AndreaBozzo/ceres-open-data-index huggingface dataset:
Simulated snowpack and meteorology at multiple resolutions for three headwater study areas in Colorado, USA, water years 1980-2019

This data release includes SnowModel output for three headwater study areas in Colorado at seven spatial resolutions and from two forcing datasets over a 40-year period from water year 1980 to 2019. The resolutions include 30 m, 50 m, 100 m, 150 m, 250 m, 500 m, and 1,000 m. The model was run with a 3-hour temporal resolution from September 1, 1980 to August 31, 2019. Two meteorology forcing datasets were used, including National Land Data Assimilation System-2 at 1/8th degree (about 12 km) resolution data and the Weather Research and Forecasting  model data at 4 km resolution. Output variables include snow-water equivalent depth (swed), runoff (roff), air temperature (tair), snow-covered area (sca), snow depth (snod), precipitation (prec), and liquid precipitation (rpre).  Additionally, topography and vegetation datasets are included for each combination of unique domain and resolution, as well as the model parameterization file for a representative year. The data are organized by water year (WY) for each forcing type. For example, 'XXXX_wyYYYY.zip', where XXXX is either NLDAS2 or WRFCTL, and YYYY is the water year, with each water year including subdirectories for each of the three headwater study areas ('ER', 'FR', and 'SB' for East River, Fraser River, and Senator Beck, respectively). Each headwater study area subdirectory contains a subdirectory for each spatial resolution ('30', '50', '100', '150', '250', '500', '1000'), and each of those subdirectories contains NetCDF files for the seven variables modeled at that resolution. For example,'SA_RES_VAR_wyYYYY.nc', where SA is one of the three headwater study areas, RES is one of the seven spatial resolutions, VAR is one of the seven output variables, and YYYY is the water year.

Tags: biota, colorado-headwaters, east-river, fraser-river, senator-beck, usgs-64877814d34ef77fcafe1847
Organization: Department of the Interior
Crested wheatgrass probability of occurrence in the Wyoming Basins Ecoregional Assessment area

Probability map of Crested wheatgrass occurrence in relation to vegetation, abiotic, and anthropogenic features.

Tags: agropyron-cristatum, biota, colorado, crested-wheatgrass, environment, geoscientificinformation, geospatial-datasets, great-basin, idaho, modeling, montana, probability-of-occurrence, scientific-interpretation, shrubland-ecosystems, usgs-64878c58d34ef77fcafe1c99, utah, wyoming
Organization: Department of the Interior
Computed daily metallic-contaminant concentrations and loads on the Clark Fork River at USGS streamgages 12324200 and 12324400 near Grant-Kohrs Ranch National Historic Site in southwestern Montana, Water Years 2019-20

In 2019, the U.S. Geological Survey (USGS), in cooperation with the National Park Service, initiated a study using surrogate technology to predict real-time metallic-contaminant concentrations (MCCs) in the Clark Fork at two USGS streamgages that bracket Grant-Kohrs Ranch National Historic Site (GRKO) near Deer Lodge, Montana. Clark Fork at Deer Lodge(streamgage 12324200), Mont., about one mile upstream from GRKO, and Clark Fork above Little Blackfoot River near Garrison (streamgage 12324400), Mont., about 12 miles downstream from GRKO property were instrumented with turbidity and acoustic sensors for monitoring the Clark Fork during National Park Service Superfund remediation activities. Time-series data from backscatter signals from fixed-point turbidity and acoustic sensors were correlated with discrete MCC samples collected from the Clark Fork and were used as surrogates for estimating real-time cadmium, copper, iron, lead, manganese, zinc, and the metalloid trace element arsenic. A stepwise regression approach was used to develop statistical models to predict MCCs based on instantaneous values of turbidity and acoustic backscatter. Simple linear regression models using turbidity as the sole explanatory variable produced the best models with R-squared values exceeding 0.90 in 9 of 12 models. Nash-Sutcliffe Efficiency values were used to evaluate the effectiveness of predictive models to approximate measured MCCs, and model biases were calculated as an additional check on model accuracy. The R-LOADEST statistical package was used to compute annual and daily metallic-contaminant loads along with 95-percent prediction intervals. R-LOADEST loads were compared to time-series computed loads to evaluate the applicability of time-series data for calculating daily and annual metallic-contaminant loads. Results from annual load estimates indicated an increase in loads for all metallic contaminants between the two monitoring sites. These results provided real-time information to National Park Service management for evaluating variation in water quality during Superfund remediation, comparing MCC values relative to aquatic life standards, and will help quantify benefits from Superfund remediation activities.

