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Kristina G. Hopkins

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A cvs file containing field datasets used to develop regression models to predict sediment and nutrient retention services for stream within the Difficult Run watershed. Field measurements of floodplain deposition and bank erosion were provided in previously published datasets from Hupp et al. (2013) and Gellis et al. (2017). At each field site 3-5 nearby cross-sections from the Toolbox where used to represent the floodplain and streambank sampling locations at the field sites. Metrics derived from the Toolbox are provided in this data table.
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Hydrologically conditioned digital elevation model (DEM) generated from lidar data clipped to the Difficult Run watershed with a 500-m buffer in ArcGIS 10.3.1 (ESRI, Redlands, CA). The DEM was hydrologically corrected by breaching through pits with no downslope neighboring cells to force surface flow to continuously move downslope using Whitebox Geospatial Analysis Tools (Lindsay and Dhun 2015, Lindsay 2016). Pits that were not properly breached were manually adjusted using elevation information from the DEM and aerial imagery to locate culverts under roadways.
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Input data on watershed drainage area characteristics and stream reach geomorphometry for statistical modeling of floodplains, streambanks, and streambeds in the Chesapeake Bay and Delaware River watersheds of the U.S. Mid-Atlantic. Characteristics include selected upstream accumulated attributes (with divergence routing) describing geology, topography, soils, hydrology, and land use for each NHDPlusV2 stream reach from Wieczorek et al. (2018), and the geomorphometry of the local stream reach summarized from Hopkins et al. (2020). These potential predictors were tested for incorporation into Random Forest statistical models to explain and predict spatial variation in floodplain and streambank flux of sediment, fine...
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