Sediment Contributions from Floodplains and Legacy Sediments To

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Geomorphology 235 (2015) 88–105

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Geomorphology

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Sediment contributions from ﬂoodplains and legacy sediments to Piedmont streams of Baltimore County, Maryland

Mitchell Donovan a,⁎, Andrew Miller a, Matthew Baker a, Allen Gellis b a University of Maryland-Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA b U.S. Geological Survey, 5522 Research Park Drive, Baltimore, MD 21228, USA article info abstract

Article history: Disparity between watershed erosion rates and downstream sediment delivery has remained an important Received 25 July 2014 theme in geomorphology for many decades, with the role of floodplains in sediment storage as a common Received in revised form 19 January 2015 focus. In the Piedmont Province of the eastern USA, upland deforestation and agricultural land use following Accepted 23 January 2015 European settlement led to accumulation of thick packages of overbank sediment in valley bottoms, Available online 3 February 2015 commonly referred to as legacy deposits. Previous authors have argued that legacy deposits represent a poten- Keywords: tially important source of modern sediment loads following remobilization by lateral migration and progressive Fluvial channel widening. This paper seeks to quantify (1) rates of sediment remobilization from Baltimore County Change detection floodplains by channel migration and bank erosion, (2) proportions of streambank sediment derived from legacy Bank erosion deposits, and (3) potential contribution of net streambank erosion and legacy sediments to downstream Legacy sediment sediment yield within the Mid-Atlantic Piedmont. Floodplain We calculated measurable gross erosion and deposition rates within the fluvial corridor along 40 valley segments from 18 watersheds with drainage areas between 0.18 and 155 km2 in Baltimore County, Maryland. We compared stream channel and floodplain morphology from lidar-based digital elevation data collected in 2005 with channel positions recorded on 1:2400 scale topographic maps from 1959–1961 in order to quantify 44–46 years of channel change. Sediment bulk density and particle size distributions were characterized from streambank and channel deposit samples and used for volume to mass conversions and for comparison with other sediment sources. Average annual lateral migration rates ranged from 0.04 to 0.19 m/y, which represented an annual migration of 2.5% (0.9–4.4%) channel width across all study segments, suggesting that channel dimensions may be used as reasonable predictors of bank erosion rates. Gross bank erosion rates varied from 43 to 310 Mg/km/y (median = 114) and were positively correlated with drainage area. Measured deposition within channels accounted for an average of 46% (28–75%) of gross erosion, with deposition increasingly important in larger drainages. Legacy sediments accounted for 6–90% of bank erosion at individual study segments, represented about 60% of bank height at most exposures, and accounted for 57% (±16%) of the measured gross erosion. Extrapolated results indicated that first- and second-order streams accounted for 62% (±38%) of total streambank erosion from 1005 km2 of northern Baltimore County. After accounting for estimated redeposition, extrapolated net streambank sediment yields (72 Mg/km2/y) constituted 70% of estimated average Piedmont watershed yields (104 Mg/km2/y). The results suggest that streambank sediments are a relatively large source of sediment from Piedmont tributaries to the Chesapeake Bay. © 2015 Elsevier B.V. All rights reserved.

1. Introduction delivery of sediment (Wolman, 1977; Walling, 1983; Trimble and Crosson, 2000; Knox, 2006), challenges arise from spatial and temporal The relation between erosion, storage, and delivery of sediments complexity of sediment sources, transport processes, anthropogenic across a watershed has been an active topic in ﬂuvial morphology impacts, and the magnitude and frequency of precipitation events throughout the last century (Gilbert, 1917; Mackin, 1937; Trimble, (Harvey, 2002; Orwin et al., 2010). The dominant source(s) of sediment 1983; Phillips, 1991), often examined using a sediment budget (Reid can vary throughout watersheds and over short time scales (Rhoades and Dunne, 2005). Despite numerous efforts to connect sources and et al., 2009; Gellis and Brakebill, 2012) as the result of widespread land use change (Wolman and Schick, 1967; Jacobson and Coleman, 1986) and agricultural practices (Gellis et al., 2009). ⁎ Corresponding author. E-mail addresses: [email protected] (M. Donovan), [email protected] (A. Miller), Observations of high sediment yield throughout the Piedmont of [email protected] (M. Baker), [email protected] (A. Gellis). the eastern U.S. have motivated investigations of sediment sources.

Although total streambank erosion has been cited as accounting for 2003). The TMDLs are calculations of the maximum amount of a partic- 50 to 80% of sediment yields in some Piedmont watersheds (Trimble, ular pollutant that can enter a water body and still meet safe water 1997; Shilling, 2009; Merritts et al., 2010; Gellis and Noe, 2013), similar quality standards as defined in the Clean Water Act. contributions have been measured from agricultural and forested upland sources in other watersheds (Phillips, 1991; Gellis et al., 2009; 2. Regional setting/segment descriptions Smith et al., 2011). One factor affecting these varied results is uncertainty in the methods and scales of comparison between watershed mea- 2.1. Regional setting surements. Short-term and reach-scale measurements of bank erosion are subject to high spatial and temporal variability (Wolman and We studied portions of 40 Piedmont streams across Baltimore Gerson, 1978; Hooke, 1980; Lawler et al., 1999; Reid and Dunne, County, Maryland (Fig. 2) within watersheds that are dominantly for- 2005; Belmont, 2011), producing considerable uncertainty when gener- ested and agricultural land. These watersheds are located mostly out- alized to address regional or long-term patterns (Wolman and Leopold, side of the zone of urban and suburban growth surrounding Baltimore 1957; Smith, 2011). In order to obtain a spatially and temporally City, which corresponds closely with the Urban–Rural Demarcation representative data set of bank erosion rates, measurements should en- Line (URDL). The majority of northern Baltimore County is underlain compass multiple decades and extend throughout the surficial channel by schist, while central and eastern portions are dominantly underlain network. by gneiss, quartzite, and marble, eventually transitioning to gravel Researchers have long observed the process of laterally migrating and sand in the Coastal Plain physiographic province. Some of our lowland channels eroding through historical valley-spanning deposits segments along Western Run flow through broad valleys underlain that resulted from upland land use activities following European by Cockeysville marble, which is relatively soluble and potentially settlement (Happ et al., 1940; Costa, 1975; Jacobson and Coleman, correlated with broad alluvial valleys. 1986; Phillips, 1991; Jackson et al., 2005; Wegmann et al., 2012). Such Prior to the 1800s, a relatively stable Piedmont landscape allowed historical deposits, collectively referred to as legacy sediments (Fig. 1), for the formation of thick upland soil profiles that were rapidly truncated may be an ongoing dominant source of sediment in watersheds caused in response to forest clearing for agricultural purposes throughout the by increased runoff and reduced upland sediment supply subsequent to period of Euro-American colonization (Costa, 1975; Costa and Cleaves, historical peaks of agricultural land use (Colosimo and Wilcock, 2007). 1984; Jacobson and Coleman, 1986). This disturbance is still evident in Despite evidence that floodplains (Church and Slaymaker, 1989; legacy sediments deposited across footslopes and pre-settlement flood- Allmendinger et al., 2007; Voli et al., 2013) and legacy sediments plains during the peak of agricultural land use in the mid to late nine- (Walter et al., 2007; Hupp et al., 2013) are large components of the teenth century (Jacobson and Coleman, 1986). Walter and Merritts total sediment load delivered from streams, mobilized sediment may (2008) proposed that mill dams were also necessary to explain the not exit Piedmont watersheds for 6 to 10 millennia (Pizzuto, 2001; extent of legacy sediments across the region. The relative importance Jackson et al., 2005; Pizzuto et al., 2014). of mill dams was investigated as a part of the project and will be ad- In order to better understand the role of streambank and legacy sed- dressed in a companion paper. In time, decreased agricultural activities iments, our research seeks to quantify (i) rates of sediment remobiliza- and improving land use management reduced sediment supply from tion from Baltimore County floodplains by channel migration and bank upland areas, as reflected in 75% reductions of annual sediment erosion, (i) proportions of streambank sediment derived from legacy yields to reservoirs (Wolman and Schick, 1967) and channel incision deposits, and (iii) potential contribution of net streambank erosion (Jacobson and Coleman, 1986) in Baltimore County. and legacy sediments to downstream sediment yields within the Mid- Atlantic Piedmont. This research has implications for river-restoration 2.2. Study segment descriptions policies, water quality regulations, land use, ecosystem, and flood-risk management (Reid and Dunne, 2005; James, 2013). Evaluating remobi- Twenty-five Piedmont streams were originally selected as represen- lization rates of sediment stored along Piedmont floodplains may help tative portions of the Baltimore County stream network, with drainage us understand its importance as a source of sediment and help guide areas from 0.18 to 155 km2 at their downstream ends. Each stream sediment reduction policies required to meet current total maximum included multiple contiguous study segments (our unit of observation) daily load (TMDL) thresholds set by the EPA (Langland and Cronin, ranging from 0.34 to 4.73 km in length. This scale of observation

