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Coarse sediment transport in a bedrock channel with complexbed topography

Jaime R. Goode1 and Ellen Wohl2

Received 17 April 2009; revised 4 August 2010; accepted 18 August 2010; published 13 November 2010.

[1] Independent lithologic and structural controls in fluvial bedrock systems interact withcoarse sediment transport processes to play a key role in bedrock incision processes suchas abrasion. During a 3 year study on the Ocoee River in the Blue Ridge Province ofthe southern Appalachians, USA, we used painted tracer clasts to measure coarse sedimenttransport dynamics and address whether different scales of morphologic variability inbedrock channels lead to coarse sediment transport processes that differ from alluvialchannels. At the reach scale, folded metasedimentary units are exposed in the channel bedand appear as linear bedrock ribs that vary in amplitude and orientation to flow. Undersimilar flow conditions for which size‐dependent transport has been observed in alluvialchannels (dimensionless Shields stress within 1.5–2.0 times the dimensionless criticalshear stress), transport distance was a significant function of grain size where bedrock ribswere longitudinal to flow (Reach 1 and Reach 2). However, transport distance was not sizedependent where bedrock ribs were oblique to flow (Reach 3). At different intrareachscales, the variables characterizing the local bedrock topography and sediment architecturewere the best predictors of transport distance in all three reaches. Therefore, bed loadtransport processes may be influenced by bed forms in bedrock streams (bedrock ribs) butat potentially smaller scales than bed forms in alluvial channels. The strong influence ofbedrock ribs on coarse sediment transport suggested that coarse sediment transportprocesses are controlled by different factors in bedrock channels only when bedrock ribscross the channel at a high angle to the flow.

Citation: Goode, J. R., and E. Wohl (2010), Coarse sediment transport in a bedrock channel with complex bed topography,Water Resour. Res., 46, W11524, doi:10.1029/2009WR008135.

1. Introduction

[2] In order to constrain parameters required for landscapeevolution models [e.g., Howard, 1994; Whipple and Tucker,2002; Sklar and Dietrich, 2004; Turowski et al., 2007], recentstudies have focused on reach scale processes involved inbedrock channel incision [Johnson and Whipple, 2007;Finnegan et al., 2007; Chatanantavet and Parker, 2008;Johnson et al., 2009]. Particular attention has focused on theimportant role of bed load material in controlling incision viaabrasion in bedrock systems [Sklar and Dietrich, 1998, 2001;Hartshorn et al., 2002], illustrating the need to understand thedynamics of coarse sediment transport in bedrock channels.While an extensive literature describes coarse sedimenttransport processes at the reach scale in alluvial channels[e.g., Einstein, 1950; Beschta, 1987; Ferguson et al., 2002;Wilcock and Crowe, 2003; Parker, 2008], the reach scalecontrols on coarse sediment transport in bedrock channels arepoorly understood, except from a few experimental studies[Johnson and Whipple, 2007, 2010; Finnegan et al., 2007;

Chatanantavet and Parker, 2008], and even more limitedfield examinations [Johnson et al., 2009]. These studiesdocument interactions and feedbacks among sediment supply,localized transport, bedrock erosion rate, and channelmorphology. Although it is reasonable to assume that alluvialand bedrock channels have fundamentally different controlson coarse sediment transport, the details of these differentcontrols have not yet been explored and adequately quan-tified in the field. By examining the controls on coarsesediment transport in natural bedrock channels, we canimprove our understanding of the processes that controlbedrock incision by abrasion.[3] In the process of abrasion, saltating bed load acts to

scour bedrock surfaces by fine‐scale removal of bedrockmaterial. Abrasion is distinguished from other physical ero-sion processes such as plucking and macroabrasion, whichremove cobble‐ and boulder‐sized blocks from the bedrockchannel substrate [Hancock et al., 1998;Whipple et al., 2000;Chatanantavet and Parker, 2009]. Bedrock incision byabrasion is conditioned on the interplay between bed loadmaterial either providing the tools that promote abrasion andincision or being the cover that inhibits incision, dependingon the ratio of sediment supply to transport capacity [Gilbert,1877; Sklar and Dietrich, 1998, 2001; Turowski et al., 2007].The incision rate is maximized for intermediate sedimentsupply relative to the transport capacity, such that a sufficientamount of bed load tools are available for abrasion, and the

1Center for Ecohydraulics Research, University of Idaho, Boise,Idaho, USA.

2Department of Geosciences, Colorado State University, Fort Collins,Colorado, USA.

Copyright 2010 by the American Geophysical Union.0043‐1397/10/2009WR008135

WATER RESOURCES RESEARCH, VOL. 46, W11524, doi:10.1029/2009WR008135, 2010

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http://dx.doi.org/10.1029/2009WR008135

bed is not fully covered by alluvium. Whereas this thresholdconcept is simple, there are unconstrained details (e.g.,interactions between sediment transport and bedrock bedforms) that arise upon experimental examination [Johnsonand Whipple, 2007; Finnegan et al., 2007; Chatanantavetand Parker, 2008].[4] The saltation‐abrasion model [Sklar and Dietrich,

1998, 2004] incorporates the concepts of tools versus covereffects quantitatively by considering bed load supply andtransport. This model assumes a planar bed surface, andit does not incorporate channel morphology as a degreeof freedom. Natural bedrock channels, however, commonlydisplay high spatial variability in bed topography as a result ofsculpting and bedrock characteristics [Whipple, 2004;Richardson andCarling, 2005]. This variability has also beenshown to control local erosion rates [Hancock et al., 1998;Johnson andWhipple, 2007] and promote feedbacks betweenincision and bedmorphology [Finnegan et al., 2007; Johnsonand Whipple, 2007, 2010]. It is well documented from allu-vial systems that variation in bed topography largely influ-ences the local flow field [Furbish, 1993; Nelson et al.,1995; Papanicolaou et al., 2001], the dynamics of sedi-ment transport [Pyrce and Ashmore, 2003; Yager et al., 2007;Thompson, 2007], and spatial variation in the surface textureof bed sediments [Dietrich et al., 1989].[5] Sediment transport and deposition in bedrock chan-

