AndreaBozzo/ceres-open-data-index huggingface dataset:
Synthetic storm-driven flood-inundation grids for coastal communities along the Raritan Bay and the Shrewsbury River and adjacent to the Sea Bright tide gage from Middletown Township to Long Branch, NJ

Digital flood-inundation maps for coastal communities within Monmouth 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, monmouth-county, new-jersey-coastal, oceans, tide-gages, usgs-623e023cd34e915b67d6b293
Organization: Department of the Interior
Synthetic storm-driven flood-inundation grids for coastal communities along the Raritan Bay and adjacent to the Keansburg tide gage from Aberdeen Township to Middletown Township, NJ

Digital flood-inundation maps for coastal communities within Monmouth 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, monmouth-county, new-jersey-coastal, oceans, tide-gages, usgs-623dfe24d34e915b67d6aebe
Organization: Department of the Interior
Synthetic storm-driven flood-inundation grids for coastal communities along the Arthur Kill and Raritan River to Raritan Bay and adjacent to the Perth Amboy tide gage from Linden to Laurence Harbor, NJ

Digital flood-inundation maps for coastal communities within Middlesex and Union Counties 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, middlesex-county, new-jersey-coastal, tide-gages, union-county, usgs-623df38ed34e915b67d6ae7c
Organization: Department of the Interior
Continuous water quality, suspended solids, and Enterococci data from the Harlem River, Bronx, New York, Jan 2021- Sept 2021: US Geological Survey data release

This data set contains continuous water-surface elevation and water-quality (temperature, specific conductance, salinity, and turbidity) data recorded at 6- and 15-minute intervals, respectively, from two sites in the Bronx on the Harlem River -- Roberto Clemente State Park and Mill Pond Park. Water elevation was monitored every second to detect changes indicative of boat wakes expected to resuspend bed sediment from nearby alcoves. Boat wake detection triggered the collection of 1-second interval water elevation and 1-minute interval turbidity data. In addition to continuous data, grab samples for fecal indicator bacteria (Enterococci) and total suspended solids were collected weekly from - March to September, 2021.

Tags: bacteria, bronx-county, hydrology, new-york-city, new-york-county, salinity, surface-water-level, usgs-623ddb2ed34e915b67d6ae04, water-quality, water-temperature
Organization: Department of the Interior
Digital surface models of Pea Island National Wildlife Refuge DUNEX Site, North Carolina in September and October 2021

The data in this part of the release are digital surface models (DSMs) that characterize 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 and are related to field activity 2021-028-FA and 2021-032-FA. During September and October 2021, USGS and Woods Hole Oceanographic Institute (WHOI) scientists conducted multiple field surveys to collect a topobathy elevation time series. Images of the beach for use in structure from motion (SfM) were taken with a camera attached to a helium filled balloon-kite (Helikite). Agisoft Metashape (v. 1.8.1) was used to create orthomosaics (combined imagery rasters) and DSMs with the collected imagery.

Tags: aerial-photography, cmhrp, coastal-marine-hazards-and-resources-program, coastal-processes, dare, digital-elevation-models, dunex, geomorphology, geoscientificinformation, image-collections, imagerybasemapsearthcover, metashape, north-carolina, oceans, pea-island, remote-sensing, structure-from-motion, topography, u-s-geological-survey, united-states, usgs, usgs-623dcdc5d34e915b67d65bc2, whcmsc, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Cottonwood Lake Study Area - Invertebrate Weights (ver. 2.0)

This dataset contains macroinvertebrate sampling data (weights) for 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-624c772bd34e21f82764df27
Organization: Department of the Interior
Cottonwood Lake Study Area - Groundwater Elevations (ver. 2.0)

This dataset contains discrete groundwater elevation measurements for wells in the Cottonwood Lake Study Area, Stutsman County, North Dakota.