Fig. 1. The evolution of Piedmont alluvial valley conditions. The shifting state of a typical Piedmont stream is illustrated for the pre-colonial period (top), settlement period (middle), and current conditions (bottom) as described in Jacobson and Coleman (1986). 90 M. Donovan et al. / Geomorphology 235 (2015) 88–105

Fig. 2. Geologic map of Baltimore County and the stream segments studied in this project. While the majority of segments in northern Baltimore County run on schist, streams in western Baltimore County run across a variety of geologic units. included channel segments sufficiently long to encompass local encompassing each study segment. The 2006 National Land Cover Data- variability in erosion and lateral migration rates. Channels spanning base (NLCD; Fry et al., 2011) was used to quantify the Anderson level 1 multiple Strahler orders were apportioned into multiple respective urban, forested, and agricultural proportions in upstream contributing segments, providing a total of 40 study segments (Table 3). Segments areas of each study segment. Other geospatial data sets used included represented first- through sixth-order streams and a broad range of for- high-resolution orthophotos (2005, 2008), geologic units, and soil ested and agricultural lands with low levels (b20%) of urban land cover type boundaries. in all but three contributing areas (21, 22, and 28% urban land cover). Historical topographic maps (Fig. 3) were created using photogram- Additional criteria such as dominant geology (Dicken et al., 2005), chan- metric methods according to USGS standards. The maps contain natural nel width, and slope characteristics were compiled as secondary traits to features such as forests, ponds, and streambank or channel centerline help explain observed variations in erosion rates. Complete data on the locations, as well as anthropogenic features including building corners, characteristics of sampled stream segments and methods for scaling are road junctions, bridge abutments, and surveyed points/monuments provided below. The 40 segments represent our best attempt to provide from the National Geodetic Survey. These features as well as corners a reasonable sample for extrapolating local streambank sediment of other topographic map tiles were used to georeference historical erosion measurements along Baltimore County's drainage network maps. A magnified portion of the scanned map in Fig. 3 illustrates and comparison with regional watershed sediment yields. three georeferenced control points from buildings visible on historical maps and on 2005/2008 aerial orthophotos. The horizontal accuracy 3. Material and methods of each map was dependent on the quality, quantity, and spatial distribution of control points, which varied between 13 and 41 for each map We quantified 44–46 years of streambank erosion across 40 seg- used in the study. A second-order polynomial transformation, which ments of the Baltimore County drainage network using a 1-m resolution often yields the greatest accuracy (Hughes et al., 2006), was applied to lidar digital elevation model (DEM) from 2005 and scanned 1:2400 control point locations during map adjustment, resulting in an average scale historical topographic maps dated from 1959 to 1961. The raw horizontal RMSE of 1.05 m, equivalent to 0.02 m/y when scaled to lidar scan, acquired during the spring of 2005 by Sanborn Mapping, intervening years between data sources (n =45). was the subject of two vertical error assessments in addition to 91 Each studied segment length was selected based on criteria includ- ground truth points that determined that 95% of the lidar elevations ing accessibility, evidence of altered or artificial channels, presence were within 0.23–0.24 m of ground elevation. A lidar bare-earth DEM of an established floodplain, or availability of accurate historical was generated by the authors with a nearest neighbor interpolation and contemporary data. Selection of historical maps for analysis and used to create hillshade, slope, and curvature maps for terrain was constrained by warping during the scanning process and sparse M. Donovan et al. / Geomorphology 235 (2015) 88–105 91

Fig. 3. A portion of historical map tile NW26J from the scanned topographic archive. This image highlights a portion of Piney Run (blue lines) along with three points georeferenced to aerial orthophotos from 2008. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.). georeferencing information on some maps. We also avoided areas banks. For each sample we recorded (i) the height of the sample from where lidar-based DEM data contained inaccurate data caused by ex- the bottom of the exposed streambank; (ii) the primary color (using a tremely dense vegetation or gaps in lidar coverage at some locations Munsell chart); (iii) the texture based on touch; (iv) a preliminary (Aguilar et al., 2010). label of pre-settlement, legacy sediment, or point bar; and (v) the thick- Although historical topographic maps provided 5-foot (1.52-m) ness of pre- and post-European settlement material. Uncertainty in contour intervals, their resolution was not detailed enough to use in density values arising from sediment packing, varying percent satura- DEM differencing between initial and final time periods (Lane et al., tion and percent organic matter, and porosity are quantified in the 1994; Wheaton et al., 2010; James et al., 2012). Therefore, only plani- Discussion. metric information from the maps was used to measure change over Using the stratigraphic criteria established previously, we identified time. In our comparisons, we assumed that no significant channel the presence of legacy sediment at all but one segment, and we incision or aggradation occurred from 1960 to 2005. Whereas this measured the percent of bank material that could be classified as legacy assumption may result in underestimates if channels incised over time sediment in 2 to 16 streambank exposures within each segment. in response to variable land use (Costa, 1975), our field evidence and Because the proportion of legacy sediment varied across exposures in past research indicate that many Piedmont streams have experienced each study segment, we calculated the segment-averaged percent of no net incision beyond their pre-settlement depths (Colosimo and bank material identified as legacy sediment to quantify longitudinal Wilcock, 2007; Schenk and Hupp, 2009; James, 2011; Wegmann et al., and lateral variability in legacy sediment thickness. 2012) with the exception of headwater channels in urban areas. The role of overbank aggradation is addressed later in the manuscript, including quantitative estimates of floodplain deposition.

3.1. Sediment sampling and identiﬁcation methods

Sediment cores were sampled from distinct layers using polyvinyl chloride (PVC) cylinders of known volume at multiple exposed streambanks along each study segment. Each layer was identified as pre-settlement sediment, legacy sediment, or recently deposited channel material using stratigraphic discontinuities in their color, grain size, and density, along with their location within the bank profile. Similar to James (2013),wedefine legacy sediments as alluvial overbank sediment that was deposited post-settlement, regardless of the geomorphic process or conditions governing its deposition. Typical profiles exhibited a distinct contact between mineral rich layers of black to dark gray (Munsell system, 10YR2/1 to 7.5YR2.5/1) pre-settlement material, overlain by fine grained orange to brown (5YR4/6 to 7.5YR3/4) silty sands (Fig. 4), typical of legacy sediments described by previous authors (Happ et al., 1940; Jacobson and Coleman, 1986; Pizzuto, 1987; Bain and Brush, 2005; Walter and Merritts, 2008; Wegmann et al., 2012). For stratigraphic sequences not easily interpreted in the context of historical land use patterns, we assigned samples to the most probable category in the field based on their location within the bank and an initial visual inspection. Once in the lab, the color, density, and bank position characteristics of each sample were compiled in a database to confirm or re-categorize the sample. Across all stream segments, we sampled 195 streambank cores of known volume (100, 150, or 200 cm3), of which 173 were used in deter- mining characteristic bulk densities and 98 were wet sieved for particle Fig. 4. A field image of a stratigraphic profile and sample locations. A distinctive boundary size distributions. The number of samples per study segment ranged is seen at the transition from pre- to post-settlement material. The white tubes are from 4 to 22, owing to segment length and the number of exposed samples before they were extracted. 92 M. Donovan et al. / Geomorphology 235 (2015) 88–105