nels are generally different from alluvial systems, in that(1) sediment loads are relatively low compared to transportcapacity, (2) highly turbulent flows are capable of trans-porting up to boulder‐sized particles for large distances, and(3) lateral hillslope connection directly supplies coarse sedi-ment through diffusive hillslope processes, landslides, rock-falls, or debris flows [Wohl, 1999; Whipple, 2004]. Bedrockcharacteristics (i.e., lithology and structure) also have a stronginfluence on channel geometry [Montgomery and Gran,2001; Whipple, 2004; Goode and Wohl, 2010], potentiallyregulating bed load transport.[6] In bedrock channels, sediment supply, grain size, and

bedrock detachment are all interrelated variables that tend tooffset variation in one another [Sklar and Dietrich, 2008].Roughness supplied from sculpted forms in bedrock systemsincreases form drag, which likely reduces the local shearstress [Shepherd and Schumm, 1974; Wohl and Ikeda, 1997;Wohl, 1998; Wohl et al., 1999; Johnson and Whipple, 2007;Finnegan et al., 2007; Turowski et al., 2007; Chatanantavetand Parker, 2008]. As a result, roughness may locallyreduce sediment transport capacity, such that the local bed-rock topography controls the spatial distribution of sedimenttransport. In this study, we examine how spatial heterogeneityat different scales controls the dynamics of coarse sedimenttransport in a bedrock channel with bed morphology that isinfluenced by lithologic and structural variation.[7] In alluvial channels, strong spatial and temporal var-

iability in bed load transport rates are explained by variabilityin transport over bed forms [Schmidt and Gintz, 1995;Thompson et al., 1996; Cudden and Hoey, 2003], temporalvariability in sediment supply [Beschta, 1987], variation inarmoring and sorting [Whiting et al., 1988], and burial andvertical mixing [Ferguson and Hoey, 2002; Ferguson et al.,2002]. The spatial and temporal controls on bed load trans-port in gravel bed streams have been characterized bytracking the movement of individually marked gravels [e.g.,Church and Hassan, 1992; Wilcock, 1997; Ferguson et al.,

2002; Lenzi, 2004]. Results from these tracer studies indi-cate that under moderate flow conditions, the structure ofthe bed sediment (i.e., variability in sediment size, sorting,and packing) is an important control on bed load transport,whereas the flow characteristics are the dominant control onbed load transport at higher flows [Ferguson and Wathen,1998; Lenzi, 2004]. Size selectivity in bed load transporttends to occur in either of two scenarios: (1) over a range offlows for particles that are unconstrained by interparticlepacking and fully exposed to the fluid forces or (2) at mod-erate flows, when the shear stress is slightly above thethreshold of motion for the median grain size, for particlesthat are constrained by interparticle contacts (i.e., imbri-cated and incorporated into the armor layer) [Church andHassan, 1992; Ferguson et al., 2002; Lenzi, 2004].[8] Here we use painted tracer clasts in order to examine

the controls on coarse sediment transport in a bedrockchannel with a high degree of spatial variability in bedtopography. We frame this study around a fundamentalquestion: Is coarse sediment transport in bedrock channelscontrolled by the same hydraulic conditions and sedimentproperties that control coarse sediment transport in gravelbed streams? Specifically, we seek to understand whatconditions (flow or sediment architecture), if any, lead tosize‐dependent transport. We address this question by testingthree specific alternative hypotheses. (H1) In all studyreaches, transport distance is a significant function of grainsize, D. (H2) Differences in coarse sediment transport dis-tance exist between study reaches can be explained by dif-ferences in reach scale hydraulics and bedrock topography.This second hypothesis is designed to test the idea that, iftransport distance is not size dependent, then observed dif-ferences in transport distance can be explained by reach scalevariations in bedrock channel bed morphology. (H3) Thelocal scale variability in bedrock channel topography andsediment architecture is the dominant control on transportdistance. This hypothesis is based on the assumption thatbedrock ribs in the channel examined here exert a strongcontrol on coarse sediment transport. We use the term coarsesediment transport rather than bed load transport because thenature of this study precludes determination of the mode oftransport. The focus is on coarse gravel, cobbles, and boulders(32 mm < D < 362 mm).

2. Study Area

[9] The study area is located in the Ocoee River gorge,Tennessee between the Tennessee Valley Authority (TVA)Ocoee No. 3 dam and the 1996 Olympic whitewater course(Figure 1). Here the Ocoee River flows through the BlueRidge Province of the Southern Appalachians, with a drain-age area of approximately 1300 km2. Although the gorge isdeeply incised, hillslopes exhibit limited bedrock exposureand are densely vegetated andmantled with thick soils typicalof humid temperate landscapes. Homogenous denudationrates (25 ± 5 m/Myr) over 104–105 year time scales [Matmonet al., 2005] characterize this tectonically quiescent region.Bedrock in this region consists of slates and metasandstonescontained within the Precambrian Ocoee Supergroup. Spe-cifically, bedrock exposures through the Ocoee River gorgeare the Precambrian‐age Sandsuck Formation in the westerngorge, which is composed of phyllites thinly interbeddedwith arkosic and calcareous quartzites; the Dean Formation,

GOODE AND WOHL: COARSE SEDIMENT TRANSPORT IN A BEDROCK CHANNEL W11524W11524

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composed of thinly bedded quartzites and phyllites; and theHothouse Formation, composed of metagreywacke and micaschist in the eastern gorge [Sutton, 1991]. Through the gorge,the rock units alternate between resistant ledges of meta-greywacke and quartzite and softer phyllite sequences.Because the channel meanders across the folded metamor-phic units at scales larger than the reach scale (Figure 1), theorientation of flow relative to the dip and lithology of thebedrock varies.[10] This lithologic and structural heterogeneity appears

in the channel bed as undulating rib‐like bedrock forms thatwe refer to as bedrock ribs. These bed forms are not uniqueto the Ocoee River [Goode and Wohl, 2010] but have notreceived much attention in the literature. In their report onsculpted forms in bedrock channels, Richardson and Carling[2005] describe similar structurally influenced features such

