log-Pearson Type III frequency analysis was performed for 

each gage located in the study area and was used with regional 

regression equations to determine the best weighted estimates 

of peak flow. This analysis was the basis used for determining 

the recurrence interval of the most significant peaks of record. 

Dates of known flooding events also were inspected for each 

gage. Fifteen gages were selected to represent the flooding 

history of the study area. These gages recorded a total of 52 

peaks that represent flooding ranging from about the 10-year 

flood to greater than a 500-year flood (table 1). The 52 peaks 

were specific to 16 different years. Most of the gages showed 

flooding during 1961, 1979, and 1990. Ten of the gages in 

the study area have peaks greater than the 50-year recurrence 

interval flood (fig. 9). The year and geographic location of the 

floods were compared to the construction dates of the bridges 

in the database. Correlations were made to determine if the 

bridges in the database were affected by a significant flood. 

The probable floods of impact were determined for each scour 

site and are listed in Appendix 1. The more noteworthy floods 

(1929, 1951, 1955, 1961, 1964, 1979, and 1990) are presented 

in more detail later in this report. 

There are two types of storms associated with floods in 

Alabama: frontal systems and tropical storms. The effects 

of intense precipitation and storm surge of coastal waters 

associated with tropical storms and hurricanes, thunderstorms, 

and slow-moving frontal systems usually result in flooding. 

The flooding potential is increased when rivers and creeks 

are already swollen with spring runoff. The average annual 

precipitation varies seasonally and geographically. The 

statewide average rainfall is about 55 inches and varies from 

about 50 inches in central and west-central Alabama to about 

65 inches near the Gulf of Mexico (Paulson and others, 1991). 
Data Assumptions 13

Table 1. Approximate recurrence interval for selected flood years at selected streamflow-gaging stations in the study area in Alabama.[mi2, square mile; AL, Alabama; +, plus; —, not available]

Gaging 

station

number

Gaging station name and location County

Drainage

area 

(mi2)

Period 

of

record

(years)

1929 1943 1944 1945 1949 1951 1955 1961 1962 1964 1975 1979 1990 1994 1998 2001

02419000 Uphapee Creek near Tuskegee, AL Macon 333 65 50+ 25+ 25 — 25+ — — 10+ — 50 — — 25+ 10+ 10 — 02421000 Catoma Creek near Montgomery, AL Montgomery 290 52 — — — — 25+ — — 50+ — — 25+ — 50+ — — 10+02422000 Big Swamp Creek near Lowndesboro, AL Lowndes 244 35 — 10+ — — 50+ — — 25 — — — — 10 — — — 02425500 Cedar Creek at Minter, AL Dallas 211 30 — — — — — — — 100 — — 500+ — — — — — 02425655 Mush Creek near Selma, AL Dallas 44.4 22 — — — — — — 100+ 25 100 25 — — 25+ — — — 02426000 Bogue Chitto Creek near Browns, AL Dallas 95.4 31 — 50 — — — 10+ — — — 10 — 10 — — — — 02427700 Turkey Creek at Kimbrough, AL Wilcox 97.5 39 — — — — — — — 200+ — — — 25+ 10+ — — — 02447000 Sipsey River near Pleasant Ridge, AL Greene 769 22 — — — — — — — 25+ — — — — — — — — 02448500 Noxubee River near Geiger, AL Sumter 1,097 59 — — — — 10+ — — 10+ — — — 500+ — — — — 02449245 Brush Creek near Eutaw, AL Greene 43.2 26 — — — — — — — — — — — 25+ 50+ — — — 02449400 Jones Creek near Epes, AL Sumter 11.8 16 — — — — — — — 25+ — — — — — — — — 02467500 Sucarnoochee River at Livingston, AL Sumter 607 64 — — — — — 10 — 10+ — — — 100 10+ — — — 02468000 Alamuchee Creek near Cuba, AL Sumter 62.3 17 — — — — — — — 10+ — 25 — 25+ — — — — 02468500 Chickasaw Bogue near Linden, AL Marengo 257 29 — — 25+ 25+ — — — — — — — 25+ 10+ — — — 02469000 Kinterbish Creek near York, AL Sumter 90.9 16 — — — — — — — 10+ — 25+ — — — — — — 
14 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 Figure 9. Maximum recurrence interval of streamflow-gaging stations located in the study area in Alabama (refer to table 1 to identify gage with corresponding number). HALE PERRY DALLAS LOWNDES MONTGOMERY BUTLER LEE RUSSELL WILCOX MACON BULLOCK MARENGO GREENE PICKENS SUMTER EXPLANATION Maximum recurrence interval flood at gaging station Study area Streamflow-gaging station and number 25+ 50+ 100+ 200+ 500+ LOCATION OF STUDY AREA IN ALABAMA

Sougahatchee Cr.

Uchee

Uchee

Little

Creek

Uphapee

Cr.

Creek

Line

Bughall Cr.

Creek

Catoma

Pintlalla

Big

Alabama

Swamp

River

Creek

Creek

Alabama River

Cedar Cr.

Cahaba

Bogue Chitto Creek

R.

Cahaba River

Pine

Barron

Creek

Turkey

Creek

Horse

Chickasaw

Cr.

Creek

Bogue

Big

Big

Brush

Prairie

Tombigbee

Alamuchee River

Cr.

Sucarnoochee

River

River

Bodka

Lubbub

Noxubee

Tombigbee

Cr.

River

Creek

Sipsey

Black Warrior

River

River

Creek

Creek Oakmulgee

Persimmon

Pigeon

Creek

Creek

0 25 50 KILOMETERS

0 25 50 MILES

88 87 86 85

3332

02447000

02448500 02449245

02449400

02467500

02468000

02469000

02468500

02426000

02427700

02425655

02425500

02422000

02421000

02419000

02447000
Data Assumptions 15

Flood of 1929

The flood of March 1929 was estimated to rank between 

a 25-year and greater than the 100-year recurrence interval 

flood depending on the location. The area most affected was 

the southeast portion of the State. The storm was centered 

around Elba and produced 20 inches of rain on March 15. The 

total rainfall was 29.6 inches in 72 hours. This event produced 

flooding across a nine-county area greater than the 100-year 

recurrence interval flood (Paulson and others, 1991). The 

portion of the study area that was affected by the 1929 flood 

ranked between a 25- and 50-year recurrence interval flood 

event (fig. 10). 

flooding experienced in the study area, however, contributed to 

the development of several scour holes noted in the database. 

Flood of 1955

Moderate to heavy rainfall occurred during April 8–11, 

1955. The rainfall affected southwestern Alabama and parts 

of Mississippi, Louisiana, and Florida. The slow movement 

of the storm system led to the flooding of Mush Creek near 

Selma (USGS 02425655) (fig. 11; table 1). The event was 

calculated to be greater than a 100-year flood and the highest 

stage measured for the stream crossing at State Route 41. 

Figure 10. Areal extent of major floods—March 1929, February–March 1961, March–April 1973, and March–April 1979—in 

Alabama (modified from Paulson and others, 1991).

Mush Creek is located in the central portion of the study area 

and is a tributary to the Alabama River. 

Floods of 1961

During February 17–26, 1961, Alabama, Florida, 

Georgia, Louisiana, and Mississippi experienced widespread, 

prolonged flooding. A succession of three large storms 

produced accumulated rainfall totals as high as 18 inches in 

central and southern Alabama (figs. 12 and 13). Many small 

streams experienced flooding that became superimposed in 

the large rivers to produce record-breaking peak flows (Barnes 

and Somers, 1961). The extreme variations in intensity 

produced prolonged inundation. 

A second noteworthy flood occurred during 1961. During 

December 5–18, 1961, a series of low-pressure systems 

affected parts of Louisiana, Mississippi, and Alabama. Heavy 

rain fell on December 10 along a narrow band of southwestern 

Alabama extending from Washington to Wilcox Counties. 

During a 10-day period, some parts of Alabama experienced 

a total of 19 inches of rainfall. Twelve of the gages shown in 

figure 11 were affected by the floods of 1961. Flood-frequency 

relations indicate the magnitude of flooding at gaged sites in 

the study area ranged in recurrence interval from greater than a 

10-year flood to greater than a 200-year flood (table 2).

Areal extent of major flood

EXPLANATION

Areal Extent of Floods

Recurrence interval, in years

25

to

50

More

than

50

March 1929 (water year 1929)

February-March 1961 (water year 1961)

March-April 1973 (water year 1973)

March-April 1979 (water year 1979) March 1929 February-March

1961

March-April

1973

March-April

1979

The Uphapee Creek gage (USGS 02419000) (fig. 11; 

table 1) has an estimated recurrence interval that exceeds the 

50-year flood flow for the 1929 flood. This information was 

provided by a local resident. Prior to the 1930s, flood information was limited to a small network of continuous record gages 

operated on larger streams. The gage height was estimated 

based on a reference to the 1964 flood. 

Floods of 1951

Substantial flooding occurred in Alabama and adjacent 

states as a result of storms on March 27–30, 1951. The 

storms progressed from southwest to northeast, with Alabama 

experiencing heavy rainfall on March 27. Some places 

experienced heavy rainfall sporadically for 40–50 hours (U.S. 

Geological Survey, 1953). Most flooding occurred in streams 

in the Mobile River Basin. Rainfall totals were estimated to be 

8 inches at Marion during the period of March 27–March 29. 

A greater than 10-year recurrence interval flood occurred on 

Bogue Chitto Creek near Browns, Alabama (USGS 02426000) 

(fig. 11; table 1), on March 29, 1951. The Sucarnoochee River 

at the Livingston gage (USGS 02467500) also recorded about 

a 10-year recurrence interval flood. The effects of this storm 

system were minimal in the study area. It is probable that any 
16 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 Figure 11. Significant floods affecting streamflow gaging stations located in the study area in Alabama (refer to table 1 to identify gage with corresponding number). HALE PERRY DALLAS LOWNDES MONTGOMERY BUTLER LEE RUSSELL WILCOX MACON BULLOCK MARENGO GREENE PICKENS SUMTER LOCATION OF STUDY AREA IN ALABAMA

Sougahatchee Cr.

Uchee

Uchee

Little

Creek

Uphapee

Cr.

Creek

Line

Bughall Cr.

Creek

Catoma

Pintlalla

Big

Alabama

Swamp

River

Creek

Creek

Alabama River

Cedar

Cr.

Cahaba

Bogue Chitto Creek

R.

Cahaba River

Pine

Barron

Creek

Turkey

Cr.

Horse

Chickasaw

Cr.

Creek

Big

Bogue

Big

Brush

Prairie

Tombigbee

Alamuchee River

Cr.

Sucarnoochee

River

River

Bodka

Lubbub

Noxubee

Tombigbee

Cr.

River

Creek

Sipsey

Black Warrior

River

River

Creek

Creek Oakmulgee

Persimmon

Pigeon

Creek

Creek

Cr.

0 25 50 KILOMETERS

0 25 50 MILES

88 87 86 85

3332

02447000

02448500 02449245

02449400

02467500

02468000

02469000

02468500

02426000

02427700

02425655

02425500

02422000

02421000

02419000

02447000

EXPLANATION

Study areaStreamflow-gaging station and gage number affected by flooding

1929 flood1943 flood1944 flood1945 flood1949 flood1951 floods

1955 flood1961 floods1964 floods1975 flood1979 floods1990 floods

1994 flood1998 flood2001 flood
Data Assumptions 17

Figure 12. Isohyetal map of the Southeastern States showing storm rainfall, 

February 17–26, 1961 (modified from Rostvedt, 1961, p. 8).

Figure 13. Isohyetal map of the Southeastern States showing storm rainfall, 

February 23–26, 1961 (modified from Rostvedt, 1961, p. 8).

100 0 100 MILES

EXPLANATION

4 Rainfall, in inches

92 90 88 86 84 82

35

33

31

29

100 0 100 MILES

EXPLANATION

8 Rainfall, in inches

92 90 88 86 84 82

35

33

31

29

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA
18 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Floods of 1964

Alabama’s streams and rivers experienced many thunderstorms and heavy rainfall throughout April 1964. The city of 

Montgomery had more than 15 inches of rainfall during April. 

