AndreaBozzo/ceres-open-data-index huggingface dataset:
Synthetic storm-driven flood-inundation grids for coastal communities along the Barnegat Bay and adjacent to the Seaside Heights tide gage from Lavallette to Lanoka Harbor, NJ

Digital flood-inundation maps for coastal communities within Ocean County in New Jersey were created by water surfaces generated by an Advanced Circulation hydrodynamic (ADCIRC) and Simulating Waves Nearshore (SWAN) model from the Federal Emergency Management Agency (FEMA) Region II coastal analysis and mapping study (Federal Emergency Management Agency, 2014). Six synthetic modeled tropical storm events from a library of 159 events were selected based on parameters including landfall location or closest approach location, maximum wind speed, central pressure, and radii of winds. Two storm events were selected for the tide gage providing two "scenarios" and accompanying inundation-map libraries. 
The contents of this data release support the following publication:
Suro, T.P., Niemoczynski, M.J., Boetsma, A.C., and Niemoczynski, L.M., 2023, Moderate flood level scenarios: synthetic storm-driven flood-inundation maps for coastal communities in 10 New Jersey counties: U.S. Geological Survey Scientific Investigations Report 2023-5005, 64 p., https://doi.org/10.3133/sir20235005.
The landing page on which this and 24 other storm scenarios reside is:
Niemoczynski, L.M., Niemoczynski, M.J., Boetsma, A.C., and Suro, T.P., 2023, Synthetic storm-driven flood-inundation grids for coastal communities in 10 New Jersey counties: U.S Geological Survey data release, https://doi.org/10.5066/P9RVF9P8.
References cited:
Federal Emergency Management Agency, 2014, FEMA Region II Coastal Analysis and Mapping Study, accessed November 2, 2018, at http://www.region2coastal.com/resources/about-the-coastal-flood-study/

Tags: digital-maps, flood-inundation-maps, floods, new-jersey-coastal, ocean-county, oceans, tide-gages, usgs-624318e7d34e131ff705f996
Organization: Department of the Interior
Occurrence of plants in plots along the Gunnison River, Colorado, 1990-2017

In 1990 the US Geological Survey Fort Collins Science Center and National Park Service Water Resources Division established 133 permanent 1meter (m) X 2 m plots along the Gunnison River near Warner Point in Black Canyon of the Gunnison National Park.  A one-dimensional hydraulic model was calibrated to determine the inundation necessary to inundate each plot, and this can be combined with daily flow data to determine the inundation duration or percentage of time a plot is under water. Occurrence of all plant species in these plots was determined in late July of 1990, 1994, 2001, 2006 and 2013. This data set includes 3 csv files of plot data. One file gives characteristics of plots, including plot name, inundating discharge, mean number of species occurring in the plot, mean vegetative cover, Mean Sorensen Index and mean inundation duration with flows exponentially weighted for recency using a half-life of 1.5 years. A second file gives characteristics of all the plant species that have occurred in the plots including scientific and common names, plant family, life span, occurrence of rhizomes, height, total occurrences across years, median inundating discharge of plots containing the plant, half-life for exponential weighting of flows selected by regressions relating species occurrence to flow in each sample year, slope, probability and variance of half-life regressions, and the optimum inundation duration, probability and variance of logistic regressions relating occurrence of species in all sample years to flow. A third file documents occurrence of species in plots in all five sample years as well as the inundation duration, number of species and total vegetative cover in each plot in each sample year. The 1990 data were interpreted by Auble et al. (1991 and 1994), and all five years of data were interpreted by Friedman et al. (2022). This data set also includes a library of repeat views of the river bars containing the plots photographed from the same set of 21 camera locations in 1990, 1994, 2001, 2006, 2013 and 2017, a total of 117 images. Finally, this data set also includes a csv file listing the years each view was photographed and the approximate latitude and longitude of each camera location.