as concave sculpted joint furrows and bedding plane furrows.Bedrock ribs differ from these features as opposing topo-graphic features. Concave sculpted joint furrows and beddingplane furrows are long, narrow portions of bedrock thatprotrude above the surrounding bed, whereas bedrock ribs areasymmetrical in cross section, regardless of planform orien-tation, consistently oriented parallel to the metamorphicfoliation in the rock, and occasionally follow dominant joints.The strike of the bedrock ribs varies as the trend of the sinuouschannel changes downstream, which suggests that rib orien-tation is controlled by structural features in the underlyingfolded metasedimentary units. The occurrence of sculptedforms such as potholes (along the upstream and downstreamfaces of transverse bedrock ribs and in the troughs betweenlongitudinal bedrock ribs) suggests that abrasion is thedominant mechanism of fluvial incision in this system.[11] Alluvial material in this system consists of sand‐ to

boulder‐sized sediment, which covers roughly half of thechannel bed area in three distinct areas: discontinuous patches,the intervening lows between bedrock ribs, and within pot-holes. In isolated locations of the channel bed, this alluvialmaterial is armored by large cobbles and boulders. The wakezones of bedrock ribs tend to be associated with high con-centrations of well sorted, gravel‐sized material (Figure 2a).Sediment angularity ranges from very well‐rounded particleswithin potholes to slightly more angular particles across thechannel bed. This difference in angularity appears to reflectnot only the local hydraulic environment but also the litho-logic origin (phyllite produces more angular particles,whereas the metagreywacke corresponds to well‐roundedparticles) and fluvial transport distance.[12] After the closure of the Ocoee No. 3 dam in 1942,

the natural‐channel flow was diverted through a bypass tothe hydropower station downstream, beyond the study area.Since the 1996 Olympics, however, the TVA has guaranteedrecreational flows in this section of roughly 45 m3/s for 6 hon both Saturday and Sunday, from the last weekend inMay through the last weekend in August. Only exceptionalwinter stormflows that exceed the hydropower capacityare routed through the natural channel. Winter and springstorms produce flows for which the daily average releasesfrom the dam range from 40 to 60 m3/s, and peak flows canreach 800 m3/s. Infrequent flow releases and flow diversionhas led to woody vegetation establishment in many loca-tions of the channel bed. We intentionally avoided thesesections in this study.

3. Methods

[13] Three study reaches within the study area wereselected according to the dominant lithology and the orien-tation of the bedrock ribs to flow (Figure 1 and Table 1):Reach 1 (phyllite and longitudinal ribs), Reach 2 (meta-graywacke and longitudinal ribs), and Reach 3 (meta-greywacke and oblique ribs). A fourth reach, Reach 4(metagraywacke and transverse ribs), was initially includedin this study, but anthropogenic disruption of the experimentsforced us to eliminate it [Goode, 2009]. Longitudinal ribsvaried 0° ± 10° with respect to the main flow direction,transverse ribs were oriented 180° ± 10° with respect to flow,and oblique ribs occurred at all other angles to flow. Thelength of each surveyed reach was determined by the per-sistence of the rib morphology: reaches continued for as long

Figure 1. Digital Orthophoto of the Ocoee River studyarea [U.S. Geological Survey, 1997]. Reach boundaries areindicated by the solid white lines. The downstream variationof rib orientation can be seen in this areal photo of the drychannel bed, with black dashed lines indicating the riborientation. Reach boundaries are indicated with white lines.


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as the bedrock rib orientation and dominant lithology wasmaintained within a straight, single flow channel.[14] In each of the three study reaches, we used painted

tracer clasts, which we selected from the existing alluvialpatches. A total of 300 tracers were randomly selected usinga Wolman point count, where we paced the channel in aconceptual grid. While it is argued that this method tends tobias the sample toward the coarse grains [Kellerhals andBray, 1971], our interest was focused on sediment thatwas larger than coarse gravel (>32mm), which supported thevalidity and practicality of this selection approach in thisfield study. The pattern that we followed for this selectionprocedure allowed us to span the channel width severaltimes and capture both a representative distribution of par-ticle sizes and a wide range of depositional zones associatedwith the highly variable bedrock channel bed topography(i.e., grains that were located upstream and downstream ofbedrock ribs, in the thalweg, or in pools). If a selectedparticle was fully incorporated into the armor layer, suchthat the particle boundaries could not be seen, it was notincluded in the sample. This occurred for less than fivecobble‐ and boulder‐sized grains in each reach.

[15] For each tracer, we recorded the size (measured alongthe intermediate axis), applied a roughly 5 cm square patchof yellow concrete paint, and wrote the tracer number on thepaint patch with a black permanent marker. Care was takennot to disrupt the bed material when clasts were tagged withpaint. If the tracer was not incorporated in the armor layer, apaint patch and number were applied to a second side toincrease the likelihood of finding the tracer if it flipped overafter transport. A laser total station positioning system wasused to map the initial tracer locations. During this survey,the area within one grain diameter was visually assessed forits potential influence on the transport of a given tracer(Figure 2b). Five categories defined this local scale: uncon-strained (no surrounding particles or bedrock ribs protrudedabove the tracer), shielded (bedrock ribs protruded abovethe tracer, and likely interfered with transport), imbricated(surrounding particles constrained the movement), buried(required removing sediment in order to recover the tracer), orembedded (packed into the armor layer). Tracers that wereboth constrained by surrounding grains and bedrock ribs wereassigned imbricated and shielded.[16] In addition to the local scale, we defined two other

spatial scales within each reach: (1) cross‐section scale, withtracers linked to the nearest cross section, in the previoussurvey and (2) zone scale, with tracers linked to geomor-phically similar bed regions. The cross‐section scale wasquantified by the cross‐sectional averaged hydraulic metrics,obtained from the modeling results of Goode and Wohl[2010], wherein we applied the U.S. Army Corps ofEngineers (USACE) one‐dimensional flowmodel HEC‐RAS[U.S. Army Corps of Engineers (USACE), 2002] to iterativelydetermine the Manning’s roughness coefficients by matchingthe known discharges from the 2006 summer release flows(Q = 45 m3/s) and the surveyed water surface elevations ateach cross section. Using these Manning’s roughnesscoefficients, we used HEC‐RAS to model each peak dis-charge between tracer resurveys. Without known water sur-face elevations at the upstream and downstream reachboundaries for these peak flows, because we were not presentin the field area during these flows, we set the downstreamboundary condition to the normal flow depth. A sensitivityanalysis on the choice of the downstream boundary andresponse of the calculated hydraulic variables showed nosignificant difference (P > 0.05) in the hydraulic variables,especially in the upstream cross sections where the tracersexisted. This enhanced our confidence in the hydraulicmodeling results despite the uncertainty in the downstreamboundary conditions. Although supercritical flow likelyoccurs locally within each reach, model runs were performed

Figure 2. (a) Photograph illustrating the coarse sedimentdeposition in between bedrock ribs in Reach 3. (b) Tracerclast (circled) downstream of a bedrock rib in a localhydraulic environment classified as shielded. Tape measurefor scale. Arrows indicate flow direction. Photos were takenbetween summer release flows when the channel was dry.