3.2. Channel and floodplain delineations of legacy sediment found in the streambanks of each study segment was multiplied by the measured gross erosion for the study segment Following georectification of historical maps, the right and left chan- to obtain the gross legacy sediment erosion rate. nel edges were manually digitized (blue lines, Fig. 3) and compared to the 2005 lidar channel delineations, extracted cross sections, and aerial 3.4. Calculating net erosion; refining in-channel redeposition and estimat- orthophotos at locations where the channel had not migrated. The com- ing floodplain deposition parisons indicated that channel lines on the historical topographic maps were drawn along the wetted channel boundary. Thus, we delineated Research has demonstrated very little overlap in the grain size of the edges of the modern (2005) wetted channel boundaries using channel deposition and fine-grained sediments eroded upstream slope grids, hillshade maps, aerial orthophotos from 2005, and minima (Walling et al., 1998; Owens et al., 1999; Merritts et al., 2013). We com- in profile curvature1 that occur at the toe of streambanks. From the pared the grain size distribution of streambank samples with channel wetted-channel edges, a single channel center line was generated. deposit samples to estimate the proportion of redeposition that might Along the centerline, thalweg elevation (defined by the local minimum have been derived from streambanks. Grain size overlap between sam- elevation) and wetted-channel width were measured. The elevation ple classes provided an indication of potential streambank redeposition. measurements were used to create a continuous raster surface of the In order to ensure that our net streambank erosion was not biased high, channel elevation, assuming that the channel thalweg elevation did we assume that none of the fine-grained sediments stored in the not change substantially over the study period. channel came from external sources. Local maxima in profile curvature occurring at transitions from flat Floodplain deposition may exceed upstream bank erosion (Hupp floodplains to steeply sloping streambanks (Fig. 5)wereusedtodelin- et al., 2013) and represents an important factor in any sediment budget, eate the floodplain edge. Lidar-based and field-measured cross sections but is rarely considered alongside erosion measurements within the of the streambanks were used to confirm that the delineations most ac- Mid-Atlantic region. We established a range of values for floodplain ac- curately represented the height of overbank legacy sediment deposits cumulation rates from 1.0 to 5.0 mm/y (mean (μ) = 3.0) by combining that constitute many floodplains and streambanks. Because elevation field observations and published floodplain sedimentation rates for values on opposite sides of the channel often differed, the elevation watersheds with similar land use history and/or physiographic traits along the right- and left-floodplain delineations (red lines, Fig. 5) (Happ, 1945; Leopold et al., 2005; Allmendinger et al., 2007; Gellis were interpolated across the channel to generate a raster surface et al., 2009; Trimble, 2009; Smith and Wilcock, 2015). Accumulation representing the floodplain elevation. rates were converted to annual floodplain deposition per unit length For 13 study segments—primarily those with smaller drainage areas (Mg/km/y). —the historical maps represented the stream as a single channel center- The estimates are predicated on the assumption that one-third of the line rather than channel margins. In the absence of right and left chan- valley is an active floodplain, based on our field observations and past nel margins (ideal for our methods), the width of historical channels research demonstrating that a majority of floodplain deposition occurs were approximated as the average width of the modern channel. along near-channel levee deposits (Walling et al., 1998; Hupp et al., 2013; Schenk et al., 2013). Although our results may differ with direct 3.3. Mapping and calculating erosion and deposition measurements of floodplain deposition, this assumption is included to account for a major component of the sediment budget that, if omitted, Channel delineations from each time period were overlain and would lead to overestimation of the net sediment yield associated with converted to discrete polygons of ‘Erosion’, ‘Deposition’, ‘EroDepo’ bank erosion. The method for calculating uncertainty associated with (indicating erosion and deposition), or ‘No change’ (Fig. 6). Polygons our estimated floodplain deposition is provided in Section 5.4 and smaller than 1 m2 and narrow slivers were removed from the analysis Appendix B. Eq. (1) illustrates the steps used to convert the floodplain in order to omit geomorphic change below the level of detection deposition rates (m/y) to an annual mass per unit length (Mg/km/y). (LoD) caused by georectification error. Our measured in-channel deposition data were used as an estimate A DEM of difference (DoD) between modern topography and of redeposition downstream and combined with estimates of floodplain channel elevation raster represented deposition, which was usually in deposition to calculate the total deposition. These were subtracted from the form of lateral accretion deposits or point bars consisting of coarse the measured gross erosion to estimate the net streambank erosion. sediment deposited as the channel migrated from its 1961 location. In Within Appendix A, we provide an alternate net erosion calculation 1961, the EroDepo zone was occupied by a floodplain that was eroded that is based solely on measurements made in our study, removing between 1961 and 2005 as the channel migrated laterally. The volume the uncertainty associated with estimated floodplain deposition. of sediment eroded from this area was estimated by the difference between the floodplain elevation (red-dashed line, Fig. 6) and channel 3.5. Measuring linear rates of lateral migration elevation (blue-dashed line, Fig. 6). The volume of redeposition that formed concurrently was measured as the difference between the mod- The Channel Planform Statistics Tool (available from the National ern topography DEM and channel elevation raster. The area occupied by Center for Earth-Surface Dynamics Stream Restoration Toolbox, http:// the channel in 2005 was interpreted as subject to net erosion. Therefore, www.nced.umn.edu/content/tools-and-data) was used to calculate lat- subtracting floodplain elevation raster from the modern topography eral migration rates. The ‘Lateral Offset Measurement’ tool (Lauer, 2006) yielded the DoD of sediment eroded within this zone. estimates the mean lateral migration distance between two stream Volumes of erosion and deposition were multiplied by their respec- channel centerlines at equally spaced increments. At each increment tive mean bulk densities (averaged from samples collected across the along the stream, the migration distance is averaged from four line seg- study region) to obtain estimates of mass. The mass of sediment was ments bridging the stream channel centerlines from each time period. then summed for each discrete zone (polygon) of Erosion, Deposition, Over 1000 measurements of lateral migration were averaged for each or EroDepo. Cumulative erosion and deposition (Mg) for each study study segment in order to compile data for regional comparison of segment were divided by the segment's length (0.34–4.73 km) and migration rates. the time elapsed (44–46 years) to obtain measurable gross erosion Using Eq. (2), the average rate of lateral migration (LM) along the and gross in-channel deposition rate (Mg/km/y). The average fraction entirety of each study segment was converted to the annual mass of streambank sediment eroded per unit channel length (Mg/km/y). 1 The rate of change in slope over a distance measured in the downstream direction Variables in the equation include segment-averaged bank height (Peckham, 2003). (Hbh), segment length (Lseg), and bulk density of streambank sediments M. Donovan et al. / Geomorphology 235 (2015) 88–105 93

Fig. 5. Channel edges delineated from a curvature grid. (Top) Right- and left-edge of water lines (blue) and floodplain lines (green) delineated from curvature and slope grids. The inset plot contains curvature (red), with a local minimum at the wetted channel edge and a local maximum corresponding with the transition from channel to floodplain. (Bottom) The delineated channel is overlaid with a digital orthophoto from 2005 demonstrating the accuracy. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).

