scour depth at bridges: method including soil properties. i: maximum scour depth prediction

Scour Depth at Bridges: Method Including Soil Properties.I: Maximum Scour Depth Prediction

Jean-Louis Briaud, Dist.M.ASCE1

Abstract: Scour of the soil by flowing water around bridge supports is the number one reason for bridge collapse. Predicting the depth of thescour hole is an integral part of the bridge foundation design, as it impacts the depth of the piles. Indeed, the scour depth must be ignored in thevertical and horizontal resistance of the piles. This paper presents a method to calculate the maximum depth of the scour hole around bridgesupports when subjected to a constant water velocity. Most existing methods take into account the water velocity and the geometry of the ob-stacle but not the soil type. The method presented in this paper keeps those important variables and adds the paramount influence of the soilerosion characteristics. It is developed on the basis of 94 flume tests, some of them very large laboratory-scale tests, as well as dimensionalanalysis and experience. It applies to pier scour, contraction scour, and abutment scour. The method is evaluated by comparing the maximumscour depth predictions against measured data from 10 databases of pier, contraction, and abutment scour depths. DOI: 10.1061/(ASCE)GT.1943-5606.0001222. © 2014 American Society of Civil Engineers.

Author keywords: Bridges scour; Predicted depth; Measured depth; Pier scour; Contraction scour; Abutment scour.

Introduction

Collapse of bridges due to scour of the soil around the foundationis a worldwide problem, but it is particularly acute in the UnitedStates (Fig. 1). In some countries (such as Germany and France), theproblem has been addressed in design for a long time. In others(including the United States), it has only recently been incorporatedin everyday design. In theUnited States, the scourwake-up call camein the early hours of April 5, 1987, when the New York StateThruway bridge over Schoharie Creek collapsed during a majorflood (Fig. 2) and 10 people died after falling into the raging waters.The Federal HighwayAdministration reacted promptly by asking allstate DOTs to evaluate their bridges for scour and by preparing thefirst version of a design guideline document called Hydraulic En-gineering Circular 18 (HEC18) (Richardson et al. 1991).At the sametime, theNationalCooperativeHighwayResearchProgram (NCHRP)undertook to address many of the unanswered issues associated withscour prediction and countermeasures. From 1990 to 2010, manyresearch projects and associated design documents, including fiveversions ofHEC18 (Arnesonet al. 2012), have significantly advancedthe state of knowledge and the state of practice in bridge scourpredictions. The result is that the number of failures has decreasedsignificantly (Fig. 3), which demonstrates the value of research ininfrastructure safety.

At the beginning of the scour research process, the work wasdone by many talented hydraulic engineers including Richardsonand his colleagues at Colorado State University (CSU). To developa safe method to predict scour depth at bridges in a relatively shorttime, they used fine sand, because it was the easiest soil to manage in

large flume experiments. This led towhat is known today as the CSUmethod. This method was extremely useful for a good while, butafter some time, it left many engineers unsatisfied, if not frustrated,because the measured data on full-scale case histories demonstratedthat it was overly conservative on average. The main reason wasthat the method did not include a soil property characterizing the soilresistance to erosion, thereby giving the same scour depth whetherthe bridge was founded in fine sand or in weathered rock. Starting inthe mid-1990s, Briaud and his colleagues at Texas A&M University(TAMU) started to develop a method that would include soilproperties so that a proper distinction could be afforded to low- andhigh-erodibility soils. This required a large number of very time-consuming large-scale flume tests in clay and some in sand tocharacterize the influence of the geometry of the obstacle, flowproperties, and soil properties on the scour depth. This paper sum-marizes 20 years of effort to assemble this method, which will bereferred to as the TAMU-scour method, and to evaluate its precisionand accuracy. The TAMU-scour method is based on the followingelements.