The storms that occurred on April 6–8 affected the study area 

and caused flooding in several south-central Alabama streams. 

Rainfall was measured to be 9 inches in several parts of 

Montgomery (fig. 14). Based on gage data, the western part of 

the study area was affected by the storms on April 6, and the 

eastern edge was affected on April 9. Four of the gaged sites 

in the study area were affected by the rainfall during April, 

resulting in flooding ranging from about a 10-year to a 50-year 

recurrence interval (table 3).

Floods of 1979

The floods affecting Mississippi and Alabama during 

1979 were intensified by the heavy rainfall during the winter 

of 1978. The total precipitation for December 1978 was more 

than one and a half times the normal amount (Edelen and 

others, 1986). This rainfall greatly increased the flooding 

potential for future thunderstorms. The heavy rainfall continued through January and February 1979, with nine significant 

events during a total of 22 days. The total rainfall values were 

once again greater than 50 percent above normal. Through 

March and April, a total of eight storms brought heavy 

rainfall to Mississippi and Alabama. The average rainfall for 

this period was more than 8 inches in the Tombigbee River 

Basin, with a maximum value of 17.3 inches at Pickensville, 

Alabama (Paulson and others, 1991). 

Two floods greatly affected the study area. The first 

occurred during March 3–4, following significant rainfall 

during February 21–25. This succession of storms produced 

flooding at two gages in the study area on March 4. Both 

gaged streams exceeded the flow magnitude of the 25-year 

recurrence interval flood. The rainfall for this storm was 

widespread across the two-State area and averaged around 

5 inches across the Tombigbee River Basin (Edelen and others, 

1986). Heavy rains continued to saturate the ground and kept 

rivers and streams swollen as a result of six more storms that 

occurred during March 10–11, March 14, March 21, March 

23–24, April 1–4, and April 8–9. The final storm occurred 

during April 11–14 (fig. 15) and resulted in severe flooding. 

The flooding was intensified by extremely moist antecedent 

soil conditions. Following the event, 28 counties were declared 

a disaster area (Alabama Coastal Hazards Assessment, 2001). 

The most severely affected area was central Alabama. This 

storm produced extensive flooding on five gaged streams in 

the study area. Statewide, 28 percent of the streamflow-gaging 

stations were significantly affected by this flood (Perry and 

others, 2001). The magnitude of flooding ranged from the 

10-year flood to exceeding the 500-year flood (table 4). The 

Sucarnoochee River gage (USGS 02467500) (fig. 11) experienced a flow magnitude about equal to the 100-year flow. This 

gage is located 500 ft upstream from the railroad crossing used 

in the scour database. 

Table 2. Peak discharges, dates, and approximate recurrence intervals for the 1961 floods for selected streamflow-gaging stations in 

the study area in Alabama.

[mi2, square mile; ft3/s, cubic foot per second; AL, Alabama; +, plus]

Gaging 

station 

number

Gaging station name and location County

Drainage 

area

(mi2)

Date of flood Peak flow

(ft3/s)

Period of 

record

Approximate 

recurrence 

interval

(years)

02419000 Uphapee Creek near Tuskegee, AL Macon 333 February 25 25,500 65 10+

02421000 Catoma Creek near Montgomery, AL Montgomery 290 February 25 48,600 52 50+

02422000 Big Swamp Creek near Lowndesboro, AL Lowndes 244 February 25 30,300 35 25

02425500 Cedar Creek at Minter, AL Dallas 211 February 25 45,600 30 100

02447000 Sipsey River near Pleasant Ridge, AL Greene 769 February 25 35,000 22 25+

02449400 Jones Creek near Epes, AL Sumter 11.8 February 21 5,160 16 25+

02467500 Sucarnoochee River at Livingston, AL Sumter 607 February 22 31,500 64 10+

02468000 Alamuchee Creek near Cuba, AL Sumter 62.3 February 22 12,000 17 10+

02469000 Kinterbish Creek near York, AL Sumter 90.9 February 22 11,500 16 10+

02425655 Mush Creek near Selma, AL Dallas 44.4 December 13 19,100 22 25

02427700 Turkey Creek at Kimbrough, AL Wilcox 97.5 December 10 39,600 39 200+

02448500 Noxubee River near Geiger, AL Sumter 1,097 December 18 44,000 59 10+
Data Assumptions 19

Figure 14. Flood area; location of flood-determination points and isohyets for April 6–8, 

1964, floods in Alabama (modified from Rostvedt and others, 1970, p. C21).

Table 3. Peak discharges, dates, and approximate recurrence intervals for the 1964 floods for selected streamflow-gaging stations in 

the study area in Alabama.

[mi2, square mile; ft3/s, cubic foot per second; AL, Alabama]

Gaging 

station 

number

Gaging station name and location County

Drainage 

area

(mi2)

Date of flood Peak flow

(ft3/s)

Period

of record

Approximate 

recurrence 

interval

(years)

02425655 Mush Creek near Selma, AL Dallas 44.4 March 15 13,100 22 25

02419000 Uphapee Creek near Tuskegee, AL Macon 333 April 9 32,200 65 50

02426000 Bogue Chitto Creek near Browns, AL Dallas 95.4 April 8 10,200 31 10

02468000 Alamuchee Creek near Cuba, AL Sumter 62.3 April 6 12,700 17 25

02469000 Kinterbish Creek near York, AL Sumter 90.9 April 6 15,500 16 25+

0 25 50 75 MILES

EXPLANATION

Isohyet, showing total amount of

 precipitation, in inches, for April 6–8

Flood-determination point

10

33

32

31

88 87 86 85

ALABAMA
20 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure 15. Isohyetal map of the Southeastern States showing storm rainfall, 

April 11–14, 1979 (modified from Edelen and others, 1986, p. 24).

Table 4. Peak discharges, dates, and approximate recurrence intervals for the 1979 floods for selected streamflow-gaging stations in the 

study area in Alabama.

[mi2, square mile; ft3/s, cubic foot per second; AL, Alabama, +, plus]

Gaging 

station 

number

Gaging station name and location County

Drainage 

area

(mi2)

Date of flood Peak flow

(ft3/s)

Period

of record

Approximate 

recurrence 

interval

(years)

02427700 Turkey Creek at Kimbrough, AL Wilcox 97.5 March 4 20,000 39 25+

02468500 Chickasaw Bogue near Linden, AL Marengo 257 March 4 34,000 29 25+

02426000 Bogue Chitto Creek near Browns, AL Dallas 95.4 April 13 10,600 31 10

02448500 Noxubee River near Geiger, AL Sumter 1,097 April 14 156,000 59 500+

02449245 Brush Creek near Eutaw, AL Greene 43.2 April 13 6,450 26 25+

02467500 Sucarnoochee River at Livingston, AL Sumter 607 April 14 62,200 64 100

02468000 Alamuchee Creek near Cuba, AL Sumter 62.3 April 14 14,700 17 25+

0 50 100 200 MILES

0 50 100 200 300 KILOMETERS

EXPLANATION

4 Isohyet showing total precipitation, April 11–13, 1979, in inches

35

34

33

32

31

30

29

92 91 90 89 88 87 86 85 84 83

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA
Data Assumptions 21

Floods of 1990

Alabama, Georgia, and Florida sustained significant 

flooding during 1990. Flooding was caused by three separate 

events during February, March, and December. The cyclonic 

storms during February and March resulted in flooding in 

the study area (fig. 16). Throughout the three-State region 

(Alabama, Florida, and Georgia), 74 gaging stations exceeded 

previously recorded maximum streamflows, and 46 exceeded 

the 100-year flow (Pearman and others, 1991). The area 

affected by the storms was more widespread than the area 

affected by 1979 flood (fig. 10). 

The year began with above-average rainfall during January. The first flood occurred as a result of heavy rainfall during 

February 15–16. The west-central and northeastern counties 

of Alabama incurred most of the rainfall, with totals ranging 

from 4 to 8 inches (Jordan and Combs, 1996). One gage in 

the study area exceeded the 50-year flow for the February 

flood (table 5). The March flood affected a greater portion of 

the study area and the State. The rainfall began on March 15 

in southwestern Alabama and proceeded northeastward on 

March 16. Rainfall ranged from 8 to 13 inches across most of 

southwestern and south-central Alabama with local highs in 

other areas. About 35 percent of the State had 2-day rainfall 

totals exceeding 8 inches (Pearman and others, 1991). Six 

gages in the study area were affected by the March flood, with 

peaks ranging from about the 10-year flood to greater than 

the 50-year flood (table 5). Figures 17 and 18 show lines of 

equal recurrence intervals based on gage data for unregulated 

and unurbanized streams with drainage areas between 10 and 

1,000 mi2. 

Figure 16. Areas affected by heavy rainfall—Alabama, Georgia, and Florida—in 

February and March 1990 (modified from Pearman and others, 1991, p. 4).

88 86 84 82

34

32

30

ALABAMA

FLORIDA

GEORGIA

Gulf

of

Mexico

Atlantic

Ocean

0 50 100 150 MILES

0 50 100 150 KILOMETERS

Area affected by heavy rainfall of February 1990

EXPLANATION

Area affected by heavy rainfall of March 1990

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA
22 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Table 5. Peak discharges, dates, and approximate recurrence intervals for the 1990 floods for selected gaging stations in the study area 

in Alabama.

[mi2, square mile; ft3/s, cubic foot per second; AL, Alabama; +, plus]

Gaging 

station 

number

Gaging station name and location County

Drainage 

area

(mi2)

Date of flood Peak flow

(ft3/s)

Period

of record

Approximate 

recurrence 

interval

(years)

02449245 Brush Creek near Eutaw, AL Greene 43.2 February 16 8,100 26 50+

02467500 Sucarnoochee River at Livingston, AL Sumter 607 February 17 23,000 64 10+

02419000 Uphapee Creek near Tuskegee, AL Macon 333 March 17 28,400 65 25+

02421000 Catoma Creek near Montgomery, AL Montgomery 290 March 17 49,100 52 50+

02422000 Big Swamp Creek near Lowndesboro, AL Lowndes 244 March 17 20,300 35 10

02425655 Mush Creek near Selma, AL Dallas 44.4 March 16 15,000 22 25+

02427700 Turkey Creek at Kimbrough, AL Wilcox 97.5 March 16 14,600 39 10+

02468500 Chickasaw Bogue near Linden, AL Marengo 257 March 16 23,900 29 10+

Figure 17. Location of lines of equal recurrence intervals for February 1990 peak discharges 

for unregulated and unurbanized streams in Alabama and Georgia (modified from Pearman 

and others, 1991, p. 9).

35 88 87 86 85 84 83 82 81

34

33

32

31

30 Gulf

of

Mexico

Atlantic

Ocean

0 50 100 MILES

0 50 100 KILOMETERS

LINE OF EQUAL RECURRENCE INTERVAL—Interval variable, in years

EXPLANATION

25

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA
Data Assumptions 23

Risk Analysis

Based on historic flood records, it is probable that most 

bridges in the database have had a 50-year flow magnitude or 

greater. The gage data show that 10 of the 15 gages selected 

in the study area experienced a flood greater than the 50-year 

event (fig. 9). Most of the sites selected for the scour database 

are associated with a particular flood or gaging station to 

ensure the bridge has endured at least a 50-year magnitude 

flood flow. Figure 11, however, indicates sparse gage coverage 

for the eastern portion of the study area, and scour database 

points 1, 2, 3, 11, and 14 (Appendix 1) are slightly isolated 

from the gages with significant flooding. Another concern was 

the extreme southwestern potion of the study area. With the 

exception of the Sucarnoochee River gage (USGS 02467500), 

the gages in this part of the study area do not show a flooding 

event greater than the 25-year recurrence interval flood. To 

substantiate the assumption of large flood flows in these areas 

and for all sites in the database, a statistical risk analysis was 

made. The date of construction was researched for the bridges 

in the database, with the exception of railroad bridges, and the 

bridge age was calculated based on the dates the scour holes 

were measured. Based on the age of the bridge, a binomial 

distribution was used to predict the probability or risk of 

occurrence (Bedient and Huber, 1988) for any given recurrence interval flood. The equation is defined as follows:

where

Risk is the probability that the T-year event will 

occur at least once in n years;

T is the recurrence interval, in years; and

n is the period for accessing the risk, in years.

