AndreaBozzo/ceres-open-data-index huggingface dataset:
Modeled change in the Seasonality between 1951-1960 and the 1971-2000 Normal period

Originators: US Environmental Protection Agency Publisher: US EPA Office of Research & Development (ORD) - National Health and Environmental Effects Research Laboratory (NHEERL) Publication place: Corvallis, OR Publication date: Time Period of Data: 1900-2010; Projected data for 2041-2070. Data location: GeoPlatform ("https://www.geoplatform.gov/") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA’s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration.  This raster contains the modeled change in the seasonality of the month of maximum surplus precipitation between the target time period (in title) and the 1971-2000 Normal period (1 = same season, 0 = earlier season, 2 = later season).

Tags: 020:094, 1900 -2010, 2041-2070, climate, downloadable data, environment, united states, water
Organization: U.S. Environmental Protection Agency
GFPLAIN90_Africa

All floodplains were derived using modified scripts from GFPLAIN v1.0 (https://github.com/fnardi/GFPLAIN).    This data was created by modifying the scripts to work with 90-m data.
Global FloodPLAIN (GFPLAIN) mapping uses a geomorphic algorithm. Geomorphic FloodPLAIN mapping algorithm GFPLAIN is based on Nardi et al. (2006, 2018).  
The data is available at the hydrobasin 4 level.  HydroBASINS data provides a series of polygon layers that depict watershed boundaries and sub-basin delineations at a global scale (http://www.hydrosheds.org).   

Tags: 020:096, 020:121, africa, drought mitigation, flood-hazard, floodplain, floodplains, global, hydrobasin, non-floodplain, wetland habitat, wetland mapping
Organization: U.S. Environmental Protection Agency
Manasquan River (New Jersey) sewage no-discharge zone, 1998, EPA HQ OWOW

This is a No Discharge Area (NDA) for Manasquan River, NJ. The actual NDA areas/polygons were primarily created using narrative description from Federal Register notices and digitized against basemap data for hydrography and from recent aerial photography.

Tags: 020:078, downloadable data, environment, marine, new jersey, water
Organization: U.S. Environmental Protection Agency
Modeled change in the average Feddema Moisture Index (multiplied by 1000) between 1981-1990 and the 1971-2000 Normal period.

Originators: US Environmental Protection Agency Publisher: US EPA Office of Research & Development (ORD) - National Health and Environmental Effects Research Laboratory (NHEERL) Publication place: Corvallis, OR Publication date: Time Period of Data: 1900-2010; Projected data for 2041-2070. Data location: GeoPlatform ("https://www.geoplatform.gov/") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA’s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration.  This raster contains the modeled change in the average Feddema Moisture Index over 1981-1990 relative to the 1971-2000 Normal period.

Tags: 020:094, 1900 -2010, 2041-2070, climate, downloadable data, environment, united states, water
Organization: U.S. Environmental Protection Agency
EPA RE-Powering Mapper Region 6

The U.S. Environmental Protection Agency (EPA) Office of Land and Emergency Management (OLEM) Office of Communications, Partnerships and Analysis (OCPA) initiated the RE-Powering America's Land Initiative to demonstrate the enormous potential that contaminated lands, landfills, and mine sites provide for developing renewable energy in the United States. EPA developed national level site screening criteria in partnership with the U.S. Department of Energy (DOE) National Renewable Energy Laboratory (NREL) for wind, solar, biomass, and geothermal facilities. While the screening criteria demonstrate the potential to reuse contaminated land for renewable energy facilities, the criteria and data are neither designed to identify the best sites for developing renewable energy nor all-inclusive. Therefore, more detailed, site-specific analysis is necessary to identify or prioritize the best sites for developing renewable energy facilities based on the technical and economic potential. Please note that these sites were only pre-screened for renewable energy potential. The sites were not evaluated for land use constraints or current on the ground conditions. Additional research and site-specific analysis are needed to verify viability for renewable energy potential at a given site.