Tags: chase-lake-wetland-management-districtgtstutsman-county-waterfowl-production-areagteddy, chase-lake-wetland-management-districtgtstutsman-county-waterfowl-production-areagtshuler, climatic-change, cottonwood-lake-study-area, effects-of-climate-change, geoscientificinformation, ground-water, groundwater-level, hydrology, inland-waters, inlandwaters, north-dakota, northern-great-plains, prairie-pothole-region, stutsman-county, united-states-of-america, usgs-624c75fad34e21f82764df1e, water-sampling, wells, wetland-ecosystems, wetland-functions, wetlands
Organization: Department of the Interior
Target-chemical concentrations and bioassay results for assessment of mixed-organic/inorganic chemical and biological exposures in Minneapolis/St Paul, Minnesota tapwater, August 2019

This dataset contains the concentration and quality assurance results for inorganic and organic analytes collected for the U.S. Geological Survey (USGS), Ecosystems Mission Area, Environmental Health Infrastructure Program, Tapwater Exposure Project conducted in Minnesota, in August of 2019. Samples were obtained from multiple publicly distributed water sources in Minnesota in 2019. Due to privacy concerns, the exact location where samples were collected are not reported and station identification numbers have been anonymized. Water-quality samples were analyzed for pesticides, pharmaceuticals, volatile organic compounds and per- and polyfluoroalkyl substances at the USGS National Water Quality Laboratory (NWQL), Denver, Colorado; disinfection byproducts were analyzed at the USGS Organic Chemistry Research Laboratory (OCRL), Sacramento, California; inorganic analytes (cations, anions, nitrate, and trace elements) were analyzed at the USGS Redox Chemistry Laboratory (RCL), Boulder, Colorado; cyanotoxins were analyzed at the USGS Organic Geochemistry Research Laboratory (OGRL), Lawrence, Kansas. Water samples for bioassay analyses (estrogen, androgen, and glucocorticoid receptor) were extracted at the OGRL and analyzed at the U.S. Environmental Protection Agency, Durham, North Carolina.

Tags: drinking-water-treatment, drinking-water-use, environment, environmental-health-human, geoscientificinformation, health, inorganics, minneapolis, minnesota, organics, point-of-use, st-paul, tapwater, united-states, usgs-623dcc41d34e915b67d656c0, water-quality
Organization: Department of the Interior
Single-beam bathymetric data in Pea Island National Wildlife Refuge, North Carolina in November 2020 and April, September, and October 2021

The data in this part of the release are bathymetry data collected in the nearshore using single-beam echosounders mounted on surf capable self-righting electric autonomous survey vehicles at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge (PINWR) and at the Basnight Bridge (BB), NC. In November 2020, April, September, and October 2021, USGS and Woods Hole Oceanographic Institute (WHOI) scientists conducted multiple field surveys to collect the bathymetry as part of a topobathy time series. 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 and donated data 2020-024-DD and are related to field activity 2021-028-FA and 2021-032-FA.

Tags: bathymetry, cmhrp, coastal-and-marine-hazards-and-resources-program, dare, dunex, elevation, geoscientificinformation, north-carolina, oceans, pea-island, remote-control-boat, remote-sensing, single-beam-echo-sounder, u-s-geological-survey, united-states, usgs, usgs-623dcbc6d34e915b67d6552f, whcmsc, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Topobathy Products in Pea Island National Wildlife Refuge, North Carolina in November 2020 and April, September, and October 2021

The data in this part of the release characterize the beach and nearshore environment at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge (PINWR) and at the Basnight Bridge (BB), NC. In November 2020, April, September, and October 2021, USGS and Woods Hole Oceanographic Institute (WHOI) scientists conducted multiple field surveys to collect a topobathy elevation time series. Bathymetry for topobathy products was collected in the nearshore using a single-beam echosounder mounted on a surf capable self-righting electric autonomous survey vehicle. Topography is produced using GPS walking surveys or structure-from-motion (SfM) with the imagery and ground control point data provided in the larger citation. 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 and donated data 2020-024-DD and are related to field activity 2021-028-FA and 2021-032-FA.

