AndreaBozzo/ceres-open-data-index huggingface dataset:
Bias Feature for the Florida east coast (FLec) coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs.  Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion along the southeast US coastline and implications for vulnerability to future storms.

Tags: atlantic-coast, bias, bias-feature, cmgp, coastal-and-marine-geology-program, coastal-processes, digital-shoreline-analysis-system, dsas, environment, florida, georgia, geoscientificinformation, geospatial-datasets, gulf-coast, high-water-line, hwl, linear-regression-rate, lrr, mean-high-water, mhw, north-america, oceans, pdb, proxy-datum-bias, shoreline-change, u-s-geological-survey, united-states, usgs, usgs-614bd5c3d34e0df5fb97c84a, whcmsc, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Fish community and species distribution predictions for streams and rivers of the Chesapeake Bay Watershed

This data release contains predictions of selected  fish community metrics and fish species occurrence using Random Forest models with landscape data for inland reaches across the Chesapeake Bay Watershed (CBW). Predictions were made at four time intervals (2001, 2006, 2011, and 2016) according to changes in landcover using the National Land Cover Database (NLCD). The fish sampling data used to compute these metrics were compiled from various fish sampling programs conducted by state and federal agencies, county governments, universities, and river basin commissions across the watershed. Community metrics describe composition, tolerances, habitat preferences, and functional traits of fish communities (and were derived from Krause and Maloney, 2021). Community analyses were developed for four aggregated Level III ecoregions: Northern Appalachians (NAP), Southern Appalachians [split into two sub-regions; the SAP-Piedmont (Piedmont and Northern Piedmont Ecoregions; SAPPIED] and other ecoregions [SAPNW]) and the Coastal Plains (CPL), and a final index was calculated for each ecoregion as the average of selected metric deciles with higher scores inferring less biologically altered (i.e., better) conditions. Species distribution models were created for key sensitive and gamefish species (including Brook Trout, Northern Hog Sucker, Smallmouth Bass, and Torrent Sucker) to predict species occurrence. Uncertainty was calculated for both approaches using model prediction intervals. For complete data descriptions and data interpretation see associated publication (Maloney et al., 2022; https://doi.org/10.1016/j.ecolind.2021.108488).

Tags: district-of-columbia-national-district, habitats, maryland-state, natural-resource-assessment, new-york-state, pennsylvania-state, prediction, random-forest, species, usgs-61533111d34e0df5fb9c5bc5, virginia-state, west-virginia-state
Organization: Department of the Interior
01) Revised groundwater-level contours for Smith Valley and Mason Valley, Nevada, 1970

These contours represent static groundwater levels based on depth-to-water measurements in Smith Valley and Mason Valley, Nevada. Groundwater-level contours for Smith Valley were first published by Rush and Schroer (1976) and subsequently published electronically by Welborn and Medina (2022). The Smith Valley groundwater-level contours represent conditions in the spring of 1972. Groundwater-level contours for Mason Valley were first published by Huxel and Harris (1969) and subsequently published electronically by Lopes and others (2006). The Mason Valley groundwater-level contours represent conditions during 1965-1966. The original groundwater-level contours from Smith Valley and Mason Valley (Huxel and Harris, 1969; Rush and Schroer, 1976) were modified in this study for consistency with the methods used to develop groundwater-level contours by Lopes and Allander (2009) for fall 2006. In the revised dataset, three contours in Smith Valley and 21 contours in Mason Valley were adjusted where they approach and cross the river while maintaining their general form and interpretation away from the river. In this study, because groundwater conditions were generally considered static in Smith Valley and Mason Valley between 1965-72, the two groundwater-level contour datasets are jointly referred to as the 1970 groundwater-level contours.

Tags: geoscientificinformation, great-basin, groundwater, inlandwaters, lyon-county, mason-valley, nevada, smith, smith-valley, usgs-614cdb31d34e0df5fb98691f, water-level-altitude, yerington
Organization: Department of the Interior
Depth to water, spring 2016, Mississippi River Valley alluvial aquifer, raster format, in feet

This dataset is a raster surface, in feet, of the depth to water, spring 2016, Mississippi River Valley alluvial aquifer (MRVA). The raster cell size is 1,000 meters (3,280.8 ft). . The raster was interpolated using (1) depth-to-water (GW_D2W) data from wells and (2) an assumed value of zero for depth to water at streamgages (SW_D2W) because the precise depth to groundwater at the streamgage is not known. The streamgage data is used only when it appears the regional aquifer and surface water are hydrologically connected.