Elements of the TAMU-Scour Method

In scour depth predictions, a distinction is made between pier scour,contraction scour, and abutment scour (Fig. 4). Pier scour occursaround the pier, because the water must accelerate to get around thepier while maintaining the same flow rate. Contraction scour occursacross the contracted cross section, because the water must accel-erate within the restricted cross section. Abutment scour occurs nearthe abutment, because the water must accelerate around the abut-ment. Note that, at the pier, the total scour depth is the sumof the pierscour and the contraction scour, whereas at the abutment, the totalscour depth is the abutment scour depth. Most equations available topredict these scour depths assume that the velocity is constant andlasts long enough to create the maximum depth of scour zmax. In fact,the velocity in a river is not constant, and each velocity does not lastforever. The depth of scour reached after a given sequence of ve-locities (hydrograph of velocity versus time) is called the final depthof scour zfinal. For a low-erodibility soil, zfinal can be much smaller

1Professor and Holder of the Buchanan Chair, Zachry Dept. of CivilEngineering, Texas A&M Univ., College Station, TX 77843-3136. E-mail:[email protected]

Note. Thismanuscript was submitted on February 10, 2014; approved onSeptember 19, 2014; published online on October 30, 2014. Discussionperiod open until March 30, 2015; separate discussions must be submittedfor individual papers. This paper is part of the Journal of Geotechnical andGeoenvironmental Engineering, © ASCE, ISSN 1090-0241/04014104(13)/$25.00.

© ASCE 04014104-1 J. Geotech. Geoenviron. Eng.

J. Geotech. Geoenviron. Eng.

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http://dx.doi.org/10.1061/(ASCE)GT.1943-5606.0001222


mailto:[email protected]

than zmax, and taking advantage of the time rate of erosion becomesimportant. For a high-erodibility soil, a single flood event may besufficiently long to create zmax, and the effort of calculating zfinalmay not be warranted. There are many equations, such as the CSUequation, to predict zmax based on the water velocity and the ge-ometry of the obstacle. The TAMU-scour method gives both zmax

and zfinal. The novelty of the zmax equation according to the TAMU-scour method is that, in addition to the velocity and the geometry ofthe obstacle, it includes a soil parameter, the soil critical velocity,which leads to different scour depths in different soils. For zfinal,the erosion rate is required, and the TAMU-scour method uses twoinput quantities to quantify that rate: the erosion function, char-acterizing the soil resistance and linking the erosion rate _z to theshear stress t at the soil-water interface, and the maximum shearstress tmax, characterizing the load at thewater-soil interface createdby the presence of the obstacle before the scour hole starts.

The TAMU-scour method predicts the depth of pier scour,contraction scour, and abutment scour separately. There are eightelements for the TAMU-scour method:1. Scour depth versus time equation z versus t;

2. Maximum scour depth zmax equations for a constant velocity(pier, contraction, abutment);

3. Erosion function determination _z versus t;4. Maximum shear stress around the obstacle tmax for a constant

velocity;5. Algorithm to accumulate the scour depth because of a series of

flood velocities;6. Algorithm to handle the scour depth accumulation in the case

of a layered system;7. Probability of exceedance of the predicted scour depth and

LRFD factors for a pile foundation;8. Software to automate all the calculations.Most of these steps represent contributions of new knowledge,

as Step 2 (without a soil property in the equation) was the only oneavailable to predict scour depth before the development of theTAMU-scourmethod. These contributions allow the engineer tomakepredictions of scour depth for different soils, for any velocity hydro-graph, for any layered system, including the probability of exceedanceof the predicted scour depth. In this article, Steps 1 and 2 are de-scribed. The companion paper describes Steps 3–8 (Briaud 2014).

Experimental Basis

The maximum scour depth equations for pier scour, contractionscour, and abutment scour were developed over many years of

Fig. 1. Causes of bridge failure in the United States (reprinted fromBriaud 2006)

Fig. 2.One of the Schoharie Creek bridge spans plunging into the creek(reprinted from Koob et al. 1987, with permission from New York StateThruway Authority)

Fig. 3. Benefit of research efforts in decreasing bridge scour failure(reprinted from Briaud 2006)

Fig. 4. Definition of pier scour, contraction scour, and abutment scour



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mostly large-scale laboratory flume tests (Fig. 5). During each ex-periment, the depth of scour was monitored, and the largest depth zwas plotted as a function of time t. It was found that these z-t curveswere well described by a hyperbolic model of the form (Fig. 6)

z ¼ t1_ziþ tzmax

(1)

where z 5 deepest scour depth observed at time t around the ob-stacle; _zi5 initial rate of scour (m=s); and zmax 5 asymptotic value ofthe hyperbola. The experiments were conducted by first choosinga reference case. This reference case was selected by first estab-lishing average full-scale conditions and then applying scaling laws