(ρfp). Gross erosion in Mg/km/y derived from segment-averaged lateral Environment, 2006) as well as long-term sedimentation records based bank migration rates was compared with gross erosion measured using on historical reservoir surveys (Wolman and Schick, 1967; Dendy and the pixel-based approach described earlier. This allowed us to assess the Champion, 1978; Ortt et al., 2000; Smith, 2011) available for compari- replicability of the results using two different measurement techniques son with our net streambank sediment yield estimates. Finally, two with the same DEM data. streams within the study area, Chimney Branch and Powell's Run, were small enough to have erosion rates calculated for more than 75% 3.6. Statistical assessments of erosion rates across all study segments of their drainage network (first- through third-order) that contained geomorphic evidence of floodplain development. Linear correlations were used as the primary exploratory statistic for Our analytical approach for predicting erosion rates across the assessing how remobilization rates varied in relation to independent drainage network was selected to reduce variance in the results and to watershed characteristics. The results of the correlations were useful avoid parametric assumptions associated with typical linear regression. for understanding patterns (McKillup, 2010). Although we did not We used nonparametric classification and regression trees (CART; infer causation from linear regression relationships, coefficients of Breiman et al., 1984) to bin erosion rate estimates based on a set determination provided a measure of strength for predicting erosion of input variables that could be mapped at the scale of the entire county rates using watershed characteristics. using a 10-m DEM: Strahler stream order, Shreve-magnitude, segment- averaged slope, and valley width. 3.7. Extrapolating bank erosion rates throughout the drainage network Averaged gross erosion and total deposition rates were predicted by the CART analysis for each output bin/class and extrapolated to the re- The area selected for extrapolation covered a total of 1005 km2 with maining channels draining 1005 km2 in northern Baltimore County. 3030 km of total stream length; it is approximately coincident with the Subtracting gross erosion by total deposition provided the net erosion northern extent of Baltimore County URDL and contains drainage areas rate for each stream pixel, which was summed for the entire area. The and land use patterns (primarily forested and agriculture) similar to net streambank sediment yield (Mg/km2/y) was obtained by dividing those of our study segments (Table 1). Our streambank measurements the cumulative net erosion by the total drainage area. covered a cumulative length of 75.0 km, which were used as a representative sample of basins draining a total of 267 km2 within the zone of 3.8. Additional considerations for tributary channel erosion extrapolation. An additional extrapolation was performed specifically for the Smith et al. (2011) found that first-order basin areas were an aver- Western Run drainage basin (220 km2) using 12 study segments age of 0.3 km2 but occupied 62% of the total drainage area in Cattail (Fig. 7). Western Run drains into the Loch Raven Reservoir, which has Creek, Maryland, indicating that channels at this scale should not be TMDL requirements for sediment (Maryland Department of the overlooked in sediment budgets. Observations by other authors indicate 94 M. Donovan et al. / Geomorphology 235 (2015) 88–105

Fig. 6. Planform and profile view of a channel illustrating the calculations of erosion and deposition. (Top right) An aerial view of the erosion, deposition, and erodepo zones found within the migrating channel of Piney Run (top left). The black line indicates where the cross section was extracted from. The different ‘geomorphic zones’ are expressed with unique hues and textures (bottom), illustrating how the volume of erosion/deposition was calculated within each. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Conversion from linear floodplain sedimentation (m/y) to annual deposition (Mg/km/y).

Dep Area ρ Floodplain deposition rate ¼ fp fp erosion L seg (1) m Mg m2 y 3 −1 −1 Units : m ¼ Mg km y : km Converting linear rates of channel migration to annual gross erosion per unit channel length.

ρ LM Hbh Lseg fp

Lseg m Mg m m (2) y 3 ‐1 −1 Units : m ¼ Mg km y : km

that alluvial storage does not generally occur at drainage areas below to narrow valleys and limited space for sediment storage, but that 1.7–3.5 km2 in North Carolina (Phillips, 1995) or along low-order legacy sediment deposits did indeed occur. Recognizing that alluvial channels in the Mid-Atlantic Piedmont (Allmendinger et al., 2007). sediment deposits were discontinuous, we used lidar to measure the Along such channels, our ﬁeld and lidar observations indicated that proportion of channel length containing alluvial deposits at 21 stream ﬂoodplains—and therefore legacy sediments—were discontinuous due reaches with drainage areas between 0.07 and 0.5 km2. The details of

Table 1 Cumulative watershed and land use characteristics for study segments and the extrapolation areas.

Characteristics Land use

Area Drainage area (km2) Total stream length (km) Agriculture (%) Forested (%) Urban (%)

Cumulative study segment area 267 828a 49.5% 37.2% 9.1% Extrapolation — N. Baltimore County 1005 3030 33.2% 46.6% 14.8% Extrapolation — Western Run 211 665 38.3% 38.9% 20.0%

a Represented by 75.0 km of channel length studied in this project. M. Donovan et al. / Geomorphology 235 (2015) 88–105 95

Fig. 7. Western Run drainage basin, 220 km2. The 10 red portions of the stream network represent our study segments within the drainage basin. Three segments were along the main stem of Western Run. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) our floodplain measurements along tributary channels are provided in In-channel deposition accounted for a volume equal to 28 to 75% of Appendix A.2. In order to ensure that the contributions from low-order the average gross erosion (masses equal to 21–94%) across the study tributaries were not overestimated, we provide alternate streambank segments, but, as indicated above, was substantially different in particle erosion and sediment yield calculations with reductions applied to size distribution than sediment derived from streambanks. Assuming erosion from first- and second-order channels in the Discussion. that a maximum of 30% of the in-channel deposition comes from streambank sediment, in-channel deposition was 6 to 28% of gross 4. Results streambank erosion. The magnitude of channel deposition rates2 (column XIII, Table 3) generally increased more rapidly than gross 4.1. Sediment sample density and grain size characteristics erosion rates from small to larger streams. The net erosion rates in Fig. 9 accounted for floodplain and in- After an ANOVA test detected significant differences (p b 0.001) in dry channel deposition and generally declined at larger drainage areas. bulk densities of legacy, pre-settlement, and channel deposit samples However, they did not exhibit strong correlations with Shreve magni- (Clément and Piégay, 2003), a post-hoc Tukey test confirmed that each tude or any of the independent variables (not shown here). group was indeed significantly different (p b 0.01) (Tukey, 1949). The averages and distributions of each sample type can be found in Table 2 and Fig. 8. Relatively low standard deviations reflect narrow ranges of the 4.3. Legacy sediment storage and erosion rates densities for each class of material. A Hartigan's Dip test for unimodality (Hartigan and Hartigan, 1985) indicated that the distribution of density Using our stratigraphic criteria, we identified the presence of legacy values for pre-settlement samples were nonunimodal (D = 0.0464, p- sediment at all but one study segment, and we measured the percent of value = 0.71). Interpretations of these results and comparisons with pre- bank material that could be classified as legacy sediment in 2 to 16 viously published values can be found in the Discussion. streambank exposures at each segment. Although an increasing trend Although grain size distributions for each sample class did not existed between average legacy sediment thickness and log-drainage indicate a clear central tendency (Fig. 8), average legacy sediments area, observed reach-scale variability in legacy deposits demonstrated were 64% silt/clay and 34% sand, whereas pre-settlement material was that local influences on legacy sediment storage are also important. predominantly sand (56%) with a substantial fraction of silt/clay The local variability is reflected in the relatively high standard error (40%). Both legacy and pre-settlement material contained low propor- (SE) in mean thickness of legacy deposits (Appendix B.5, Table B.2). tions of gravel, yet channel deposits contained an average of 50% gravel Gross legacy sediment erosion rate at each site was based on an av- and only 3.6% silt/clay. Samples from channel deposits were composed erage thickness from multiple bank profiles, and resulting values ranged of only 30% fine sand, silt and clay compared to 92% fines within legacy from 3 to 220 Mg/km/y and represented 6 to 90% of the gross erosion sediments. along individual study segments (column XVI, Table 3). A Shapiro– Wilk test indicated that the proportion of gross erosion from legacy sed- 4.2. Gross erosion, gross deposition, and net erosion rates iment was not normally distributed (W = 0.98, p = 0.01); however, when the lone segment with minimal to no legacy sediment was Segment-averaged gross streambank erosion rates ranged from 43.7 excluded from the test, the distribution was normal (W = 0.89, to 309.6 Mg/km/y (column XII, Table 3). A strong correlation (r = 0.72) p = 0.91; Fig. 10)withμ =65%. existed between the gross erosion rates and log-Shreve magnitude— a A strong positive correlation (r = 0.76) existed between legacy surrogate for drainage area (Fig. 9). Other independent variables such sediment erosion rates and drainage area. Correlations also existed as log-drainage area, slope, log-bank height, log-stream width, and val- between legacy sediment erosion rates and channel slope, stream ley width had similar correlations caused by their relation to watershed contributing area (not shown). 2 Does not account for downstream redeposition on floodplains. 96 M. Donovan et al. / Geomorphology 235 (2015) 88–105

Table 2 A summary of sample size, density, and grain size characteristics for legacy sediment, pre-settlement, and point/channel bar material; these three classes were the primary types of sediment characterized and sampled in the ﬁeld.

