CONTRIBUTION OF IN-CHANNEL PROCESSES TO SEDIMENT …...CONTRIBUTION OF IN-CHANNEL PROCESSES TO SEDIMENT YIELD OF AN URBANIZING WATERSHED1 Lisa M. Fraley, Andrew J. Miller, and Claire

CONTRIBUTION OF IN-CHANNEL PROCESSES TO SEDIMENTYIELD OF AN URBANIZING WATERSHED1

Lisa M. Fraley, Andrew J. Miller, and Claire Welty2

ABSTRACT: A study was conducted between September 2003 and September 2006 to obtain baseline sedimentinventories and monitor sediment transport and storage along a 3.7 km length of the channel of Valley Creekwithin Valley Forge National Historical Park, Pennsylvania. Valley Creek is a tributary of the Schuylkill Riverand drains an urbanizing 60.6 km2 watershed that currently has 18% impervious land cover. Numerous fieldmethods were employed to measure the suspended sediment yield, longitudinal profile, cross-sections, banklines,and particle size distribution of the streambed. Suspended sediment yield for the watershed was measured at aUSGS gage located just upstream of the park boundary between July 2004 and July 2005, the period corre-sponding to field surveys of bank erosion and channel change. The estimated suspended sediment yield of95.7 t ⁄ km2 ⁄ year is representative of a year with unusually high discharge, including a storm event that pro-duced a peak of 78 m3 ⁄ s, the second highest discharge on record for the USGS gage. Based on the medianannual streamflow for the 24 years of record at the USGS gage from 1983 to 2006, the median annual sedimentyield is estimated to be closer to 34 t ⁄ km2 ⁄ year, considerably lower than median and mean values for other siteswithin the region. The mass of silt, clay, and fine sand derived from bank erosion along the 3.7 km study reachduring the field survey period accounts for an estimated 2,340 t, equivalent to about 43% of the suspended sedi-ment load. The mass of fine sediment stored in the bed along the study reach was estimated at 1,500 t, withabout 330 t of net erosion during the study period. Although bank erosion appears to be a potentially dominantsource of sediment by comparison with annual suspended sediment load, bed sediment storage and potential forremobilization is of the same order of magnitude as the mass of sediment derived from bank erosion.

(KEY TERMS: suspended sediment load; erosion; urbanization; watershed; sedimentation; turbidity monitoring.)

Fraley, Lisa M., Andrew J. Miller, and Claire Welty, 2009. Contribution of In-Channel Processes to SedimentYield of an Urbanizing Watershed. Journal of the American Water Resources Association (JAWRA) 45(3):748-766. DOI: 10.1111/j.1752-1688.2009.00320.x

INTRODUCTION

Changes in biological and physical characteristicsof a stream channel can occur when large quantities

of sediment are introduced into a system previouslycarrying small quantities of suspended and bed-loadmaterials. Potential physical changes include deposi-tion of channel bars, coarsening of suspended sedi-ments, and bank erosion as a result of deposition

1Paper No. JAWRA-07-0164-P of the Journal of the American Water Resources Association (JAWRA). Received December 2, 2007; acceptedDecember 1, 2008. ª 2009 American Water Resources Association. Discussions are open until six months from print publication.

2Respectively, Research Specialist (Fraley), Center for Watershed Protection (Lisa Fraley-McNeal), 8390 Main Street, 2nd Floor, EllicottCity, Maryland 21043; Associate Professor, Department of Geography and Environmental Systems (Miller) and Professor of Civil and Envi-ronmental Engineering and Director, Center for Urban Environmental Research and Education (Welty), University of Maryland BaltimoreCounty, Baltimore, Maryland (E-mail ⁄ Fraley: [email protected]).

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within the channel, obstruction of flow and increasedflooding, and shifting configurations of the channelbottom (Wolman and Schick, 1967). Biologicalchanges may include blanketing of bottom dwellingflora and fauna, alteration of the flora and fauna as aresult of light transmission changes and abrasiveeffects of sediment, and alteration of fish species as aresult of changes produced in the flora and faunaupon which the fish depend (Wolman, 1967).

Over the past 250 years, the hydrology and sedi-ment supply of Piedmont watersheds has varied sub-stantially due to changes in land use, as documentedby Gupta and Fox (1974), Jacobson and Coleman(1986), Pizzuto et al. (2000), and Walter and Merritts(2008). Sediment yields from areas undergoing con-struction can be up to several hundred times greaterthan from rural lands or woodland (Wolman andSchick, 1967). After development is complete,increased runoff from urban areas may contribute tochannel and bank erosion (Wolman, 1967). For anurban stream in southern California, Trimble (1997)found that channel erosion contributed about two-thirds of the total sediment yield. A study by Pizzutoet al. (2000) compared eight urban and rural water-sheds in the Piedmont physiographic province ofsoutheastern Pennsylvania and concluded that thebed, banks, and hillslopes are contributing sedimentsources. Bed material continues to be supplied tothese channels, even after decades of urbanizationand with the upland surfaces of the urban catch-ments covered with nonerodible impervious surfaces.Allmendinger et al. (2007) calculated a sediment bud-get for the period 1951-1996 for a small (4.05 km2)watershed in Montgomery County, Maryland, andfound that upland erosion, channel enlargement, andfloodplain storage are all approximately equal compo-nents of the sediment budget.

While the importance of sediment has been recog-nized in the scientific community, limited sedimentdata is available over long periods of record. Fundingpriorities in the United States (U.S.) have not empha-sized the collection of sediment data at stream gagelocations. Most estimates (including those cited above)are based on proxy evidence rather than continuousmonitoring of sediment loads. This study includesestimates of sediment yield based on continuous moni-toring of turbidity at a USGS stream gage, as well asdirect measurement of changes in the bed and banksof the stream. The purpose of the study was to investi-gate multiple components of the sediment budget,including bank erosion as a sediment source, and themass of fine sediment stored and remobilized from thestreambed, in relation to estimates of the annual sus-pended sediment load. Although floodplain storage isrecognized as an important component of the sedi-ment budget during years when there are large floods,

it was not measured as part of this investigation. Thedata collected have been provided to the NationalPark Service as a baseline dataset against whichfuture site conditions can be compared.

VALLEY CREEK WATERSHED

The study area for this investigation was the3.7 km portion of Valley Creek in Valley ForgeNational Historical Park (VAFO), Pennsylvania, nearthe confluence with the Schuylkill River (Figure 1).Several locations in the channel are unstable andexperiencing rapid bank erosion. Channel morphologyalong some parts of Valley Creek has changed andcontinues to do so in response to changes in sedimenttransport, deposition, and erosion (Reed, 1991; Gu-towski and Stauffer, 1996; CCWRA et al., 2004).Streambank destabilization has accelerated recently,leaving Route 252 and the Valley Creek hiking trailthat are adjacent to the creek in danger of beingeroded by a severe storm. The altered hydrology andrecent channel instability are believed to result fromupstream urbanization, as the reach within the parkhas remained undeveloped.

Valley Creek is a third-order stream that is tribu-tary to the Schuylkill River and lies in the Piedmont

FIGURE 1. Location Map for Valley Creek Watershed.

CONTRIBUTION OF IN-CHANNEL PROCESSES TO SEDIMENT YIELD OF AN URBANIZING WATERSHED

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 749 JAWRA

physiographic province, about 32 km west of Phila-delphia, Pennsylvania, within the Delaware Riverbasin. The creek drains a 60.6 km2 area and includesan estimated 55 km of streams (CCWRA et al., 2004).Average annual rainfall for 133 years of recordthrough 2004 in Philadelphia is 104.5 cm (NCDC,2005). The average annual discharge between the1983 and 2006 water years as recorded by USGSstream Gage 01473169, which drains 53.8 km2 of thewatershed, is 0.9 m3 ⁄ s (USGS, 2008). The valley flooris underlain by carbonate rocks, including limestoneand dolomites, and is flanked by hills of less erodiblecrystalline rock, mostly quartzite, schist, and gneiss(Bascom and Stose, 1938). The stream has an averagegradient of 1.2% and is dominated by cobbles andgravel, with deposits of sand and silt. Exposed bed-rock is present in some sections of the channel. Over75% of the entire length of Valley Creek is character-ized as either runs or riffles.