Tags: acoustics, biota, clark-fork, deer-lodge, garrison, grant-kohrs-ranch-national-historic-site, loads, metallic-contaminant, streamflow, surrogate, usgs-64879c80d34ef77fcafe1cca, usgs-id-12324200, usgs-id-12324400, water-quality
Organization: Department of the Interior
Crosswalk table between selected Conterminous United States (CONUS) Global Reservoir and Dam Database (GRanD) site and High-Value National Hydrographic Datasets

This data release provides coupling of Conterminous United States and several Canadian operational reservoirs used in recent hydrologic modeling studies to authoritative national hydrographic datasets used to identify, calibrate, model, and assess streamflow, water quantity, quality, and ecological resources. The National Inventory of Dams (NID) provides linkages to dams operated in the United States, GRanD provides linkages to Global Dams and Reservoirs, and the National Hydrography Dataset Plus (NHDPlus) provides linkages to the stream network and waterbodies to easily couple with National Hydrologic Models and landscape parameters. The Geospatial Fabric for National Hydrologic Modeling, version 1.1 (GFv1.1) provides linkages to existing National Hydrologic Model (NHM) spatial modeling units.  All crosswalks, linkages, and other information is provided in a comma-separated value (csv) file.

Tags: dam-sites, national-inventory-of-dams-nid, usgs-64887139d34ef77fcafe345c, utilitiescommunication
Organization: Department of the Interior
Monthly crop irrigation withdrawals and efficiencies by HUC12 watershed for years 2000-2020 within the conterminous United States

The USGS has published United States water-use data every five years since 1950. To increase the temporal and spatial availability of water use estimates using nationally consistent methods, the USGS is developing national water-use models for each major water-use category. This data release publishes crop irrigation withdrawals for the conterminous United States (CONUS) that are calculated using modeled irrigation consumptive use (Martin and others, 2023), irrigation efficiencies, and source-water proportions (Dieter and others, 2018). Crop irrigation withdrawals and irrigation consumptive use refer to water removed and consumed, respectively, from a groundwater or surface-water source to produce agricultural crops. Monthly withdrawals provided include groundwater, surface water, and the combined total withdrawal for areas contained in the twelve-digit watershed boundary (HUC12) dataset during the reanalysis period, 2000-2020.
HUC12 annual 2000-2020 irrigation efficiencies included in this data release combine efficiencies from irrigation system types (accounting for water lost during application to crops) and conveyances (accounting for water lost during transmission through canals and pipes). Irrigated crops were mapped using the Landsat-based Irrigation Dataset (LANID; Xie and Lark, 2021; Martin and others, 2023) and the Cropland Data Layer (USDA NASS, 2022) that were linked to irrigation system types (USDA NASS, 2014) to estimate irrigation system efficiencies for each HUC12 in the CONUS (Howell, 2003 and FAO, 1989). Conveyance loss volumes (USDA NASS, 2020) were used to estimate and map surface-water conveyance efficiencies.  Total efficiencies were calculated for HUC12 units by combining irrigation system and conveyance efficiencies. 
Irrigation withdrawals and efficiencies were produced using published data sources to provide these estimates in a timely manner. On-going work to develop dynamic maps of irrigation system type and other datasets for the CONUS will be used in the future to refine the estimates provided here. Estimation of irrigation withdrawals using irrigation consumptive use and efficiencies neglects some components of water use for crops, including water used for frost protection, salt leaching, harvesting, and other non-consumptive-use based treatments.  For this reason, irrigation withdrawals provided here may under-estimate total withdrawals where non-consumptive treatments are significant.

Tags: inlandwaters, irrigation, usgs-6488734cd34ef77fcafe347a, water-use
Organization: Department of the Interior
Identifying structural priors in a hybrid differentiable model for stream water temperature modeling at 415 U.S. basin outlets, 2010-2016

&lt;p&gt;This model archive (Rahmani et al. 2023a) provides all data, code, and model outputs used in Rahmani et al. (2023b) to improve model representations toward improved prediction of stream temperature and groundwater/subsurface flow contributions to stream temperature. Briefly, we modeled stream temperature at sites across the continental United States using a hybrid differentiable model that combines neural network components with differentiable implementations of several structural priors, i.e., process-based equations. The differentiable framework permits estimation of parameters and comparison of structural priors as well as prediction of stream temperature.&lt;/p&gt;
&lt;p&gt;The data are organized into these child items: &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/648f9bbdd34ef77fcb001ffc"&gt; 1. Model code &lt;/a&gt;- Python files and README for reproducing model training and evaluation &lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/648f9c49d34ef77fcb001fff"&gt; 2. Inputs &lt;/a&gt;- Basin attributes and shapefiles, forcing data, and stream temperature observations &lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/648f9caed34ef77fcb002001"&gt; 3. Simulations &lt;/a&gt;- Simulation descriptions, configurations, and outputs &lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/6495df90d34ef77fcb01e285"&gt; 4. Figure code &lt;/a&gt;- Jupyter notebook to recreate the figures in Rahmani et al. (2023b) &lt;/li&gt; &lt;/p&gt;
&lt;p&gt;The publication associated with this model archive is: Rahmani, F., Appling, A.P., Feng, D., Lawson, K., and Shen, C. 2023b. Identifying structural priors in a hybrid differentiable model for stream water temperature modeling. Water Resources Research. &lt;a href=https://doi.org/10.1029/2023WR034420&gt;https://doi.org/10.1029/2023WR034420&lt;/a&gt;.&lt;/p&gt;
&lt;p&gt;This data compilation was funded by the Integrated Water Prediction Program at the U.S. Geological Survey.&lt;/p&gt;