Table 1. Summary of Differences in ReachMorphology, Lithology,Hydraulic Roughness, and Grain Size

Reach 1 Reach 2 Reach 3

Rib orientation to flow longitudinal longitudinal obliqueDominant lithology phyllite metagreywacke metagreywackeMean rib amplitude (m) 0.44 0.57 0.79Reach gradient 0.0075 0.0082 0.0106Manning’s n 0.059 0.075 0.094D16 (mm) 50 46 48D50 (mm) 115 100 150D84 (mm) 240 230 252


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assuming subcritical flow and typical step‐backwater calcu-lations were performed. The substantial protrusion of thebedrock ribs from the channel bed, which appear to exert adownstream hydraulic control, and the relatively shallow bedslopes, support this assumption of subcritical flow. The fol-lowing hydraulic variables were obtained from this modelingand used in both cross section and reach‐averaged scaleanalysis (Table 2): streamwise velocity u, total boundaryshear stress t, and unit stream power w.[17] To examine the effect of variable bed morphology on

coarse sediment transport within each reach, we dividedeach reach into four to six zones (∼500 m2) of contiguousand internally consistent bed morphology (e.g., an alluvialpatch with limited bedrock rib exposure versus a zone withsubstantial bedrock exposure and high amplitude bedrockribs). We visually defined these zones in the field and usedthe surveyed boundaries to assign each tracer to a givenzone after plotting the tracer locations and morphologicalzones. These zones typically did not span the channel width.Within each morphologic zone, we calculated the standarddeviation of the bed elevation Zstdev, from bed topographypoints that were sampled at a 1 m resolution. We also sur-veyed transects, orthogonal to the bedrock ribs, to calculatethe mean amplitude of the bedrock ribs A within each zoneand reach. These values provided a quantitative metric forcomparing the mesoscale variability in morphology.

[18] The locations of the recovered tracers were resur-veyed after each of four summer recreational flow releasesin 2006 (Qpeak = 47 m3/s) and two annual hydrographs withpeak flows Qpeak in 2007 and 2008 of 81 and 88 m3/s,respectively (Figure 3). Tracers were recovered by walkingthe channel in progression of the numbering sequence of theinitial installment. If a tracer was “missing” from its initiallocation, the surrounding channel was visually searched with-out disrupting the bed. We only searched for buried clasts inthe well‐sorted patches associated with bedrock ribs, wherewe suspected vertical mixing. Transport distance was calcu-lated as the linear displacement of a tracer between eachresurvey. During each resurvey, we visually categorized thelocal grain scale for each tracer. The corresponding mor-phologic zone and nearest cross section were determinedfrom the surveyed coordinates of each tracer after eachresurvey.[19] Tracers were considered mobile if the calculated

transport distance between surveys was greater than theparticle diameter. This accommodated for any error inherentto repeat surveys. We minimized this type of error by con-sistently reoccupying the setup location of the laser totalstation, so that the backsight did not exceed 5 mm in distanceor elevation. Also, we consistently surveyed the patch of painton the boulder‐sized tracers, which enhanced our confidencethat repeat surveys reliably documented the same location on

Table 2. Hydraulic Variables From HEC‐RAS Modeling of Peak Discharges in Each Reach Between Each Recovery

Variable

Summer 2006: Mean of FourResurveys 2007 Resurvey 2008 Resurvey

Reach 1 Reach 2 Reach 3 Reach 1 Reach 2 Reach 3 Reach 1 Reach 2 Reach 3

Qpeak (m3/s) 47 47 47 81 81 81 88 88 88

Manning’s n 0.06 0.08 0.09 0.06 0.08 0.09 0.06 0.08 0.09Velocity (m/s) 1.5 1.1 1.0 1.8 1.4 1.2 1.9 1.4 1.2Unit stream power (W/m2) 100 72 88 168 145 146 184 157 160Total boundary shear stress (N/m2) 87 75 108 115 123 140 123 129 147Shields parameter t*50 0.047 0.046 0.044 0.062 0.076 0.058 0.066 0.080 0.061D50 (mm) 115 100 150 115 100 150 115 100 150D50mobile (mm) 60 60 60 80 70 80 75 70 80

Figure 3. Annual hydrograph for Ocoee No. 3 for 3 years of study. Note the systematic fluctuations insummer recreational release flows. Hourly discharge data were obtained from the TVA.


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each tracer, and transport distances were not misrepresentedby inconsistent survey points.

4. Results

[20] The size distributions of tracers in the three reacheswere relatively similar (Figure 4), with median sizes D50 of115, 100, and 110 mm, respectively. This consistency allowedinterreach comparisons of transport dynamics without adjust-ing for differences in the bed material size distribution. In allthree reaches during the recoveries between summer flows inthe first year (2006), the recovery ratewas nearly 100%(Table 3).There were several cases in the 2007 and 2008 resurveyswherethe tracer number was indistinguishable. Renumbering andmeasurement, along with spatial comparison to the previousyear’s location, allowed for these tracers to be accurately

matched to the original number and included in the recovery.Despite these difficulties, recovery rates remained above 60%in all three reaches (61%, 63%, and 70%, respectively).

