Data is based on overlap of topographic, soil drainage, and national wetland inventory areas. This dataset is associated with the following publication: Horvath, E., J. Christensen, M. Mehaffey, and A. Neale. Building a Potential Wetland Restoration Indicator for the Contiguous United States.. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 83: 462-473, (2017).

Data is based on overlap of topographic, soil drainage, and national wetland inventory areas. This dataset is associated with the following publication: Horvath, E., J. Christensen, M. Mehaffey, and A. Neale. Building a Potential Wetland Restoration Indicator for the Contiguous United States.. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 83: 462-473, (2017).

Nature-based solutions is a leading policy option for mitigating climate change. We mapped areas of potential restoration and conservation opportunities in the conterminous U.S. (CONUS). The potential for five scenarios were examined: increasing forest cover in urban centers, restoring historically forested areas that have been converted to grasslands, conserving pristine grasslands, rewetting peatlands, and conserving vulnerable tidal wetlands.

The Potential Wetland Area (PWA) layer shows areas where conditions may be suitable for wetland habitat at a 10-m resolution. Since the 1600's, an estimated 53% of wetlands in the Conterminous United States have been lost, with many areas being converted for agricultural or urban use. The ecosystems services provided by wetlands are extremely valuable, providing flood attenuation, water filtration, nutrient sequestration, vital habitat, and many others. Wetland restoration or creation can help restore these benefits for the surrounding community. There are several government and community projects that can utilize these data to assist in site selection for wetland restoration projects. This layer was created using the Random Forest (RF) machine learning algorithm in Google Earth Engine (GEE). The RF model utilized 17 data inputs to identify areas where attributes on the landscape are similar to the attributes found in existing wetlands. The input data for this layer fall into three categories: topographic variables, soils, and satellite imagery. Topographic - DEM's sourced from USGS 3D Elevation Program (10-m) -Elevation -Aspect -Slope -Compound Topographic Index (CTI) -Vertical Overland Flow Distance (VOFD) -Horizontal Overland Flow Distance (HOFD) -Pythagoras Overland Flow Distance (POFD) -Soils - Natural Resource Conservation Service's gNATSGO and gSSURGO products · Potential Wetland Soils (PWS) -European Space Agency's Sentinel-1 Synthetic Aperture Radar (10-m) Using these variables, the Random Forest model was run for each 2 digit Hydrologic Unit Code (HUC) in Google Earth Engine. The model used wetlands from the National Wetland Inventory (NWI) to create training data, masking out deep water areas such as the centers of lakes and rivers, and excluding estuarine and marine wetlands. For each HUC an equal number of wetland and non-wetland training points proportional to the size of the HUC were generated, with 30% of those points being reserved for accuracy assessment. 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 Potential Wetland Area (PWA) layer shows areas where conditions may be suitable for wetland habitat at a 10-m resolution. Since the 1600's, an estimated 53% of wetlands in the Conterminous United States have been lost, with many areas being converted for agricultural or urban use. The ecosystems services provided by wetlands are extremely valuable, providing flood attenuation, water filtration, nutrient sequestration, vital habitat, and many others. Wetland restoration or creation can help restore these benefits for the surrounding community. There are several government and community projects that can utilize these data to assist in site selection for wetland restoration projects. This layer was created using the Random Forest (RF) machine learning algorithm in Google Earth Engine (GEE). The RF model utilized 17 data inputs to identify areas where attributes on the landscape are similar to the attributes found in existing wetlands. The input data for this layer fall into three categories: topographic variables, soils, and satellite imagery. Topographic - DEM's sourced from USGS 3D Elevation Program (10-m) -Elevation -Aspect -Slope -Compound Topographic Index (CTI) -Vertical Overland Flow Distance (VOFD) -Horizontal Overland Flow Distance (HOFD) -Pythagoras Overland Flow Distance (POFD) -Soils - Natural Resource Conservation Service's gNATSGO and gSSURGO products · Potential Wetland Soils (PWS) -European Space Agency's Sentinel-1 Synthetic Aperture Radar (10-m) Using these variables, the Random Forest model was run for each 2 digit Hydrologic Unit Code (HUC) in Google Earth Engine. The model used wetlands from the National Wetland Inventory (NWI) to create training data, masking out deep water areas such as the centers of lakes and rivers, and excluding estuarine and marine wetlands. For each HUC an equal number of wetland and non-wetland training points proportional to the size of the HUC were generated, with 30% of those points being reserved for accuracy assessment. 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 Percentage Potential Wetland Area by HUC-12 (Pct_PWA) layer shows areas where conditions may be suitable for wetland restoration or creation at a 10-m resolution. Since the 1600's, an estimated 53% of wetlands in the Conterminous United States have been lost, with many areas being converted for agricultural or urban use. The ecosystems services provided by wetlands are extremely valuable, providing flood attenuation, water filtration, nutrient sequestration, vital habitat, and many others. Wetland restoration or creation can help restore these benefits for the surrounding community. There are several government and community projects that can utilize these data to assist in site selection for wetland restoration projects. This layer was created using the Random Forest (RF) machine learning algorithm in Google Earth Engine (GEE). The RF model utilized 17 data inputs to identify areas where attributes on the landscape are similar to the attributes found in existing wetlands. The input data for this layer fall into three categories: topographic variables, soils, and satellite imagery. Topographic - DEM's sourced from USGS 3D Elevation Program (10-m) -Elevation -Aspect -Slope -Compound Topographic Index (CTI) -Vertical Overland Flow Distance (VOFD) -Horizontal Overland Flow Distance (HOFD) -Pythagoras Overland Flow Distance (POFD) -Soils - Natural Resource Conservation Service's gNATSGO and gSSURGO products · Potential Wetland Soils (PWS) -European Space Agency's Sentinel-1 Synthetic Aperture Radar (10-m) Using these variables, the Random Forest model was run for each 2 digit Hydrologic Unit Code (HUC) in Google Earth Engine. The model used wetlands from the National Wetland Inventory (NWI) to create training data, masking out deep water areas such as the centers of lakes and rivers, and excluding estuarine and marine wetlands. For each HUC an equal number of wetland an non-wetland training points proportional to the size of the HUC were generated, with 30% of those points being reserved for accuracy assessment. The model results were then summarized to calculate the areal coverage of PWA within each HUC-12 watershed in the United States. 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).