Tags: biota, black-canyon-of-the-gunnison-national-park, colorado, dam, ecological-competition, environment, gunnison-river, inlandwaters, montrose, streamflow, usgs-624227e4d34e915b67eae221, vegetation, wetland-ecosystems
Organization: Department of the Interior
Field-verified inventory of postfire hydrologic response for the 2020 CZU Lightning Complex, River, Camel, and Dolan Fires following a 26-29 January 2021 atmospheric river storm sequence

This data release is a field-verified inventory of postfire hydrologic response for the 2020 CZU Lightning Complex, River Fire, Camel Fire, and Dolan Fire following a 26-29 January 2021 atmospheric river storm sequence. Postfire hydrologic response types include a) no response, b) minor response, and c) major response. A “minor” response was deemed capable of impairing infrastructure functioning (e.g., deposition or erosion along a road that could be regraded by mechanized earth-moving equipment within a matter of hours) or causing minor bodily injury (e.g., abrasions, sprains, or broken bones). A “major” response was deemed capable of causing sustained infrastructure impairment (e.g., damage to roads requiring weeks or more of emergency repair efforts or residential structures made uninhabitable) or serious bodily injury (e.g., protracted disfigurement or death). The README.txt file describes the data fields for the “Inventory.csv” file. Fields with value “-9999” indicate that data are not available or do not exist.

Tags: county-of-monterey, county-of-santa-cruz, hydrology, usgs-62421d7dd34e915b67eae200
Organization: Department of the Interior
Cottonwood Lake Study Area - Invertebrate Counts (ver. 2.0)

This dataset contains macroinvertebrate sampling data for the wetlands in the Cottonwood Lake Study Area, Stutsman County, North Dakota.

Tags: biota, chase-lake-wetland-management-districtgtstutsman-county-waterfowl-production-areagteddy, chase-lake-wetland-management-districtgtstutsman-county-waterfowl-production-areagtshuler, community-composition, cottonwood-lake-study-area, freshwater-ecosystems, macroinvertebrates, north-dakota, northern-great-plains, prairie-pothole-region, stutsman-county, united-states-of-america, usgs-624c779ad34e21f82764df2e
Organization: Department of the Interior
Seagrass map, Cat Island and Ship Island, Mississippi, 2014

This product depicts the spatial coverage of seagrass beds from 0.5-m color-infrared orthoimagery for Cat Island and Ship Island, Mississippi from early fall of 2014. Specifically, the map includes presence and absence of seagrass beds within a potential seagrass extent that was based on topobathymetric data. A minimum mapping unit of 4 square meters was used for this mapping effort.

Tags: aquatic-vascular-vegetation, aquatic-vegetation, environment, geoscientificinformation, gulf-of-mexico, habitat-alteration-and-disturbance, habitat-map, mapping, mississippi, seagrass-bed, united-states-of-america, usgs-62420e03d34e915b67eae1cb
Organization: Department of the Interior
Seagrass map, Cat Island and Ship Island, Mississippi, 2011

This product depicts the spatial coverage of seagrass beds from 0.5-m color-infrared orthoimagery for Cat Island and Ship Island, Mississippi from early fall of 2011. Specifically, the map includes presence and absence of seagrass beds within a potential seagrass extent that was based on topobathymetric data. A minimum mapping unit of 4 square meters was used for this mapping effort.

Tags: aquatic-vascular-vegetation, aquatic-vegetation, environment, geoscientificinformation, gulf-of-mexico, habitat-alteration-and-disturbance, habitat-map, mapping, mississippi, seagrass-bed, united-states-of-america, usgs-62420a83d34e915b67eae1bb
Organization: Department of the Interior
R script that creates a wrapper function to automate the generation of boxplots of change factors for all ArcHydro Enhanced Database (AHED) basins (basin_boxplot.R)