4.1. Grain Size‐Dependent Transport Distance

[21] An examination of the transport distance of mobiletracers after each recovery indicated trends in transport dis-tance and grain size were not consistent for all reaches, allrecovery periods, or for all grain size classes (Figure 5). In2006 and 2007, Reach 1 showed a decrease in transportdistance with increasing grain size, only for the finer tail ofthe size distribution (D < 54 mm, in D < 108 mm, respec-tively). Reach 2 also showed a similar trend in 2007, only forD < 108 mm. In 2008, this trend occurred in all three reachesfor D < 108 mm. Considering the cumulative transport dis-tance over the study period, Reach 2 and Reach 3 showed adecrease in transport distance for D < 152 mm. These grainsize threshold values, for which transport distance depends ongrain size, compare well to the size of the D50 within eachreach (Table 1 and Figure 4).[22] Transport distance was a significant function of grain

size only in Reach 1 and Reach 2 in 2007 (P < 0.01) andReach 1 in 2008 (P = 0.01), based on regression analyses ofnonbinned, log‐transformed data in each reach. Althoughthis result in these two reaches supported the alternativehypothesis that transport distance is a function of grain size,inconsistency in these relationships among all three reachesresulted in a failure to reject the first null hypothesis thattransport distance is not a function of grain size in all reaches.Lack of a significant result in all three reaches led to thesecond hypothesis, which investigated reach scale controls ontransport distance.

4.2. Interreach Variability in Transport Distance

[23] The size distributions of the tracers that were trans-ported during the entire study period were similar for all

Table 3. Summary of Transport Distances and Tracer Sizes Transporteda

Year Qpeak (m3/s) nmobile % Recovered Lmean (m) Lmax (m) LD50 (m) D50mobile (mm) DLmax (mm)

Reach 1 2006 (1) 48 81 99 0.38 ± 0.06 2.4 0.40 70 502006 (2) 47 166 99 0.27 ± 0.05 6.4 0.23 60 1102006 (3) 48 129 99 0.16 ± 0.01 1.2 0.10 50 752006 (4) 46 110 99 0.22 ± 0.04 3.7 0.58 55 552006 (mean) 47 122 99 0.3 ± 0.04 3.4 0.33 59 732007 81 142 77 3.5 ± 0.39 27 2.7 80 502008 89 68 61 4.7 ± 0.71 29 4.2 75 45Cumulative 266 4.2 ± 0.40 40 4.7 75 35

Reach 2 2006 (1) 48 117 99 0.2 ± 0.02 1.1 0.23 60 652006 (2) 47 86 99 0.27 ± 0.10 8.0 0.18 55 202006 (3) 48 73 99 0.2 ± 0.04 2.7 0.08 45 652006 (4) 46 94 99 0.16 ± 0.02 1.3 0.14 85 252006 (mean) 47 93 99 0.2 ± 0.04 3.3 0.16 61 442007 81 112 82 0.87 ± 0.13 7.4 0.81 70 252008 89 55 61 2.8 ± 0.81 26 2.5 70 105Cumulative 232 2.5 ± 0.26 29 2.5 80 20

Reach 3 2006 (1) 48 127 99 0.45 ± 0.06 4.0 0.38 55 902006 (2) 47 105 99 0.35 ± 0.06 5.2 0.32 50 852006 (3) 48 179 99 0.34 ± 0.04 4.2 0.28 75 202006 (4) 46 168 99 0.36 ± 0.03 3.1 0.40 70 502006 (mean) 47 145 99 0.4 ± 0.05 4.1 0.34 63 612007 81 130 73 1.2 ± 0.16 12 0.36 80 302008 89 69 70 1.9 ± 0.32 14 2.6 80 30Cumulative 227 2.3 ± 0.20 27 1.8 90 30

aLmean, mean transport distance for all tracers in the reach; Lmax, maximum transport distance of an individual clast; LD50, transport distance of themedian grain size; D50mobile, median grain size of mobile tracers only; DLmax, grain size of the farthest transported tracer.

Figure 4. Size distribution of painted tracers, which weresampled from the existing bed material in each reach.


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three reaches (Figure 6). Whereas the median grain size ofall the transported tracers, D50mobile, did not vary greatlyamong the three reaches, the corresponding transport dis-tance for tracers of that size, LD50, varied substantially, withthe largest LD50 in Reach 1 (Table 2). In the 2008 resurveyafter the largest peak flow (89 m3/s) and the longest durationof flows (Figure 3), LD50 in Reach 1 was roughly 2 times thedistance in Reach 2 and Reach 3 (LD50 = 4.21, 2.45, and2.55 m, for D50mobile = 75, 70, and 80 mm, respectively).Considering the sediment sizes and transport distances inte-grated over the entire 3 year study period the median grainsize mobilized varied slightly between the three reaches(75, 80, and 90 mm, respectively).[24] Reach‐averaged hydraulic data from HEC‐RAS

modeling of all peak flows are presented in Table 2. Thetrends in total boundary shear stress in each reach wereconsistent with the D50mobile in each reach. For example,Reach 3 was associated with the largest D50mobile, as wellas the greatest total boundary shear stress. The Shields

parameters for the D50 in each reach ranged from 0.04 to0.05 in the 2006 flows and from 0.06 to 0.08 for the 2007and 2008 peak flows.[25] Comparison of the distribution of transport distance

after the 2007 and 2008 recoveries indicated that more tra-cers were transported longer distances in Reach 1 (Figure 7).More tracers were transported shorter distances in Reach 3,whereas Reach 2 yielded an intermediate distribution oftransport distances. In all reaches, more tracers were trans-ported longer distances during the 2008 flows, which werelongest in duration and had the highest peak discharge in thestudy period. According to the Tukey HSD multiple com-parison tests on the log‐transformed mean transport distancebetween reaches, Reach 1 was consistently associated withsignificantly greater transport distances than the other tworeaches (Figure 8). Transport distances in Reach 2 and Reach 3were statistically similar after all resurveys. Hypothesis 2 waspartly rejected because the mean transport distances were notsignificantly different in all three reaches: transport distances

Figure 5. Transport distance versus the tracer size. Tracers are binned into 0.5� size diametric classes(� = −log2D (mm)), and transport distances represent the mean for all tracers in that size class, withcorresponding standard errors. Each plot shows results from that recovery period. The 2006 plot showsaverages for all four resurveys during summer release flows. The cumulative plot represents the totaltransport over entire study period.


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in Reach 1 were significantly different from the other tworeaches, but transport distances were not significantly dif-ferent in Reach 2 and Reach 3.