Tags: aquifers, arkansas, biota, depth-to-water-surface, digital-elevation-models, groundwater, groundwater-altitude, groundwater-and-surface-water-interaction, groundwater-level, groundwater-levels, hydrogeology, illinois, inlandwaters, kentucky, louisiana, mississippi, mississippi-alluvial-plain, mississippi-river-delta, mississippi-river-valley-alluvial-aquifer, missouri, surface-water-altitude, tennessee, usgs-614ce01bd34e0df5fb986929
Organization: Department of the Interior
Depth to water, spring 2020, Mississippi River Valley alluvial aquifer, raster format, in feet

This dataset is a raster surface, in feet, of the depth to water, spring 2020, Mississippi River Valley alluvial aquifer (MRVA). The raster cell size is 1,000 meters (3,280.8 ft). The raster was interpolated using (1) depth-to-water (GW_D2W) data from wells and (2) an assumed value of zero for depth to water at streamgages (SW_D2W) because the precise depth to groundwater at the streamgage is not known..The streamgage data is used only when it appears the regional aquifer and surface water are hydrologically connected.

Tags: aquifers, arkansas, biota, depth-to-water-surface, digital-elevation-models, groundwater, groundwater-altitude, groundwater-and-surface-water-interaction, groundwater-level, groundwater-levels, hydrogeology, illinois, inlandwaters, kentucky, louisiana, mississippi, mississippi-alluvial-plain, mississippi-river-delta, mississippi-river-valley-alluvial-aquifer, missouri, surface-water-altitude, tennessee, usgs-614ce037d34e0df5fb98692b
Organization: Department of the Interior
04) Groundwater-level contours for Smith Valley and Mason Valley, Nevada, 2020

These contours represent static groundwater levels based on depth-to-water measurements made at 165 monitoring wells during water years 2016-2020 in Smith Valley and Mason Valley, Nevada. For each monitoring well, the median groundwater-level altitude during the five-year period (2016-2020) was used for developing the groundwater-level contours. Depth-to-water measurements were collected by the USGS and the Nevada Division of Water Resources (NDWR).

Tags: geoscientificinformation, great-basin, groundwater, inlandwaters, lyon-county, mason-valley, nevada, smith, smith-valley, usgs-614ce636d34e0df5fb986990, water-level-altitude, yerington
Organization: Department of the Interior
03) Revised groundwater-level contours for Smith Valley and Mason Valley, Nevada, 2006

These contours represent static groundwater levels based on depth-to-water measurements in Smith Valley and Mason Valley, Nevada, for fall 2006. Groundwater-level contours were first published by Lopes and Allander (2009) and subsequently published electronically by Medina and others (2022). Since the time of the dataset's original publication, the position and land-surface altitude at 23 monitoring wells in Smith Valley used to develop the original 2006 groundwater-level contours have been updated. As such, 10 contours in Smith Valley were revised using the updated monitoring well locations and land-surface altitudes while maintaining, to the extent possible, the original interpretation made by Lopes and Allander (2009).

Tags: geoscientificinformation, great-basin, groundwater, inlandwaters, lyon-county, mason-valley, nevada, smith, smith-valley, usgs-614ce7cad34e0df5fb986993, water-level-altitude, yerington
Organization: Department of the Interior
Data and Model Archive for Preliminary Machine Learning Models of Manganese and 1,4-Dioxane in Groundwater on Long Island, New York