to determine the size of the obstacle to be tested in the flume, thewater velocity, and the water depth. The reference case was tested asa first experiment. Then, each parameter (e.g., pier width, waterdepth, attack angle) was increased or decreased from the referencevalue while keeping all other parameters the same. This processisolated the influence of each parameter. Once all the experimentswere conducted, dimensional analysis and regression analysis wereused along with engineering judgment and experience to optimizethe form of the root equation and each of the influence factors. Thetotal number of experiments is presented in Table 1 for the threescour types. The width of the flumes used for these tests ranged from4 to 0.45 m wide. Several types of sand and vacuum-extruded clayswere used, and the ranges of their properties are listed in Table 2.This set of flume tests represents a major effort over many years,because placing the clay beds would take approximately 1 month,and each experiment lasted at least another month. Yet, the numberof experiments and soil types is limited. This is why, once themethodwas completed, itwas evaluated by comparing predictions tofull-scale observations as well as other data; this is shown in the“Measured versus Calculated Maximum Abutment Scour Depth”section. The equations for zmaxðpierÞ, zmaxðcontÞ, and zmaxðabutÞ weredeveloped on the basis of the flume tests results, dimensionalanalyses, previous equations, and engineering judgment. They arepresented next.

Maximum Pier Scour Depth

The equation for zmaxðpierÞ is (Oh 2009) (Fig. 7)

zmaxðpierÞB9

¼ 2:2KpwKpshKpaKpsp

�2:6 ×FðpierÞ2FcðpierÞ

�0:7(2)

where zmaxðpierÞ 5 maximum depth of pier scour; B9 5 projectedwidth of the pier perpendicular to the flow; Kpw 5 water depthinfluence factor for pier scour depth; Kpsh 5 pier shape influencefactor for pier scour depth; Kpa 5 aspect ratio influence factor forpier scour depth (the aspect ratio L=B is the ratio of pier length Lover pier width B); Kpsp 5 pier spacing influence factor for pierscour depth; FðpierÞ 5 pier Froude number (defined later) based on

Fig. 5. Placement of the clay and abutment erosion experiment in a4-m-wide flume

Fig. 6. Scour depth versus time for an abutment erosion experimentin a 4-m-wide flume

Table 1. Experiments Performed at TAMU to Develop the TAMU-ScourDepth Prediction Method

Scour typeNumber of

experiments in clayNumber of

experiments in sand Reference

Pier 40 7 Gudavalli (1997)Kwak (2000)Li (2002)

Contraction 30 — Li (2002)Oh (2009)

Abutment 17 — Oh (2009)

Table 2. Range of Soil Properties for the Flume Tests Performed at TAMUto Develop the TAMU-Scour Depth Prediction Method

Soil type Property Value

Clay Plasticity index PI 14–40%Water content w 30–40%Undrained shear strength su 11–20 kPaCritical shear stress tc 0.5–0.8 Pa

Sand Mean grain size D50 0.1–0.6 mmGradation UniformCritical shear stress tc 0.1–0.5 Pa



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the approach velocity V1 and pier width B9; and FcðpierÞ 5 criticalpier Froude number based on critical velocity. This critical ve-locity or critical shear stress can be estimated from the mean grainsize D50 for coarse-grained soils (Briaud 2014, Figs. 6 and 7) andmeasured in an erosion device such as the erosion function ap-paratus (EFA) (Briaud et al. 2001) for fine-grained soils. It is alsopossible to use soil classification categories for an estimate of Vc

(Briaud 2014, Figs. 4 and 5) or a lower bound value (Briaud 2014,Figs. 6 and 7). The projected width B9 is given by

B9 ¼ B�cos uþ L

B× sin u

�(3)

where B9 5 projected width; B 5 pier width; L 5 pier length; andu5 attack angle, which is the angle between the flow direction andthe main direction of the pier.

The water depth influence factorKpw corrects for the fact that theterm in parentheses on the right-hand side of Eq. (2) was developedfor a pier in deep water. Deep water is defined as a water depth hwlarger than 1:43B9. If the water depth is shallower than 1:43B9, themaximum scour depth is reduced. The equation for Kpw is (Briaudet al. 2004)

Kpw ¼

8><>:

0:89

�hwB9

�0:33

forhwB9

, 1:43

1:0 else

(4)

The pier shape influence factor Kpsh is given in Table 3; it correctsfor the fact that the term in parentheses on the right-hand side ofEq. (2) was developed for a cylindrical pier.