4.3. Intrareach Variability in Transport Distance

[26] Transport distance according to the three spatial scales(cross section, zone, local) was considered for the 2007 and2008 resurveys only, because these categorical variables fromthe four 2006 resurveys varied in each of the four resurveys.ANOVA of transport distance by cross‐sectional differenceswas not significant in either the 2007 or 2008 recovery periodin any of the reaches (Table 4). Within each reach, transportdistances did not differ significantly when the tracers weregrouped according to the cross section for which they werenearest to in the proceeding survey. This suggested that dif-ferences in cross‐section averaged hydraulics cannot accountfor differences in coarse sediment transport. In Reach 1,despite a nearly twofold difference in unit stream powerbetween two cross sections, mean transport distances of thegroups of tracers referenced to those cross sections, were notsignificantly different between these groups (Figure 9).[27] Considering the morphologically similar zones, sig-

nificant differences in mean transport distance were notconsistently controlled by zone scale differences in bedtopography (i.e., bedrock rib amplitude). In Reach 1, trans-port distance was significantly different in some of the zones,but not in the zones that we expected to correspond to thesedifferences (Figure 10, 2007). For example, the mean trans-port distance in the zone where the bedrock rib amplitude waslowest (A = 0.42 m) was not significantly different than themean transport distance of tracers in the zone where thebedrock rib amplitude was the highest (A = 0.65 m). For the2007 tracer recovery, the significant ANOVA results indi-cated zone scale differences in transport distance in Reach 1and Reach 3 (Table 4). Zone scale differences were notassociated with significantly different mean transport dis-tances in Reach 2 for 2007 or any reach for the 2008 recovery.The mean transport distances were not greater in bed regionswhere the bedrock rib amplitude A and standard deviation of

the bed topography Zstdev were relatively low, which indi-cated that at the zone scale, these metrics were not a signifi-cant control on transport distance. Also, in Reach 3, pairwisecomparison of all zones, using the Tukey HSD followingANOVA, indicated that the only zones with significantlydifferent mean transport distances had similar mean ribamplitudes (A = 0.65 and 0.69 m, respectively) and standarddeviations of the bed elevation (Zstdev = 0.33 and 0.36 m,respectively) within each zone. Within each reach, at thescale of morphologically similar zones, neither bedrock ribamplitude nor topographic variability controlled differencesin transport distance.[28] In all three reaches and for both recovery periods,

there was a strong relationship between transport distanceand the local scale characteristics (unconstrained, shielded,imbricated, buried embedded; Table 4). In Reach 1, particlesthat were unconstrained by surrounding grains and unob-structed by bedrock ribs were transported the greatest dis-tances (Figure 11). In some cases, particles that wereshielded by ribs were transported unexpectedly long dis-tances, which may have been a result of local turbulencefluctuations in the wake zones of ribs. Pairwise comparisonsof all local scale categories, using the Tukey HSD following

Figure 7. Cumulative distributions of transport distancesafter the 2007 and 2008 resurveys for all three reaches. Cor-responding flows are reported in Table 2.

Figure 6. Size distribution of mobile tracers from eachreach over the entire study period. Tracers were consideredmobile if transport distances were greater than one particlediameter in at least one resurvey period.


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ANOVA, consistently showed that the transport distance ofunconstrained tracers was significantly different (P < 0.05)from imbricated, shielded, or buried particles, in all threereaches and for both years. The significant difference intransport distance according to local scale distinctions pro-vided support for hypothesis 3. This hypothesis was morerigorously tested in a multiple regression analysis.[29] Multiple linear regression with model selection, based

on the minimum Akaike’s Information Criterion (AIC)[Burnham and Anderson, 2002] and adjusted R2, furthersupported that local scale characteristics explained the largestproportion of the variability in transport distance (supportinghypothesis 3). The parameters tested in these modelsincluded: tracer size D (mm), Reach (categorical), totalboundary shear stress t, (at the nearest cross section), meanrib amplitude within the morphologic zone, A, and the localscale (categorical). The best one‐parameter model includedonly local scale classification (P < 0.01 in both years; adjustedR2 = 0.45 and 0.20 for 2007 and 2008, respectively). Thebest two‐parameter model included the reach and local scale

(P < 0.01 in both years; adjusted R2 = 0.48 and 0.32 for2007 and 2008, respectively). Both parameters in these modelswere also significant at P < 0.01.[30] Recognizing that the local scale sediment character-

istics had the strongest influence on transport distance, wereexamined the relationship between transport distance andgrain size by stratifying the data according to local catego-ries (Figure 12). For the unconstrained tracers, transportdistance was a significant power function of grain size (L =aDb) in Reach 1 and Reach 2 in 2007 (P < 0.01, R2 = 0.54,and P < 0.01, R2 = 0.53). No other significant relationshipswere found for nonlinear regression analyses of grain sizeand transport distance.

5. Discussion

5.1. Controls on Transport Distance

[31] Transport distance was a significant function of grainsize in Reach 1 and Reach 2, but not in Reach 3. As onepossible explanation for this, bedrock ribs were oriented

Figure 8. Reach scale variation in transport distances. Years indicate the resurvey period. The box plotsindicate upper and lower quartiles as box ends, 10th and 90th percentiles as whiskers, and median valuesas the line within each box. Dots indicate values outside the 10th and 90th percentiles. Transport distanceswere log‐transformed for normality. Different mean transport distances are indicated by contrasting lettersabove each box (Tukey’s HSD following ANOVA on log‐transformed data, P < 0.05).