Tags: cleanup, energy, environment, facilities, land, remediation, sites, united states, waste
Organization: U.S. Environmental Protection Agency
High Marsh at Lower Maurice, NJ, Lower Delaware Bay, Intermediate Sea Level Rise Scenario, “Protect Developed Dry Land” model protection scenario, EPA ORD NCEA

This raster GIS dataset contains 5-meter-resolution cells depicting the areas of HIGH marsh gain (value=1), lost (value=-1) and remaining (no change; value=0). High marsh (HM) was defined as the aggregation of irregularly-flooded marsh [SLAMM category 7] and transitional salt marsh [SLAMM category 20]. HM is covered by water only sporadically (once per day or less). Based on SLAMM simulation outputs, we generated the gain and loss map by using the “Raster Calculator” tool under “Spatial Analyst Tools” in ArcGIS software. The methodology consists of the three steps listed below (where we use low marsh [LM] as an example). The same process can be applied to other SLAMM land cover categories. 

1) Open ArcMap, add SLAMM simulation raster outputs (all SLAMM categories) for baseline year and future years. 

2) In Raster Calculator, set the SLAMM code equal to 8 (low marsh = SLAMM category 8) to generate a new raster. Each individual cell in the new raster is assigned a value of “0” or “1”. “1” is low marsh and “0” is any other SLAMM land cover category. Perform this step for both the baseline year and future year. 

3) In Raster Calculator, subtract the new raster for the baseline year from the new raster for the future year (formula = new future year raster - new baseline year raster). The calculation generates a new raster, in which each individual cell is assigned a value of “-1”, “0”, or “1”. Based on the calculation, “-1” means low marsh loss in the future (the cell has converted from low marsh to a different SLAMM category), “0” means low marsh is remaining (the cell stays the same), and “1” means low marsh gain in the future (the cell has converted from a different SLAMM category to low marsh). 

Prior SLAMM work has been performed in the Delaware Bay, but our methods differ in that we derive results for specific marsh areas and utilize more recent, higher resolution elevation data (2015 USGS CoNED Topobathy Model: New Jersey and Delaware), the most recent SLR projections, and site-specific accretion data (through 2016). These SLAMM simulations were performed as part of a larger project by the USEPA on frameworks and methods for characterizing relative wetland vulnerabilities. 

Note: additional raster files from this project are available upon request. These include files from low and high SLR scenarios and different model protection scenarios. For more information, contact Jordan West (West.Jordan@epa.gov).

Tags: 020:094, coastal wetland, delaware, downloadable data, ecosystem, environment, estuary, exposure, modeling, natural resources, new jersey, relative vulnerability, sea level rise, united states
Organization: U.S. Environmental Protection Agency
Weathered Oil and Tar Sampling Data for BP Spill/Deepwater Horizon

The Deepwater Horizon oil spill (also referred to as the BP oil spill) began on 20 April 2010 in the Gulf of Mexico on the BP-operated Macondo Prospect. Following the explosion and sinking of the Deepwater Horizon oil rig, a sea-floor oil gusher flowed for 87 days, until it was capped on 15 July 2010. In response to the BP oil spill, EPA sampled air, water, sediment, and waste generated by the cleanup operations.

Tags: alabama, cleanup, contaminant, disaster, emergency, environment, florida, hazards, health, human, louisiana, mississippi, response, toxics, waste
Organization: U.S. Environmental Protection Agency
Low Marsh at Broadkill, DE, Lower Delaware Bay, Intermediate Sea Level Rise Scenario, “Protect Developed Dry Land” model protection scenario, EPA ORD NCEA

This raster GIS dataset contains 5-meter-resolution cells depicting the areas of LOW marsh gain (value=1), lost (value=-1) and remaining (no change; value=0). Low marsh (LM) was defined as regularly flooded marsh [SLAMM category 8]. LM is normally inundated by tidal water at least once per day. Based on SLAMM simulation outputs, we generated the gain and loss map by using the “Raster Calculator” tool under “Spatial Analyst Tools” in ArcGIS software. The methodology consists of the three steps listed below (where we use low marsh [LM] as an example). The same process can be applied to other SLAMM land cover categories.

1) Open ArcMap, add SLAMM simulation raster outputs (all SLAMM categories) for baseline year and future years.