Sample type # of samples Density (g/cm3) Grain size averages

Density Grain size Mean Std. dev. Gravel (%) Sand (%) Silt/clay (%)

Legacy sediment 93 62 1.15 0.14 1.9 33.8 64.3 Pre-settlement 43 34 1.07 0.20 4.1 55.7 40.3 Channel deposit 33 12 1.43 0.22 50.2 46.2 3.6 width, and valley width, all of which correlate with drainage area (data 4.5. Floodplain and downstream deposition not shown here). The correlations suggest that geomorphic conditions along broad alluvial valleys facilitated increased storage during historical Total deposition (Fig. 9, Table 3), which includes in-channel and upland denudation by comparison with steep and narrow headwater ﬂoodplain deposition, was 14% to 110% (μ = 39%) of gross erosion channels lacking ample alluvial storage. across individual study segments and generally increased with larger drainage areas. This is equivalent to rates between 45 and 455 Mg/km/y. 4.4. Lateral migration rates

The segment-averaged lateral migration rates (column XVII, Table 3) 4.6. Extrapolated streambank erosion rates varied between 0.04 and 0.19 m/y, with higher rates at larger drainage areas. Variables correlated with watershed scale, such as log-drainage Across the study segments, CART analysis identiﬁed four distinct area, log-Shreve magnitude, log-stream width, and Strahler order, subclasses of gross erosion and total deposition rates based on Shreve were also strongly correlated with rates of lateral migration. The migra- magnitude and Strahler order, which can be readily interpreted by trac- tion rates exhibited a maximum within the range of drainage areas ing each output branch visualized in the top of Fig. 12. For gross erosion between 40 and 80 km2, similar to trends found in previous studies of rates, the four classes of streams were grouped as: (i) stream order ≤ 2; bank erosion (Lawler et al., 1999; Hupp et al., 2010). Upon conversion (ii) stream order N 2 and magnitude b 37; (iii) magnitude ≥ 37 to annual migration as a percent of channel width, the migration rates and b111; and (iv) magnitude N 111. For total deposition rates, varied around an average of 2.5% (standard deviation, σ =0.89%)across the groups were: (1) magnitude ≤ 12; (2) magnitude N 12 and ≤34; all drainages (Fig. 11). (3) magnitude N 34 and b111; and (4) magnitude ≥ 111. Gross measurable streambank sediment erosion was 2.16 × 105 (±4.16 × 104) Mg/y, and equivalent to a gross streambank sediment yield of 224 (±43) Mg/km2/y from northern Baltimore County. After

Fig. 8. Frequency distributions of sediment sample densities (left), percent sand (middle), and percent silt and clay (right). From top to bottom, each respective row represents legacy sediment, pre-settlement, and point bar samples. Table 3 A summary of characteristics for the 40 study segments (after they were divided into by their stream order); colors indicate the segment's CART classiﬁcation based on the gross erosion rate or total deposition rate (Mg/km/y); GER = gross erosion rate, GDR = gross deposition rate, TDR = total deposition rate, NER = net erosion, LSER = legacy sediment erosion rate, and LMR = lateral migration rate.

I II III IV V VI VII VIII IX X XI XII XIII XIV XV XVI XVII

ID# Segment ID Strahler Shreve Area Segment a a a a a a a a b b a Slope Channel Bank Legacy sediment Valley width GER GDR TDR NER LSER LMR order magnitude (km²) length (km) (m/m) width (m) height (m) (%) (m) (m/y)

1 Bee Tree Run 4 102 23.23 4.25 0.0044 3.90 1.37 84% 82.7 122.4 54.6 105.9 36.6 103.4 0.073 2 Blackrock Run 2 13 0.88 1.43 0.0171 1.48 1.01 61% 83.5 47.9 25.9 14.5 –29.9 29.0 0.049

3 Blackrock Run 3 22 3.62 1.63 0.0088 2.72 1.13 61% 93.1 98.6 72.8 24.7 –1.4 59.8 0.092

4 Blackrock Run 4 37 5.81 0.48 0.0056 2.82 1.09 61% 89.1 67.8 35.3 39.8 –17.6 41.1 0.080

5 Buffalo Run 3 42 7.53 3.46 0.0157 2.92 1.15 52% 101.7 90.7 41.6 44.9 –7.0 46.9 0.072

6 Buffalo Run Trib 1 3 0.34 0.54 0.0482 2.54 1.40 52% 22.9 106.6 85.0 5.5 61.9 55.1 0.075

7 Chimney Branch 1 1 0.24 0.75 0.0247 3.30 1.36 6% 25.0 64.8 26.3 4.3 36.0 4.1 0.047

8 Chimney Branch 2 3 0.58 1.79 0.0247 2.94 1.02 6% 39.8 43.7 31.9 5.9 0.8 2.7 0.050

9 Chimney Branch 3 10 1.72 1.34 0.0247 3.28 1.85 6% 56.7 51.4 25.9 13.3 –3.9 3.2 0.063

10 Cooks Branch 2 7 0.72 0.55 0.0210 2.34 0.96 72% 29.1 49.6 31.5 9.3 15.7 35.9 0.047

11 Cooks Branch 3 22 3.13 2.89 0.0210 2.68 1.18 72% 60.2 142.7 87.7 24.7 65.9 103.4 0.110

12 First Mine Branch 3 20 2.75 0.81 0.0103 3.76 1.25 52% 75.6 64.0 43.2 23.8 –12.3 33.4 0.048 88 (2015) 235 Geomorphology / al. et Donovan M.

13 First Mine Branch 4 77 12.78 3.39 0.0103 4.06 1.73 52% 100.1 167.6 76.4 81.1 60.7 87.4 0.080

14 First Mine Branch Trib 3 11 3.35 0.91 0.0095 2.82 1.33 52% 59.5 115.2 70.6 13.8 44.1 60.1 0.090

15 Fourth Mine Branch 4 46 6.63 2.76 0.0099 2.56 1.17 55% 78.8 79.7 41.8 48.6 1.0 43.6 0.073

16 Jones Falls 4 92 13.60 2.23 0.0066 3.40 0.91 83% 153.8 87.1 67.8 95.4 –62.3 72.5 0.103

17 Jones Falls 5 217 33.06 0.44 0.0066 3.62 1.05 83% 187.0 84.6 34.3 220.6 –82.6 70.4 0.078

18 Keysers Run 3 25 3.10 1.28 0.0173 2.68 1.50 69% 59.7 113.5 23.4 57.1 56.4 78.2 0.067

19 Little Falls 4 52 10.33 2.28 0.0098 2.88 1.10 75% 80.6 75.8 49.9 54.9 –6.7 56.7 0.067

20 Little Piney Run 4 32 4.66 1.89 0.0230 3.48 1.37 41% 61.3 103.3 40.7 35.5 39.7 42.0 0.076

21 Little Piney Run Trib 2 4 0.67 0.87 0.0206 1.01 0.96 41% 41.5 48.5 37.4 5.0 2.5 19.7 0.080

22 McGill Run, Butler Rd 4 120 16.20 3.39 0.0088 5.32 1.63 72% 88.7 274.9 170.5 125.3 149.4 198.0 0.069

23 McGill Run, Byerly Rd 3 24 4.60 2.10 0.0210 2.16 1.22 45% 56.1 101.7 52.1 26.2 39.0 45.4 0.129

24 Mingo Branch 3 15 2.05 2.10 0.0300 3.16 1.34 59% 33.9 104.0 52.5 18.2 59.8 61.9 0.067 – 25 Norris Run 3 38 5.61 4.10 0.0175 2.92 1.55 62% 69.7 206.0 146.7 40.9 103.6 127.8 0.077 105