Tags: bathymetry, cmhrp, coastal-and-marine-hazards-and-resources-program, dare, dunex, elevation, geoscientificinformation, north-carolina, oceans, pea-island, remote-sensing, single-beam-echo-sounder, topobathy, topography, u-s-geological-survey, united-states, usgs, usgs-623dcb84d34e915b67d65441, whcmsc, whoi, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Estimated crop irrigation water use withdrawals in Lower San Pedro Groundwater Basin, Arizona for 2020

Observations of irrigated agricultural land within the Lower San Pedro Groundwater Basin in Arizona. Crops were verified in situ once in 2020 on July 14th; based on digitized field boundaries. Field boundaries were digitized from U.S. Department of Agriculture, National Agricultural Imagery Program images dated 2019 and supplemented with Landsat and Sentinel2 imagery collections accessed via the U.S. Geological Survey LandLook Viewer (https://landlook.usgs.gov/) and Sentinel Hub, Sentinel Playground (https://apps.sentinel-hub.com/sentinel-playground). Satellite images were also used to identify the length of the growing season and crop condition. Water withdrawals were calculated using the modified Blaney-Criddle model of calculating consumptive use (U.S. Bureau of Reclamation, 1992 appendix A) using crop coefficients from Doorenbos and Pruitt (1975), the number of acres with active crops, crop condition, and irrigation system efficiency. The withdrawal equation was modified from "Water withdrawals for irrigation, municipal, mining, thermoelectric-power, and drainage uses in Arizona outside of active management areas, 1991-2000" (Tadayon, 2005) to account for variations in water application.

Tags: agricultural-sites, arizona, cochise, gila, graham, groundwater, irrigation, lower-san-pedro-camp-grant-wash-groundwater-subbasin, lower-san-pedro-groundwater-basin, lower-san-pedro-mammoth-groundwater-subbasin, pima, pinal, usgs-623caa51d34e915b67d39661, water-use
Organization: Department of the Interior
Cottonwood Lake Study Area - Amphibians (ver. 2.0)

This dataset contains the number of captured individuals recorded for each amphibian species surveyed in all wetlands in the Cottonwood Lake Study Area, Stutsman County, North Dakota. While amphibians were the target of the surveys, reptiles (i.e., turtles, snakes) were also captured over the course of the surveys and are included in the data file.

Tags: amphibians, animal-populations, aquatic-animals, biomonitoring, biota, chase-lake-wetland-management-districtgtstutsman-county-waterfowl-production-areagteddy, chase-lake-wetland-management-districtgtstutsman-county-waterfowl-production-areagtshuler, cottonwood-lake-study-area, effects-of-climate-change, indicator-species, inland-waters, long-term-changes, north-dakota, northern-great-plains, prairie-pothole-region, salamanders, stutsman-county, united-states-of-america, usgs-624c7543d34e21f82764df13, wetland-functions, wetlands, wildlife
Organization: Department of the Interior
Slow-moving landslides and subsiding fan deltas mapped from Sentinel-1 InSAR in the Glacier Bay region, Alaska and British Columbia, 2018-2020

This data set provides GIS shapefiles and Google Earth kmz files containing polygons delineating slow-moving (0.5-6 cm/year in the radar line-of-sight direction) landslides and subsiding fan deltas in the Glacier Bay region of Alaska and British Columbia. Landslides and fan deltas were identified from displacement signals captured by Interferometric Synthetic Aperture Radar (InSAR) interferograms of Sentinel-1 C-band Synthetic Aperture Radar images. The images were acquired at 12-day intervals from June to October from 2018 to 2020. We applied the persistent scatterer InSAR (PSInSAR) methods to images from both descending (scene P145) and ascending (scene P50) satellite tracks. We used PSInSAR results from the descending track as a primary means to identify ground movement and then used results from the ascending track to confirm the ground movement. The overlapping area covered by both images is 14,780 sq. km.  
Each polygon in the shapefile and .kmz file outlines an area of moving ground from 2018 to 2020. We categorized each area of moving ground into one of three categories: 1) slow-moving landslides on steep rocky slopes not near (&gt; 2 km away from) present-day glacier termini, 2) slow moving landslides directly adjacent to (&lt; 2 km away from) and associated with glacier thinning and retreat; and 3) subsidence of outwash fan deltas near glacier termini.  These three categories are differentiated in the shapefile attribute table and in an explanation box in the kmz file. The attribute table also provides the area of each polygon in sq. meters. Overall, we detected 4 landslides distal to glacier termini, 22 adjacent to termini, and 5 subsiding fan deltas. We have also included shapefiles for the boundary of Glacier Bay National Park and Preserve; the coverage area for scenes P145 and P50, and the overlap between the two; and points and labels for each polygon of moving ground.  
These data were used in the following interpretive paper: Kim, J., Coe, J.A., Lu, Z., Avdievitch, N.N., and Hults, C.P., in review, Spaceborne InSAR mapping of landslides and subsidence in rapidly deglaciating terrain, Glacier Bay National Park and Preserve and vicinity, Alaska and British Columbia: Remote Sensing of Environment.