Data and preliminary machine-learning models used to predict manganese and 1,4-dioxane in groundwater on Long Island are documented in this data release. Concentration data used to develop the models were from 910 wells for manganese and 553 wells for 1,4-dioxane, primarily public supply wells, from U.S. Geological Survey, U.S. Environmental Protection Agency (USEPA), and Suffolk County Water Authority sources. Thirty-two explanatory variables describe depth, groundwater flow, land use, soil properties, and other features of the aquifer system. The models use XGBoost, an ensemble tree machine learning method. Four models are documented for manganese, predicting the probability of concentrations relative to four thresholds: 10 micrograms per liter (detection), 50 micrograms per liter (the USEPA Secondary Maximum Contaminant Level), 150 micrograms per liter, and 300 micrograms per liter (the USEPA lifetime health advisory). One model is documented for 1,4-dioxane, predicting the probability of concentrations relative to 0.07 micrograms per liter (detection). The models were used to predict concentrations in two layers of the upper glacial aquifer and three layers of the Magothy aquifer. Predictions were made at a 500-square-foot resolution across the entire island for manganese and across Suffolk County, which occupies the eastern two-thirds of Long Island, for 1,4-dioxane.   
The data are provided in data tables, raster files, and model files. One data table describes the 32 explanatory variables (LI_mn_14dx_exp_vars.txt). One data table describes the well data and includes the manganese and 1,4-dioxane concentrations, explanatory variables, and predictions for the wells (LI_mn_14dx_well_data.txt). There is a compressed group (zip file) of five files providing the explanatory variable data used to make predictions for the five aquifer layers (LI_mn_14dx_predinput_griddata.zip) and a zip file of 25 files providing model predictions for each model and aquifer layer (LI_mn_14dx_predoutput_rasters.zip). The data release also contains a tif-format raster file of the prediction grid (LI_mn_14dx_prediction_grid.tif). The models are documented in a zip file (LI_mn_14dx_models.zip) that contains the model object files (R data format) and scripts that can be used to run the models to produce the predictions provided in this data release. Filenames for prediction input and for model output are distinguished by names and numbers as follows: 1_upper_glacial, top layer of the upper glacial aquifer; 3_upper_glacial, bottom layer of the upper glacial aquifer; 5_Magothy, top layer of the Magothy aquifer; 14_Magothy, middle layer of the Magothy aquifer; and 23_Magothy, bottom layer of the Magothy aquifer.

Tags: 14-dioxane, groundwater-quality, kings-county, long-island, machine-learning, manganese, nassau-county, nawqa, new-york, queens-county, regional-groundwater-quality, suffolk-county, usgs-614d0486d34e0df5fb986a43, xgboost
Organization: Department of the Interior
Model predictions for heterogeneous stream-reservoir graph networks with data assimilation

&lt;p&gt;This data release provides the predictions from stream temperature models described in Chen et al. 2021.  Briefly, various deep learning and process-guided deep learning models were built to  test improved performance of stream temperature predictions below reservoirs in the Delaware River Basin. The spatial extent of predictions was restricted to streams above the Delaware River at Lordville, NY, and includes the West Branch of the Delaware River below Cannonsville Reservoir and the East Branch of the  Delaware River below Pepacton Reservoir. Various model architectures, training schemes, and data assimilation methods were used to generate the table and figures in Chen et a.l (2021) and predictions of each model are captured in this release. For each model, there are test period predictions for 56 river reaches from 2006-10-01 through 2020-09-30. Model input and validation data can be found in Oliver et al. (2021). 
&lt;p&gt;The publication associated with this data release is Chen, S., Appling, A.P., Oliver, S.K., Corson-Dosch, H.R., Read, J.S., Sadler, J.M., Zwart, J.A., Jia, X, 2021, Heterogeneous stream-reservoir graph networks with data assimilation. International Conference on Data Mining (ICDM). DOI: https://doi.org/10.1109/ICDM51629.2021.00117.&lt;/p&gt;

Tags: climate-change, deep-learning, environment, hybrid-modeling, inlandwaters, machine-learning, modeling, new-york, ny, pa, pennsylvania, reservoirs, temperature, united-states, us, usgs-614e0b38d34e0df5fb98a0b7, water, water-resources
Organization: Department of the Interior
Metal and other element partitioning in southwest Puerto Rico ultramafic soil, Rio Loco sediment, and Guanica Bay sediment

Five-stage sequential extractions were performed on ultramafic soil from Bosque Susua and Guanica Dry Forest, stream sediment from Rios Loco and Yauco, and nearshore sediment from Guanica Bay in southwest Puerto Rico. Sequential extractions showed partitioning of geologically enriched metals and other elements among five phases: 1) adsorbed and calcium-bound, 2) iron-, manganese-oxyhydroxide-bound, 3) crystalline iron-oxide-bound, 4) sulfide-bound, and 5) residual. Total element contents are also reported. Soil and sediment were collected between June 19, 2017, and March 27, 2018.