The South Florida Water Management District (SFWMD) and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 174 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in central and south Florida. The change factors were computed as the ratio of projected future to historical extreme precipitation depths fitted to extreme precipitation data from various downscaled climate datasets using a constrained maximum likelihood (CML) approach. The change factors correspond to the period 2050-2089 (centered in the year 2070) as compared to the 1966-2005 historical period.  
An R script (basin_boxplot.R) is provided provided as an example on how to create a wrapper function that will automate the generation of boxplots of change factors for all AHED basins. The wrapper script sources the file create_boxplot.R and calls the function create_boxplot() one AHED basin at a time to create a figure with boxplots of change fators for all durations (1, 3, and 7 days) and return periods (5, 10, 25, 50, 100, and 200 years) evaluated as part of this project. An example is also provided in the code that shows how to generate a figure showing boxplots of change factors for a single duration and return period. A Microsoft Word file documenting code usage is also provided within this data release (Documentation_R_script_create_boxplot.docx). As described in the documentation, the R script relies on some of the Microsoft Excel spreadsheets published as part of this data release.

Tags: climatologymeteorologyatmosphere, depth-duration-frequency, extremes, florida, precipitation-atmospheric, precipitation-extremes, south-florida, south-florida-water-management-district, southern-florida, usgs-624209a0d34e915b67eae1b4
Organization: Department of the Interior
Documentation of R scripts to create boxplots of change factors by NOAA Atlas 14 station, or for all stations in an ArcHydro Enhanced Database (AHED) basin or county (Documentation_R_script_create_boxplot.docx)

The South Florida Water Management District (SFWMD) and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 174 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in central and south Florida. The change factors were computed as the ratio of projected future to historical extreme precipitation depths fitted to extreme precipitation data from various downscaled climate datasets using a constrained maximum likelihood (CML) approach. The change factors correspond to the period 2050-2089 (centered in the year 2070) as compared to the 1966-2005 historical period.  
An R script (create_boxplot.R) is provided which generates boxplots of change factors by NOAA Atlas 14 station, or for all NOAA Atlas 14 stations in an ArcHydro Enhanced Database (AHED) basin or county. In addition, the R script basin_boxplot.R is provided as an example on how to create a wrapper function that will automate the generation of boxplots of change factors for all AHED basins. This Microsoft Word file (Documentation_R_script_create_boxplot.docx) serves as documentation on the code usage and available options for running the scripts. As described in the documentation, the R scripts rely on some of the Microsoft Excel spreadsheets published as part of this data release.

Tags: climatologymeteorologyatmosphere, depth-duration-frequency, extremes, florida, precipitation-atmospheric, precipitation-extremes, south-florida, south-florida-water-management-district, southern-florida, usgs-624208e4d34e915b67eae1af
Organization: Department of the Interior
Gridded South Carolina StreamStats Runoff Curve Numbers by NLCD Landcover and SSURGO Soils Class (ver. 1.1, September 2025)

This dataset was produced by the US Geological Survey (USGS) as a supporting dataset to be used for the purpose of calculating stream gage basin characteristics in preparation for the South Carolina StreamStats application. This integer raster dataset represents runoff curve numbers for combinations of hydrologic soils groups and land cover classes within the South Carolina StreamStats study area. The source of the soils data was the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) Soil Survey Geographic Database (SSURGO). The source of the land cover data was the USGS 2019 National Land Cover Database (NLCD) data. This dataset will be used in peak flow regression equations that are used to predict flow in South Carolina streams. The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, as well as for engineering and design purposes.
Inventory of data release:
SC_RCN_LU_CO.tiff (one .tif file):
Cloud optimized GeoTIFF containing integer rasters of runoff curve numbers for soils/land cover combinations
SoilLU_RCN_Cross.csv (one .csv file):
Table of 239 land cover/soils combinations showing sources used to make RCN assignments
RevisionHistory_SouthCarolina_RunoffCurveNumbers.txt (one .txt file):
Text file documenting revision history to this data release.
First posted - August 29, 2022
Revised - September 24, 2025 (version 1.1)