Characteristics of the channel profile are relatedto natural and anthropogenic controls (Figure 2).Anthropogenic structures include: (1) an old cottonmill dam demolished in 1920, referred to as thebreached dam on Figure 2, about 350 m upstream ofthe confluence with the Schuylkill River; (2) anexisting dam, built after 1920, about 700 mupstream of the confluence; and (3) a covered bridge,about 2,100 m upstream of the confluence. The thal-weg has a sharp slope break near the location of theexisting dam, with average thalweg gradients down-stream and upstream of the dam of 0.68 and 0.32%,respectively. The steepest parts of the channel arecharacterized by the coarsest bed particle sizes (Fra-ley, 2006; Fraley et al., 2007). The water-surfaceprofile also includes steps and pools that are preva-lent downstream of the covered bridge, caused byponding behind the dams mentioned above, as wellas hydraulic controls caused by longitudinal irregu-larities in bed and channel morphology. High bank-lines that average 3.75 m from the top of the bankto the water surface are present upstream of the oldmill dam because Valley Creek is cutting throughlegacy deposits and is reworking the stack of sedi-ments stored in the aggraded floodplain. The exist-ing dam traps sediment in reaches upstream of itslocation. Immediately downstream of the coveredbridge, the stream is also forced into a narrow gorgebetween two bedrock knobs, known locally as MountMisery and Mount Joy. Upstream of the coveredbridge, the water-surface profile is much smootherand shows no major breaks in slope. Low banklinesthat average 1 m from the top of the bank to thewater surface extend to the park boundary at theInterstate 76 overpass.

Valley Creek basin has undergone considerabledevelopment since 1970; since that time, existing

agricultural and forested land has been converted toresidential, commercial, and industrial areas (Reed,1991). Impervious cover doubled from 9% in 1987(Sloto, 1988) to 18% in 2000 (Steffy, 2003). Currentland use in the watershed includes dense urbandevelopment along the Route 30 corridor; scatteredsuburban, commercial, and industrial development;and major limestone quarry operations (CCWRAet al., 2004). An estimated 23,187 residents lived inthe watershed in 2000. Based on population projec-tions from the Chester County Planning Commission,the number of residents in the watershed is esti-mated to increase by 3,200 (13%) by 2030 (CCWRAet al., 2004).

Peak discharge has increased in Valley Creek atthe same time as commercial and residential develop-ment has grown (Figure 3). The slope of the trendline in Figure 3 shows an approximate doubling ofthe annual maximum discharge between 1983 and2006. Although we cannot demonstrate that theincreased magnitude of flood peaks is independent ofclimatic trends (during the same period, total annualprecipitation has shown an increasing trend on theorder of 20-25%), the relative size of the increaseleads us to believe that land cover change is animportant factor.

METHODOLOGY

The methods used in field investigations included:(1) field survey of a longitudinal profile, (2) channelcross-section and bankline analysis, (3) measurementof channel bed particle size distributions, and (4) tur-bidity measurement and estimation of suspendedsediment load. For the purpose of identifying repre-sentative sampling locations, the channel of ValleyCreek within VAFO was divided into 12 reaches (Fig-ure 2). Areas with similar flow regimes, channel mor-phology, and sediment storage characteristics weregrouped together. Some reaches were dynamic andincluded sites where hydraulic conditions in thechannel have led to alternating storage and remobili-zation of gravel and sand deposits. Others tended tohave simpler morphology and a greater tendency forsediment to move through without forming substan-tial accumulations; they were therefore more stablein form.

Longitudinal Profile

A Sokkia SET510 total station was used to surveyelevations approximately every 2 m along the top of

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bank, water’s edge, and thalweg of the 3.7 km portionof Valley Creek within VAFO. Coordinates used tocalibrate the station were taken from a 2000 ortho-photo, obtained from the Delaware Valley RegionalPlanning Commission. All elevation measurementswere based on an arbitrary zero foot elevation datumset at the confluence of Valley Creek with the Schuyl-kill River (downstream end of the longitudinal pro-file). Profiles of the thalweg, water surface, and rightand left banklines were plotted. The longitudinal pro-file was measured from the confluence of ValleyCreek with the Schuylkill River to the USGS gage,which is just upstream of the Interstate 76 overpass.The longitudinal profile of elevation measurements isshown in Figure 2.

Cross-Section Analysis

In each of the 12 reaches, three representativelocations were chosen for cross-section installation.The cross-sections were oriented perpendicular tothe direction of flow. Rebar (0.6 m length) wasinstalled on the left and right streambanks to monu-ment the endpoints. The total station was used tosurvey channel elevations between the endpoints atapproximately 0.3 m intervals, as well as locationsalong the cross-section where noticeable breaks instreambed elevation occurred. Cross-section installa-tion and baseline surveys were conducted duringJune and July 2004. Resurveys after major stormevents were used to monitor changing channel bedelevations. One resurvey occurred after a storm

event with an estimated recurrence interval of10 years on September 28, 2004, producing a dis-charge peak of 78 m3 ⁄ s, the second highest dis-charge on record for Valley Creek. The otheroccurred after a storm event with an estimatedrecurrence interval of five years on April 2, 2005,producing a discharge peak of 58 m3 ⁄ s. The area ofchange for each cross-section was calculated asshown in Figure 4.

Bankline Analysis

Thirty-eight locations of bank instability weredocumented during the channel characterizationprocess based on detailed visual observation and asubset of 10 locations that exhibited the most evi-dence of severe bank erosion were chosen for moni-toring. There are many potentially confounding

FIGURE 4. Calculation for Determining theArea of Change for Each Cross-Section.

FIGURE 3. Peak Annual Streamflow Recorded at the USGS Stream Gage on Valley Creek at the PA Turnpike Bridge Near Valley Forge.



factors related to the plan form location and extentof bank erosion along the 3.7 km study reach,including sediment deposits upstream of dams, localhydraulic controls associated with existing struc-tures, and constrictions and expansions along thevalley. Riparian vegetation can also play a signifi-cant role in the extent of bank erosion and channelwidening (Hession et al., 2003; Sweeney et al.,2004). Although the goal of this study was not toevaluate the physical causes of bank instability,this topic may be of interest for future studies inValley Creek.

The total station was used to survey bank topsand bottoms of the 10 erosion locations at approxi-mately 0.3 m intervals. As with the cross-sectionalresurveys, these detailed bankline surveys wereconducted after major storm events. Survey pointsfor the bank tops and bottoms taken after each ofthe storm events were plotted in ArcGIS, Version9.1 (Environmental Systems Research Institute,Inc., Redlands, California) on the 2000 orthophoto.The areas of top and bottom bank change werefound by drawing polygons connecting the surveyedbanklines from one storm event to the next. Thisarea was divided by the surveyed length of bank tocalculate the average lateral distance of bankretreat between storm events. With information onthe average rate of top and bottom bank retreat, aswell as average bank height, the net volume of sed-iment eroded from the streambank was calculated.To obtain the mass of sediment eroded from thebanks, a soil bulk density was used as a conversionfactor. Because this measurement was not directlymade in the field, moist soil bulk density valueswere obtained from the Natural ResourcesConservation Service and the Penn State GeospatialTechnology Program for soils constituting thestreambanks of Valley Creek (NRCS and PennState Geospatial Technology Program, 2005).