26 Panther Branch 3 22 3.04 2.10 0.0330 2.96 1.70 67% 21.4 110.0 38.8 25.0 80.4 73.6 0.119

27 Panther Branch Trib 1_1 1 1 0.18 0.50 0.0335 2.26 1.49 67% 28.4 46.7 25.2 3.3 15.3 31.3 0.055

28 Panther Branch Trib 1_2 2 4 0.65 0.65 0.0464 2.64 1.15 67% 36.4 53.2 19.8 6.6 16.7 35.6 0.049

29 Panther Branch Trib 2_2 2 2 0.38 0.46 0.0460 2.14 1.47 67% 28.2 69.4 31.0 4.1 36.5 46.5 0.040

30 Piney Run, Mantua Mill Rd 5 200 32.89 2.36 0.0065 5.70 1.47 68% 111.1 282.1 266.0 205.7 109.1 193.0 0.192

31 Piney Run, Mt. Zion Rd 5 146 21.16 1.43 0.0066 4.32 1.45 65% 106.1 164.6 136.1 150.3 34.7 106.2 0.155

32 Piney Run, Trenton Rd 4 41 7.95 2.11 0.0128 3.72 1.70 65% 78.9 186.6 88.7 44.7 93.8 120.5 0.143

33 Powells Run 1 1 0.15 0.56 0.0361 2.12 1.12 65% 16.2 47.0 34.1 3.1 23.2 30.6 0.060

34 Powells Run 2 5 0.79 0.34 0.0361 2.24 1.07 65% 19.2 59.4 29.2 7.2 34.6 38.7 0.055

35 Powells Run 3 12 1.82 1.08 0.0361 2.52 1.46 65% 27.8 114.5 56.1 14.5 74.4 74.5 0.070

36 Third Mine Branch 4 90 13.67 3.09 0.0103 3.32 1.17 72% 89.3 84.5 41.4 93.3 –2.9 61.2 0.060

37 Western Run, Cuba Rd 6 1015 152.44 4.73 0.0026 11.74 1.83 90% 241.8 229.3 182.6 1026.7 –28.3 206.6 0.104

38 Western Run, Cuba Rd Trib 1 2 0.21 0.27 0.0282 2.36 1.41 71% 25.1 68.8 27.1 4.4 39.6 49.0 0.042

39 Western Run, Gadd Rd 6 664 99.46 3.12 0.0029 9.54 1.63 74% 392.0 242.8 126.1 673.5 –123.9 179.3 0.129 40 Western Run, Mantua Mill Rd 6 574 92.20 2.60 0.0032 7.82 1.76 71% 222.0 309.6 216.5 581.8 58.4 220.5 0.182

aStudy reach averaged CART class value. 1234 b

Adjusted for floodplain and 97 downstream redeposition. 98 M. Donovan et al. / Geomorphology 235 (2015) 88–105

Fig. 9. The proportion of gross erosion that was derived from legacy sediment, plotted as a histogram. Once the outlier was removed, the proportion of legacy sediment within streambanks was normally distributed.

accounting for channel and ﬂoodplain deposition, net streambank sediment erosion was 7.32 × 104 (±5.40 × 104) Mg/y over the 44 years covered by our measurements, totaling 3.22 × 106 (±2.38 × 106) Mg. The largest fraction of net sediment contributions from bank erosion (62%) was from ﬁrst- and second-order streams (class 1), with decreasing inputs from larger order segments. Net streambank sediment yield estimated for northern Baltimore County was thus 72 (±54) Mg/km2/y (Table 4). Gross legacy sediment yield was 128 (±60) Mg/km2/y; and after estimating legacy sediment redeposition, net legacy sediment yield was 39.9 (±33.0) Mg/km2/y (Table 4). Further interpretation of the sediment contributions from each class and a table of uncertainty for sediment yields follow in the Discussion below.

5. Discussion

5.1. Sediment sample comparisons

Comparison of sediment densities suggests that pre- and post- settlement deposits are distinct. The much coarser texture of channel deposits as compared with floodplain sediments suggest that very little (b30%) of the fine-grained sediment derived from bank erosion is redeposited in the channel. Density values for legacy sediments match the range (0.74–1.34 g/cm3) described in Merritts et al. (2010), and those values for pre-settlement material were similar to those Fig. 10. Trends in the erosion and deposition rates with increasing Shreve magnitude. (0.77–1.05 g/cm3)citedinSchenk and Hupp (2009). Within each graph, the color of the points indicates which class it was apportioned by Legacy sediment typically is finer in texture than pre-settlement ma- the CART analyses. The values in parentheses indicate the average rate of each class. fi (For interpretation of the references to color in this figure legend, the reader is referred terial, consistent with the ndings of Hupp et al. (2013) who reported to the web version of this article.) that legacy overbank sediment was composed of 65% silts and clays, M. Donovan et al. / Geomorphology 235 (2015) 88–105 99

Fig. 11. Site-averaged annual lateral migration expressed as a linear rate and as a percent of channel width. (Top) Each plotted value represents the site-average of lateral migration expressed as a linear rate (blue) or a percentage of the channel width (red). (Bottom) Boxplots and a histogram showing the distributions of lateral migration rates, along with the narrow range of variability once the rates were expressed as a fraction of channel width. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this article.)

with pre-colonial overbank sediment 40% or less silt and clay. Our greatest discrepancies with past research arose from values measured results also overlap with those found in (Merritts et al., 2011, 2013). post dam breach (e.g., Merritts et al., 2010)orduringfreeze–thaw pe- Although stratigraphy along many streams appeared similar to the riods (Wolman, 1959; Leopold, 1973). Along the South River, Virginia, sequence described by Jacobson and Coleman (1986), grain sizes dif- Stotts et al. (2014) estimated decadal scale channel migration ranged fered from their reports of coarser material in legacy sediments relative from 0.03 to 0.118 (μ = 0.04) m/y using exposed root analysis. Such to pre-settlement soils. This difference likely arose from the broader comparisons conform to observations by Hooke (1980), who concluded spatial extent of our pre-settlement sample and because our pre- that a map-based, long-term approach may produce smoothed and settlement sample class included organic backswamp facies and buried lower measurements of migration rates than those measured over A-soil horizons that were distinguished separately in Jacobson and short time intervals along reaches with active migration. Measurements Coleman (1986).Basedonfield observation and sediment analysis, integrating active and inactive portions of the channel (across time and streambank stratigraphy and composition of pre-settlement material space) will generally result in lower average rates than field measure- across Baltimore County cannot be characterized by a single model, ments biased toward high rates at eroding cutbanks. which is reflected in the bimodal distribution of density values in pre- Lateral migration rates were converted to estimates of bank erosion settlement samples. as Mg/km/y and compared to the raster-based calculation of gross erosion rates (see Section 3.4). The two approaches produced mostly sim- 5.2. Lateral migration rates ilar values (Fig. 14), with some larger differences at individual sites. Although differences expressed as a fraction of the lidar-based gross Lateral migration rates measured in this study showed considerable erosion rate ranged between 0 and 117%, 26 of 40 study segments had overlap with those published for other Piedmont streams (Fig. 13). The differences b20% and 33 had differences b50%. The differences in

Fig. 12. Classiﬁcation of segment erosion and deposition rates based on surrogates of drainage area. CART output for gross erosion (left) and total deposition (right) rates illustrate break points distinguishing each stream segment class. 100 M. Donovan et al. / Geomorphology 235 (2015) 88–105

Table 4 A summary of net sediment yield and net sediment ﬂux estimates that account for in- channel and ﬂoodplain deposition; alternate values and uncertainty for the estimates are provided in Table 6 within the Discussion.