The 50-year flood was investigated to determine how 

well it statistically correlated to the bridge scour database. 

The risk equation was 

applied to several bridge 

ages (table 6) and used 

to access the likelihood 

of the 50-year flood for 

all bridges with scour 

data points. A frequency 

plot of the bridge ages 

in the database shows 

that most of the bridges 

are 40 years old or older 

(fig. 19). The oldest and 

youngest bridges in the 

database are 81 and 17 

years old, respectively. 

The average bridge 

Table 6. Percent risk for the 

occurrence of the 50-year 

recurrence-interval flow for 

selected bridge ages.

Bridge age,

in years

Risk,

in percent

10 18

20 33

30 45

40 55

50 64

60 70

70 76

80 80

(6)

Figure 18. Location of lines of equal 

recurrence intervals for March 1990 

peak discharges for unregulated and 

unurbanized streams in Alabama, Georgia, 

and Florida (modified from Pearman and 

others, 1991, p. 10).

0 50 100 MILES

0 50 100 KILOMETERS

LINE OF EQUAL RECURRENCE INTERVAL—Interval variable, in years

EXPLANATION

5

88 87 86 85 84 83 82 81

35

34

33

32

31

30 Gulf

of

Mexico

Atlantic

Ocean

NORTH

CAROLINA

SOUTH

CAROLINA

GEORGIA ALABAMA

LOUISIANA

ARKANSAS

TENNESSEE

MISSISSIPPI

FLORIDA

1 11 ,

n

Risk

T

  =− −    
24 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

age for the database is 47 years old, which corresponds to 

a 61- percent risk of occurrence for the 50-year flood. The 

bridges that show a low probability of occurrence (based on 

bridge age) for the 50-year flood were verified through flood 

data at local gaging stations. The probable floods of impact 

were determined for each site and are listed in Appendix 1. As 

previously mentioned, several scour data points are isolated 

from the gage coverage, and gages in the southwest portion 

of the study area only indicate a 25-year recurrence interval 

flood. The bridge ages for the data points isolated from the 

gage coverage (1, 2, 3, 11, and 14, Appendix 1) range from 39 

to 48 years, which indicates a 55–62 percent chance that these 

bridges have endured the 50-year flood. The bridges located in 

the southwest portion of the study area have an average age of 

58 years indicating about a 69-percent chance of the 50-year 

flood. The gages in the southwest are short-term sites with an 

average age of 21 years. It is possible that the lifespan of these 

gages lacks the sufficient length to have recorded historical 

peaks experienced by the bridges in the scour database. Based 

on gage data and risk analysis, it was determined that there 

is a high probability that flooding comparable to the 50-year 

recurrence interval occurred at the bridges in the database and 

therefore was used as the correlation flood. 

Justification for the Assumption of EquilibriumScour Conditions

The Black Prairie Belt district was chosen as the area 

of investigation based on previous studies and inspection of 

current methods. The soils of this district are characterized as 

highly cohesive consolidated clay. The clearwater contraction-scour depths computed for 

bridge crossings in this area can be extreme, 

and engineering judgment must be applied to 

provide a realistic estimation of scour depths. 

The methods recommended in HEC-18 are 

used to predict equilibrium scour depths 

and not necessarily scour associated with 

a single flood event. Equilibrium scour is 

based on sediment discharge continuity. 

When the scour hole deepens, the flow area 

is increased and the velocity and shear stress 

are decreased. The hole continues to deepen 

until the applied shear stress is no longer 

great enough to move the bed material. When 

sediment transport equilibrium is reached, 

the depth of the scour hole will remain 

constant. Equilibrium scour is equivalent to 

the maximum attainable scour for clear-water 

conditions. This is a longer process for 

clear-water scour than live-bed scour, and 

theoretically results in deeper scour depths. 

The focus of this study was the 

documentation of observed clear-water 

contraction scour depths and their correlation 

to several hydraulic properties. One concern 

was that the measured scour depths do not represent equilibrium scour. The current equations for predicting equilibrium 

scour are based on laboratory tests, operated under steadyflow conditions with uniform, noncohesive bed material. A 

stream experiencing a constant peak, until equilibrium scour 

is reached, is not always applicable to field conditions. It is 

assumed that under typical flow conditions maximum scour 

will be reached after several floods (Richardson and Davis, 

2001). This is a valid assumption for some loose granular 

soils, but is not always valid for bed material showing 

strong cohesive properties. Loose granular soils are eroded 

rapidly, whereas materials bound by cohesion are more scour 

resistant. Under constant flow conditions, sand beds may reach 

equilibrium scour within hours while cohesive bed materials 

may not reach equilibrium scour for days, months, or years 

(Richardson and Davis, 2001). 

Typically, the velocities associated with a flood peak 

may continue for several days (Briaud and others, 2004). 

During this time period, the depth generated in cohesive soils 

may only represent a fraction of the equilibrium scour depth. 

The erodibility of bed material is related to the critical shear 

stress of the soil. The critical shear stress for cohesive soils 

is affected by soil properties other than median grain size. 

Depending on the size and material properties of the bed, 

different scour rates will occur. An increase in void ratio and 

swell are known to cause an increase in erodibility of cohesive 

soils (Briaud and others, 2004). Due to the many variables 

influencing the scouring rate of cohesive soils, the critical 

shear stress corresponding to scour is not well established 

(Mueller and Wagner, 2005). 

Figure 19. Frequency of bridge ages and the probability of occurrence for the 

50-year recurrence interval flood for the bridge-scour database in the Black Prairie 

Belt of Alabama.

0

5

10

15

20

25

0 to 10 10 to 20 20 to 30 30 to 40 40 to 50 50 to 60 60 to 70 70 to 80 80 to 90

BRIDGE AGE, IN YEARS

FREQUENCY

0

10

20

30

40

50

60

70

80

90

100

PERCENT RISK

Frequency

50-year flood risk
Approach 25

Research has been performed to investigate a timedependent relation between shear stress and erodibility for 

many cohesive soils. The Erosion Function Apparatus (EFA) 

has been used to simulate flood velocities ranging from 0 foot 

per second (ft/s) to 16 ft/s. A curve (erosion function) is 

developed to describe the relation between the scour rate and 

shear stress. The critical shear stress also can be determined 

from the curve. This value indicates the shear stress below 

which scour will not occur. When the applied shear stress 

is great enough to exceed the critical shear stress, the bed 

material begins to scour. This process may have to occur for 

several floods for equilibrium scour to be attained. Current 

methods (HEC-18) dictate that the equilibrium scour depth 

is computed for the 100- and 500-year peak flows. Based on 

EFA results and the improbability of multiple floods near the 

100-year flow occurring, equilibrium scour depths for the 100- 

and 500-year flows for bridge crossings in Alabama likely will 

not be attained during the life of the structure.

The Highway Research Center of Auburn University 

developed erosion functions for selected sites in Alabama 

using an EFA. An erosion function was developed for the U.S. 

Highway 84 crossing of Pea River at Elba (Crim and others, 

2003). To determine the applicability of equilibrium scour to 

the cohesive soils in the study area, the erosion functions were 

used with flood hydrographs to determine the length of time 

needed for a scour hole to reach equilibrium conditions. 

Since the construction of the Pea River Bridge in 1930, 

the National Weather Service and USGS have operated a 

streamgaging station at the site. During a period of 77 years 

(1930–2006), the bridge has experienced four significant 

floods. The largest recorded flood since the construction of 

the bridge was the 1990 flood. The estimated peak flow for 

this event was 58,000 cubic feet per second (ft3/s), which 

ranks between a 50- and 100-year flood (51,400 ft3/s and 

63,500 ft3/s, respectively) (Hedgecock, 2003). Significant 

flooding also occurred during 1975, 1994, and 1998.

The Pea River Bridge crossing is not located in the study 

area, but soil samples taken showed similar characteristics 

to those in the Black Prairie Belt. Three soil samples were 

collected at different depths from the overbank of the bridge. 

The measured D50 values ranged from 0.03 to 0.04 millimeters 

(mm), and the soil was about 3 percent clay (Crim and others, 

2003). An erosion function was developed for each soil sample 

by the Highway Research Center. The critical shear stress, 

critical velocity, and scour rate were determined from the 

erosion function. The maximum critical shear stress computed 

for the three samples was 1.5 Newton per square meter 

(N/m2). This value corresponds to an approximate critical 

velocity of 2.4 ft/s. 

The HEC-18 methods also were used to compute the 

critical velocity for the Pea River Bridge. Based on a particle 

size of 0.04 mm, the critical velocity was 0.81 ft/s. The 

equilibrium scour depth is computed based on bed movement 

beginning at this velocity. This value is almost three times 

smaller than the critical velocity computed from the EFA. 

The EFA critical velocity value also was used to compute 

the effective duration of the four floods on Pea River. The 

effective duration is the time, during the life of the bridge, 

that the velocity was great enough to move bed material. The 

one-dimensional flow model, Water-Surface Profile (WSPRO) 

(Shearman, 1990), was used to estimate the minimum flow 

that would produce an average velocity greater than the critical 

velocity. During the life of the bridge, the flow exceeded 

this value a total of 172 hours. The computed 50-year flood 

equilibrium scour, based on equations outlined in HEC-18, 

was 15.3 ft. At the maximum scour rate, from the EFA 

analysis (3 mm/hour or 0.2362 ft/day), it would take about 

1,555 hours to reach equilibrium scour depth. This is under the 

assumption that the added area from the scour hole would not 

decrease the velocity and scour rate.

Bridges are designed to withstand scour produced by the 

100- and 500-year floods. The largest flooding event occurring 

during the life of the Pea River Bridge was slightly larger than 

the 50-year recurrence interval flood. According to EFA data 

for the Pea River Bridge crossing, the 77-year-old bridge has 

only experienced 11 percent of the duration needed to produce 

equilibrium scour for the 50-year flood. This result raises 

concern of the applicability of laboratory-defined equilibrium 

scour to cohesive beds. The scour data collected for the 

database were selected to represent unaltered scour depths 

located under older bridges having endured a significant flood. 

The scour depths may not represent HEC-18-defined equilibrium conditions, but provide a good indication of expected 

scour depths for the typical bridge in the Black Prairie Belt 

resulting from large floods. The typical bridge would have an 

expected lifespan of 50 years and would have experienced at 

least a 50-year recurrence interval flood flow.

Approach

Once the sites were selected for the database and 

the proper assumptions verified, the necessary field data 

were collected for the estimation of (1) hypothetical flows, 

(2) hydraulic data, (3) actual scour depths, and (4) theoretical 

scour depths. Similar processes are used for hydraulic studies 

for bridge replacement. To provide consistency, the same 

techniques were used in the processing and application of the 

data in this report. The primary difference is that the resulting 

data were used for the correlation of hydraulic properties to 

observed scour depths. 
26 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Estimation of Hydrologic Data 

The 50-year recurrence interval flood was determined 

to be the best-fit hypothetical flood for the scour holes in 

the database. The 50-year flow was computed for each site 

unless a larger flood was directly documented for the stream 

crossing. Each stream crossing and its associated drainage 

basin were inspected for effects of urbanization. A site 

visit provided minimal information near the bridge. Aerial 

photography and land-use data were inspected for urbanization 

in the entire drainage basin. It was determined that all stream 

crossings in the database drain areas having little or no urban 

development. A flood-frequency relation was developed 

for flood-peak discharges for the 2-, 5-, 10-, 25-, 50-, 100-, 

200-, and 500-year recurrence intervals using the procedures 

described in Magnitude and Frequency of Floods in Alabama, 

by Atkins, (1996). Flood-peak discharge estimates were 

computed using the rural regional regression equations for 

the appropriate hydrologic region. Twenty of the 25 sites are 

located within flood region 3. The equations for this region 

produce the highest runoff per square mile in the State. The 

remaining five sites are located in region 4, just south of the 

flood region 3 boundary.