The aspect ratio influence factor Kpa corrects for the fact that theterm in parentheses on the right-hand side of Eq. (2) was developed

for a cylindrical pier. This influence factor is taken care of by the useof the projected width B9 instead of B, so Kpa is always 1. The pierspacing influence factor Kpsp corrects for the fact that the term inparentheses on the right-hand side of Eq. (2) was developed for asingle pier. If another pier is placed within the influence zone of thefirst one, then the scour depth will be larger. The equation forKpsp is(Briaud et al. 2004)

Kpsp ¼

8><>:

2:9

�SB9

�20:91

forSB9

, 3:22

1:0 else

(5)

where S 5 pier spacing; and B9 5 projected width. Eq. (5) indicatesthat piers spaced more than 3.42 times the projected pier width fromeach other do not increase the scour depth at the pier. The pier Froudenumber FðpierÞ is given by

FðpierÞ ¼ V1ffiffiffiffiffiffiffiffiffiffig ×B9

p (6)

where V1 5 water velocity at the location of the pier if the pierwere not there; g 5 acceleration due to gravity; and B9

Fig. 7. Definition of pier parameters: (a) water depth effect; (b) pier spacing effect; (c) pier shape effect; (d) attack angle effect

Table 3. Correction Factor for Pier Nose Shape (Kpsh) (Data from Arnesonet al. 2012)

Shape of pier nose Kpsh

Square nose 1.1Round nose 1.0Circular cylinder 1.0Sharp nose 0.9



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5 projected width of the pier. The critical pier Froude numberFcðpierÞ is given by

FcðpierÞ ¼ Vcffiffiffiffiffiffiffiffiffiffig ×B9

p (7)

whereVc 5 critical velocity for the soil. The comparison between thescour depth predicted by Eq. (2) and the scour depth measured in theflume tests used to develop Eq. (2) is shown in Fig. 8.

Maximum Contraction Scour Depth

The equation for zmaxðcontÞ is (Li 2002) (Fig. 9)

zmaxðcontÞhwm1

¼ 1:27ð1:83Fm2 2FmcÞ (8)

where zmaxðcontÞ 5 maximum depth of contraction scour; hwm15 water depth in the main channel at the approach section (Zone 1)before the contracted zone; Fm2 5 Froude number for the mainchannel at the bridge in the contracted zone (Zone 2); Fmc 5 criticalFroude number for the main channel at the bridge. The Froudenumber Fm2 is given by

Fm2 ¼ V1=CRffiffiffiffiffiffiffiffiffiffiffiffighwm1

p (9)

where V1 5 velocity in the approach section; g 5 acceleration at-tributable to gravity; hwm1 5 water depth in the main channel at theapproach section; and CR 5 contraction ratio defined as

CR ¼ Q2Qblock

Q(10)

Fig. 8. Comparison between pier scour depths predicted by Eq. (2) and those measured in the flume tests used to develop Eq. (2)

Fig. 9. Definition of contraction scour parameters



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where Q 5 total discharge; and Qblock 5 part of the discharge Qblocked by the approach embankments. The critical Froude numberFmc is given by

Fmc ¼ Vmcffiffiffiffiffiffiffiffiffiffiffiffighwm1

p ¼ ðtc=rÞ0:5gnh0:33wm1

(11)

where Vmc 5 critical velocity for the soil in the main channel; g5 acceleration due to gravity; hwm1 5 water depth in the mainchannel at the approach section; tc 5 critical shear stress for the soilin themain channel; r5mass density of the soil; and n5Manning’scoefficient. Manning’s coefficient is a coefficient characterizing theroughness of the river bottom. Estimated values are given in Table 4.The comparison between the scour depth predicted byEq. (8) and thescour depth measured in the flume tests used to develop Eq. (8) isshown in Fig. 10.

Maximum Abutment Scour Depth

The equation for zmaxðabutÞ is (Oh 2009) (Fig. 11)

zmaxðabutÞhwf 1

¼ 243KashKaskKalKagR20:28f 2

�1:65Ff 22Ffc

�(12)

where zmaxðabutÞ 5maximum depth of abutment scour; hwf 1 5waterdepth in the floodplain in the approach flow next to the abutment;Kash 5 shape factor for abutment scour;Kask 5 skew angle influencefactor for abutment scour; Kal 5 influence factor that takes into

account the proximity of the abutment to the main channel; Kag

5 geometry of the channel influence factor for abutment scour; Rf 2

5 Reynolds number around the toe of the abutment; Ff2 5 Froudenumber around the toe of the abutment; and Ffc 5 critical Froudenumber for the soil near the toe of the abutment. The shape factorKash corrects for the fact that the term in parentheses on the right-hand side of Eq. (12) was developed for a wing-wall abutment(Fig. 11).