Tags: alaska, biota, climate-change, fan-delta, glacial-geology, glacial-outwash, glacier-bay-national-park-and-preserve, insar, interferometric-synthetic-aperture-radar, landslide, landslide-hazards, monitoring, remote-sensing, rock-slide, sentinel, southeastern-alaska, tsunami, usgs-623ca899d34e915b67d39648
Organization: Department of the Interior
Modeling data for burn severity of the East Troublesome and Grizzly Creek for integration with post-fire debris flow in the upper Colorado River basin, USA

These data were compiled for/to provide an example and assess methods and results of pre-fire estimation of predicted differenced normalized burn ration (dNBR) for predicting post-fire debris flow hazard classification. Objective(s) of our study were to develop predictive models for burn severity, using variables of pre-fire conditions, for two large wildfires from 2020 in Colorado, USA. These data represent pre-fire predictions of post-fire differenced normalized burn ratio (dNBR) as a proxy of burn severity and further understand pre-fire modeling of burn severity. These data were collected/created in the fire perimeters the East Troublesome Fire (10/14/2020 – 11/30/2020) and the Grizzly Creek Fire (8/10/2020 – 12/18/2020), Colorado, USA. These data were collected/created by use of random forest modeling of variables representing pre-fire conditions (satellite spectral data, landscape biophysical data, GIS topographic data, and meteorological/climate data) against observed estimates of post-fire difference in normalized burn ratio (dNBR). These data can be used to provide estimates of burn severity for post-fire hazard analysis.

Tags: arapaho-national-forest, biota, burn-severity, colorado, data-release, debris-flow, differenced-normalized-burn-ratio, dnbr, east-fork-troublesome-creek, east-troublesome-fire, environment, estes-park, fire-damage, fire-perimeters, fires, fuel, garfield-county, glenwood-canyon, glenwood-springs, granby, grand-county, grand-lake, grizzly-creek, grizzly-creek-fire, hazards, kremmling, landslides, machine-learning, modeling, post-fire-differenced-normalized-burn-ratio, post-fire-hazard, pre-fire-conditions, pre-fire-estimation, pre-fire-modeling, pre-fire-predictions, predicted-differenced-normalized-burn-ration, predictive-models, random-forest-modeling, remote-sensing, rocky-mountain-national-park, usgs-623c8a96d34e915b67d39482, volume-of-debris-flow, water-quality, white-river-national-forest, wildfire, wildland-fire
Organization: Department of the Interior
Data to support water quality modeling efforts in the Delaware River Basin: 3) Model Driver Data

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 includes model drivers such as gridded weather data (NOAA GEFS and GridMET), and the stream network distance matrix for the Delaware River Basin. Additionally, inputs and outputs from an uncalibrated process-based stream temperature model (PRMS-SNTemp) are included.

Tags: de, delaware, environment, inlandwaters, maryland, md, modeling, new-jersey, new-york, nj, ny, pa, pennsylvania, reservoirs, streams, temperature, united-states, us, usgs-623e5587d34e915b67d83806, water, water-quality, water-resources
Organization: Department of the Interior