To measure the particle size distribution of bankmaterial, a sample was collected at each of the 10identified erosion locations and returned to the labfor sieving. A hand shovel was used to scrape a con-sistent volume of material from the bank top to thebank bottom. The material was then wet sieved inthe lab, oven dried, and weighed. The resulting datawere tabulated and used to generate the particle sizedistributions.

Channel Bed Particle Size Distributions

Pebble counts were conducted along all cross-sec-tions where the water depth was shallow enough toallow sampling. A design by Bunte and Abt (2001)was used to create a grid based approach to the

pebble count, which prevents operator bias for selec-tion of coarse particles over finer ones. The spacing ofgrid points was 0.5 m, which was larger than theDmax particle size in most cross-sections to avoid dou-ble counting any individual particle in the samplingprocess. Particle intermediate axes were measuredwith a gravelometer, an aluminum frame containingsquare holes with widths at half-phi increments(Bunte and Abt, 2001). Approximately 200 particleswere selected and diameters measured in the reachimmediately upstream and downstream of each sam-pled cross-section. The sample size of 200 was deter-mined as a representative particle size distributionbased on a preliminary in-depth analysis of a samplecontaining 1,113 particles (Fraley, 2006; Fraley et al.,2007). The data were analyzed to generate particlesize distributions for each measured cross-section,representing grain sizes found in the channel armorlayer.

A second method for obtaining grain-size distribu-tions was based on a design by Klingeman andEmmitt (1982) and involved volumetric sampling. A0.2 m3 (55 gallon) steel drum was cut in half and fit-ted with handles. It was then wedged into thestreambed to a depth of approximately 5 cm. All sed-iment within the barrel was scooped out with asmall hand shovel, leaving fine particles suspendedin the water column within the barrel. A 125 mlsample was taken from the water in the barrel afterit was thoroughly mixed. The water depth of thebarrel was measured after sampling to be used inextrapolating the amount of fine sediment in the125 ml aliquot to the volume of water containedwithin the barrel. Five of these measurements weretaken across each cross-section that was shallowenough to allow for sampling. The five bed sampleswere thoroughly mixed together and 1 ⁄ 5 of the sedi-ment scooped from the barrel was returned to thelab. The five 125 ml aliquots were also mixedtogether, and one 125 ml aliquot was taken from thecombined sample. In the lab, the sediment wassieved, oven dried, and weighed.

The barrel sampler provided a volumetric mea-surement of the particle size distribution of the sur-face layer of sediment. However, it is not directlycomparable to the pebble count data because whencollecting the samples from the barrel, some of thesubsurface sediment could also have been collected.Separating the surface and subsurface layers wasbased on the operator’s perception. By taking a vol-umetric sample, it was more likely that fine mate-rial would be captured than would be measuredwith the pebble count. Therefore, we believe thatthe barrel samples allowed a more accurateestimate of the amount of fine sediment in thematrix. Conversely, the pebble counts provide a



more accurate subdivision of the coarse particle sizeranges.

Suspended Sediment

A sediment station was installed in July 2005 atthe USGS stream Gage (01473169 Valley Creek atPA Turnpike Bridge near Valley Forge). The stationconsisted of a YSI 6136 turbidity optical sensorcombined with a YSI 600 OMS sonde (YSI, Inc.,World Headquarters, Yellow Springs, Ohio) placedin the stream at the gaging location. The probewas housed within a permeable hard casing for pro-tection. It was also fitted with a wiper mechanismto prevent the optical path from becoming cloggedand recording spurious turbidity estimates. Thesonde recorded turbidity measurements at 15-minintervals, corresponding to the 15-min continuousdischarge measurements at the gage. Turbiditydata were then uploaded automatically to the inter-net to allow real-time data access through theUSGS website (http://waterdata.usgs.gov/pa/nwis/uv?01473169).

An ISCO model 6712C compact portable sampler(Teledyne Isco, Inc., Lincoln, Nebraska) was set to col-lect stream samples at water level thresholds abovebase flow. USGS collected 25 ISCO samples at the Val-ley Creek gage during nine storm events between Octo-ber 2005 and August 2006 with discharges rangingfrom 0.6 to 40.4 m3 ⁄ s. These ISCO samples were fil-tered, dried, and weighed by USGS, using standard

methods (Guy, 1969). The resulting concentration ofsuspended sediment was plotted against turbidity,allowing further turbidity measurements to serve as asurrogate for suspended sediment measurement (Gip-pel, 1995). We assumed that the sediment concentra-tion was well-mixed across the flow cross-section at thesampling point, particularly at higher flows when mostof the suspended sediment is transported. Error attrib-utable to cross-section variations in sediment concen-tration cannot be quantified from available data.

RESULTS

Suspended Sediment Load for Valley CreekWatershed

A linear function describing suspended sedimentconcentration as a function of turbidity was derivedfrom a simple linear regression (R2 = 0.99) based onthe 25 suspended sediment samples collected by theISCO sampler at the USGS Valley Creek gage(Figure 5). Upper and lower confidence and predictionlimits shown in Figure 5 were calculated using meth-ods described in Helsel and Hirsch (1992). Theregression equation was subsequently used to esti-mate suspended sediment concentration from turbid-ity data recorded at 15-min intervals during theperiod between July 25, 2005 and September 30,2006. Suspended sediment concentration and water

FIGURE 5. Relationship Between Suspended Sediment Concentration in mg ⁄ l and Turbidity inNTUs for Valley Creek Based on 25 Samples From Nine Storm Events.



discharge data were then used to generate a 15-mintime series of suspended sediment discharge values.These instantaneous values were integrated overtime to calculate suspended sediment loads. Becauseof delays in the installation of the ISCO and opticalprobe, there is no overlap between the time series ofsuspended sediment data and the field measurementsof bankline change and cross-section change. How-ever, the data obtained from the ISCO and opticalprobe do allow us to estimate short-term watershedsediment yield, and the suspended sediment data canbe compared with the field data on sediment derivedfrom changes in the channel banks and bed.

For the 2006 water year (October 1, 2005 to Sep-tember 30, 2006), estimated sediment load was2,540 t (47.2 t ⁄ km2 ⁄ year). Estimated 95% confidencelimits for this value range between 2,090 and 2,990 t(38.8-55.6 t ⁄ km2 ⁄ year) (See Appendix for derivation).This range of variation does not account for theuncertainty due to use of a single sampling pointrather than multiple verticals. Additional turbiditydata, not included in this estimate, were collectedbetween July 25, 2005 and October 1, 2005. By utiliz-ing the entire dataset, a range of estimated annualsuspended sediment loads was calculated for each365-day time period between July 25, 2005 and Sep-tember 30, 2006 (e.g., July 25, 2005 to July 24, 2006;July 26, 2005 to July 25 2006; and so forth). Themaximum 365-day calculated annual suspended sedi-ment load was 2,540 t (from the 2006 water year)and the minimum was 1,890 t (35.2 t ⁄ km2 ⁄ year).

Mass of Fine Sediment Stored in the Streambed

The mass of fine sediment stored in and potentiallyremobilized from the streambed was estimated fromthe lowest channel bed elevation reached during scourevents throughout the study period. The baselinecross-section surveys were conducted in June andJuly 2004 and resurveyed after a 10-year storm eventresulted in the second highest discharge on record atthe USGS Valley Creek gage in September 2004. Dueto its magnitude, we assumed that the channel bedelevation surveyed after this event is the lowest thatcan occur during large storms. The depth of themobile layer ranged from 0 to 1.4 m, with an averagedepth of 0.4 m. It was estimated at each cross-sectionas the greatest erosion depth between the baselinesurvey and the survey after the 10-year event. Thedepth at each cross-section was multiplied bythe channel width, which is the distance between theleft and right edge of water. The area was then multi-plied by the length of channel that each cross-sectionrepresents to estimate the volume of sediment in m3,which can potentially be mobilized in the channel.