Tags: bay, bosque-estatal-de-susua, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-plain, environment, geochemistry, geoscientificinformation, guanica-bay, island-of-puerto-rico, mass-spectroscopy, pacific-coastal-and-marine-science-center, pcmsc, rio-loco, rio-yauco, river, sediment, soil, soil-chemistry, substrate, u-s-geological-survey, usgs, usgs-614e30d0d34e0df5fb98a12f, watershed
Organization: Department of the Interior
Hawaii Island bird activity from 2014 through 2019

We used an automated radio telemetry network to document the activity of radio telemetered Hawaiian forest birds in two study sites, one a continuous forest and the other a fragmented forest. Four bird species were studied: the nectarivorous ʻiʻiwi (Drepanis coccinea) and ʻapapane (Himatione sanguinea), the frugivorous ʻōmaʻo (Myadestes obscurus), and the generalist Hawaiʻi ʻamakihi (Chlorodrepani virens; hereafter ʻamakihi). In the continuous forest we also tracked two non-native species: the frugivorous red-billed leiothrix (Leiothrix lutea), and the generalist warbling white-eye (Zosterops japonicus). Using sequential changes in radio signal strength we were able to estimate when birds were moving or resting. This data release consists of one tabular dataset with 2,026,289 records that contains the bird information, designated activity characterization, telemetry network information, and signal strength.

Tags: biota, hakalau-forest-national-wildlife-refuge, hawaii-forest-birds, hawaii-island, movement-patterns, radio-telemetry, upper-waiakea-forest-reserve, usgs-614e5bc7d34e0df5fb98dff2
Organization: Department of the Interior
Compilation of geologic slip rate constraints used in 1996—2014 U.S. National Seismic Hazard Models(ver. 2.0, February 2022)

A key input for probabilistic seismic hazard analysis (PSHA) is geologic slip rate data. Here, we compile all geologic slip rates that are reportedly used in U.S. National Seismic Hazard Map (NSHM) releases from 1996, 2002, 2007, 2008, and 2014. Although a new NSHM was released in 2018, no changes were made in geologic slip rate data used. The geologic slip rates are collated from existing NSHM reports and documentation, and no new data are reported herein. The geologic slip rates are coupled with the most up-to-date fault geometries utilized for NSHM calculations, and the data are presented spatially as a shapefile (SHP), in keyhole markup language (KML) and geoJSON. A readme file accompanies this dataset explaining details of the data compilation. This data release corrects minor typographical errors in the initial compilation of geologic slip rates used in U.S. National Seismic Hazard Models (1996-2014). The original compilation (version 1, published August 2020) is now superseded by this edited compilation (version 2, published February 2022). To compare changes between release, a 'Version Changes' file is included in this Data Release.

Tags: alaska, arizona, california, colorado, faults, geologic-slip-rates, idaho, montana, national-seismic-hazard-model, nevada, new-mexico, nshm, oregon, texas, united-states, usgs-6151d987d34e0df5fb9b96dc, utah, washington, wyoming
Organization: Department of the Interior
Reach-scale predicted annual streamflow permanence probabilities, predicted monthly mean stream temperature for August, and predicted monthly streamflow discharge for stream reaches in the Pacific Northwest, USA (2004-2015) (ver. 2.0, January 2023)

This dataset is a combination of annual Probability of Streamflow Permanence (PROSPER) predictions, Northwest Stream Temperature (NorWeST) predictions of monthly mean stream temperatures for August of each year, and predicted monthly streamflow discharge for stream reaches in the Pacific Northwest from the USGS database of natural monthly streamflow estimates, U.S., 2004-2015. The PROSPER model provides predictions of the annual probability of a 30-meter stream segment maintaining year-round streamflow. The NorWeST model provides annual predictions of monthly mean stream temperature for August for 1-kilometer stream segments. Finally, predictions of natural monthly streamflow were combined with NorWeST and PROSPER to provide information on the volume of water in a given system. The data are merged using the Medium Resolution National Hydrography Dataset, which serves as the foundation for the stream lines that the data are represented with. The intent of this merged dataset is to analyze the availability of current and future aquatic habitat.