The values of Kash are

Kash ¼

8>>><>>>:

1:0 for wing-wall abutment

1:22 for vertical-wall abutment

0:73 for spill-through abutment with 2:1 slope

0:59 for spill-through abutment with 3:1 slope

(13)

The skew angle factor Kask corrects for the fact that the term inparentheses on the right-hand side of Eq. (12) was developed foran approach embankment that is perpendicular to the river bank(Fig. 11). If the embankment alignment is oblique to the river bank,then the abutment scour depth is different. The equation for Kask is

Kask ¼1:02 0:005ðju2 90�jÞ for 60�#u# 120�0:85 for other u-values

(14)

where u5 skew angle as shown in Fig. 11. The influence factor forthe proximity of the abutment to themain channelKal corrects for thefact that the term in parentheses on the right-hand side of Eq. (12)was developed for an abutment far away from the bank of the mainchannel.When the abutment is close to the bank of themain channel,the abutment scour depth becomes larger. The equation for Kal is

Kal ¼

8><>:

20:23

�Lf 2 Le

�hwf 1

þ 1:35 for

�Lf 2 Le

�hwf 1

, 1:5

1:0 otherwise

(15)

whereLf 5 length of thefloodplain;Le 5 length of the embankment;and hwf 1 5 water depth in the approach channel near the abutment.The channel geometry influence factor Kag corrects for the fact thatthe term in parentheses on the right-hand side of Eq. (12) wasdeveloped for a compound channel geometry. For a rectangularchannel geometry, the abutment scour depth is smaller. The valuesfor Kag are

Table 4.Manning Coefficient n in V 5 ð1=nÞR0:67h S0:5e with V the Velocity

in m=s, Rh the Hydraulic Radius of the Channel in m, and Se the Slope of theEnergy Line (m=m) (Data from Briaud 2013)

Roughness n (s ×m20:33)

Smooth clay surface 0.011Sand (D50 5 0:2 mm) 0.012Sand (D50 5 0:4 mm) 0.020Sand (D50 5 1 mm) 0.026Gravel (D50 5 2e64 mm) 0.028–0.035Cobble (D50 5 64e230 mm) 0.030–0.050Boulder (D50 . 230 mm) 0.040–0.070

Fig. 10. Comparison between contraction scour depths predicted by Eq. (8) and those measured in the flume tests used to develop Eq. (8)



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Kag ¼(1:0 for compound channel

0:42 for rectangular channel(16)

The Reynolds number Rf 2 is in the equation to respect the scalinglaws and the influence of size. It is defined as

Rf 2 ¼ Vf 2hwf 1n

(17)

where hwf1 5water depth in the approach channel near the abutment;n 5 kinematic viscosity of water (in 1026 m2=s); and Vf2 5 localvelocity near the abutment in the floodplain obtained as

Fig. 11. Abutment parameter definitions



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Vf 2 ¼

8>>>>>>>><>>>>>>>>:

Q0:5

A2for short setback

�Lf 2 Le

�# 5hwm1

�Qf 1

Af 2for long setback

�Le # 0:25Lf

�

linearly interpolated velocity betweenQ0:5

A2for

�Lf 2 LeÞ ¼ 5hwm1 and

Qf 1

Af 2for Le ¼ 0:25Lf otherwise

(18)

where Q0:5 5 flow in half the channel defined as the sum of halfthe upstream flow in the main channel, 0:5Qm1, plus the flow in thefloodplain immediately upstream of where the abutment is situated,Qf 1; hwm1 5 water depth in the main channel in the approach flow;A2 5 area in the contracted zone corresponding to the flow Q0:5;Af 2 5 flow area on the floodplain at the contracted section; Lf5 width of the floodplain in the approach zone; and Le 5 length ofembankment leading to the abutment.