The estimated volume of sediment was convertedto mass using bulk density estimates based on parti-cle size distributions of the streambed. Particle sizedistributions were obtained from the barrel samplesbecause they measure more of the fine bed materialthan is sampled with the pebble counts. Barrel sam-ples were measured for 19 of the 36 cross-sections insummer 2004 and 16 of the 19 cross-sections in sum-mer 2005. Particle size distributions were used fromthe summer 2004 data because more cross-sectiondata are available for this dataset (19 compared with16 cross-sections) and the 2004 data represent theparticle sizes that were initially available for trans-port at the beginning of the study period. For cross-sections where the bed was too coarse to measurewith the barrel sample, the pebble count data wereused as a surrogate. Some cross-sections were toodeep to be measured by either the barrel sampler orpebble counts. For these cross-sections, estimates ofthe particle size distributions were made based onvisual comparison of the streambed with other cross-sections where measurements were available. Bulkdensity values were obtained from Smith and Wheat-craft (1993), which contained the following estimatesin g ⁄ cm3: clay (1.06-1.59), silt (1.33-1.72), fine sand(1.46-2.12), and coarse sand (1.72-2.25). These datawere used to determine the bulk density estimatesfor the various size classes utilized in this study andare shown in Table 1. For the Valley Creek particlesize classes where estimates from Smith and Wheat-craft (1993) were unavailable (very fine to coarsegravel) the bulk densities were obtained by interpola-tion between bulk density for the previous size classand the solid rock bulk density of 2.65 g ⁄ cm3.

The volume of sediment represented by each cross-section was multiplied by the bulk density estimateof streambed sediment based on particle size toobtain the mass of sediment stored in the channel.Table 1 shows the result of these calculations.

TABLE 1. Estimated Total Mass of Fine Sediment Stored in theStreambed of Valley Creek Within Valley Forge National Historical

Park (summer 2004) and Bulk Density Estimates Based on andInterpolated From Smith and Wheatcraft (1993).

Size Class

BulkDensity(g ⁄ cm3)

Mass(t)

% ofTotal

Clay and silt (0.00045-0.063 mm) 1.33 720 2Very fine sand (0.063-0.075 mm) 1.46 760 2Very fine to very coarse sand(0.075-2 mm)

1.72 3,200 10

Very fine to medium gravel (2-10 mm) 2.25 4,000 12Medium to coarse gravel (10-32 mm) 2.40 6,000 18Coarse gravel to cobbles and boulders(>32 mm)

2.65 19,000 56



The total amount of sediment sand size and smal-ler (<2 mm) stored in the streambed within VAFO isestimated to be 4,700 t. The amount of very finesand, clay, and silt (<0.075 mm) stored in the stream-bed is estimated to be 1,500 t.

Change in the Mass of Fine Sediment Stored in theStreambed

To determine the change in the amount of finesediment stored in the bed between the baseline sur-vey and the final survey after the five-year event inApril 2005, the amount of cross-section erosion anddeposition found in Figure 2 was used. The area ofchange was multiplied by the length of channel thateach cross-section represented to obtain the volumeof erosion and deposition. Bulk density estimateswere then used to obtain the mass of erosion anddeposition as described in Mass of Fine SedimentStored in the Streambed. Table 2 provides the massof erosion and deposition of the streambed for thelength of Valley Creek within VAFO. The resultsshown in the table are categorized by the mass ofsediment represented by each particle size class. Netchange in the mass of sediment of sand size andsmaller on the streambed was 1,000 t of erosion.The net change of fine sediment <0.075 mm was330 t of erosion.

Sediment Derived From Bank Erosion

Although the survey period (from July 2004 toApril, May, or June 2005, depending on location) wasless than a full year, qualitative field observationsduring late spring and early summer 2005 indicatedlittle or no additional erosion. Therefore, the sur-veyed amounts of bank erosion are considered repre-

sentative of the annual total for the period July 2004to July 2005.

The cumulative mass of bank erosion calculatedfor the 10 most severe erosion sites identified duringthe channel characterization process (Table 3)amounts to 711 t. In estimating the mass of sedi-ment derived from bank erosion along the entirelength of Valley Creek within VAFO (Table 4), bank-line changes from surveyed cross-sections were usedto supplement the bankline surveys. For Table 4 cal-culations, where one of the cross-sections overlapped

TABLE 3. Estimated Volume and Mass of Bank Erosionfor the 10 Surveyed Bankline Locations in Valley Forge National

Historical Park for the Period July 2004-2005.

ID

Total VolumeEroded Baseline

Survey toStorm 3 (m3)

BulkDensity(g ⁄ cm3)

TotalMass

(t)

Total Massper Unit Bank

Length(t ⁄ m)

E1 191 1.35 258 3.4E2 68 1.35 92 3.4E4B 22 1.35 30 0.9E4A 25 1.35 34 2.0E10 121 1.35 164 2.1E11 24 1.35 32 1.4E21 8 1.30 11 0.3E22 55 1.30 71 2.8E35 14 1.30 18 0.5E38 1 1.30 1 0.1

Total 711

TABLE 2. Estimated Total Mass of Sediment Deposition andErosion in the Streambed of Valley Creek Within Valley Forge

National Historical Park for the Period July 2004-2005.

Size Class1Deposition

(t)Erosion

(t)

Clay and silt (0.00045-0.063 mm) 70 230Very fine sand (0.063-0.075 mm) 80 250Very fine to very coarse sand(0.075-2 mm)

310 1,000

Very fine to medium gravel (2-10 mm) 330 1,100Medium to coarse gravel (10-32 mm) 440 1,700Coarse gravel to cobbles and boulders(>32 mm)

1,800 5,300

1The same bulk densities were used as those presented in Table 1.

TABLE 4. Cumulative Volume and Mass of BankErosion Estimated From Field Measurements Along Valley

Creek for the Period July 2004-2005.

IDVolume

(m3)Mass

(t)

Mass perUnit Reach

Length (t ⁄ m)

Reach 1 425 574 3.5Reach 2 183 247 2.0Reach 3 73 98 1.4Reach 4 70 95 0.7Reach 5 365 493 2.5Reach 6 173 234 1.2Reach 7 266 359 1.7Reach 8 123 166 0.9Reach 9 495 668 0.8Reach 10 136 184 0.4Reach 11 186 251 0.4Reach 12 38 51 0.1Total 2,530 3,420

Notes: Reach 9 contained rip-rap and stone walls protectingapproximately 20% of the channel length within the reach. Theunit volume of erosion for this reach was multiplied by a reachlength of 80% of the actual length to obtain the mass of sedimentfrom bank erosion.



a bankline survey location, the value from the bank-line survey was used rather than the point valuebased on the cross-section. Along reaches wherethere were no bankline surveys the unit volume ofbank erosion was calculated for individual cross-sec-tions and multiplied by channel longitudinal dis-tances that were assigned to each individual cross-section based on field observations. The resultingvalues of cumulative erosion volume along eachreach were cross-checked against an alternative cal-culation based on multiplying total reach length bya simple arithmetic average of the unit volumes oferosion for the three cross-sections within the reach.Typically the results did not vary by more than 15-25%, and neither method yielded values that weresystematically higher or lower than those derivedusing the other method. Along reaches where therewere both bankline surveys and cross-sections, butwhere they did not overlap, the cross-section surveyvalues were used to derive unit volumes of erosionfor the part of the reach not covered by the banklinesurveys. Along Reach 9, which was the longest ofthe 12 reaches in this study, field inspection indi-cated the presence of rip-rap and stone walls pro-tecting about 20% of the channel length of thisreach, and therefore the unit volumes of erosion forReach 9 were multiplied by a reach length amount-ing to 80% of the actual length.