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parallel to flow in both of these reaches, leaving down-streamflow and sediment transport generally unobstructed(Figure 2a). In Reach 3, where bedrock ribs were obliqueto flow and of greater amplitude (Table 1), transport dis-tance was not a significant function of grain size after anyrecovery period (Figures 5 and 12). Because the trend intransport distance and grain size was not similar in Reach 3,where the bedrock rib characteristics were the most differ-ent from the other two reaches, it is likely that bedrock ribsinfluence sediment transport when they are oriented obliqueto flow. In Reach 3, the Manning’s roughness was sub-stantially larger than in Reach 1 and Reach 2, suggestingthat bedrock ribs account for a large proportion of the totalroughness. Hence, less of the total boundary shear stress isavailable for sediment transport in Reach 3. This may alsoexplain why Reach 3 did not show a trend in transportdistance with grain size in any of the recovery periods. Asa result, where bedrock ribs are larger in amplitude andoriented in a direction that obstructs flow and sedimenttransport, these bedrock bed forms exert the greatest controlon sediment transport.[32] The central finding from this field study (variable

bedrock topography (bedrock ribs) influences sediment trans-port distance) corresponds well with experimental observa-tions of sediment transport patterns in bedrock channels withspatial variation in bed topography [Johnson and Whipple,2007, 2010; Finnegan et al., 2007; Chatanantavet andParker, 2008]. In the field, the additional boundary rough-ness supplied by bedrock ribs most likely limits the amountof boundary shear stress required to transport coarse sedi-ment. This was apparent from the lower transport distancesin Reach 3 (oblique ribs and largest hydraulic roughness, n).Similarly, experimental studies have shown that erosional bedforms act to dissipate energy and reduce the sediment trans-port capacity [Johnson and Whipple, 2007; Finnegan et al.,2007; Chatanantavet and Parker, 2008].[33] In a comparison of variables thought to control

transport distance at different spatial scales, none of themodels selected in the multiple regression analysis explainedmore than 50% of the variability in transport distance.However, more variability was explained by the local scalebedrock topography and sediment architecture than therelationships of transport distance as a power function of

grain size. Also, grain size did not appear as a significantexplanatory variable in any of the models, which furtherindicates that in this bedrock river, bedrock rib character-istics at the reach scale, and variations in morphology andsediment architecture at the local scale, are the mostimportant controls on sediment transport.

5.2. Different Controls on Coarse Sediment Transportin Alluvial and Bedrock Channels

[34] It is well established that bed load transport is an eventdependent process and, whether or not transport distance issize dependent, is controlled by the flow conditions andsediment structure [e.g., Parker, 2008]. If size‐dependenttransport is governed by similar processes in alluvial andbedrock channels, then we would expect transport distanceto be size dependent when the Shields stresses t*50 are 1.5–2.0 times the dimensionless critical shear stress of the

Figure 9. Box plot comparing the transport distance oftracers linked to the nearest cross sections in Reach 1.(a) Transport distance (2007) by cross section (ANOVA,F = 1.77, P = 0.14). (b) Transport distance (2008) by crosssection (ANOVA, F = 1.15; P = 0.34), so comparison ofmeans was not appropriate. The box plots indicate upperand lower quartiles as box ends, 10th and 90th percentilesas whiskers, and median values as the line within each box.Dots indicate values outside the 10th and 90th percentiles.Hydraulic variables at each cross section: streamwise velocityu, total boundary shear stress t, and unit stream power w,were obtained from HEC‐RAS modeling of the peak dis-charge between recoveries [Goode and Wohl, 2010].

Table 4. Summary of ANOVA Analysis of Transport Distance byIntrareach Spatial Scalea

2007

XS ZONE LOCAL

F P F P F P

Reach 1 1.77 0.14 3.46 0.005 19.2 <0.0001Reach 2 0.52 0.47 0.76 0.47 8.9 <0.0001Reach 3 1.44 0.23 3.79 0.006 36.1 <0.0001

2008

XS ZONE LOCAL

F P F P F P

Reach 1 1.15 0.34 1.56 0.19 26.3 <0.0001Reach 2 0.22 0.64 0.93 0.40 19.3 <0.0001Reach 3 0.48 0.70 1.59 0.21 6.8 <0.0001

aBolded values indicate significance (P < 0.05). XS, cross‐section scale;ZONE, scale of morphologically similar bed zones; LOCAL, local scalecharacteristics.


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D50 t*c50, as demonstrated in gravel bed streams by Fergusonand Wathen [1998], Wilcock and Crowe [2003], and Parker[2008]. When the dimensionless Shields stresses werewithin this range for the 2007 and 2008 peak flows (t*50 =0.06–0.08, compared to for bedrock rivers t*c50 = 0.03)[Sklar and Dietrich, 2004], transport distance was sizedependent in Reach 1 (2007 and 2008) and Reach 2 (2007only), both of which have longitudinal ribs. Although thedimensionless Shields stress was also within this range inReach 3 for both years, size‐dependent transport did notoccur. This suggests that, in bedrock channels with bedforms that do not intersect the flow (longitudinal ribs) ,theprocesses controlling coarse sediment transport are similarto alluvial channels. However, in bedrock channels with bed

forms that intersect and obstruct the flow (oblique ribs),processes that control coarse sediment transport are notsimilar to alluvial channels. Furthermore, the transportdistance of unconstrained clasts in Reach 3 (oblique ribs)was not dependent on tracer size as has been reported inalluvial studies [Church and Hassan, 1992].[35] Similar to alluvial channels, where variations in

channel morphology and sediment structure at differentscales are an important control on variations in transportdistance [Ferguson et al., 2002; Lisle et al., 2000; Wilcockand Crowe, 2003], the variations in bedrock topographyalso control bed load transport differences, but at scalespotentially smaller than bed form scales of alluvial channels[Schmidt and Gintz, 1995; Thompson et al., 1996; Cuddenand Hoey, 2003]. In alluvial channels, long‐term storagecan occur through deposition in bars, zones of reducedvelocity, or clast burial [Ferguson and Hoey, 2002; Fergusonet al., 2002]. The bedrock reaches examined here behavesimilar to these alluvial systems, but it is the variation in

Figure 10. Box plot comparing tracer transport distanceby zone topographic metrics in Reach 1. (a) Transport dis-tance (2007) by zone (ANOVA, F = 3.46, P < 0.01). Signif-icant pairwise differences in means (P < 0.05) are indicatedby contrasting letters above each box (Tukey’s HSD follow-ing ANOVA on log transformed data). (b) Transport dis-tance (2008) by zone was not significant (ANOVA, F =1.56; P = 0.19), so comparison of means was not appropri-ate. The box plots indicate upper and lower quartiles as boxends, 10th and 90th percentiles as whiskers, and median va-lues as the line within each box. Dots indicate values outsidethe 10th and 90th percentiles. Zstdev is the standard deviationof the bed elevation within the bed zone, and A is the meanamplitude of bedrock ribs within that area. Boxes are inorder of increasing A from left to right.