The Froude number Ff 2 is calculated around the toe of theabutment and is given by

Ff 2 ¼ Vf 2ffiffiffiffiffiffiffiffiffiffiffighwf 1

p (19)

where Vf 2 5 defined in Eq. (12); g 5 acceleration due to gravity;and hwf 1 5 water depth in the approach flow near the abutment.The critical Froude number Ffc is calculated around the toe of theabutment and is given by

Ffc ¼ Vcffiffiffiffiffiffiffiffiffiffiffighwf 1

p (20)

where Vc 5 critical velocity for the soil around the toe of theabutment; g5 acceleration due to gravity; and hwf1 5water depth inthe approach flow near the abutment. The comparison between thescour depth predicted by Eq. (12) and the scour depthmeasured in theflume tests used to develop Eq. (12) is shown in Fig. 12.

Measured versus Calculated Maximum PierScour Depth

To evaluate the accuracy of the maximum scour depth equations,databases independent from the experiments used to develop themethod were sought. For pier scour, two databases were identifiedwhere sufficient data were available (Froehlich 1988; Muellerand Landers 1996). The soils associated with these databaseswere primarily coarse-grained soils; no database with primarily fine-grained soils could be found. These two databases have very good piergeometry data, average flow data, and poor soil data withoutcritical shear stress or river bottom roughness. The velocity reportedin the databases was obtained from the highest flood recorded bya flow gauge when one was available. In this case, the highest waterdepth was used together with the estimated channel slope,

Fig. 12. Comparison between abutment scour depths predicted by Eq. (12) and those measured in the flume tests used to develop Eq. (12)

Table 5. Range of Hydraulic and Geotechnical Characteristics in Froehlich (1988) and Mueller and Landers (1996)

Reference Parameter B9 (m) L (m) u (degrees) hw (m) V1 (m=s) D50 (mm) Measured zðpierÞ (m)

Froehlich (1988) Maximum 19.50 38 35 19.5 3.67 90 10.4Average 3.25 10.07 5.66 4.19 1.57 13.03 1.9Minimum 0.29 0.98 0 0.43 0.15 0.01 0.15

Mueller and Landers (1996) Maximum 4.27 27.43 43 12.62 4.08 108.00 7.65Average 1.15 10.46 4.29 4.09 1.31 14.2 0.81Minimum 0.29 2.44 0 0.12 0.15 0.17 0



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roughness, and cross section geometry to back-calculate the ve-locity. If no flow gauge was available, then extrapolation of datafromnearbygaugeswas used.This process lead to uncertainties in thevelocity values in the database. The critical shear stress used in thepredictions was obtained from the value of D50 for coarse-grained

soils and through classification for fine-grained soils (Briaud 2013,Sections 23.1–23.5). The ranges of hydraulic and geotechnicalcharacteristics in the two databases are summarized in Table 5,and Fig. 13 shows the comparison of the predicted maximum pierscour depths to the field measurements in Froehlich (1988) andMueller and Landers (1996). The comparison shows that thescatter is very large but that generally Eq. (2) gives safe pre-dictions. In many cases, the predictions are larger than themeasurements, and this may be because of the fact that the erosionrate of the soil was low enough or the biggest flood did not lastlong enough for the scour hole to reach the maximum scour depth.In other words, the predicted value is the maximum scour depth,but themeasured valuemay not be; this would explainmany of theconservative predictions. In fewer cases, the predictions are lowerthan the measurements, and this could be attributable to over-estimating the critical shear stress or critical velocity. Part of thescatter is likely attributable to the uncertainties in the data in thedatabase (velocity, soil critical velocity, and scour rate) and thelimitations of the model. Overall, the comparison shows thatgenerally Eq. (2) gives safe predictions and that multiplying thepredictions by a factor of 1.5 minimizes the number of cases wherethe predictions are smaller than the measurements. Note that onFig. 13 the line with FS 5 1.5 represents the location of the lineseparating overpredictions and underpredictions should the pre-dicted maximum scour depth value be multiplied by 1.5. Note alsothat the predictions by the HEC18 sand method (Arneson et al.2012) compared with themeasurements in theMueller and Landers(1996) database are presented in Briaud et al. (2014).