Table 4 provides a summary of the total volumeand mass of bank erosion estimated for the surveyperiod by reach. The cumulative total amounts to2,500 m3 of sediment, with a mass of about 3,400 t.Thus the bankline surveys, covering a cumulativechannel length of about 365 m or slightly less than10% of the total channel length within VAFO, arebelieved to account for about 21% of the sedimentderived from bank erosion.

Seven of the 10 locations had bank compositionswith 60% or more silt and clay (<0.063 mm). Theexceptions were erosion Location 2 with a bank com-position of 87% medium and coarse sand (0.075-2 mm), erosion Location 4A with a bank compositionof 30% silt and clay and 32% medium and coarsesand, and erosion Location 22 with a bank composi-tion of 70% gravel or larger (>32 mm). Each set ofparticle size measurements was based on five verti-cally integrated samples taken from bank profilesdistributed along the erosion site. The estimatedmass of silt and clay derived from bank erosionalong Valley Creek within VAFO for the period July2004 to July 2005 is 2,250 t; the estimated mass ofsilt, clay, and fine sand, which is the quantity con-sidered most comparable to the particle size range ofsuspended sediment, is 2,340 t, and the medium tocoarse sand fraction accounts for an additional865 t.

DISCUSSION

Suspended Sediment Monitoring

Sediment yield estimates in many watersheds withUSGS stream gages are based on a limited number ofdiscrete suspended sediment samples used to derive adischarge-load or a discharge-concentration regres-sion relationship. Although the calculated loads arenot typically reported with error estimates, there isconsiderable uncertainty owing to the limited tempo-ral coverage of the samples and the assumption thatthe discharge-load relationship is single-valued. Acommon approach to load estimation involves the useof a log-linear multiple regression model that incorpo-rates functions of discharge and time to account forseasonal variations and other trends (Runkel et al.,2004). An alternative is the use of pumping samplersthat collect discrete suspended sediment samplesbased on either a fixed time or equal-volume incre-ment. However, the cost of processing the individualsamples is high enough that there are almost no gag-ing locations with such samplers operating on a con-tinuous basis. Historical sediment records aregenerally based on daily sediment samples and moreintensive sampling during storms, but even at suchstations, complete coverage of the storm hydrographis rare.

Continuous turbidity monitoring can offer improve-ment over these approaches to deriving sedimentyield estimates and was used in this study as a prac-tical method for obtaining a continuous record of sus-pended sediment data. This method has been used inrecent years by USGS as a surrogate for suspendedsediment concentration (Ziegler, 2003; Rasmussenet al., 2005). Lewis (2003) reports that regressions ofsuspended sediment concentration vs. turbidity oftenare linear with low variance, allowing accurate esti-mation of sediment flux as long as suspended sedi-ment concentration data are available to establish arelationship. Potential sources of error include:greater variance of turbidity measurements at highsuspended sediment concentrations; variability insediment shape, color, and size distribution; and bio-logic fouling of the sensor by algae (Ankcorn, 2003;Landers, 2003).

Optimal conditions for placement of the turbiditysonde are described by Ankcorn and Landers (2003)as including the following: adequate mixing withinthe stream cross-section; sufficient velocity to createnatural flushing and prevent fouling; adequate pro-tection of the sonde at high flow; and adequate waterdepth at low flow. As is the case with any automaticsampler, the data represent a single sampling pointrather than a series of depth-integrated samples at



multiple verticals across the channel. The ideal condi-tion would be one in which the point samples couldbe compared with concentrations that are representa-tive of the average concentration throughout thecross-section over the entire range of flow. However,as Edwards and Glysson (1999) point out, this israrely possible. Gray et al. (2003) cite an examplewhere continuous in situ turbidity measurementswere made at a site on the Kansas River and com-pared with depth-integrated samples collected usingmultiple verticals across the channel, over a range ofconcentrations between 35 and 3,660 mg ⁄ l. The tur-bidity-concentration relationship explains 93% of thevariance in suspended sediment concentration, andprovides data over the full range of flow conditions,regardless of magnitude or duration.

Estimation of Sediment Yield

Estimation of the suspended sediment yield frommeasurements of discharge and turbidity was a majorcomponent of this study. The relationship betweenthese two variables shows a broad range of scatter,with up to two orders of magnitude variation in therange of turbidity values associated with a singlevalue of discharge over the 14-month period repre-sented by the turbidity data (Figure 6). Given themuch tighter relationship between turbidity and con-centration (Figure 5), it can be demonstrated that thepattern in Figure 6 is representative of the relation-ship between discharge and concentration as well.

There appears to be some seasonality to the relation-ship: in general, the values collected during the per-iod of June through August are higher than thevalues collected during the period of October throughNovember, and values collected during the period ofFebruary through April fall in between these tworanges. There is also the potential for year to yearvariation in the same month that shows even greaterseparation than the separation between seasons, asindicated by the comparison of September 2005 andSeptember 2006. This suggests that the sequencing ofweather events may play an important role in deter-mining the amount of sediment produced by runoffevents and that simple seasonal relationships maynot be reliable predictors of sediment concentrationor sediment load for any particular year.

A considerable amount of variation may beobserved even over the duration of a single stormevent. The complex hydrograph shown in Figure 7has two major peaks and four subsidiary peaks. Thefigure shows that for the two major peaks, turbidityreaches a maximum on the rising limb of the hydro-graph and then quickly drops to a small fraction ofthe maximum value while discharge is still near itspeak. The resulting pattern of hysteresis in the con-centration-turbidity relationship is illustrated in Fig-ure 8 for the two large hydrograph peaks during thisstorm event. These figures illustrate that even withina single storm it is not advisable to define a simplerating curve defining turbidity as a single-valuedfunction of discharge because the pattern follows aclockwise loop, with values on the falling limb much

FIGURE 6. Scatter Plot Showing Trends in the Turbidity-Discharge Relationship for Valley Creek at the USGS Stream Gage.



smaller than values on the rising limb of the hydro-graph. It is likely that some of the variability in thesediment transport curve can be explained by chang-ing patterns of sediment availability. For example,the rising limb of Hydrograph 2 has much lower tur-bidity values than the rising limb of Hydrograph 1but is fairly close to the trend on the falling limb ofHydrograph 1. This suggests the possibility that somedepletion of the readily available sediment supplymay have occurred during the earlier part of thismultiple-peak event, and that sediment was lessreadily available by the time Hydrograph 2 began itsrise. Similar hysteresis loops have been observed inmany previous studies of suspended sediment data(e.g., Heidel, 1956; Wood, 1977; Sidle and Campbell,1985; Dinehart, 1998; Topping et al., 2000).

From the analysis above, it clearly would be difficultto predict sediment concentrations based on dischargealone due to seasonal variation, as well as variation

over the course of an individual storm event. In thisstudy, we did not use discharge to predict instanta-neous sediment concentration, as we had a continuousturbidity record over a 14-month period. We were ableto use the much tighter turbidity-concentration rela-tionship to develop instantaneous concentration valuesfor use in calculation of sediment discharge at 15-mintime increments. The turbidity-concentration relation-ship covers suspended sediment samples collected atdischarges between 0.6 and 40.4 m3 ⁄ s (21-1,425 ft3 ⁄ s)with concentrations between 20 and 846 mg ⁄ l andturbidity values between 8 and 810 NephelometricTurbidity Unit (NTU). The maximum dischargerecorded during the period of turbidity data collectionwas 43.5 m3 ⁄ s (1,535 ft3 ⁄ s), the maximum recordedturbidity was 900 NTU, and the maximum estimatedsuspended sediment concentration was 831 mg ⁄ l. Forthe period of continuous measurement, the highestpredicted concentrations are only slightly outside therange of values used to compile the turbidity-concen-tration relationship, and the maximum discharge onlyslightly exceeds the maximum discharge at which sedi-ment concentration was recorded.