Wetlands provide numerous critical functions, including nutrition cycling and water quality improvement, that have made them a critical component of many state and local stewardship programs. Quantifying landscape nutrients entering wetlands are crucial components of state-led efforts to improve nutrient reduction strategies, both for water quality within wetlands themselves and for other water sources, such as lakes and streams, that wetlands provide a buffer for nutrient inputs. However, these data are rarely assembled at comprehensive scales that are relevant to management, such as local wetland basins, stream catchments, watersheds. This subproduct provides downscaled data from EPA's National Nutrient Inventory (NNI; https://www.epa.gov/water-research/national-nutrient-inventory-portfolio) for approximately 84 million individual wetland basins over a 30-yr period accumulated for individual wetland basins, local stream catchments and full accumulative watersheds across the conterminous US. We generated annual landscape nutrient inputs from several anthropogenic sources across nearly 12 million wetland basins at 5-yr increments from 1987-2017 (1987, 1992, 1997, 2002, 2007, 2012, 2017), resulting in a novel and robust resource to explore effects of nutrient inputs on wetlands and the effect of wetland interception of landscape nutrients on other water resources. The new metrics cover all major anthropogenic sources of urban and agricultural nutrient inputs, including nitrogen metrics from livestock manure excretion, crop removal, and fertilizer. The accessibility of these data will greatly advance the way state partners generate nutrient budgets for impaired waters and conduct conservation and restoration planning to meet statutory requirements under the Clean Water Act.

The dataset includes information to make Figure 4 within the manuscript. This dataset is associated with the following publication: Golden, H., A. Rajib, C. Lane, J. Christensen, Q. Wu, and S. Mengistu. Non-floodplain Wetlands Affect Watershed Nutrient Dynamics: A Critical Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(13): 7203-7214, (2019).

The dataset includes information to make Figure 4 within the manuscript. This dataset is associated with the following publication: Golden, H., A. Rajib, C. Lane, J. Christensen, Q. Wu, and S. Mengistu. Non-floodplain Wetlands Affect Watershed Nutrient Dynamics: A Critical Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(13): 7203-7214, (2019).

This EnviroAtlas dataset shows the percent land cover with potentially restorable wetlands on agricultural land for each 12-digit Hydrologic Unit (HUC) watershed in the contiguous U.S. Beginning two centuries ago, many wetlands were turned into farm fields or urban areas, yet wetlands play an important role in removing water pollution, regulating water storage and flows, and providing habitat for wildlife. Wetland restoration could help restore these benefits. Potentially restorable wetlands, as developed for this map, are lands currently in agriculture that naturally accumulate water due to topography and have historically had poorly or very poorly draining soils. This dataset was produced by the US EPA to support research and online mapping activities related to the 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).