2) In Raster Calculator, set the SLAMM codeequal to8 (low marsh = SLAMM category 8) to generate a new raster. Each individual cell in the new raster is assigned a value of “0” or “1”. “1” is low marsh and “0” is any other SLAMM land cover category. Perform this step for both the baseline year and future year. 

3) In Raster Calculator, subtract the new raster for the baseline year from the new raster for the future year (formula = new future year raster - new baseline year raster). The calculation generates a new raster, in which each individual cell is assigned a value of “-1”, “0”, or “1”. Based on the calculation, “-1” means low marsh loss in the future (the cell has converted from low marsh to a different SLAMM category), “0” means low marsh is remaining (the cell stays the same), and “1” means low marsh gain in the future (the cell has converted from a different SLAMM category to low marsh).

Prior SLAMM work has been performed in the Delaware Bay, but our methods differ in that we derive results for specific marsh areas and utilize more recent, higher resolution elevation data (2015 USGS CoNED Topobathy Model: New Jersey and Delaware), the most recent SLR projections, and site-specific accretion data (through 2016). These SLAMM simulations were performed as part of a larger project by the USEPA on frameworks and methods for characterizing relative wetland vulnerabilities. 

Note: additional raster files from this project are available upon request. These include files from low and high SLR scenarios and different model protection scenarios. For more information, contact Jordan West (West.Jordan@epa.gov).

Tags: 020:094, coastal wetland, delaware, downloadable data, ecosystem, environment, estuary, exposure, modeling, natural resources, new jersey, relative vulnerability, sea level rise, united states
Organization: U.S. Environmental Protection Agency
Geologic Basin Boundaries (Basins_GHGRP) GIS Layer

This is a coverage shapefile of geologic basin boundaries which are used by EPA's Greenhouse Gas Reporting Program. For onshore production, the "facility" includes all emissions associated with wells owned or operated by a single company in a specific hydrocarbon producing basin (as defined by the geologic provinces published by the American Association of Petroleum Geologists). This layer is limited to the contiguous United States.

Tags: 020:033, boundaries, climate, facilities, united states
Organization: U.S. Environmental Protection Agency
Hydrologic Landscape Classification of the U.S.

We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. The data in this data set is specifically for the 1971-2000 normal period.

Tags: 020:094, climate, environment, ground water, map files, natural resources, united states, water
Organization: U.S. Environmental Protection Agency
Global Non-Floodplain Wetlands_Europe

This raster GIS dataset contains 30 meter cells depicting non-floodplain wetlands in a hydrobasin. This base dataset is a combination of three globally-available datasets, creating a new dataset that is inclusive of finer-resolution data, while accounting for a wide range of wetland sizes. 
The three source datasets are:
 1) CW-WTD 500-m dataset resampled to 30 m. – Wetland dataset built from a composite wetland-water table depth (Tootchi 2019); 
 2) CCI (Climate Change Initiative) data resampled from 300 m to 30 m – CCI defined wetlands as “…mixed classes of flooded areas with tree covers, shrubs, or herbaceous covers plus inland water bodies;” and
 3) Global Surface Water (GSW)  30-m (Pekel et al. 2016) – A pixel was considered a wetland if it had at least one inundation event over a 32-year range.

A 1-km buffer was applied to the HydroBASINS (Lehner and Grill 2013) coastline area and any wetland partially or completely overlain by the 1-km buffer was removed from analysis. In addition, to avoid including large lakes in  the data, we also applied a mask using HydroLAKES and removed lake systems ≥10 ha (Messager et al. 2016).

The dataset was then overlain by the GFPlain90 floodplain data (resampled to 30 meters) and wetlands overlain by the floodplain were removed.



Tags: 020:096, 020:121, biogeochemical processing, downloadable data, drought mitigation, europe, geographically isolated wetland, global, hydrobasin, non-floodplain, watershed, wetland habitat, wetland mapping, wetlands
Organization: U.S. Environmental Protection Agency
Jamaica Bay (New York) sewage no-discharge zone, 2011, EPA HQ OWOW

This is a No Discharge Area (NDA) for Jamaica Bay, NY. The actual NDA areas/polygons were primarily created using narrative description from Federal Register notices and digitized against basemap data for hydrography and from recent aerial photography.