For purposes of this study, we needed to extrapo-late sediment loads outside the period of continuousrecord. As was noted above, the turbidity probe andISCO sampler had not yet been installed during theperiod between July 2004 and July 2005 when thebankline and cross-section surveys were being made.We cannot make a direct comparison between our cal-culated sediment loads for the 2006 water year andthe estimated amount of sediment mobilized fromother sources during the previous year because of thedifference in magnitude and frequency of largestorms between the two years. Rather than attemptto estimate concentrations directly from instanta-neous discharge values for July 2004 to July 2005,we investigated a much simpler approach.

It is possible to generate predictions of storm-period suspended sediment load by using peak dis-charge as an explanatory variable. Gellis (2003)reached the same conclusion in a study of four tropi-cal watersheds in Puerto Rico. For Valley Creek,storm-period suspended sediment loads were calcu-lated for 36 individual events with peak dischargeabove 2 m3 ⁄ s for which both flow and turbidity datawere available at the stream gage. A power functionrelationship (R2 = 0.90) was developed for predictionof storm-period sediment load as a function of peakdischarge. The data are illustrated in Figure 9.

The sum of the storm-period sediment loadspredicted for these 36 events based on the powerfunction (with bias correction as described in theAppendix) is equal to 102.8% of the sum of the storm-period sediment loads calculated from the originaldata and is therefore a reasonable surrogate for

FIGURE 7. Plot Showing Discharge and Turbidityfor a Complex Hydrograph in June 2006.

FIGURE 8. Plot Showing Hysteresis Loops for the TwoLarge Hydrograph Peaks Shown in Figure 7.



estimating general trends in the relationship betweenflow and suspended sediment load. The 36 stormevents used in the analysis accounted for 82.5% ofthe total suspended load for the period between July25, 2005 and September 30, 2006. The six largest dis-charge peaks accounted for 55.1% of the total and thethree largest peaks accounted for 39.5% of the total.All flows not associated with storm events peaking at2 m3 ⁄ s or more during the 2006 water year accountedfor a cumulative total of 386 t of suspended sediment.

Using the derived power function relationshipsfrom Figure 9 together with discharge records fromthe USGS gage, we estimate that flow events withpeak discharge exceeding 2 m3 ⁄ s during the periodJuly 18, 2004 to July 17, 2005 accounted for a cumu-lative 4,765 t of suspended load. The two largest floodevents during that period had peak discharges of 77.6and 58.3 m3 ⁄ s, respectively, and their combinedstorm-period suspended load amounts to 33.1% of thetotal derived using the regression. Because these twoevents fall outside the range of discharges repre-sented in Figure 9, the predicted total is subject toadditional uncertainty that cannot be quantified.However, the relationship shown in Figure 9 showsenough consistency throughout the range of mea-sured values that we see no reason to expect that itwould change significantly if extrapolated a short dis-tance above the measured range. We believe it ispreferable to estimate the suspended load for July2004 to July 2005 by this method rather than toassume that the 2006 water year is a valid basis forcomparison with field measurements.

If we assume that lower flows during the remain-der of this 12-month period accounted for about 385 t

of suspended sediment, comparable to the amountcalculated for the 2006 water year, we can estimate atotal suspended load of about 5,150 t and a sedimentyield of 95.7 t ⁄ km2 ⁄ year, slightly more than twice thevalues calculated for the 2006 water year. This same12-month period had an average discharge of1.49 m3 ⁄ s, more than double the average for the 2006water year (0.59 m3 ⁄ s) and about 60% higher thanthe average for all years of record from 1983 to 2004.

The minimum annual sediment yield calculated forany one-year period within the 14-month record atthe gage, 35.2 t ⁄ km2 ⁄ year, was associated with a cor-responding value of mean annual streamflow of0.94 m3 ⁄ s. This is only slightly more than the medianvalue of annual mean streamflow (0.91 m3 ⁄ s) for the24 years from 1983 to 2006. The value of sedimentyield estimated for the 2006 water year was47.2 t ⁄ km2 ⁄ year and mean streamflow for that timeperiod is 1.06 m3 ⁄ s, which would place within theupper quartile of annual streamflow values at theValley Creek gage. If we assume that the relationshipbetween sediment concentration and dischargeobserved during the study period is representative forthe period 1983-2006, we can infer that the medianannual sediment yield is around 35 t ⁄ km2 ⁄ year andthat the maximum sediment yield is between two andthree times that amount.

Comparison With Regional Data

To place the annual sediment yield calculated forValley Creek within the regional context, we exam-ined sediment data for other sites in the Piedmont

FIGURE 9. Peak Discharge vs. Sediment Load for 36 Storm Events From July 25, 2005 Through September 30, 2006.



physiographic province in the Mid-Atlantic region.We also examined literature values to assess trendsin sediment yield associated with urban development.Data from both of these sources are summarized inTable 5.

The watersheds included in the table span a rangeof lithology, land-use history, period of record, andmethodology used in estimating sediment loads. Val-ley Creek watershed represents a mix of lithologies,including carbonate, quartzite, schist, and gneiss, aswell as a mix of land cover types and a history ofrecent change in land cover. Comparisons in Table 5cannot be adjusted for the wide range of conditionsrepresented or the potential sources of uncertaintyin the load values. They are intended primarily toprovide context for our observations and to illustratewhere Valley Creek falls within the range of sedi-ment yield values reported from locations throughoutthe region. Most of the tabulated data were derivedeither from the online USGS NWIS system or frompublished USGS reports that are referenced in thetable. Gellis et al. (2005) provide detailed discussionand additional references for the methods used tocompile suspended sediment loads and concentrationat various sites.

Table 5 reports maximum, median, and meanannual suspended loads for each station where avail-able. There are two reasons for this. First, the meanvalue may be skewed by the inclusion of outliers, par-ticularly in a dataset that includes only a few yearsof record. Reporting both mean and median valuesallows readers to assess the extent to which thesemeasures of central tendency are comparable. Second,the Valley Creek data represents a short time periodand was used to infer a value for the median annualsuspended load based on the time period of continu-ous measurement that is most comparable with med-ian annual discharge for the period of record.Because we are not able to estimate a mean value, itwas preferable to include both median and mean val-ues for stations where both were available to illus-trate how these stations compare with Valley Creek.

It is well known that construction sites can gener-ate enormous amounts of sediment, particularly inthe absence of sediment control measures. Guy andFerguson (1962) estimated construction-site sedimentyields in the Washington, D.C. metropolitan area inthe range 8,750-17,500 t ⁄ km2 ⁄ year, and Wolman(1967) cited values of the order of 35,000 t ⁄ km2 ⁄ year.Yorke and Herb (1978) published sediment yield data

TABLE 5. Regional Suspended Sediment Yield Comparisons With Valley Creek.