Alternative methods were used for computing peak 

flows for 2 of the 25 sites; USGS streamflow gage data 

were available at these sites. Flood estimates at gaged sites 

were determined by weighting the regional and station flood 

estimates for the specified recurrence interval using the 

number of years of station record and the accuracy of the 

regional flood-frequency equations expressed as equivalent 

years of record (Atkins, 1996). 

The Big Swamp Creek gage (USGS 02422000) (fig. 11) 

was operational for 33 consecutive years and experienced a 

flood during 1943, 1949, 1961, and 1990. The 1949 flood was 

slightly larger than the 50-year event. The stream crossing 

has five structures for the eastbound lanes and five structures 

for the westbound lanes. All of the structures were examined 

for the effects of scour. The deepest holes were found under 

the four relief bridges on the eastbound lanes. These bridges 

were constructed during 1946 and were affected by the 1948 

flood. The 50-year flood was used as the hypothetical flow 

that contributed to the measured scour. The bridges located on 

the westbound lanes were constructed during 1982 and did not 

experience the 1949 flood. These bridges were not included in 

the database. 

The database contains two railroad structures. One of 

these structures, the Sucarnoochee River bridge, is located 

500 ft downstream from a USGS streamflow gage. The 

Sucarnoochee River gage (UGSG 02467500) has been 

operational since 1939 and was affected by the 1979 flood. 

This flood was calculated to be about a 100-year flood event. 

Based on the 1979 flood, the 100-year flood flow was used as 

the hypothetical flow for scour correlations. This was the only 

scour site for which a larger than 50-year recurrence interval 

flood flow was directly determined.

Estimation of Hydraulic Data 

A stage-discharge relation was developed using WSPRO 

for each site just downstream from the crossing. Water-surface 

elevations for selected recurrence interval floods were 

determined using this stage-discharge relation. The same 

techniques used for bridge replacement studies were used in 

the construction and execution of the hydraulic models for this 

study. The models were constructed based on the definition 

of (1) energy slope, (2) geometry and roughness of floodplain 

cross sections, and (3) geometry and characteristics of 

hydraulic structures and associated roadways.

The models were constructed of a series of cross sections 

(exit, full valley, bridge, and approach) that segment the valley 

reach into short subreaches (fig. 20). The hydraulic control 

was identified for each site and the appropriate cross section 

surveyed, using an electronic total station. In all cases, the 

normal depth downstream from the crossing was identified 

as the control. A cross section was defined downstream 

from the bridge opening to represent the exit section. This 

cross section represents the section of minimum area and 

controls the water-surface elevation at the bridge. The starting 

water-surface elevation was computed at the exit section 

based on the slope-conveyance method. The geometry was 

defined at the full valley section, just downstream from the 

bridge, on natural (prescoured) ground. This section also was 

used to represent the ground-surface elevations in the bridge 

opening. This section represents the minimal flow area prior 

to the effects of scour. The width of the bridge section was 

determined based on the beginning and ending stations of the 

bridge and adjusted for the effects of skew. A weir section also 

was surveyed in the event that the 50-year flood overtopped 

the roadway.

 Many of the sites have relatively uniform reaches 

without any significant changes in floodplain width. For 

these sites, the exit section was propagated upstream from 

the bridge to represent the approach section. Additional cross 

sections were surveyed for sites that had significant changes in 

floodplain width. 

Eleven of the 25 sites were on U.S. or State routes; for 

these sites, as-built plans were furnished by ALDOT, which 

provided prescoured ground elevations near the bridge and 

showed any modifications to the natural channel route. This 

information was helpful in determining the authenticity of the 

scour hole. Recent highway plans included floodplain cross 

sections that were verified and used in conjunction with the 

surveyed cross sections.

The assumption was made that each of the bridges in 

the database has experienced a 50-year flood flow at least 

once during the life of the structures. This assumption was 

determined based on the construction date of the bridge 

and documented floods in the general area. Each site was 

correlated to a particular flood(s) experienced in the general 

area (Appendix 1). These flood(s) were considered to be a 

contributor to the existing scour hole. The conditions reflective 

of the flooding period were considered in developing the 
Approach 27

WSPRO model. During the field visit, each site was assigned 

Manning’s roughness coefficients reflective of current 

conditions. Some sites had relatively new changes in land use 

that were not reflective of the conditions during the scouring 

process. Several sites had areas with new development of 

planted pines or recently clear-cut areas. These changes were 

notated but not used in the model. Each site was researched to 

provide the most accurate land use and roughness coefficients 

during the life of the structure and during any documented 

flooding event(s) in the area. Aerial photography and the 

National Land Cover Dataset (Multi-Resolution Land Characteristics Consortium, 2006, and U.S. Geological Survey, 1992) 

of varying dates were obtained for each site. The research was 

focused on the year and season of the flooding event(s). Less 

data were available for the life of the structure of older sites. 

The results were used in conjunction with the current roughness values and any surveyed changes in land use to develop 

the hydraulic model.

The use of hydrologic data, slope, geometric 

characteristics, and roughness values were used to 

develop a stage-discharge relation for each site. This 

was done for the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 

500-year recurrence interval floods. The 50-year flood 

was determined to be the best estimated hypothetical 

flow for use with scour correlations. The other flood 

flows were used for comparison purposes. The two 

sites that have available gage data were calibrated 

to the gage rating, developed through flow measurements. The remaining sites lacked calibration data 

and were checked using other methods. Each site was 

inspected for the presence of a high-water flood mark. 

These marks were used as a comparison point for the 

stage-discharge relation. The 2-year flood also was 

used for sites that lacked calibration data. Typically 

for most sites, the 2-year flood is a couple of feet deep 

in the floodplain (Methods and others, 2003). The 

overbank depth of the 2-year flood was used as an 

alternative method for testing the applicability of the 

stage-discharge relation at the low end of the rating.

Measurement of Actual Scour Depths 

Depths were measured for each of the 37 

scour holes in the study reach using an electronic 

total station. This was accomplished by first taking 

several representative ground shots of the unscoured 

floodplain on both the upstream and downstream sides 

of the bridge opening. Regression techniques were 

used to develop a best-fit ground line on either side 

of the bridge using these surveyed ground points. An 

estimated unscoured ground line was developed for 

beneath the bridge by linear interpolation between 

the upstream and downstream floodplain ground 

lines. The maximum scour depth for a particular site 

was determined by finding the maximum difference 

between the estimated unscoured ground line (under bridge) 

and ground points surveyed in the bottom of the scour hole.

Finding the location of the deepest areas of scour was 

more difficult at some of the more swampy sites due to 

standing water near the bridge. For these situations, a twoperson jon boat was deployed to do a reconnaissance of the 

submerged area. Using a common level rod, water depth was 

measured at several locations to locate the deepest areas of 

the scour hole. Once the deepest areas were located, several 

ground shots were taken using an electronic total station. 

Clear-water scour typically has three separate components: abutment scour, contraction scour, and pier scour. For 

all the sites used in this study, clear-water contraction scour 

was considered the dominant component of clear-water scour. 

For the 37 scour holes used in this study, based on the shape 

and location of the scour holes, abutment scour was considered to be a minimal factor in the creation of the scour holes, 

especially at the locations coinciding with the deepest scour 

Figure 20. Schematic diagram of cross-section locations used in the 

Water-Surface Profile (WSPRO) model (Shearman, 1990).

Roadway

Approach or start

 of contraction

Exit or end of 

 expansion

Full valley or

downstream face

of contraction

Bridge or contraction
28 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

depths. Surprisingly, the deepest scour holes were typically 

located near the middle of a bridge span and not at the piers or 

abutments.

For clear-water pier scour, it was observed that for sites 

that had contraction scour present there was little additional 

scour around the piers. The low points of the scour holes next 

to the piers were at about the same elevation as the low points 

of the scour holes at the midspan of the bridges. Sites that 

had the deepest pier-scour holes typically had no contraction 

scour present. For these sites, the depth of pier scour was 

usually from 2 to 3 ft. The deepest clear-water pier-scour hole 

observed in the study area was 4.6 ft. deep. At this site, there 

were no other types of scour observed. The largest difference 

between a pier-scour hole and a neighboring contraction-scour 

hole was about 2 ft. Usually there was little difference in these 

depths, which likely indicates that the various components 

of scour are not additive. It should be noted that all the piers 

observed in this study were narrow in width (less than 3 ft). 

Bridges with wide piers possibly could have greater scour 

depths. The database of observed scour depths used in this 

study for both statistical and graphical analyses consists 

entirely of clear-water contraction scour data. Clear-water 

pier scour was noted at many of the sites, but was not used for 

analyses. 

Computation of Theoretical Scour Depths 

Theoretical clear-water contraction scour was computed 

for each of the 37 bridges using the techniques and equations 

outlined in HEC-18. The Laursen equation (Richardson and 

Davis, 2001) (equations 2 and 3) was used to compute the 

theoretical scour depth for each overbank on which there was 

measured scour. Median grain-size 

(D50) values were taken from 

grain-size analyses of sediment 

core samples taken at each site. 

The contracted width for a given 

overbank was defined as the 

distance from the abutment toe to 

the channel bank. The flow across 

the overbank was determined by 

prorating the total flow through 

the bridge by the ratio of conveyance within the overbank to that 

of the entire bridge cross section. 

The average depth of flow prior 

to the occurrence of contraction 

scour was obtained by dividing 

the flow area of the overbank by 

the overbank width. 

For sites with swampy channels or relief structures with no 

defined channel, the entire bridge 

opening experiences clear-water 

contraction scour. In this case, the 

contracted width was defined as the distance from abutment 

toe to abutment toe. The average depth of flow prior to the 

occurrence of scour was obtained by dividing the entire flow 

area of the bridge by the contracted width. Theoretical scour 

computations were performed for the 50-year recurrence 

interval flood. 

Comparison of Actual and Theoretical 

Scour Depths

Comparison of actual and theoretical scour depths 

indicates that the theoretical scour was, on average, about 

475 percent higher than the actual measured scour depths. 

The theoretical scour depths were computed using the D50

obtained from actual field sediment samples. The maximum 

and minimum differences between theoretical and actual scour 

depths were 73 ft and -2.5 ft, respectively, with an average 

difference of about 20 ft. Thirty-five of the sites had larger 

theoretical depths, while two sites had larger actual measured 

depths (fig. 21).

The difference between actual and measured scour may 

be attributed to the complex nature of scour and the difficulties of modeling it. The current equations, recommended 

by HEC-18, for predicting equilibrium scour, are based on 

laboratory tests operated under steady-flow conditions with 

uniform, noncohesive bed material. It has been considered that 

the depth of scour will be less for nonuniform bed material 

than for uniform bed material (Fortier and Scobey, 1926). 

An adequate relation between critical velocity and scour 

for cohesive bed material has not yet been well established. 

Not accounting for the effects of cohesion may explain 

the conservative numbers calculated for the bridges in the 

Figure 21. Relation of observed clear-water contraction-scour depth and theoretical clearwater contraction-scour depth for the 50-year flood. (Theoretical clear-water contraction-scour 

depth calculated with Laursen (1963) equation.)

0

10

20

30

40

50

60

70

80

90

0 2 4 6 8 10 12 14

OBSERVED CLEAR-WATER CONTRACTION-SCOUR DEPTH, IN FEET

THEORETICAL CLEAR-WATER CONTRACTION-SCOUR

DEPTH, IN FEET

Line of agreement
Variables Influencing Clear-Water Contraction Scour 29

database. Additionally, the laboratory tests were simulated 

with a flat prescoured surface. As the surface begins to scour 

the complex nature of scour is intensified. The area added 

from the scouring process reduces the velocity acting on the 

bed surface and lessens the effects of scour. The removal of 

bed material then becomes a problem of defining the bed 

configuration (Richardson and others, 1990) and is not easily 

simulated under laboratory conditions. The calculation of 

scour depths can be further complicated by the estimated 

hydraulic data provided by flow models. Often calibration data 

are limited and may introduce error into scour calculations. 

While the HEC-18 equations are considered the best practice 

available, they are validated by little field data and tend to 

oversimplify flow conditions in the field.