Tags: freshwater-ecosystems, geoscientificinformation, idaho, inlandwaters, mathematical-modeling, montana, oregon, streamflow, surface-water-non-marine, usgs-61520513d34e0df5fb9ba045, washington, water-temperature
Organization: Department of the Interior
Locations of Dams and Basins in South Carolina, derived from U.S. Army Corps Engineers National Inventory of Dams

Reliable peak-streamflow information is critical for proper design of stream-related infrastructure, such as bridges, and StreamStats is a Web-based Geographic Information Systems (GIS) application that provides a user-friendly interface to estimate peak flows (https://streamstats.usgs.gov/ss/). StreamStats develops these peak-flow estimates using basin characteristics for the entire contributing area to a user-selected point; however, infrastructure planners often need to estimate flows for an area downstream from a known control such as a reservoir release or a weir. This dataset was compiled in cooperation with the South Carolina Department of Transportation (SCDOT) to provide a GIS layer of filtered regulation points from the U.S. Army Corps Engineers (USACE) National Inventory of Dams and upstream basin polygons for those points, for use within the South Carolina StreamStats client application. A select few characteristics were computed for each basin in the polygon dataset to enable the application to estimate flows above and below each regulation point and better assist SCDOT personnel when designing new or revising existing stream-related infrastructure.

Tags: bridges, dam-sites, georgia, north-carolina, region-1, region-2, region-3, region-4, region-5, south-carolina, usgs-6154584dd34e0df5fb9d3a6c, watershed-management
Organization: Department of the Interior
Risk assessment of chanchita Cichlasoma dimerus (Heckel, 1840), a newly identified non-native cichlid fish in Florida

Cichlasoma dimerus was only recently discovered in Florida and little is known of its dispersal abilities and potential impacts. Many factors likely contribute to the variability in establishment and spread of non-native fishes in Florida, including biotic (e.g., predation and competition) and abiotic variables (e.g., cold tolerance, low-oxygen tolerance). Of the abiotic variables, cold tolerance is an important regulator of non-native fish geographic ranges in Florida. 
Its tolerance to cold temperatures is experimentally evaluated and available information on its biology and ecology was synthesized. In the cold-temperature tolerance experiment, temperature was lowered from 24 C by increments of 1 C per hour, mimicking a typical cold weather front. Fish lost equilibrium at a mean temperature of 7.8 C and died at 4.7 C.

Tags: biota, population-and-community-ecology, temperature, usgs-615478ced34e0df5fb9d6193
Organization: Department of the Interior
Growth, Drought Response, and Genomic Structure Data for Whitebark Pine in the Sierra Nevada of California (ver. 2.0, May 2023)

These data represent stem growth from whitebark pine at 27 sites in the Sierra Nevada of California. Values for stem growth were derived from increment cores, processed following standard methods. Samples were also compared against a genomic data collected at the same trees.

Tags: biota, california, carbon-isotope-analysis, core-analysis, ecology, environment, sierra-nevada, time-series-datasets, usgs-6154a72fd34e0df5fb9d871b
Organization: Department of the Interior
Polygon Locations of Basins upstream from Dams in South Carolina, derived from U.S. Army Corps Engineers National Inventory of Dams

Reliable peak-streamflow information is critical for proper design of stream-related infrastructure, such as bridges, and StreamStats  provides a user-friendly interface to estimate peak flows (https://streamstats.usgs .gov/ss/). StreamStats develops these peak-flow estimates using basin characteristics for the entire contributing area to a user-selected point; however, infrastructure planners often need to estimate flows for an area downstream from a known control such as a reservoir release or a weir. This dataset was compiled in cooperation with the South Carolina Department of Transportation (SCDOT) to provide a Geographic Information System (GIS) layer of filtered regulation points from the U.S. Army Corps Engineers (USACE) National Inventory of Dams and upstream  basin polygons for those points, for use within the South Carolina StreamStats client application. A select few characteristics were computed for each basin in the polygon dataset to enable the application to estimate flows above and below each regulation point and better assist SCDOT personnel when designing new or revising existing stream-related infrastructure.

Tags: bridges, dam-sites, georgia, north-carolina, region-1, region-2, region-3, region-4, region-5, south-carolina, usgs-6154b7aed34e0df5fb9d8c97, watershed-management
Organization: Department of the Interior