Tags: biota, georgia, hydric-soils, land-use-and-land-cover, national-land-cover-dataset, nlcd-2019, north-carolina, runoff-curve-number, soil-sciences, south-carolina, ssurgo-database, streamstats, tr-55, usgs-6241fcc0d34e915b67eae16a
Organization: Department of the Interior
Data to support water quality modeling efforts in the Delaware River Basin: 1) Spatial data for rivers, reservoirs, and monitoring locations

This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning approaches to water quality modeling, including the prediction of stream temperature.
This section provides spatial data files that describe the rivers, reservoirs, and observational data in the Delaware River Basin included in this release. One shapefile of polylines describes the 459 river reaches that define the modeling network, and another shapefile of polygons includes the three reservoirs (Pepacton, Cannonsville, and Neversink) for which data are included in this release. Additionally, a point shapefile contains locations of monitoring sites along the reaches with supporting attributes that describe the monitoring location.

Tags: de, delaware, environment, inlandwaters, maryland, md, modeling, new-jersey, new-york, nj, ny, pa, pennsylvania, reservoirs, streams, temperature, united-states, us, usgs-623e54c4d34e915b67d83580, water, water-quality, water-resources
Organization: Department of the Interior
Data to support water quality modeling efforts in the Delaware River Basin

This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning approaches to water quality modeling, including the prediction of stream temperature. Reservoirs in the DRB serve an important role as a source of drinking water, but also affect downstream water quality. Therefore, this data release includes data that characterize both rivers and a subset of reservoirs in the basin. This release provides an update to many of the files provided in a previous data release (Oliver et al., 2021).
The data are stored in 3 child folders: 1) spatial information, 2) observations, and 3) model driver data.
&lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/623e54c4d34e915b67d83580"&gt; 1) Spatial Information &lt;/a&gt;- Spatial data used for modeling efforts in the Delaware River Basin&lt;/li&gt; - a shapefile of polylines for the river segments, point data for observation locations, and polygons for the three (Pepacton, Cannonsville, and Neversink) reservoirs in this dataset. &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/623e550ad34e915b67d8366e"&gt; 2) Observations &lt;/a&gt;- Reservoir (surface levels, releases, diversions, water temperature) and river (water temperature and flow) observations that can be used to train and test water quality models. &lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/623e5587d34e915b67d83806"&gt; 3) Model driver data &lt;/a&gt;- Driver data used to force water quality models, including stream reach distance matrices and daily meteorology data from NOAA GEFS and gridMET. This child item also includes the inputs and outputs of an uncalibrated run of PRMS-SNTemp which predicts mean water temperature at all reaches in the DRB.
This data compilation was funded by the USGS.

Tags: de, delaware, environment, inlandwaters, maryland, md, modeling, new-jersey, new-york, nj, ny, pa, pennsylvania, reservoirs, streams, temperature, united-states, us, usgs-623e4418d34e915b67d7dd78, water, water-quality, water-resources
Organization: Department of the Interior
Ground control points collected for Helikite operations at the Pea Island National Wildlife Refuge DUNEX Site, North Carolina in September and October 2021

The data in this part of the release provide the location information of the temporary ground control points placed on the beach at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal environments, including hazards to humans and infrastructure and changes in landscape and natural habitats. Collected data are part of field activity 2021-029-FA. During September and October 2021, USGS and Woods Hole Oceanographic Institute (WHOI) scientists conducted multiple field surveys to collect an elevation time series. Ground control point location data were collected using a real time kinematic – satellite navigation system (RTK-GNSS) receiver. Images of the beach for use in structure from motion were taken with a camera attached to a helium filled balloon-kite (Helikite). Agisoft Metashape (v. 1.8.1) was used to create orthomosaics and digital surface models (DSMs) with the collected imagery and ground control points.