Variables Influencing Clear-Water 

Contraction Scour 

The variables that potentially describe the behavior 

of clear-water scour in the Black Prairie Belt of Alabama 

were selected for statistical analyses. The variables include 

hydraulic properties from the correlation flood (50-year event) 

and characteristics of the bridge and surrounding areas. The 

variables were selected based on current scour-depth calculations methods, engineering judgment, and similar studies 

(Benedict, 2003; and Benedict and Caldwell, 2005). 

Most of the variables considered in this study were 

chosen based on engineering judgment resulting from extensive experience in hydraulic modeling, flood studies, and flood 

measurements. The variables selected were grouped into seven 

primary classifications: (1) median grain size, (2) velocity 

variables, (3) channel contraction ratio, (4) hydraulic ratios, 

(5) geometric contraction ratios, (6) depth variables, and 

(7) other variables. A detailed description of each variable, 

including the method of calculation and degree of correlation, 

is discussed in the following sections.

Median Grain Size 

Initially, the variables analyzed were those relating 

to the derivation of the Laursen equation (equations 2 and 

3) (Richardson and Davis, 2001). The current clear-water 

contraction-scour equation (HEC-18) is based on the principal 

of incipient motion. A relation can be developed between the 

flow depth, velocity, and resistance to determine the applied 

shear stress. At incipient motion, this value is called the 

critical shear stress. When the applied shear stress exceeds the 

critical shear stress, bed material is transported downstream. 

As previously stated, the Laursen equation was not developed 

to calculate scour depths for cohesive bed materials. The calculation of critical shear stress and critical velocity is directly 

related to noncohesive uniform bed material. The implicitly 

derived Shields relation (Vanoni, 1975) was used to determine 

a relation between critical shear stress and bed material size 

(D) for a noncohesive bed. The equation is shown below:

where 

τc is the critical shear stress, in pounds per 

square foot; 

Ks is the Shields coefficient;

ρs is the density of sediment, in slugs per cubic 

feet;

ρ is the density of water, in slugs per cubic feet;

g is the acceleration rate of gravity, in foot per 

square second; and

D is the diameter of the smallest 

nontransportable particle in the bed 

material, in feet.

Fine-grain cohesive soils are more complex and do 

not follow the assumptions made by the Shields relation. 

The movement of fine-grain cohesive soils is dominated by 

electrostatic forces and turbulence. The use of this relation 

tends to underestimate the values of critical shear stress and 

critical velocity for cohesive soils. An adequate determination 

of these values has not been well-established for cohesive bed 

material, bed material that varies with depth, heavily vegetated 

floodplains, previously developed scour holes, and armored 

beds (Mueller and Wagner, 2005). The use of the Shields 

relation for cohesive soils was considered in the selection 

of potential explanatory variables. The Laursen equation 

uses a simplified relation where the value 4(D50) is assumed 

to represent τc, which indicates that the primary variable in 

determining critical shear stress is the median bed diameter 

(D50). 

The median bed diameter was selected as a variable for 

comparison with measured scour. Current practice requires 

the use of a sediment particle grade scale. The scale is divided 

into five classes: boulders, gravel, sand, silt, and clay. Each 

class is divided into different subclasses with an upper and 

lower range of particle-size values. The Laursen equation was 

developed to compute scour for the upper sediment classes 

(boulders, gravel, and sand). It has become common practice, 

however, to apply the equation to the lower classes (silt and 

clay). The result of this practice is often overprediction of 

scour depths in silty and clayey soils. To understand the effect 

that D50 has on scour depth, the Laursen equation (equation 2) 

was rearranged to isolate the D50 term. Assuming the hydraulic properties are held constant (C), the equation becomes

where

y2 is the average equilibrium flow depth in the 

contracted section after the contraction 

scour, in feet;

(7)

2 2 7

50

1 y C and

D

  =     (8)

2 1, s yyy = −

( ),   c ss = − K gD
30 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

C is a constant value under the same hydraulic 

and hydrologic conditions, and is defined 

as 

D50 is the median diameter of bed material, in 

feet;

y1 is the average flow depth in the upstream main 

channel, in feet;

ys is the average scour depth, in feet; and

W is the width of the contracted section less pier 

widths, in feet.

The equation shows that the average depth of flow after 

the occurrence of clear-water contraction scour increases 

exponentially as the D50 value decreases. The magnitude 

of this increase was inspected for the lower range of each 

subclass for sand, silt, and clay (table 7). Table 7 indicates that 

under the same hydraulic and hydrologic conditions, the scour 

depth computed for very fine clay can be 10 times larger than 

for very coarse sand. 

The sites in the database were selected based on the 

observance of soil properties indicative of the Black Prairie 

Belt. The typical soil types observed in the Black Prairie Belt 

are silts, clays, and some mixture of fine sand. Fine-grain soils 

typically consist of some mixture of silt and clay (Leonards, 

1950). A field dilatancy test was performed at each site to 

determine if clay was present. Each site showed some degree 

of cohesion. 

A sediment sample was taken near all 37 scour holes to 

determine the median diameter of the bed material (D50). The 

samples were obtained in natural, prescoured areas near the 

scour hole. A hole was excavated to the measured scour depth 

and samples were taken at incremental depths and in areas 

of notable soil and color change. The Alabama Department 

of Transportation Materials and Test Laboratory analyzed 

the sediments. Due to the small gradation of the samples, a 

hydrometer was used to determine the D50 values. The range 

of D50 values calculated was from 0.001 mm to 0.18 mm 

with most of the samples falling between 0.001 and 0.005 

mm. According to the particle-size scale, most of the samples 

would be considered fine-grained sediments with a significant 

content of clay. The D50 values were graphically (fig. 22) and 

statistically analyzed to determine if a correlation could be 

made between the D50 values and scour depth. The results of 

the comparison showed that a reasonable correlation could not 

be made between the measured scour holes and the calculated 

D50 values. 

Fine-grained soil properties were further researched to 

validate that a reasonable correlation could not be made with 

the scour dataset. Grain size, gradation, and shape are good 

indicators of the engineering properties for granular soils. 

The properties of fine-grained soils, however, are controlled 

by factors other than grain size. Since clay and silt commonly 

exist in a mixture, they are typically referred to qualitatively 

and are not distinguished between based on grain-size distribution (Leonards, 1950). Fine-grained soils are best described 

by the degree of plasticity, consistency in the undisturbed and 

disturbed state, and natural water content. Another concern 

was the lack of homogeneity of the soil within the bridge 

opening. Natural soil deposits commonly exist in stratified 

layers. Each layer is a product of the condition under which it 

was deposited. The layers can vary horizontally and vertically. 

Soil deposits are never considered truly homogenous (Leonards, 1950). As shown in similar studies (Benedict, 2003), D50

values can vary significantly for multiple soil samples taken 

in close proximity. Based on the statistical analysis and the 

factors controlling the engineering properties of fine-grained 

soils, it was determined that median grain size does not 

provide a good correlation with measured scour depths for 

cohesive soils.

Velocity Variables

Hydraulic structures imposing an unnatural contraction 

on a stream increase the velocity, bed shear stress, and the 

potential for scour. Previous studies (Richardson and others, 

1990; and Dongol, 1993) have indicated that the depth of 

scour is a function of velocity parameters. The bridge velocity, 

critical velocity, approach velocity, and the velocity index 

were examined for each site. These values were compared 

to the measured scour depths graphically and statistically to 

determine if a useful correlation exists for assessing scour 

depths.

3 7 2

2 151

Q C

W

 

=      

Table 7. Comparison of the effect that median grain size has 

on clear-water contraction scour.

[D50, median grain size; mm, millimeter; ft, foot; ; 

C = 

3/ 7

2

2

151 



 





W

Q ]

Description of 

material

D50

(mm)

D50

(ft)

Magnitude 

of effect 

on y2

(ft)

Very coarse sands 1 0.0033 5.1*C

Coarse sand 1/2 0.0016 6.2*C

Medium sand 1/4 0.00082 7.6*C

Fine sand 1/8 0.00041 9.3*C

Very fine sand 1/16 0.00021 11.3*C

Coarse silt 1/32 0.00010 13.8*C

Medium silt 1/64 0.00005 16.8*C

Fine silt 1/128 0.000026 20.5*C

Very fine silt 1/256 0.000013 25.0*C

Coarse clay 1/512 0.000006 30.5*C

Medium clay 1/1,024 0.000003 37.1*C

Fine clay 1/2,048 0.000002 45.3*C

Very fine clay 1/4,096 0.0000008 55.2*C

;

2 2 7 50

1 y C and

D

  =    
Variables Influencing Clear-Water Contraction Scour 31

The initial velocity computed for analysis was the 

velocity in the bridge opening. Two methods were used to 

determine the average velocity near the scour hole. An average 

velocity was computed for the entire overbank by dividing the 

overbank flow by the overbank area. This provided an average 

velocity for the entire overbank. The maximum local velocity 

also was examined. Using WSPRO, velocity and conveyance 

distributions can be obtained for individual cross sections. The 

cross section is divided into 20 equal conveyance tubes with 

each representing 5 percent of the flow. The tube velocities 

represent an average value for each 5-percent portion. The 

maximum tube velocity for the overbank was determined and 

compared with the computed average velocity. Comparison of 

the computed average velocity and the tube velocity showed 

that the tube velocities were higher and generally the spread 

increased as the average velocity increased. 

Both velocity values were compared statistically and 

graphically to the measured scour depths (fig. 23). The 

comparison showed that the same trend exists for both 

average and tube velocity values. As the velocity increases the 

measured scour increases. An envelope curve was developed 

for the average and tube velocities, and scour values estimated 

from the curves were compared. On average, the scour values 

estimated by the tube velocity data were 0.5 ft higher than 

those of the average velocity data. The difference in the 

two estimated scour values has an absolute minimum and 

maximum of 0 and 3.81 ft, respectively.

There was some concern that the average and tube 

velocities provide a skewed relation to the measured scour 

depths. The velocity values computed using WSPRO are 

average vertical velocities and do not represent the velocity 

distribution near the bed material. According to laboratory 

test and field measurements, the average vertical velocity 

is located at about 0.63 times the depth below the surface 

(Daugherty and Ingersoll, 1954). The bed material can sustain 

a higher value of average vertical velocity for deeper depths. 

Using the channel slope, average velocity, and the depth in the 

bridge, the Prandtl universal logarithmic velocity distribution 

law (Daugherty and Ingersoll, 1954) was used to estimate the 

velocity profile. The velocity values at several points above the 

bed were computed and compared with the measured scour. 

The comparison showed a trend similar to that of the average 

and tube velocity. The use of the velocity distribution did 

not provide an improved correlation between bridge velocity 

and measured scour. There was also some concern that the 

estimated velocity profile may not be applicable in areas 

of contracted flow. As an alternative approach, the velocity 

per unit depth in the bridge was examined. Statistically and 

graphically, this did not improve the correlation between 

bridge velocity and measured scour.

Several methods have been developed for estimating critical velocities. Critical velocity is the flow velocity at which 

a sediment of given size will erode. Typically, these methods 

are used to compute flow intensity, which is the ratio of the 

approach velocity to the critical velocity. The flow intensity 

is used for determining whether clear-water or live-bed 

conditions are present. Since the scour holes in the database 

were determined to be the product of clear-water contraction 

scour, the critical velocity was used to compute the scouring 

potential based on velocity. By rearranging the basic equation 

(eq. 2) for clear-water scour, HEC-18 provides an equation 

for determining the critical velocity (eq. 5) as a function of 

the flow depth and grain size. The ratio of the bridge velocity 

to the critical velocity calculated for the bridge was used to 

provide an indication of how much the bridge velocity exceeds 

the value required for the beginning of scour. Ratios equal to 

Figure 22. Relation of observed clear-water contraction-scour depths to the median grain size at 

selected sites in the Black Prairie Belt of the Coastal Plain of Alabama.

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20

MEDIAN GRAIN SIZE, IN MILLIMETERS

0

2

4

6

8

10

12

14

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET

Observed clear-water contraction scour

 from field investigations
32 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

one indicate that the bridge velocity is great enough to remove 

bed material from under the bridge. Theoretically, as the ratio 

increases so does the potential for scour.

The HEC-18 equation and Neill’s formulation of the 

critical velocity equation (Neill, 1973) were used to compute 

the scouring potential based on velocity. As expected, the 

ratios were greater than 1 and in most cases were excessive. 