StationDrainage

Area (km2)Period ofRecord

Maximum SedimentYield (t ⁄ km2 ⁄ year)

Median SedimentYield (t ⁄ km2 ⁄ year)

Mean SedimentYield (t ⁄ km2 ⁄ year)

Valley Creek at PA TurnpikeBridge (01473169)

53.9 July 2004 toSeptember 2006

96.0 35.0

Schuylkill R at PortCarbon, PA (01467470)1

70.2 1950, 1976-1977 189 109 131

Schuylkill R at Berne,PA (01470500)1

919 1952-1981 97.1 19.6 28.2

Schuylkill R at Manayunk,Philadelphia, PA (01473800)1

4,740 1954-1981, 1983,1986

190 55.8 68.4

Perkiomen Creek at Grateford,PA (01473000)1

723 1950-1952, 1964-1965,1972-1973

98.8 73.9 68

Brandywine Creek at ChaddsFord, PA (01481000)1

743 1964-1977 123 45.5 58.6

NW Branch Anacostia R nearColesville, MD (01650500)2

54.9 1963-1974 514 244 245

Good Hope Tributary,Montgomery County, MD3

4.05 1951-1995 135

Little Patuxent River atSavage, MD (01594000)4

255 1987, 1988, 1990 36.4

Little Conestoga Creek site 3A nearMorgantown, PA (0157608335)4

3.68 1986, 1988-1991 116

Little Conestoga Creek nearChurchtown, PA (01576085)4

15.1 1985-1992 368

Mill Creek at Eshelman Mill Rd,PA (01576540)4

140 1993-1995 112

Conestoga R at Conestoga,PA (01576754)4

1,220 1985-1988, 2001 60.9

1Data available from http://waterdata.usgs.gov/pa/nwis/.2Yorke and Herb (1978, table 3, p. 13).3Allmendinger et al. (2007).4Gellis et al. (2005, table 5, p. 30-31).



for the period 1963-1974 for the watershed of theNorthwest Branch Anacostia River near Colesville,Maryland. During this period the Anacostiawatershed was experiencing rapid urbanization andsediment control measures were not introduced inthe region until the early 1970s. The range of sedi-ment yield values was 90-510 t ⁄ km2 ⁄ year and themedian value was 244 t ⁄ km2 ⁄ year, about seven timesas large as our estimated median value for ValleyCreek at Pennsylvania Turnpike Bridge. Allmending-er et al. (2007) report a sediment yield estimate of135 t ⁄ km2 ⁄ year based largely on geomorphic evidencefor the Good Hope tributary in Montgomery County,which they characterize as an average for construc-tion and postconstruction periods. Gellis et al. (2005)tabulated sediment yield data for other watershedsdraining to Chesapeake Bay; maximum values forthe Pennsylvania Piedmont are from the ConestogaRiver watershed in Lancaster County and range from61 t ⁄ km2 ⁄ year (Conestoga River at Conestoga) to368 t ⁄ km2 ⁄ year (Little Conestoga Creek near Church-town). These sites are characterized by predomi-nantly agricultural land cover. By contrast, the LittlePatuxent River at Savage, Maryland, drains an areaof mixed land use with increasing urban developmentover the last three decades within the context ofregional sediment controls; sediment yield for theYears 1987, 1988, and 1990 averages 36.4 t ⁄ km2 ⁄year, comparable with our estimate of mediansediment yield for Valley Creek.

Sediment data are also available for multiple sta-tions in and near the Schuylkill River watershed(Table 5), although the records are typically of shortduration and several records are limited to the late1940s and early 1950s. Preliminary analysis suggeststhat some of these values may be anomalous andtherefore we rely more heavily on comparisons withthe more recent data. For stations with long periodsof record, the early part of the record was excludedfrom consideration (data prior to 1960). Although theavailable data are not consistent in temporal cover-age or watershed drainage area, they do provide auseful context for interpretation of the Valley Creekdata. We conclude that Valley Creek sediment yieldis much lower than values collected in urbanizingwatersheds prior to the advent of sediment controlsand is consistent with other watersheds in the Penn-sylvania Piedmont and within the Schuylkillwatershed, but not particularly high by comparisonwith the maximum values measured in the region.Although this comparison by itself does not tell uswhether sediment should be considered a seriousproblem for environmental conditions within VAFO,it does indicate that sediment influx from theupstream watershed is not as high as may have beenanticipated prior to the study.

Comparison of Sediment Sources

The goal of this investigation was to assess howmuch fine sediment was stored and remobilized inthe bed along the 3.7 km length of channel withinVAFO, and to compare this quantity with the mass ofsediment derived from bank erosion and with sus-pended sediment crossing the upstream park bound-ary. Analysis of data from Tables 1 and 2 indicatesthat for the period July 2004 to July 2005, the massof sediment finer than 2 mm in the mobile layer isapproximately 4,700 t, and of this total 1,500 t isfiner than 0.075 mm. The estimated sediment masseroded from the bed during the survey period finerthan 2 mm is 1,480 t; of this total, 480 t is finer than0.075 mm. Because deposition in this size rangeamounted to 150 t, net erosion finer than 0.075 mmis 330 t (Table 2). The estimated mass of sedimentderived from bank erosion for the same time period is3,420 t for all size fractions including gravel. Of thistotal, 3,200 t is less than 2 mm in size, including2,300 t finer than 0.075 mm.

The results indicate: (1) the mass of sediment finerthan 2 mm stored in the channel bed within VAFO(based on summer 2004 field surveys) is about 2.5times the amount of our best estimate for medianannual suspended load at the gage upstream of thepark boundary; the fraction of channel bed sedimentfiner than 0.075 mm is about 80% of our estimatedmedian annual suspended load; (2) the amount ofsediment finer than 2 mm eroded from the channelbed during the period July 2004 to July 2005 is about30% of the estimated suspended load at the gage forthat same time period, and the fraction finer than0.075 mm is about 9% of the suspended load for thatperiod; (3) bank erosion along Valley Creek withinVAFO during the period July 2004 to July 2005 gen-erated a mass of fine (<0.075 mm) sediment equiva-lent to about 45% of the estimated suspended load atthe park boundary in that time interval; (4) becausethe period July 2004 to July 2005 was characterizedby large storm events (including a 10-year and 5-yearstorm event) and had an average streamflow(1.49 m3 ⁄ s) larger than the maximum value in the24-year record at the Valley Creek gage, suspendedsediment load, streambed and bank erosion are allthought to have been much higher during the periodJuly 2004 to July 2005 than would be expected inmost years. Nevertheless the comparison amongthese components of the sediment budget is consid-ered to be valid for that time period.

This study involves measurements along a fractionof the total length of Valley Creek, and yet themasses of fine sediment stored in the streambed andderived from bank erosion are both of the same orderof magnitude as the annual suspended sediment load;



the net erosion from the streambed is a smaller, butstill considerable fraction of the annual total. Stream-bed sediment and bank sediment are both forms ofstorage in the landscape. Although sediment in themobile layer of the bed may be considered a moretransient form of storage, our measurements showthat because of the nature of the armor on the bed ofValley Creek, even very large storms cause only lim-ited erosion of the bed. Thus, at least for the sur-veyed reach of Valley Creek within VAFO, finesediment stored in the banks is equally accessibleand perhaps more accessible for erosion and trans-port during large storms than fine sediment stored inthe bed.

Our investigations did not include field measure-ments of channel sediment or bank erosion in thewatershed upstream of the USGS gage. We thereforehave no real basis for extrapolation of these num-bers to quantify the relative importance of either ofthese sources for the remainder of Valley Creek andits tributaries by comparison with annual suspendedsediment load. However, given the fact that theupstream watershed has a drainage area of nearly54 km2, together with the observation that approxi-mately 30% of upstream channel length may beexperiencing severe bank erosion (CCWRA et al.,2004), we believe one may reasonably infer thatthese two sources (and bank erosion in particular)are dominant components of the total sediment bud-get. It is likely that over the course of the year cov-ered by our measurements, cumulative exchange offine sediment with the bed throughout the drainagenetwork was of the same order of magnitude as thetotal suspended sediment load. It is also likely thatthe total mass of fine sediment derived from bankerosion throughout the drainage network was con-siderably larger than the total suspended sedimentload measured at the gage. If this is true, then itmust also be true that much of the sediment derivedfrom bank erosion did not leave the watershed andthat floodplain storage is still an active and impor-tant component of the sediment budget during yearswhen there are large flood events. The two largestfloods that occurred during the study period inun-dated even the highest banks along Valley Creek,but the extent of flood inundation and opportunitiesfor floodplain deposition of sediment are limited toreaches where the banks are lower during the smal-ler flood events. Allmendinger et al., 2007 suggestthat floodplain storage in their study watershed wasequivalent to 50% of the total sediment yield over a45-year period. The spatial distribution and netamount of floodplain deposition along Valley Creekremain to be quantified, but we would not be sur-prised if floodplain storage turned out to be equallyimportant here.