Tags: 020:078, downloadable data, environment, marine, new york, water
Organization: U.S. Environmental Protection Agency
EPA Facility Locations and Regional Boundaries - National Geospatial Data Asset (NGDA)

This downloadable package contains the following layers: EPA facility points, EPA region boundary polygons and EPA region boundary polygons extended to the 200nm Exclusive Economic Zone (EEZ). Included in this package are a file geodatabase (v. 10.0), Esri ArcMap map document (v. 10.0) and XML files for this record and the layer level metadata. This dataset was produced by EPA Office of Environmental Information (OEI).

Tags: 020:072, environment, facilities, governmental units and administrative and statistical boundaries theme, national geospatial data asset, ngda, united states
Organization: U.S. Environmental Protection Agency
Nantucket (Massachusetts) sewage no-discharge zone, 1992, EPA HQ OWOW

This dataset details No Discharge Zones (NDZ) for Nantucket, MA. Boaters may not discharge waste into these areas. Boundaries were determined mostly by Federal Register Environmental Documents in coordination with Massachusetts Coastal Zone Management (MA CZM) and EPA Region 1 Office of Ecosystem Protection (OEP) staff.

Tags: 020:078, downloadable data, marine, new hampshire, water
Organization: U.S. Environmental Protection Agency
Region 1 Engineered Controls Points

Point locations of certain engineered controls on RCRA sites in EPA Region 1. Locations are accurate as of 4/15/2020 and should have corresponding information in RCRAInfo.

Tags: 020:088, cleanup, compliance, connecticut, downloadable data, environment, facilities, hazards, human, maine, massachusetts, new hampshire, regulatory, remediation, rhode island, sites, toxics, vermont, waste
Organization: U.S. Environmental Protection Agency
Sediment Sampling Data for BP Spill/Deepwater Horizon

The Deepwater Horizon oil spill (also referred to as the BP oil spill) began on 20 April 2010 in the Gulf of Mexico on the BP-operated Macondo Prospect. Following the explosion and sinking of the Deepwater Horizon oil rig, a sea-floor oil gusher flowed for 87 days, until it was capped on 15 July 2010. In response to the BP oil spill, EPA sampled air, water, sediment, and waste generated by the cleanup operations.

Tags: alabama, cleanup, contaminant, disaster, emergency, environment, florida, hazards, health, human, louisiana, mississippi, response, toxics
Organization: U.S. Environmental Protection Agency
All Wisconsin waters except Lake Superior Mississippi River, and part of St. Croix River sewage no-discharge zone, 1976, EPA HQ OWOW

This geospatial dataset depicts a sewage no-discharge zone established under Clean Water Act Section 312. The area(s) depicted are zones where the discharge of any sewage, treated or untreated, from vessels is prohibited. This layer was created using information from the corresponding Federal Register notice and is created for informational purposes, not to be used for enforcement.

Tags: 020:078, downloadable data, environment, marine, water, wisconsin
Organization: U.S. Environmental Protection Agency
Global Wetlands Siberia

This raster GIS dataset contains 30 meter cells depicting wetlands in a hydrobasin.  
This base dataset is a combination of three globally available datasets creating a new dataset is that is inclusive of both finer-resolution data while accounting for a wide range of wetland sizes. 
The three source datasets are:
 1) CW-WTD 500 m dataset resampled to 30 m. – Wetland dataset built from a composite wetland-water table depth (Tootchi 2019), 
 2) CCI (Climate Change Initiative) data resampled from 300 m to 30 m - CCI defined wetlands as “…mixed classes of flooded areas with tree covers, shrubs, or herbaceous covers plus inland water bodies” and
 3) Global Surface Water (GSW)  30-m (Pekel et al. 2016) – A pixel was considered a wetland if it had at least one inundation event over a 32-year range.



Tags: 020:096, 020:121, biogeochemical processing, downloadable data, drought mitigation, geographically isolated wetland, global, hydrobasin, non-floodplain, siberia, watershed, wetland habitat, wetland mapping, wetlands
Organization: U.S. Environmental Protection Agency