The computed ratios range from 1.7 to 35.7. As an alternative 

approach, nonscour velocities for compact cohesive soils as 

a function of depth were compared to the bridge velocities 

(Keown and others, 1977). Almost one-half of the ratios 

computed using the nonscour velocities were less than 1. 

The average computed ratio was 1.1, with a maximum and 

minimum value of 2.0 and 0.5, respectively. This indicates that 

the velocities within the bridge are not great enough to result 

in a scour hole. It was determined that the methods suggested 

by HEC-18, Neill (1973), and Keown and others (1977) do not 

accurately describe the critical velocities in the Black Prairie 

Belt. These three methods provided values that were unrealistic with respect to the computed average velocities within the 

bridge overbank areas. 

The velocity upstream from the bridge crossing 

(approach velocity) is known to have an effect on pier scour. 

An increase in approach velocity results in an increase in scour 

depth (Richardson and others, 1990). To determine if a similar 

relation exists for clear-water contraction scour, the approach 

velocity was graphically and statistically compared to the 

measured scour. The average and tube velocities were computed for the overbank portion of the approach. To eliminate 

any significant changes in geometry on the outer boundaries 

of the floodplain, the inspection area was limited to the bridge 

abutments projected onto the approach section (q subsection) 

(figs. 24 and 25). The average and tube velocities for the 

respective overbank were determined for the q subsection. 

For relief structures, the velocity values were determined 

for the entire q subsection. Comparison of the average and 

tube velocities indicated that the average value provided a 

better estimate of the velocity in the approach. Due to the 

computational process of the model, the overbank velocity 

tubes sometimes overlap the channel velocity tubes giving an 

overestimated value of maximum tube velocity.

 The average approach velocity was compared to the 

measured scour depths to determine if a correlation could be 

made (fig. 26). The data indicated that clear-water contraction 

scour decreases with increases in approach velocity. This 

trend seems counterintuitive. One explanation for this trend, 

however, is that the relative change in the velocity between 

the approach and the bridge is important. Therefore, when 

approach velocities are large and do not significantly increase 

at the bridge, the scour will be small. In contrast, when the 

approach velocities are small but significantly increase at the 

bridge, scour will increase. To determine the validity of this 

explanation, the velocity index was computed. The velocity 

index is defined as the ratio of the average bridge overbank 

velocity to the average approach overbank velocity within the 

q subsection (figs. 24 and 25). The average velocity values 

Figure 23. Relation of observed clear-water contraction-scour depths to the bridge 

velocity at selected sites in the Black Prairie Belt of the Coastal Plain of Alabama.

0

2

4

6

8

10

12

0 1 2 3 4 5 6 7 8 9 10

BRIDGE VELOCITY, IN FOOT PER SECOND

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR DEPTH, IN FEET

Observed clear-water contraction scour

 from field investigation related to

 tube bridge velocity

Observed clear-water contraction scour

 from field investigation related to

 average bridge velocity
Variables Influencing Clear-Water Contraction Scour 33Figure 24. Definition sketch of variables used to compute (A) velocity index and (B) channel contraction ratio, eccentricity, and flow index for a single bridge opening. Exit cross section Approach cross section

Roadway

Kt

Kq Kb Ka

EXPLANATION

Projected bridge abutments

Edge of water

Roadway

Vqo

Vbo

A B

Bridge abutments

Kt = is the total approach conveyance, in cubic feet per secondKb = is the larger approach conveyance of the overbank between the station of the projected  bridge abutment and the corresponding edge of water, in cubic feet per secondKq = is the approach conveyance within the projected bridge opening, in cubic feet per secondKa = is the smaller approach conveyance of the overbank between the station of the projected  bridge abutment and the corresponding edge of water, in cubic feet per second

Vqo = is the respective average approach overbank velocity between the top of bank and the  projected bridge abutment, in feet per secondVbo = is the respective average bridge overbank velocity, in feet per second

 q subsection of the approach cross section
34 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure 25. Definition sketch of variables used to compute (A) velocity index and (B) channel contraction ratio, eccentricity, 

and flow index for a multiple bridge opening.

Roadway

Vq1 o

EXPLANATION

Edge of water

Vq2 o

Stagnation point or flow division

Exit cross section

Approach cross section

Projected bridge abutments

q subsection of the approach cross section

Bridge 1 main channel structure

Roadway

Kt1

Kq1 Ka1 Ka2 Kq2 Kb2

Kt2

Kb1

Vb1 o

Bridge 2 relief structure (without a channel)

Vb2 o

Kt1 = is the approach conveyance for the main channel bridge between the

 corresponding edge of water and stagnation point, in cubic feet per second

Kb1 = is the larger approach conveyance of the overbank between the station 

 of the projected main channel bridge abutment and the corresponding

 edge of water, in cubic feet per second

Kq1 = is the approach conveyance within the projected main channel bridge 

 opening, in cubic feet per second

Ka1 = is the smaller approach conveyance of the overbank between the station 

 of the projected main channel bridge abutment and the corresponding 

 stagnation point, in cubic feet per second

A

B

Kt2 = is the approach conveyance for the relief bridge between the corresponding

 edge of water and stagnation point, in cubic feet per second

Kb2 = is the larger approach conveyance of the overbank between the station 

 of the projected relief bridge abutment and the corresponding

 edge of water, in cubic feet per second

Kq2 = is the approach conveyance within the projected relief bridge 

 opening, in cubic feet per second

Ka2 = is the smaller approach conveyance of the overbank between the station 

 of the projected relief bridge abutment and the corresponding 

 stagnation point, in cubic feet per second

Vq1 o = is the respective average approach overbank velocity between the top of bank and the 

 projected main channel bridge abutment, in feet per second

Vb1 o = is the respective average main channel bridge overbank velocity, in feet per second

Vq2 o = is the respective average approach velocity between the projected relief bridge 

 abutments, in feet per second

Vb2 o = is the respective average relief bridge velocity, in feet per second
Variables Influencing Clear-Water Contraction Scour 35

were computed by dividing the prorated overbank flow by the 

overbank area for both the bridge and approach sections. The 

equation for the velocity index is 

where

 is the velocity index;

 is the respective average bridge overbank 

velocity, in feet per second; and

 is the respective average approach overbank 

velocity between the top of bank and the 

projected bridge abutment (q subsection), 

in feet per second.

A graphical inspection of the velocity index indicated that a 

good correlation exists with measured scour (fig. 27). Based 

on this analysis, the velocity index was selected as a suitable 

variable for assessing scour using envelope curves. 

Channel-Contraction Ratio

The channel-contraction ratio (m) (Matthai, 1967) 

describes the degree of contraction imposed by a bridge 

opening on the normal (unconstricted) stream channel and 

floodplain. The channel-contraction ratio is a measure of the 

proportion of the total flow that enters the contraction from the 

sides of the floodplain. The channel-contraction ratio can be 

computed from the following equation:

where

m is the channel contraction ratio;

K

q is the approach conveyance within the 

projected bridge opening (q subsection), in 

cubic feet per second; and

Kt is the total approach conveyance, in cubic feet 

per second.

The channel-contraction ratio is essentially the ratio of 

the conveyance sum of the Ka and Kb portions of the approach 

section (conveyance not included in the projected bridge 

opening) to the total approach conveyance (Kt). The variable 

Ka represents the smaller approach overbank conveyance 

between the station of the projected bridge abutment and the 

corresponding edge of water. The variable Kb represents the 

larger approach overbank conveyance between the station of 

the projected bridge abutment and the corresponding edge of 

water. Based on graphical inspection of a plot of measured 

scour and channel-contraction ratio, it was concluded that 

channel-contraction ratio provided a suitable correlation with 

measured scour (fig. 28).

Figure 26. Relation of observed clear-water contraction-scour depths to the average approach 

velocity at selected sites in the Black Prairie Belt of the Coastal Plain of Alabama.

, bo

i

qo

V V

V

=

Vbo

V qo

Vi

(9) 1 , q

t

K m K

  = −     (10)

0

2

4

6

8

10

12

14

0.0 0.5 1.0 1.5 2.0 2.5

AVERAGE APPROACH VELOCITY, IN FEET PER SECOND

OBSERVED CLEAR-WATER CONTRACTION-SCOUR

DEPTH, IN FEET

Observed clear-water contraction scour

 from field investigations
36 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure 27. Relation of observed clear-water contraction-scour depths to the velocity index at selected 

sites in the Black Prairie Belt of the Coastal Plain of Alabama.

Figure 28. Relation of observed clear-water contraction-scour depths to the channel-contraction ratio at 

selected sites in the Black Prairie Belt of the Coastal Plain of Alabama.

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET

Observed clear-water contraction scour

 from field investigations

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12

VELOCITY INDEX

0

2

4

6

8

10

12

14

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

CHANNEL CONTRACTION RATIO

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET

Observed clear-water contraction scour

 from field investigations
Variables Influencing Clear-Water Contraction Scour 37

Hydraulic Ratios

Several hydraulic ratios were investigated in regard to 

their effects on clear-water contraction scour. The hydraulic 

ratios that were studied in addition to the velocity ratios 

mentioned earlier included: (1) width to depth, (2) conveyance 

to depth, (3) eccentricity, and (4) flow index.

The width-to-depth ratio represents the ratio of the width 

of the approach flow of a given overbank to the average depth 

of flow of that same overbank. The average depth is computed 

by dividing the cross-sectional area of the overbank flow by 

its width. The conveyance-to-depth ratio represents the ratio 

of the conveyance of the approach flow of a given overbank to 

the average depth of flow of that same overbank. For multiple 

bridge openings, the width-to-depth and conveyance-to-depth 

ratios were computed using only the portion of the approach 

overbank that supplied flow to that respective bridge (flow 

between the stagnation point and projected bridge abutment 

of the approach section for the respective bridge [fig. 25]). 

Based on both the statistical and graphical analyses, neither 

the width-to-depth nor conveyance-to-depth ratios provided a 

good correlation with measured scour depths (figs. 29 and 30, 

respectively).

Figure 29. Relation of observed clear-water contraction-scour depths to the width-to-depth ratio at 

selected sites in the Black Prairie Belt of the Coastal Plain of Alabama

Figure 30. Relation of observed clear-water contraction-scour depths to the conveyance-to-depth 

ratio at selected sites in the Black Prairie Belt of the Coastal Plain of Alabama.

0

2

4

6

8

10

12

14

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET

0 100 200 300 400 500 600 700 800

WIDTH TO DEPTH RATIO

Observed clear-water contraction scour

 from field investigations

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000

CONVEYANCE TO DEPTH RATIO

0

2

4

6

8

10

12

14

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET

Observed clear-water contraction scour

 from field investigations
38 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Eccentricity of a bridge opening is defined as the ratio 

of the conveyances of the approach overbanks supplying flow 

to the respective bridge (Matthai, 1967). These overbank 

areas are the portions of the approach section that lie outside 

the region of the projected bridge abutments (q subsection) 

(figs. 24 and 25). Eccentricity is computed by dividing the 

smaller overbank conveyance (Ka) by the larger overbank 

conveyance (Kb). For multiple bridge openings, the outside 

boundaries of these sections are either defined by the edge 

of water at the approach section or the stagnation point(s) of 

the approach between bridge openings. Based on both the 

statistical and graphical (fig. 31) analyses, eccentricity did not 

provide a good correlation with measured scour depths.

The flow index is the ratio of the flow in the bridge 

overbank to the corresponding overbank flow in the approach 

section (within the projected bridge opening, q subsection). 

This ratio was computed by dividing the overbank conveyance 

of the q subsection (figs. 24 and 25) of the approach by the 

corresponding overbank conveyance of the bridge opening. 

For bridge sites having no defined channel, the approach 

conveyance for the q subsection was divided by the total 

bridge conveyance. Based on graphical inspection of a plot 

of measured scour and flow index, it was concluded that flow 

index provided a marginal correlation with measured scour 

(fig. 32). Since other variables provided a better graphical 

correlation, the flow index was not used in developing the 

scour envelope curve.

