In the associated manuscript, we used the State-level National Resources Inventory (NRI) annual estimates of sheet and rill erosion to calibrate our RUSLE-derived estimates. This data set provides the data used in and resulting from that calibration. The data set relates to Figs 1 a-d in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set contains estimated average annual soil loss (Mg ha-1 yr-1) and estimated average annual sediment yield (Mg ha-1 yr-1) aggregated by HUC-12 watersheds for the conterminous US. This data set corresponds to Fig 3 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set gives estimates of erosion and sediment yield based on our study for the conterminous US by land cover class. The data correspond to Fig 4 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set contains estimated average annual soil loss avoided (Mg ha-1 yr-1) and estimated average annual sediment yield (Mg ha-1 yr-1) avoided aggregated by HUC-12 watersheds for the conterminous US. This data set corresponds to Fig 5 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set contains estimated average annual soil loss avoided (Mg ha-1 yr-1) and estimated average annual sediment yield (Mg ha-1 yr-1) avoided aggregated by HUC-12 watersheds for the conterminous US. This data set corresponds to Fig 5 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set gives estimates of erosion and sediment yield avoided due to the presence of natural land cover. These estimates are given for each land cover class and summarized for the conterminous US. The data correspond to Fig 6 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This EnviroAtlas national dataset shows the average annual soil loss and sediment yield to waterbodies by 12-digit HUC subwatershed for the conterminous United States for 2011 with existing land use / land cover and under a scenario in which natural vegetation is removed. It also includes the soil loss and sediment yield prevented by natural vegetation, calculated as the difference between soil loss or sediment yield with existing land cover and under the vegetation removal scenario. This dataset is based on a collection of six rasters showing runoff, sediment delivery ratio, and sediment yield to streams and waterbodies under two land cover scenarios. The two scenarios are the existing vegetation scenario based on the 2011 National Land Cover Database (NLCD), and a scenario in which natural land cover was replaced with barren land. Average annual soil loss due to sheet and rill erosion was calculated using the Revised Universal Soil Loss Equation (RUSLE) equation for both scenarios. A Sediment Delivery Ratio (SDR) was then applied to both scenarios. The SDR was multiplied by the average annual soil loss to estimate net sediment yield to downstream waterways under both scenarios. These datasets can be used together to quantify the soil retention services of natural vegetation. The datasets used as inputs include the 2011 NLCD, 1971-2000 Rainfall-runoff erosivity factor from PRISM (Parameter-elevation Regressions on Independent Slopes Model), the U.S. Geological Survey's 30-meter digital elevation model (DEM), Soil Survey Geographic Database (SSURGO), and State Soil Geographic Database (STATSGO2) data, MODIS (Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index (NDVI), and the US Department of Agriculture (USDA)'s crop management zones (CMZs). This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

The Revised Universal Soil Loss Equation (RUSLE) estimates the annual soil loss that is due to erosion using a factor-based approach with rainfall, soil erodibility, slope length, slope steepness and cover management and conservation practices as inputs. The collection is (i) a set of maps that represent the RUSLE factors, (ii) a map of the RUSLE estimates of soil erosion in Australia and (iii) a map of the uncertainty in the estimates of erosion.