Fig. 13. Predicted maximum pier scour depth versus measured pierscour depth for Froehlich (1988) database and Mueller and Landers(1996) database

Table 6. Summary of Hydraulic and Geotechnical Characteristics of Previous Flume Tests for Contraction Scour

Reference D50 (mm) V1 (m=s) hw1 (mm) L1 (m) L2 (m) Vc (m=s) Measured zðcontÞ (mm)

Komura (1966) 0.35–0.55 0.173–0.247 28–84 0.4 0.1–0.2 0.242–0.291 34–75Gill (1981) 0.92–1.53 0.24–1.53 27–84 0.76 0.5 0.292–0.423 24–49Webby (1984) 2.15 0.213–0.373 89–131 1.586 0.524 0.494–0.527 69–105Lim (1993) 0.47 0.208–0.223 24–28 0.4 0.12–0.26 0.245–0.252 16–56

Note:hw1 5water depth at the approach section and is equal tohwm1 in rectangular channels;L1 5 channelwidth of the approach section;L2 5 channelwidth of thecontracted bridge section; Vc 5 critical velocity of the riverbed material and is equal to Vmc in rectangular channels; V1 5 average flow velocity in the approachsection.

Fig. 14. Predicted versus measured maximum contraction scour depths for Komura (1966), Gill (1981), Webby (1984), and Lim (1993) databases



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Measured versus Calculated Maximum ContractionScour Depth

For contraction scour, no full-scale databases could be found;however, a number of flume test databases were identified, includingKomura (1966), Gill (1981), Webby (1984), and Lim (1993). Theflume tests were performed in rectangular cross section channels,and the soils used were clean coarse-grained soils with D50 rangingfrom 0.35 to 2.15 mm. As in the case of the pier scour databasepredictions, the critical shear stress or critical velocity used in thecontraction scour predictions was obtained from the value of D50

using the recommendations of Briaud (2013, Sections 23.1–23.5).The ranges of hydraulic and geotechnical characteristics in thosedatabases are summarized in Table 6. Comparisons between mea-sured and predicted contraction scour depths are shown on Fig. 14.

The comparison shows that the predictions are slightly largerthan the measured values on average. It also shows that the scatter is

much smaller than in the case of the full-scale pier scour database.Although the drawback of a flume test database is that the tests aresmall-scale scour tests, the advantage is that the data aremuch higherquality than the full-scale data of the pier scour databases. The resultof the increased precision and completeness of the data is a muchreduced scatter in the comparison. In fact, the scatter is similar to thescatter for the calibration of the method against the TAMU flumetests (Fig. 10). Note that the TAMU flume tests were performedmostly on fine-grained soils, whereas the databases in Fig. 14 are forcoarse-grained soils. This gives some confidence that themethod canbe used for both soil types.

Measured versus Calculated Maximum AbutmentScour Depth

Three series of abutment scour databases from flume tests collectedby Froehlich (1989), Sturm (2004), and Ettema et al. (2008) and one

Table 7. Summary of Hydraulic and Geotechnical Characteristics of Previous Flume Tests for Abutment Scour

Reference Range value Le (m) hwf 1 (m) Vf 1 (m=s) Vf 2 (m=s) D50 (mm) Measured zðabutÞ (m)

Froehlich (1989) Maximum 1.13 0.5 0.62 1.02 3.30 0.411Average 0.34 0.11 0.31 0.43 1.05 0.154Minimum 0.02 0.03 0.10 0.11 0.29 0.003

Sturm (2004) Maximum 3.66 0.11 0.36 0.64 3.30 0.317Average 2.13 0.06 0.24 0.42 2.96 0.181Minimum 0.80 0.03 0.10 0.27 1.10 0.012

Benedict and Caldwell (2006) Maximum 485.42 4.57 1.22 3.97 0.99 5.486Average 93.19 1.98 0.33 1.40 0.14 0.717Minimum 5.61 0.30 0.03 0.11 0.003 0.000

Ettema et al. (2008) Maximum 2.76 0.15 0.33 1.03 0.45 0.370Average 1.68 0.15 0.33 0.61 0.45 0.282Minimum 0.56 0.15 0.33 0.38 0.45 0.170

Fig. 15. Predicted maximum abutment scour depth versus measured maximum abutment scour depth



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series of field measurements in the Piedmont region of SouthCarolina by Benedict and Caldwell (2006) were obtained throughliterature review. Froehlich (1989) collected and analyzed abut-ment scour measurements taken by other researchers in rectangularchannels in different laboratory flumes. Sturm (2004) conductedflume tests in a compound channel using three different types ofsands in three different setback conditions: long setback where theabutment is far from the main channel, short setback where theabutment is close to the edge of the main channel, and intermediatesetback. In Ettema et al. (2008), 11 flume tests were selected. Otherabutment scour tests by Ettema et al. (2008) were not used, becausethose tests focused on erosion of the abutment, not the scour hole infront of the abutment. The TAMU-scour method applies to thescour hole developing in front of protected abutments.