Watershed Drainage area Streambank Legacy sediment sediment

(km2) Gross Net Gross Net

N. Baltimore County 1005 224 72 128 40 Western Run 211 233 75 131 41 Chimney Branch 1.78 156 39 10 3 Powell's Run 1.82 103 26 95 33 predictions increased when the length of the study segments were reduced, further demonstrating the need for caution when generalizing migration rates from measurements along short channel reaches.

5.3. Streambank erosion contributions

In general, estimated sediment contributions from different classes of stream channels were similar to their cumulative length (Fig. 15). While larger valleys may dominate our impressions of sediment transport, this result demonstrates that this is misleading, as they are a small fraction of cumulative channel length and sediment contributions. Fig. 14. Comparison between gross erosion estimated from lateral migration rates using First- and second-order streams were slightly underrepresented rela- Eq. (1) and that measured for each study segment (x-axis). A dashed 1:1 line is provided for reference. tive to their cumulative channel length, whereas proportions of sediment from third- through sixth-order streams (classes 2–4) were slightly greater than their fraction of cumulative channel length. This trend corresponds with those in Trimble (1999), Smith et al. (2011), larger drainage areas within these Piedmont watersheds. In addition, and Hupp et al. (2013), which found that net sediment supply de- results from Hupp et al. (2013) indicated that opportunities for flood- creased with increasing stream order because of greater deposition plain deposition increased downstream reaches in Difficult Run, Virgin- rates. Legacy sediments comprised 57% (±25%) of the measured gross ia. Based on the estimates from literature, our floodplain deposition was streambank erosion, with increasing proportions from each class (53%, between 16 and 185% of streambank erosion. Most published floodplain 54%, 67%, and 75%), indicating that legacy sediments indeed constitute deposition values vary between 15% and 65% of upstream erosion a significant portion of streambank erosion across the entire drainage (Walling et al., 1998; Allmendinger et al., 2007; Gellis et al., 2009; network of Baltimore County. Smith, 2011), while Hupp et al. (2013) reported floodplain trapping The greater proportion of in-channel deposition along higher stream from −10× to 50× expected upstream erosion along Difficult Run in orders indicates opportunities for in-channel deposition increase at northern Virginia.

Fig. 13. A comparison of lateral migration rates from this study and previously published results. The data collected in this project are represented as black squares. M. Donovan et al. / Geomorphology 235 (2015) 88–105 101

Fig. 15. The proportion of sediment input from each stream class deﬁned by the CART output. Pie charts showing the percent of gross and net erosion derived from each class, along with the fraction of stream length within each class. Highlighted wedges and parenthetical labels accompanying the gross erosion pie chart indicate proportions of legacy sediment within each class.

Our estimate of net streambank sediment yield (72.8 ± 53.7 Mg/km2/y) 57% of long-term Piedmont suspended-sediment yields from Gellis is equivalent to 70% (20–120%) of long-term Piedmont sediment yield et al. (2009). With this alternate estimation, fine-grained streambank (red dashed line, Fig. 16) derived from a similar time-series of sediment contributions from first- and second-order streambanks suspended-sediment records at 21 USGS stream gages from 1952 to remained 53% (down from 62%) of total net erosion across the extrapo- 2001 (Gellis et al., 2009). Our estimate is thus consistent with previous lation extent within northern Baltimore County. Evidence collected here approximations of streambank contributions to sediment yields of and elsewhere (Walling et al., 1998; Owens et al., 1999; Merritts et al., 50–98% for Piedmont streams (Costa, 1975; Trimble, 1997; Schenk 2013) indicated that only a minor proportion of fine-grained sediment and Hupp, 2009; Shilling, 2009; Mukundan et al., 2011; Gellis and is stored in channel deposits, supporting the growing body of research Noe, 2013; Voli et al., 2013). indicating that fine-grained streambank sediment constitutes a substan- Assessment along low-order channels within the study area indicat- tial portion of downstream suspended-sediment yields (Mukundan ed that floodplains occupied 70% of their length (Appendix A, Fig. A.2). et al., 2011; Niemitz et al., 2013). Following a 30% reduction to erosion estimates from first- and second- Comparing streambank sediment yields for the Western Run water- order channels, sediment yield was nonetheless 59.3 Mg/km2/y, or shed, which is 38% of the total area draining into the Loch Raven

Fig. 16. A comparison of sediment yields reported in our project (black) with sediment yields for Piedmont streams across the Mid-Atlantic region. Dashed-lines spanning the entire plot represent pre-settlement (black), upland (orange), and long-term averaged (red) sediment yields. Acronyms include gross streambank yield (GSY), net streambank yield (NSY), and legacy sediment yield (LSY). (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this article.) 102 M. Donovan et al. / Geomorphology 235 (2015) 88–105

Table 5 An inventory of sources of uncertainty inherent in analyses and assumptions used to generate estimates of gross and net erosion; for each source, we identify the qualitative or quantitative magnitude of uncertainty. The methods of calculating uncertainty are provided in Appendix B.

Source Quantiﬁed? Method of calculating or bracketing uncertainty Estimated error Units