Figure 31. Relation of observed 

clear-water contractionscour depths to eccentricity 

at selected sites in the Black 

Prairie Belt of the Coastal Plain 

of Alabama.

Figure 32. Relation of 

observed clear-water 

contraction-scour depths 

to the flow index at 

selected sites in the Black 

Prairie Belt of the Coastal 

Plain of Alabama.

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET

Observed clear-water contraction scour

 from field investigations

0

2

4

6

8

10

12

14

0.00 0.20 0.40 0.60 0.80 1.00 1.20

ECCENTRICITY

Observed clear-water contraction scour

 from field investigations

0

2

4

6

8

10

12

14

0 1 2 3 4 5 6 7 8 9

FLOW INDEX

MEASURED CONTRACTION-SCOUR DEPTH, IN FEET
Variables Influencing Clear-Water Contraction Scour 39

Contraction Ratios

The geometric contraction ratio relating bridge width 

to the respective width of the approach section also was 

examined to see if any correlation to clear-water contraction 

scour could be determined. The geometric contraction ratio 

is an indicator of the severity of flow contraction created by 

the bridge. This ratio is defined as one minus the bridge width 

divided by the approach flow width. For single bridge openings, the width of the bridge opening (length along the center 

line) was divided by the width (top width) of the approach 

flow. For multiple bridge openings, the width of the bridge 

opening was divided by the width of the approach section that 

supplied flow to that respective bridge (between the stagnation 

point and edge of water). These same methods were used to 

compute the contraction ratios based on area and conveyance. 

The bridge area and conveyance were compared to the area 

and conveyance of the approach section supplying flow to the 

respective bridge. Based on both the statistical and graphical 

(figs. 33, 34, and 35) analyses, none of the contraction ratios 

provided a good correlation with measured scour depths.

Figure 33. Relation of observed clear-water contraction-scour depths to the geometriccontraction ratio of widths at selected sites in the Black Prairie Belt of the Coastal Plain of 

Alabama.

Figure 34. Relation of observed clear-water contraction-scour depths to the geometriccontraction ratio of areas at selected sites in the Black Prairie Belt of the Coastal Plain of Alabama

Observed clear-water contraction scour

 from field investigations

0

2

4

6

8

10

12

14

MEASURED CONTRACTION-SCOUR DEPTH, IN FEET

0.00 0.20 0.40 0.60 0.80 1.00 1.20

GEOMETRIC-CONTRACTION RATIO OF WIDTH

Observed clear-water contraction scour

 from field investigations

0

2

4

6

8

10

12

14

MEASURED CONTRACTION-SCOUR DEPTH, IN FEET

0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.00

GEOMETRIC-CONTRACTION RATIO OF AREA
40 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Depth Variables

Two aspects of flow depth were investigated in relation 

to their effects on clear-water contraction scour: (1) average 

depth in the bridge opening and (2) average depth in the 

approach section. The average depth in the bridge opening 

refers to the average depth of flow in the overbank portion of 

the bridge and is calculated by dividing the cross-sectional 

area of the overbank bridge flow by the width of that respective overbank. The average depth in the approach section 

refers to the average depth of flow in the overbank portion of 

the approach section and is calculated by dividing the crosssectional area of the overbank approach flow by the width 

of the approach overbank. Based on both the statistical and 

graphical analyses, it was determined that average depth in the 

bridge (fig. 36) and approach (fig. 37) did not provide a good 

correlation with measured scour depths.

Other Variables

Other hydraulic variables investigated in regard to their 

effects on clear-water contraction scour were (1) Froude 

number, (2) submergence, (3) head, and (4) backwater. The 

Froude number is the ratio of the inertial to gravitational 

forces of the streamflow within the bridge opening. This 

dimensionless value is computed by dividing the average 

velocity in the bridge by the square root of average depth 

times the acceleration of gravity. Submergence is the difference between the approach water-surface elevation and the low 

steel of the bridge opening. Head is the difference between the 

approach water-surface elevation and the water-surface elevation on the downstream side of the bridge. Finally, backwater 

is the difference between the approach water-surface elevation 

before and after the bridge constriction is in place. Based on 

both the statistical and graphical (figs. 38, 39, 40, and 41) 

analyses, none of these variables provided a good correlation 

with measured scour depths.

Figure 35. Relation of observed clear-water contraction-scour depths to the geometric-contraction 

ratio of conveyance at selected sites in the Black Prairie Belt of the Coastal Plain of Alabama.

Observed clear-water contraction scour

 from field investigations

0

2

4

6

8

10

12

14

0.00 0.20 0.40 0.60 0.80 1.00 1.20

GEOMETRIC-CONTRACTION RATIO OF CONVEYANCE

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET
Variables Influencing Clear-Water Contraction Scour 41

Figure 36. Relation of observed 

clear-water contraction-scour 

depths to the average depth in the 

bridge opening at selected sites in 

the Black Prairie Belt of the Coastal 

Plain of Alabama.

Figure 37. Relation of observed 

clear-water contraction-scour 

depths to the average depth in 

the approach section at selected 

sites in the Black Prairie Belt of 

the Coastal Plain of Alabama.

Figure 38. Relation of observed 

clear-water contraction-scour 

depths to the Froude number 

at selected sites in the Black 

Prairie Belt of the Coastal Plain 

of Alabama.

0

2

4

6

8

10

12

14

OBSERVED CLEAR-WATER CONTRACTION-SCOUR

DEPTH, IN FEET

Observed clear-water contraction scour

 from field investigations

0 2 4 6 8 10 12 14

AVERAGE DEPTH IN THE BRIDGE OPENING, IN FEET

Observed clear-water contraction scour

 from field investigations

0

2

4

6

8

10

12

14

OBSERVED CLEAR-WATER CONTRACTION-SCOUR

DEPTH, IN FEET

0 2 4 6 8 10 12 14

AVERAGE DEPTH IN THE APPROACH SECTION, IN FEET

Observed clear-water contraction scour

 from field investigations

0

2

4

6

8

10

12

OBSERVED CLEAR-WATER CONTRACTION-SCOUR

DEPTH, IN FEET

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80

FROUDE NUMBER
42 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure 39. Relation of 

observed clear-water 

contraction-scour depths 

to submergence at selected 

sites in the Black Prairie 

Belt of the Coastal Plain of 

Alabama.

Figure 40. Relation of 

observed clear-water 

contraction-scour depths 

to head at selected sites in 

the Black Prairie Belt of the 

Coastal Plain of Alabama.

Figure 41. Relation of 

observed clear-water 

contraction-scour depths to 

backwater at selected sites 

in the Black Prairie Belt of the 

Coastal Plain of Alabama.

Observed clear-water contraction scour

 from field investigations

OBSERVED CLEAR-WATER CONTRACTION-SCOUR

DEPTH, IN FEET 0

2

4

6

8

10

12

14

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

SUBMERGENCE, IN FEET

Observed clear-water contraction scour

 from field investigations

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET 0

2

4

6

8

10

12

14

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

HEAD, IN FEET

Observed clear-water contraction scour

 from field investigations

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR

DEPTH, IN FEET 0

2

4

6

8

10

12

14

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

BACKWATER, IN FEET
Development of the Alabama Clear-Water Contraction Scour Envelope Curves 43

Development of the Alabama 

Clear-Water Contraction Scour 

Envelope Curves

Statistical analyses were performed to determine which 

geometric/hydraulic variable(s) could provide a good correlation to measured scour observed across the Black Prairie Belt. 

The minimum R2 selection method, used by the Statistical 

Analysis System (SAS), was used to evaluate the statistical 

significance of each possible explanatory variable (Freund 

and Littell, 1991). None of the variables tested provided a 

good statistical correlation (R2 > 0.8). Graphical methods were 

used to plot each of the variables against measured scour, and 

the resulting plots were visually inspected to see which ones 

would produce the most reasonable envelope curve(s). Envelope curves are curves that define the upper limit of observed 

scour throughout the range of collected data. Envelope curves 

developed with field data are useful tools for assessing reasonable ranges of scour depth in the Black Prairie Belt. After 

graphical inspection of all the potential explanatory variables, 

it was concluded that the channel-contraction ratio and the 

velocity index provided the best envelope curves. Envelope 

curves using the velocity index and the channel-contraction 

ratio as explanatory variables are shown in figures 42 and 43, 

respectively.

Application of the Alabama 

Contraction-Scour Envelope Curves

When assessing the clear-water contraction-scour depths 

using envelope curves presented in this report, both curves 

should be applied to site(s) of interest. These two envelope 

curves will often provide different estimates for the clearwater contraction-scour depth. Application of these envelope 

curves to the 25 bridge sites (37 hydraulic structures) used in 

this study has shown that the velocity index envelope provided 

the higher estimate of clear-water contraction scour for 18 out 

of 37 structures (51 percent). On average, the velocity index 

envelope estimated about 0.15 ft more scour depth than the 

channel-contraction envelope. After comparing the results of 

both envelopes, one should use the larger of the two estimated 

scour depths. 

The channel-contraction ratio envelope curve is valid 

for channel-contraction ratios between 0.25 and 1.0, which 

roughly corresponds to scour depths between 2 and 13 ft. The 

velocity index envelope is valid for velocity indexes between 

1 and 11, which roughly corresponds to scour depths between 

4 and 11 ft. Both envelope curves should be used for sites that 

are located in the Black Prairie Belt of the Coastal Plain of 

Alabama. 

When using these envelope curves, the potential error 

and limitations of these curves should be considered. These 

envelope curves were developed using modeled hydraulic data 

that only estimate the true hydraulic conditions that created 

the observed scour. It is probable that errors exist within 

the hydraulic estimates, thus introducing error within the 

envelope curves. The clear-water contraction-scour envelope 

curves were developed using hydraulic data estimated with 

the hypothetical 50-year flood flow. Although it is unlikely 

that all study sites experienced this flow magnitude, there is 

evidence to suggest that most sites experienced flows equaling 

or exceeding this flow magnitude. The envelope curves should 

not be used to assess scour for extreme events larger than the 

100-year recurrence interval flood. Finally, engineers should 

be aware that deeper scour in this region could be possible 

and, therefore, warrant the application of a safety factor.
44 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure 42. Envelope curve of observed clear-water contraction-scour depths based on the velocity index at selected sites in the Black 

Prairie Belt of the Coastal Plain of Alabama.

qo

bo

i V

V V 

Vi = is the velocity index

Vbo = is the respective average bridge overbank velocity,

 in feet per second, (figs. 24 and 25)

Vqo = is the respective average approach overbank velocity

 between the top of bank and the projected bridge abutment,

 in feet per second (figs. 24 and 25)

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12

VELOCITY INDEX (Vi

)

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR DEPTH, IN FEET

EXPLANATION

Observed clear-water contraction

 scour from field investigation

Data points arbitrarily chosen to develop

 envelope curve and equation

Envelope curve based on a trend line

 through the points identified by circles

Estimate of clear-water contraction-

 scour depth

50-year velocity index

 (not to exceed 11.0)

ys

Vi

Equation for envelope curve

ys = 2.7081Ln(Vi

) + 4.2517

for Vi

 < 11.0
Application of the Alabama Contraction-Scour Envelope Curves 45

Figure 43. Envelope curve of observed clear-water contraction-scour depths based on the channel-contraction ratio at 

selected sites in the Black Prairie Belt of the Coastal Plain of Alabama.















  

t

q

K

K

m 1

m = is the channel contraction ratio

Kq = is the approach conveyance within the projected bridge opening,

 in cubic feet per second (figs. 24 and 25)

Kt = is the total approach conveyance, in cubic feet per second (figs. 24 and 25)

0

2

4

6

8

10

12

14

0.0 0.2 0.4 0.6 0.8 1.0 1.2

CHANNEL CONTRACTION RATIO (m)

OBSERVED CLEAR-W

ATER CONTRACTION-SCOUR DEPTH, IN FEET

EXPLANATION

Observed clear-water contraction

 scour from field investigation

Data points arbitrarily chosen to develop

 envelope curve and equation

Envelope curve based on a trend line

 through the points identified by circles

Estimate of clear-water contraction-

 scour depth

50-year channel contraction ratio

 (not to exceed 1.0)

ys

m

Equation for envelope curve

ys = 7.1797m2 + 5.5403m + 0.1824

for m < 1.0
46 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Summary

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

Alabama Department of Transportation, made observations of 

clear-water contraction scour at 25 bridge sites (37 hydraulic 

structures) in the Black Prairie Belt of the Coastal Plain of 

Alabama. Observed scour depths ranged from 1.4 to 10.4 feet. 