The ranges of hydraulic and geotechnical characteristics in thosedatabases are summarized inTable 7. For the three flume test studies,

the soil was coarse grained, and the critical velocity was obtainedfrom the D50 value of the soil. For the full-scale study by Benedictand Caldwell (2006), the same approach was followed for coarse-grained soils, but some of the soils were fine grained. For those soils,the critical velocity cannot be estimated from D50 and was insteadestimated from the soil description and classification when given.

The measured scour depths in those databases are compared withthe scour depths calculated with the maximum abutment scourdepth equation [Eq. (12)] in Figs. 15–18. The comparisons showthat there is scatter in the data in all cases, that applying a factorequal to 1.5 to the predicted value is wise, and that, with this factor,most calculated values are equal to or larger than the measuredvalues. The scatter for the full-scale observation by Benedict andCaldwell (2006) is larger than the scatter for the flume tests as is thecase for other comparisons. This is in part due to the fact that thefield velocity associated with the observed scour depth can only be

Fig. 16. Predicted maximum abutment scour depths versus measured abutment scour depths in Sturm (2004)

Fig. 17. Predicted maximum abutment scour depths versus measured abutment scour depths in Ettema et al. (2008)



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estimated. For Benedict and Caldwell (2006), two sets of calcu-lations were made: one using the 100-year flood, which may ormay not have occurred, and one using the estimated highest ve-locity during the life of the bridge. In Figs. 15–18, S.T., W.W., andV.W. represent spill-through, wing-wall, and vertical-wall abutments,respectively. In Fig. 16, short, inter, and long stand for short setback,intermediate setback, and long setback, respectively. In Fig. 18,Q100 represents the discharge corresponding to the 100-year flood,and historic data corresponds to the maximum historic discharge.

Conclusions

A new method is proposed to predict the maximum scour deptharound bridge supports including piers and abutments in all soils.The method predicts pier scour, contraction scour, and abutmentscour depth. It has the advantage over current methods of includinga soil property: the critical velocity or critical shear stress. The othermain parameters are the water velocity through the Froude numberand the characteristic dimension of the obstacle. The method isbased on 94 flume tests including some large-scale flume tests. Theflume tests were mostly in low-plasticity clays but also in fine sands.It is also based on dimensional analysis and experience. Regressionanalysis indicates that theR2-coefficient for the comparison betweenpredicted values and measured values in the flume tests used todevelop the equations varies between 0.8 and 0.9. The method isevaluated by using 10 databases of measured scour depths in-dependent from the databases used to develop the equations; sevenare laboratory flume test databases, and three are full-scale data-bases. The comparisons between predicted and measured scourdepth for these 10 databases indicate that multiplying the predictedvalues by a factor equal to 1.5 keeps most of the measured data onthe safe side and essentially converts the prediction method into adesign method. The next step could be a proper risk-based design assuggested by Briaud et al. (2014). The predicted versus measuredplots also indicate that the scatter is less for the comparison withlaboratory studies and more for the comparison with full-scalestudies. Some of the reasons given for this increased scatter arethe lack of site-specific soil erodibility information and the lack ofreliability on the velocity associated with the scour depth

observations. There is a need for a few high-quality full-scalemeasurements in bridge scour. This article describes a method tocalculate themaximumdepth of scour, but this depth is not necessarilyreached during a flood if the soil erodes sufficiently slowly. There isa need for a method to predict the development of the scour depth asa function of time (velocity hydrograph) and for layered soil deposits.This is the topic of Briaud (2014).

Acknowledgments

The author acknowledges all the Ph.D. students who worked onthis topic over the years. In chronological order they are RaoGudavalli, Kiseok Kwak, Prahoro Nurtjahyo, Yiwen Cao, YaLi, Jun Wang, Seung Jae Oh, Xingnian Chen, Anand Govindas-amy, and Congpu Yao. The author also thanks the main agenciesthat sponsored this work over the years: the Texas DOT (JohnDel-phia and Mark McClelland), NCHRP (Tim Hess), and his col-leagues at TAMU (Hamn-Ching Chen and Kuang-An Chang).

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http://dx.doi.org/10.1061/(ASCE)1090-0241(2001)127:2(105)

http://dx.doi.org/10.1061/(ASCE)1090-0241(2001)127:2(105)

scour depth at bridges: method including soil properties. i: maximum scour depth prediction

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