CONCLUDING REMARKS

Monitoring of changes in the bed and banks of Val-ley Creek has provided insight into the dynamicresponse of the channel to the flow regime and theinflux of sediment. An improved understanding ofthese relationships, and using effective methods forstudying these relationships, has provided a substan-tive contribution to the scientific understanding ofhow streams respond to urban disturbance. This inturn has additional implications for the managementof urbanizing streams.

This study is unique in that it compares directmeasurements of sediment yield, sediment derivedfrom bank erosion, and sediment stored and remobi-lized from the streambed at the same study site.Understanding sediment transport and source areasin urban areas is currently a ‘‘black box.’’ Few studiesof this type, which incorporate systematic storm-per-iod sampling, have been conducted. It is preferable tohave a longer period of direct monitoring of sedimentor turbidity, and to this end, the National Park Ser-vice has elected to continue funding the turbidity sen-sor deployed at Valley Creek beyond the period ofthis study. However, even with the short period ofrecord, the ability to estimate sediment loads for indi-vidual storms within the record allows us to makeinferences that may be applicable over a broaderrange of hydrologic conditions. Finally, the data col-lected here provide a baseline against which futureconditions can be compared. Our results lead us toconclude that: (1) suspended sediment yield from Val-ley Creek upstream of the gage is consistent withregional trends, but not nearly as high as some of theliterature values associated with urban development;(2) the component of fine-grained sediment budgetassociated with bank erosion is of the same order ofmagnitude as, and potentially larger than the totalsuspended sediment load from the upstreamwatershed; (3) transient bed storage of fine sediment,although a very small fraction of total bed sediment,still may account for a significant percentage of totalsuspended sediment load derived from upstream; and(4) overbank ⁄ floodplain storage is unquantified, butpotentially a very large component of the totalwatershed sediment budget.

APPENDIX: ESTIMATION OF UNCERTAINTY INPREDICTED SUSPENDED SEDIMENT LOAD

In the analysis that follows we consider the rangeof uncertainty associated with the predictions madeusing the liner regression of suspended sediment con-centration on turbidity and the log-log regression of



storm-period sediment load on peak discharge. Theseanalyses do not account for all possible sources oferror (e.g., error in USGS discharge data) and are lim-ited to the cases as specified.

Suspended Sediment Load for 2006 Water Year

Suspended sediment load for the 2006 water yearis based on application of the linear regression rela-tionship illustrated in Figure 5, derived from a set of25 turbidity and sediment concentration values mea-sured during the study period. We assume that sedi-ment concentration ci for each time step can beestimated as

ci ¼ b̂0 þ b̂1Ti þ ei; ðA1Þ

where Ti is turbidity and the errors ei are assumed tobe independent and normally distributed with zeromean. For each time step, the sediment flux was cal-culated as the product of sediment concentration inmg ⁄ l and stream discharge in m3 ⁄ s, with appropriateconstant coefficients to generate units of kg ⁄ s. Aver-age sediment flux was calculated for each time inter-val and multiplied by the length of the time intervalDt to generate sediment loads, which were summedover the entire record to estimate cumulative sedi-ment load. Thus the cumulative sediment load can beexpressed as a linear function of the estimatedregression parameters b̂0 and b̂1 as follows: for eachtime interval i, load Li ¼ kDt b̂0 þ b̂1 �Ti þ ei

� ��Qi; where

k accounts for unit conversions. The cumulative loadL is expressed as

L ¼ kDtXni¼1

b̂0 þ b̂1 �Ti

� ��Qi ¼ b̂0

Xni¼1

kDt �Qi

þ b̂1Xni¼1

kDt �Ti�Qi þ

Xni¼1

kDt �Qiei

ðA2Þ

We can substitute the constants C0 and C1 for thesummation formulas associated with b̂0 and b̂1,respectively. The expected value of the cumulativeload is then

L̂ ¼ b̂0C0 þ b̂1C1 ðA3Þ

Because the two regression parameters are corre-lated, the variance of this term cannot be expressedas the simple sum of the variances but must alsoinclude a covariance term. All terms are availablefrom the variance-covariance matrix of the originalregression. The standard error of the cumulative loadcan be calculated using the formula

SE ¼ C20V̂ b̂0

� �þ 2C0C1 ^cov b̂0; b̂1

� �þ C2

1V̂ b̂1

� �h i1=2

ðA4Þ

Assuming that the error is normally distributed,we calculate upper and lower confidence intervals forthe cumulative load as 1.96 standard errors aboveand below the expected value.

Suspended Sediment Load for July 2004 to July 2005

When a power function derived from a log-logregression is used to predict values of the dependentvariable in the original units rather than log units,there is a retransformation bias and the values pre-dicted by the power function typically underestimatethe true mean (Helsel and Hirsch, 1992). The recom-mended remedy is to apply a bias correction factor.Duan’s smearing estimator (1983), which is derivedby exponentiating the residuals from the log-logregression and calculating their average value, iscommonly used in sediment and water-quality studies(Helsel and Hirsch, 1992; Rasmussen et al., 2005)and was applied in the present case. The value ofthe coefficient derived from the log-log regression inFigure 9 is 1.10; this correction factor was multipliedby all storm-total suspended sediment load valuesthat were predicted using the power function.

In using the log-log regression illustrated in Fig-ure 9 to predict storm-period suspended sedimentloads for the July 2004-July 2005 period, one way toassess the variability of the predictions is to selectthe residuals from each of the 36 observations in theoriginal log-log regression, and to assume that eachof these is a realization of a random process. If weuse the regression equation to calculate the predictedlogarithm of storm-period suspended sediment loadfor each of the discharge peaks in the July 2004 toJuly 2005 period, we can generate a family of possiblevalues for each peak discharge by adding each of the36 residuals to the expected value and exponentiatingthe resulting sums. By plotting these values as afamily of curves we can illustrate the range of poten-tial variation in predicted loads. Figure A1 shows theextent to which the range of possible values widensdramatically with increasing discharge. If plottedwith logarithmic axes rather than arithmetic axes,this figure would look very similar to the pattern ofprediction limits and confidence limits in Figure 9.However there is no simple formula to estimate thevariance or standard error of the sum of a series ofstorm-total suspended load values predicted usingthe log-log regression equation; because the individ-ual load estimates are calculated by retransformationfrom log space to original units, we cannot assume



that the variance of the sum of those load estimatesis equal to the sum of the variances. There are re-sampling approaches that may be applied to thisproblem, but the problem is beyond the scope of thepresent paper.

ACKNOWLEDGMENTS

Completion of this work would not have been possible withoutmany individuals who helped with field data collection. We aregreatly appreciative of the efforts of Christy Laudadio, Hyun JinKim, Luanne Steffy, Matt Young, Matt Ballantine, Jane Diehl, andJeffrey McNeal for their tireless efforts and many long hours in thefield. We are also grateful for the expert advice and help from AllenGellis, Michael Langland, Alan Ellsworth, Margaret Carfioli, andRob Ryan. Michael Langland deserves special thanks for his helpin providing not only the suspended concentration, turbidity andflow data, but also for taking additional time to review those dataas we were writing this manuscript. We thank Nagaraj Neerchalfor guidance with the statistical analysis. This material is basedupon work supported by the National Park Service under CW-CESU cooperative agreement H309701200 and partly by the U.S.Environmental Protection Agency under Grants R-82818201-0 andCR83105801. Although the research described in this paper hasbeen funded in part by the U.S. Environmental Protection Agency,it has not been subjected to the Agency’s peer and policy reviewand therefore does not necessarily reflect the views of the Agencyand no official endorsement should be inferred. This paper is dedi-cated to the memory of Brian Lambert, Natural Resource Specialistwith the National Park Service, who worked tirelessly to preparethe way for this project.

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