Bulk density (erosion) Y Mean ± 95% confidence interval 1.13 ± 0.03 Mg/m3 Bulk density (deposition) Y Mean ± 95% confidence interval 1.43 ± 0.07 Mg/m3 Georectification error Y Removed polygon slivers and polygons less than 1 m2 μ = 1.05 m2 Legacy sediment thickness Y Mean ± SE of mean thickness at each study segment (Variable) Range: 4–18 % Historic channel geometry Y Mean historic stream width by ± 20% (Variable, only 13 study segments) m Channel elevation raster surface N – Low – Floodplain elevation raster surface N – Low – Floodplain discontinuities Y Recalculated sediment yield with 30% reduction in erosion −18% reduction in sediment yield Mg/km2 contributions from first- and second-order streams (based on field and lidar measurements). 30% of valley bottom assumed to N – (Variable, depending on valley width) – be an active floodplain Floodplain accumulation rates Y Bracketed mean accumulation rate (3 mm/y) with a range of 3 ± 2 mm/y literature values (1–5 mm/y) 30% material in channel deposits N – Low – assumed to come from streambanks reservoir, with reservoir sedimentation rates and TMDL requirements comparisons of total watershed sediment yields between forested and provided another means to estimate the relevance of streambank urban watersheds in Maryland (Allmendinger et al., 2007). We found sediment contributions. Sediment cores from the Loch Raven reservoir that streambank yields in forested watersheds accounted for 2 to 18% consist of 94% silt and clay (Ortt et al., 2000), similar to the average of watershed sediment yields in small urbanizing catchments, similar 92% fine sand, silt, and clay found in our samples of legacy sediments. to those (0–20%) reported by Allmendinger et al. (2007). Thus, despite Net streambank sediment yield (15,740 Mg/y) from Western Run distinct approaches, both studies found comparable proportions of represents 54% of the TMDL (28,925 Mg/y) established for the Loch legacy sediment inputs in small, urbanizing watersheds. Raven reservoir (Maryland Department of the Environment, 2006). Furthermore, net streambank sediment yield from Western Run is 5.5. Identifying and quantifying sources of error and uncertainty equivalent to 36% of the reservoir's estimated average sediment yield (205 Mg/km2/y) between 1913 and 1997 (Ortt et al., 2000; Smith, In order to address the considerable sources of uncertainty inherent 2011). These comparisons suggest that reducing streambank erosion in our assumptions and methodological choices, we provided an inven- would aid in meeting current TMDL goals and substantially lower the tory in Table 5 and a quantitative analyses in Appendix B. The primary rates of reservoir sedimentation. quantifiable sources of uncertainty for rates of gross erosion and (in-channel) deposition arose from: (i) density values for erosional and depositional sediment samples, (ii) legacy sediment thickness with- 5.4. Legacy sediment contributions in each study segment, (iii) channel geometry assumed for historical channels represented by only a centerline on historical maps, and Net legacy sediment yields were equivalent to 38.4% (6–96%) of (iv) georectification of historical maps. Additional uncertainty arose Piedmont sediment yield values described by Gellis et al. (2009).After from assumptions and estimates of floodplain deposition used to accounting for discontinuous floodplains, a 30% reduction in legacy compute the net erosion rates. sediment contributions to first- and second-order tributaries produced For each estimated erosion rate (gross erosion, gross deposition, net a minimum estimate of legacy sediment yield: 34 Mg/km2/y. This is erosion, and legacy sediment erosion), individual uncertainties were comparable to 33% of Piedmont sediment yields in Gellis et al. (2009) propagated using Eqs. (B.1) and (B.2) to estimate uncertainty for each and 31% of our estimated net streambank sediment yield. overall result. Uncertainty of gross erosion and total deposition for Schenk and Hupp (2009) indicated that 63% of present sediment each CART class was propagated using Eq. (B.1) (Appendix B) to esti- yield from Difficult Run, Virginia, was likely from stored legacy sedi- mate uncertainty for net erosion from each stream class. Propagated ment. Similarly, Voli et al. (2013) found that Neuse River suspended uncertainty associated with each class was accumulated and scaled by sediment was 27–63% streambank sediment largely, composed of lega- drainage area to quantify cumulative extrapolation uncertainty with cy deposits. Walter et al. (2007) reported that legacy sediments units Mg/km2/y (Table 6). accounted for 45 to 122% of suspended sediment measured at the Conestoga River mouth in southeastern Pennsylvania. Increased contributions from legacy deposits may reflect differing lithology or greater 6. Conclusions frequency of mill dams along streams in Pennsylvania, which increase the thickness of legacy deposits. In this study, we quantified remobilization rates of streambanks and Net legacy sediment yields from Chimney Branch (1.78 km2)and legacy sediments from Baltimore County over the past 44–46 years and Powell's Run (1.82 km2) in our study were analogous to other compared the magnitude of this source with regional sediment yields.

Table 6 Uncertainty in the sediment yield estimates; the format of reported values is provided within the table.

Watershed (drainage area) Streambank sediment Legacy sediment

Gross Net Gross Net

N. Baltimore County (1005 km2) 224 ± 43 [184] 72 ± 54 [59] 128 ± 60 [107] 40 ± 33 [33] Western Run (211 km2) 233 ± 45 [186] 75 ± 61 [61] 131 ± 64 [110] 41 ± 54 [34] Reporting format: estimated yield ± uncertainty [alternatea]

a Alternate calculation reﬂects sediment yield after a 30% reduction to erosion from ﬁrst- and second-order streams. M. Donovan et al. / Geomorphology 235 (2015) 88–105 103

Understanding obtained from a study across Baltimore County should area, this suggested that bank erosion contributions were proportionate be transferable to a broader regional understanding of sediment routing to drainage area. Thus, reducing streambank erosion would greatly and effects of landscape disturbances. improve the ability to reach proposed sediment regulations. Our measurements of long-term channel migration were somewhat In order to improve the understanding of sediment source contribu- lower than published channel migration rates measured over shorter tions, spatially extensive, long-term measurements of erosion are temporal and spatial scales. These results suggest that extrapolations preferable to model-based estimates and short-term observations. from short-term or localized samples should be interpreted with Important and complex patterns in erosion across different geomorphic caution, as they are subject to greater inherent variability. Spatially con- environments and landscape histories should not be interpreted from tinuous measurement of lateral migration across multiple stream seg- measurements that do not encompass adequate temporal and spatial ments in Baltimore County indicate that channels are migrating an scales. Comparable direct observations of sediment flux exiting water- average of 2.5% channel width annually, independent of contributing sheds would also be useful to contextualize long-term sediment budget area. We do not know if this observation has more general applicability, components. Increasing the spatial and temporal scales considered in and we therefore recommend future investigation of possible scale- research, monitoring sites, and restoration strategies is likely to improve independent migration rates in other study watersheds, along with our understanding of fine-grained sediment sources to Chesapeake Bay analyses of longitudinal patterns of variability in channel migration. and receiving water bodies in other landscapes. Independent calculations produced estimates of bank erosion rates within 20% for 26 of 40 study segments and within 50% for all but Acknowledgments 7 segments. Thus, local, pixel-based measurements of bank erosion were similar to coarser estimates using channel length and reach- Funding for this project was provided by the Maryland Water averaged channel width, bank height, and migration rate. While the Resources Research Center and National Institutes for Water Resources latter approach is not recommended for quantifying precise rates of Award 2012MD262B, Subaward Z974003. Equipment and space for the location-specific bank erosion, the results may nonetheless be useful research was provided by numerous organizations, including the UMBC for approximating magnitudes or general trends. Geography and Environmental Systems (GES) department, the Center If our assumptions about floodplain deposition are correct, our re- for Urban and Environmental Research and Education (CUERE), and sults suggest that Baltimore County Piedmont channels are largely in a the U.S. Geological Survey (USGS). We would like to thank Milan Pavich, state of net export, but floodplains and channel deposits remain active Sean Smith, Dorothy Merritts, and Michael Rahnis, who each provided storage sites of fine-grained streambank sediments, especially along time and resources essential for the development of this project. Addi- fifth- and sixth-order streams. Thus, our findings are consistent with tional thanks goes to Andrew Bofto for his great dedication to field and previous results (Walling et al., 1998; Trimble, 1999; Hupp et al., lab work, along with Claire Welty for her donation of lab space and re- 2010, 2013; Skalak and Pizzuto, 2010; Smith et al., 2011). Extrapolations sources. Considerable effort from Jim Pizzuto, Kevin Breen, and two suggested that within the drainage network, sediment contributions anonymous reviewers substantially improved the quality of work and per meter of channel length were greater for larger streams, but the language contained herein. We would also like to acknowledge Richard majority (41%–62%) of cumulative streambank sediment loads were Marston for his patience that provided a smooth and thorough revision from first- and second-order tributaries. The greater cumulative length process. Any use of trade, firm, or product names is for descriptive pur- of first- and second-order streams largely accounts for their dominance poses only and does not imply endorsement by the U.S. Government. in sediment contributions across the drainage network. Comparison of extrapolated net streambank erosion yields with Appendices A & B. Supplementary Material regional sediment yields indicated that streambanks are contributing a large fraction (70% ± 50%) of long-term averaged sediment yield, Supplementary data to this article can be found online at http://dx. which is consistent with investigations across the Piedmont (Costa, doi.org/10.1016/j.geomorph.2015.01.025. 1975; Trimble, 1997; Schenk and Hupp, 2009; Shilling, 2009; Merritts et al., 2010; Mukundan et al., 2011; Gellis and Noe, 2013). However, References upland erosion rates not measured here have been reported with equivalent and greater magnitudes for forested and cropland areas within the Aguilar, F.J., Mills, J.P., Delgado, J., Aguilar, M.A., Negreiros, J.G., Pérez, J.L., 2010. Modelling Maryland Piedmont (Gellis et al., 2009; Smith et al., 2011) and may con- vertical error in LiDAR-derived digital elevation models. ISPRS J. Photogramm. 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