Tags: cmhrp, coastal-and-marine-hazards-and-resources-program, dare, datasets, dunex, geolocation-measurement, geoscientificinformation, gps-measurement, gps-navigation, ground-control-points, location, north-carolina, oceans, pea-island, u-s-geological-survey, united-states, usgs, usgs-623e13aad34e915b67d6d7ee, whcmsc, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Synthetic storm-driven flood-inundation grids for coastal communities along the Delaware Bay and adjacent to the Bivalve tide gage from Maurice River Township to Lawrence Township, NJ

Digital flood-inundation maps for coastal communities within Cumberland County in New Jersey were created by water surfaces generated by an Advanced Circulation hydrodynamic (ADCIRC) and Simulating Waves Nearshore (SWAN) model from the Federal Emergency Management Agency (FEMA) Region II coastal analysis and mapping study (Federal Emergency Management Agency, 2014). Six synthetic modeled tropical storm events from a library of 159 events were selected based on parameters including landfall location or closest approach location, maximum wind speed, central pressure, and radii of winds. Two storm events were selected for the tide gage providing two "scenarios" and accompanying inundation-map libraries. 
The contents of this data release support the following publication:
Suro, T.P., Niemoczynski, M.J., Boetsma, A.C., and Niemoczynski, L.M., 2023, Moderate flood level scenarios: synthetic storm-driven flood-inundation maps for coastal communities in 10 New Jersey counties: U.S. Geological Survey Scientific Investigations Report 2023-5005, 64 p., https://doi.org/10.3133/sir20235005.
The landing page on which this and 24 other storm scenarios reside is:
Niemoczynski, L.M., Niemoczynski, M.J., Boetsma, A.C., and Suro, T.P., 2023, Synthetic storm-driven flood-inundation grids for coastal communities in 10 New Jersey counties: U.S Geological Survey data release, https://doi.org/10.5066/P9RVF9P8.
References cited:
Federal Emergency Management Agency, 2014, FEMA Region II Coastal Analysis and Mapping Study, accessed November 2, 2018, at http://www.region2coastal.com/resources/about-the-coastal-flood-study/

Tags: cumberland-county, digital-maps, flood-inundation-maps, floods, new-jersey-coastal, oceans, tide-gages, usgs-623e110cd34e915b67d6d199
Organization: Department of the Interior
Synthetic storm-driven flood-inundation grids for coastal communities along the Barnegat Bay and adjacent to the Mantoloking tide gage from Point Pleasant Beach to Toms River Township, NJ

Digital flood-inundation maps for coastal communities within Ocean County in New Jersey were created by water surfaces generated by an Advanced Circulation hydrodynamic (ADCIRC) and Simulating Waves Nearshore (SWAN) model from the Federal Emergency Management Agency (FEMA) Region II coastal analysis and mapping study (Federal Emergency Management Agency, 2014). Six synthetic modeled tropical storm events from a library of 159 events were selected based on parameters including landfall location or closest approach location, maximum wind speed, central pressure, and radii of winds. Two storm events were selected for the tide gage providing two "scenarios" and accompanying inundation-map libraries. 
The contents of this data release support the following publication:
Suro, T.P., Niemoczynski, M.J., Boetsma, A.C., and Niemoczynski, L.M., 2023, Moderate flood level scenarios: synthetic storm-driven flood-inundation maps for coastal communities in 10 New Jersey counties: U.S. Geological Survey Scientific Investigations Report 2023-5005, 64 p., https://doi.org/10.3133/sir20235005.
The landing page on which this and 24 other storm scenarios reside is:
Niemoczynski, L.M., Niemoczynski, M.J., Boetsma, A.C., and Suro, T.P., 2023, Synthetic storm-driven flood-inundation grids for coastal communities in 10 New Jersey counties: U.S Geological Survey data release, https://doi.org/10.5066/P9RVF9P8.
References cited:
Federal Emergency Management Agency, 2014, FEMA Region II Coastal Analysis and Mapping Study, accessed November 2, 2018, at http://www.region2coastal.com/resources/about-the-coastal-flood-study/

Tags: digital-maps, flood-inundation-maps, floods, new-jersey-coastal, ocean-county, oceans, tide-gages, usgs-623e0c6dd34e915b67d6c75b
Organization: Department of the Interior