Figure 11. Box plot comparing tracer transport distanceby local hydraulic environment classification in Reach 1.(a) Transport distance (2007) by local classification (ANOVA,F = 19.2; P < 0.01). (b) Transport distance (2008) by localclassification (ANOVA, F = 26.3; P < 0.01). Significant pair-wise differences inmeans (P < 0.05) are indicated by contrast-ing letters above each box (Tukey’s HSD following ANOVAon log transformed data). The box plots indicate upper andlower quartiles as box ends, 10th and 90th percentiles as whis-kers, andmedian values as the line within each box. Dots indi-cate values outside the 10th and 90th percentiles.


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bedrock morphology (bedrock rib geometry) that controlsvariability in transport distance. Because the unconstrainedtracers showed some size dependence in transport distance inReach 1 and Reach 2, but not in Reach 3, coarse sediment

transport may be influenced by factors that are similar toalluvial systems, only in bedrock rivers with relativelyhomogenous bed topography. On the other hand, if theunderlying bedrock lithology and structure create strong

Figure 12. Transport distance versus the tracer size segregated by local scale categories for each reachin 2007 and 2008. Transport distance is significantly (P < 0.05) correlated with grain size only for uncon-strained tracers in Reach 1 in both years and Reach 2 in 2007.


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heterogeneity in bed forms and channel morphology, thenlocal scale factors are the dominant control on sedimenttransport. The key difference is that bed forms in bedrockchannels can be partly controlled by independent processes(structure and lithology), whereas bed forms in alluvialchannels are directly related to the flow and sediment prop-erties. The bedrock ribs examined here exert a strong controlon transport patterns at the reach scale. Also, the finest spatialresolution of intrareach variability, which captures localvariation in bedrock ribs, was the best predictor of coarsesediment transport distance.

5.3. Temporal Scales and Resolution

[36] Although transport distance was not consistentlyrelated to grain size over the study period, it is possible thatat longer time scales transport distance varies more closelywith grain size. This is because local scale controls thatinfluence transport distance during single flows mightbecome less important when averaged over longer timespans that include multiple transport events.[37] The D50 of the unrecovered tracers was similar to the

D50 of the mobile tracers in the last resurvey. This suggeststhat unrecovered particles were transported, despite unknowntransport distances. It is uncertain whether these particleswere transported beyond the reach or moved to locationswithin the highly variable alluvial deposits and bedrockchannel bed topography (i.e., within potholes or betweenbedrock ribs). Although the recovery rates were relativelylarge between surveys, there are inherent difficulties in usingvisually identified tracers. For example, it was necessary torepaint and number most tracers each year because Sunbleaching and algal growth obscured the tracer number.[38] The shorter transport distances recorded after the four

summer 2006 flows (47 m3/s) may reflect the shorter tem-poral resolution, which facilitates documenting transportdistances that may be closer to the hop length of singletransport events. However, these flows were also half themagnitude of the yearly peak, after which larger transportdistances were measured. It is not clear how the magnitudeof individual flow peaks affects the integration of all flowevents. Complexity in coarse sediment transport in this sys-tem is also demonstrated by some clasts being transportedupstream (∼5m). These few upstream transport events alwaysoccurred in sites with substantial bedrock rib exposure, whichsuggests complex flow patterns in these areas. The turbulentflow structure that is typically associated with bed forms[Nelson et al., 1995; Papanicolaou et al., 2001] is likely toplay an important role in determining sediment transportdynamics.[39] Spatial variations in turbulence structure and thereby

sediment flux, which are not describable in terms of localbed shear stress, are important aspects of coarse sedimenttransport [Nelson et al., 1995; Papanicolaou et al., 2001].We consistently observed redistribution of gravel locatedin the lee of bedrock ribs. The gravel‐sized tracers in thishydraulic environment showed measurable transport dis-tances in each resurvey, but overall these particles typicallyremained within the same lee deposit. Tracer particles werecommonly buried within these deposits and recovery requiredsorting through the deposit. This observation is akin to gravelbed rivers [Ferguson et al., 2002], but instead of particlesbecoming buried as a result of variations in alluvial envi-

ronment, here, variations in bedrock morphology set up theconditions for burial and vertical mixing.

6. Conclusions

[40] This study demonstrates that lithologic and structuralcontrols on bedrock channel topography (bedrock ribs) exerta major control on the transport dynamics of coarse materialover time scales up to 3 year and spatial scales up to 102 m.A comparison of three reaches with different bedrock riborientations and amplitudes indicated that where bedrockribswere longitudinal to flow and of lower amplitude, transportwas less obstructed, which led to greater transport distancesthan in reaches where the bedrock ribs were oblique to flowand of larger amplitude. Under similar flow conditions forwhich size‐dependent transport has been observed in alluvialchannels (dimensionless Shields stress within 1.5–2.0 timesthe dimensionless critical shear stress), transport distance wasa significant function of grain size where bedrock ribs werelongitudinal to flow. Where bedrock ribs were oriented at ahigh angle to flow however, greater reach scale roughness andlower reach‐averaged velocity corresponded to lower trans-port distances with no relation to tracer size. Because localscale bedrock topography and sediment architecture corre-latedmost strongly with tracer transport distance, channel bedproperties at this scale (100–101 m) likely play a dominantrole in the transport of coarse sediment. The importance oflocal scale variables and the lack of size dependence on coarsesediment transport distance where bedrock ribs are orientedoblique to flow may limit the use of reach scale sedimenttransport formulas, developed for gravel bed streams, inbedrock channels with similar morphologic variability.

[41] Acknowledgments. This study was funded by the NationalScience Foundation grant EAR‐0507098. We thank William Stubblefield,William Lyons, and Roy Syrmanske for their valuable field assistance.Dmitri Hawk and the Tennessee Valley Authority supplied discharge recordsfor the Ocoee No. 3 dam. The manuscript benefited greatly from insightfuland thorough reviews by Phairot Chatanantavet and two anonymousreviewers. Kristen Jaeger and Kyle Nichols provided helpful reviews of anearlier draft.

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