Theoretical clear-water contraction-scour depths were computed for each bridge using HEC-18 methodology and were 

compared with observed scour. This comparison showed that 

theoretical scour depths, in general, exceeded the observedscour depths by about 475 percent.

Variables determined to be important in developing scour 

within laboratory studies along with several other hydraulic 

variables were investigated to understand their influence 

within the Alabama field data. The variables investigated 

included grain size, velocity variables, channel-contraction 

ratio, hydraulic ratios, contraction ratios, depth variables, and 

other variables. None of the variables tested provided a good 

statistical correlation (R2 > 0.8). Graphical methods were used 

to plot each of the variables against measured scour, and the 

resulting plots were visually inspected to determine which 

ones would produce the most reasonable envelope curve(s). 

These envelope curves define the upper limit of observed 

scour throughout the range of data collected.

The strongest explanatory variables for clear-water 

contraction scour were channel-contraction ratio and velocity 

index. Envelope curves were developed relating both of these 

explanatory variables to observed scour. When assessing the 

clear-water contraction-scour depths using the envelope curves 

presented in this report, both curves should be applied to 

site(s) of interest. After comparing the results of both curves, 

the larger of the two estimated scour depths should be used. 

When assessing the results of the envelope curves the potential 

error and limitations of these curves should be considered. The 

clear-water contraction-scour envelope curves were developed 

using modeled hydraulic data estimated with the hypothetical 

50-year flood flow. The envelope curves should not be used 

to assess scour for extreme events larger than the 100-year 

recurrence interval flood. It also should be considered that 

deeper scour in this region could be possible and may warrant 

the application of a safety factor. These envelope curves 

provide a useful tool for assessing reasonable ranges of scour 

depth in the Black Prairie Belt of Alabama.

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Appendix A 49

Appendix A. Alabama bridge-scour study sites and reference number for figure 7. — Continued[—, no data; CR, county road; AL, Alabama; +, plus]

Site 

reference 

no. for 

figure 7

County Stream Structure

Total 

number of 

structures

Road/

highway

Measured 

clear-water 

contractionscour depth

(feet)

Channel 

contraction 

ratio

Velocity 

index

Figure number 

for picture in 

Appendix B

Bridge 

age1

(years)

Probable floods of 

impact

 1 Bullock Line Creek Relief bridge 1 2 CR 7 6.9 0.84 5.3 B3, B4 48 1961, 1990, 1994, 1998 2 Bullock Line Creek Main channel bridge 2 CR 7 3.2 0.71 4.2 B1 48 1961, 1990, 1994, 1998 2 Bullock Line Creek Relief bridge 1 2 CR 7 4.5 0.54 4.0 B2 48 1961, 1990, 1994, 1998 3 Bullock Williams Creek Main channel bridge 1 CR 165 2.9 0.80 5.0 B5 42 1990, 1994, 1998 4 Dallas Brush Creek Main channel bridge 1 Railroad 4.9 0.58 3.2 B6 75+ 1943, 1961, 1951, 1979 5 Dallas Chilatchee Creek Relief bridge 1 3 AL 5 3.4 0.86 3.0 B7 32 1979 5 Dallas Chilatchee Creek Relief bridge 2 3 AL 5 2.2 0.75 3.2 — 32 1979 6 Greene Taylor Creek Main channel bridge 1 CR 148 4.6 0.78 4.4 B8 49 1961, 1979 7 Hale Cottonwood Creek Relief bridge 1 3 CR 12 10.4 0.88 9.7 B9 42 1979 8 Lowndes Big Swamp Creek Relief bridge 1 5 U.S. 80 7.5 0.70 5.0 — 60 1949, 1961, 1990, 1979 8 Lowndes Big Swamp Creek Relief bridge 2 5 U.S. 80 8.6 0.81 5.5 — 60 1949, 1961, 1990, 1979 8 Lowndes Big Swamp Creek Relief bridge 3 5 U.S. 80 8.8 0.84 5.3 — 60 1949, 1961, 1990, 1979 8 Lowndes Big Swamp Creek Relief bridge 4 5 U.S. 80 3.5 0.62 2.0 B10 60 1949, 1961, 1990, 1979 9 Lowndes Mussel Creek Relief bridge 1 2 AL 263 2.6 0.72 3.9 — 39 1975, 1979, 1990

10 Lowndes Tallawassee Creek Downstream main 

channel bridge

1 U.S. 80 2.8 0.37 7.7 — 81 1949, 1961, 1979, 1990

10 Lowndes Tallawassee Creek Upstream main 

channel bridge

1 U.S. 80 2.7 0.54 2.3 B11 30 1990

11 Macon Cubahatchee Creek Main channel bridge 2 CR 7 2.7 0.68 4.7 — 39 1979, 1990, 1994, 199811 Macon Cubahatchee Creek Relief bridge 1 2 CR 7 4.6 0.55 1.2 — 39 1979, 1990, 1994, 199812 Marengo Chickasaw Bogue Relief bridge 1 2 AL 28 4.7 0.80 4.4 B12 51 1979,1961, 199013 Marengo Michigan Creek Main channel bridge 1 AL 25 2.1 0.77 2.0 — 18 199014 Montgomery Line Creek Relief bridge 1 3 CR 2 3.2 0.36 1.9 B13 45 1961, 1990, 1994, 199814 Macon Line Creek Relief bridge 2 3 CR 2 5.2 0.55 4.2 — 44 1961, 1990, 1994, 199815 Montgomery Ramer Creek Relief bridge 1 4 CR 18 4.4 0.90 7.2 B14 25 199015 Montgomery Ramer Creek Relief bridge 2 4 CR 18 9.6 0.80 7.4 B15 31 1975, 199015 Montgomery Ramer Creek Relief bridge 3 4 CR 18 2.7 0.66 4.8 — 25 199016 Montgomery Ramer Creek Relief bridge 1 4 CR 61 4.4 0.90 5.4 — 20 1990, 2001
50 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 Appendix A. Alabama bridge-scour study sites and reference number for figure 7. — Continued [—, no data; CR, county road; AL, Alabama; +, plus] Site reference no. for figure 7 County Stream Structure Total number of structures Road/ highway Measured clear-water contraction- scour depth (feet) Channel contraction ratio Velocity index Figure number for picture in Appendix B Bridge age1 (years) Probable floods of impact 16 Montgomery Ramer Creek Relief bridge 3 4 CR 61 7.8 0.79 5.8 B16 20 1990, 2001 17 Montgomery Thompson Creek Relief bridge 2 3 Woodley Road 5.3 0.68 3.2

— 17 1990, 2001

18 Perry Bogue Chitto Creek Relief bridge 1 2 CR 38 5.8 0.71 3.7

— 45 1979

19 Sumter Alamuchee Creek Relief bridge 1 3 AL 17 1.4 0.61 1.8 B17 68 1961, 1964, 197919 Sumter Alamuchee Creek Relief bridge 2 3 AL 17 1.6 0.87 2.5

— 68 1961, 1964, 1979

20 Sumter Mill Creek Main channel bridge 1 U.S. 80 3.7 0.50 2.7

— 52 1961, 1964, 1979

21 Sumter Sanusi Creek Main channel bridge 2 AL 17 3.9 0.59 3.7

— 66 1951, 1961, 1979, 1990

22 Sumter Sucarnoochee River Relief bridge 1 2 Railroad 5.1 0.58 2.1

— 75+ 1951, 1961, 1979, 1990

23 Sumter Tributary to Sucarnoochee River Main channel bridge 1 CR 12 3.7 0.87 10.4

— 56 1951, 1961, 1979, 1990

24 Wilcox Martin Creek Main channel bridge 1 AL 5 3.9 0.85 10.2

— 68 1961, 1979, 1990

25 Wilcox Red Creek Main channel bridge 1 AL 5 3.3 0.73 2.5 B18 68 1961, 1979, 1990

1The bridge age for the railroad structures was estimated to be 75+ years old
Appendix B 51

Appendix B. Photographs of selected bridge-scour study sites in Alabama.

Figure B–1. Clear-water scour 

under relief bridge 1 at the Line 

Creek crossing of County Road 7, 

Bullock County, Alabama (see fig. 7, 

site 1, for location).

Figure B–2. Clear-water pier scour 

under relief bridge 1 at the Line 

Creek crossing of County Road 7, 

Bullock County, Alabama (see fig. 7, 

site 1, for location).

Figure B–3. Clear-water scour 

under the main channel bridge at 

the Line Creek crossing of County 

Road 7, Bullock County, Alabama 

(see fig. 7, site 2, for location).
52 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure B–4. Clear-water scour 

under relief bridge 1 at the Line 

Creek crossing of County Road 7, 

Bullock County, Alabama (see fig. 7, 

site 2, for location).

Figure B–5. Clear-water scour 

under the main channel bridge 

at the Williams Creek crossing of 

County Road 165, Bullock County, 

Alabama (see fig. 7, site 3, for 

location).

Figure B–6. Clear-water scour 

under the main channel bridge at 

the Brush Creek railroad crossing, 

Dallas County, Alabama (see fig. 7, 

site 4, for location).
Appendix B 53

Figure B–7. Clear-water scour 

under relief bridge 1 at the 

Chilatchee Creek crossing of 

Alabama Highway 5, Dallas County, 

Alabama (see fig. 7, site 5, for 

location).

Figure B–8. Clear-water scour 

under the main channel bridge at 

the Taylor Creek crossing of County 

Road 148, Greene County, Alabama 

(see fig. 7, site 6, for location).

Figure B–9. Clear-water scour 

under relief bridge 1 at the 

Cottonwood Creek crossing of 

County Road 12, Hale County, 

Alabama (see fig. 7, site 7, for 

location).
54 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure B–10. Clear-water scour 

under relief bridge 4 at the Big 

Swamp Creek crossing of U.S. 

Highway 80, Lowndes County, 

Alabama (see fig. 7, site 8, for 

location).

Figure B–11. Clear-water scour 

under the upstream main channel 

bridge at the Tallawassee Creek 

crossing of U.S. Highway 80, 

Lowndes County, Alabama (see fig. 7, 

site 10, for location).

Figure B–12. Clear-water 

scour under relief bridge 1 at the 

Chickasaw Bogue Creek crossing 

of Alabama Highway 28, Marengo 

County, Alabama (see fig. 7, site 12, 

for location).
Appendix B 55

Figure B–13. Clear-water scour 

under relief bridge 1 at the Line 

Creek crossing of County Road 2, 

Montgomery County, Alabama 

(see fig. 7, site 14, for location).

Figure B–14. Clear-water scour 

under relief bridge 1 at the Ramer 

Creek crossing of County Road 18, 

Montgomery County, Alabama 

(see fig. 7, site 15, for location).

Figure B–15. Clear-water scour 

under relief bridge 2 at the Ramer 

Creek crossing of County Road 

18, Montgomery County, Alabama 

(see fig. 7, site 15, for location).
56 Clear-Water Contraction Scour at Selected Bridge Sites in the Black Prairie Belt of the Coastal Plain in Alabama, 2006 

Figure B–16. Clear-water scour 

under relief bridge 3 at the Ramer 

Creek crossing of County Road 61, 

Montgomery County, Alabama 

(see fig. 7, site 16, for location).

Figure B–17. Clear-water 

scour under relief bridge 1 at the 

Alamuchee Creek crossing of 

Alabama Highway 17, Sumter County, 

Alabama (see fig. 7, site 19, for 

location).

Figure B–18. Clear-water scour 

under the main channel bridge at 

the Red Creek crossing of Alabama 

Highway 5, Wilcox County, Alabama 

(see fig. 7, site 25, for location).
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Lee and Hedgecock—Clear-Water Contraction Scour at Bridge Sites in the Black Prairie Belt in the Coastal Plain, Alabama, 2006—Scientific Investigations Report 2007–5260