Tags: deep-learning, environment, inlandwaters, machine-learning, modeling, streams, united-states, us, usgs-64888368d34ef77fcafe3936, water-resources, water-temperature
Organization: Department of the Interior
Data to support hierarchical models and decision support maps to guide management of subsidized avian predator densities

We combined approximately 28,000 raven point count surveys with data from more than 900 sage-grouse nests between 2009 and 2019 within the Great Basin, USA. We modeled variation in raven density using a Bayesian hierarchical distance sampling approach with environmental covariates on detection and abundance. Concurrently, we modeled sage-grouse nest survival using a hierarchical frailty model as a function of raven density as well as other environmental covariates that influence risk of failure. Raven density commonly exceeded more than 0.5 ravens per square kilometer and increased at low relative elevations with prevalent anthropogenic development and/or agriculture. Reduced sage-grouse nest survival was strongly associated with elevated raven density (e.g., more than 0.5 ravens per square kilometer) and varied with topographic ruggedness, shrub cover, and burned areas. For conservation application, we developed a spatially explicit planning tool that predicts nest survival under current and reduced raven numbers at local areas within the Great Basin to help direct management actions to locations where sage-grouse nests are at highest risk of failure. Our modeling framework can be generalized to multiple species where spatially registered abundance and demographic data are available.

Tags: anthropogenic-subsidies, bi-state, biota, california, conservation-planning, decision-support, density-surface-model, distance-sampling, ecology, great-basin, human-impacts, idaho, native-species, nest-survival, nevada, population-decline, predation, predator-prey, sagebrush, species-distribution, species-of-concern, usgs-648904e9d34ef77fcafe4484, wildlife
Organization: Department of the Interior
Water-borne electromagnetic induction, handheld thermal infrared and sediment temperature, chemical, and pressure data collected at Hen Cove, Pocasset, Massachusetts, 2022

Groundwater discharge points to coastal waters can be identified and quantified using natural electrical and temperature data. In August 2022, U.S. Geological Survey (USGS) collected water-borne electromagnetic induction and temperature along selected transects within Hen Cove on Cape Cod, Massachusetts, following a spatial survey of bed sediment temperature. Handheld thermal infrared data were also collected to locate areas of focused terrestrial groundwater discharge based on characteristic cool temperatures of groundwater in late summer. Those initial datasets guided the installation of vertical bed sediment temperature profilers, water pressure loggers suspended in piezometers, and the collection of pore water samples. The individual datasets from this study are described in more detail under the Child Items of this data release, organized by data type.

Tags: bourne-ma, cape-cod, electromagnetic-induction, environment, farming, geophysics, geoscientific-information, groundwater, location, massachusetts, oceans, poccasset-ma, temperature, usgs-6489cad8d34ef77fcafe5b6c, water-borne
Organization: Department of the Interior
Vertical profile sediment temperature and pressure head data collected at Hen Cove, Pocasset, Massachusetts, 2022

This data release provides saturated sediment temperatures from vertical temperature profilers, pressure head data from co-located pizometers, and estimates of 1D groundwater flux using a recursive-estimation framework to infer groundwater/surface-water exchange based on the collected temperature time-series (approximate 1,6,16,26cm depths, AlphaMachX vertical temperature profilers) from below the sediment/water interface. A heat-transport problem was formulated as a state-space model (SSM), in which the spatial derivatives in the convection/conduction equation are approximated using finite differences. The SSM is calibrated to estimate time-varying specific discharge using the Extended Kalman Filter (EKF) and Extended Rauch-Tung-Striebel Smoother (ERTSS) algorithms. These algorithms are described in McAliley et al., 2024 (https://doi.org/10.1029/2021WR030443) and relevant algorithm has been publicly released previously on ScienceBase (https://doi.org/10.5066/P99DBTKT). This data release contains 3 zipped folders, EKF_ERTSS_results.zip that contains EKF and ERTSS groundwater flux estimates, Temperature_observations.zip that contains raw observed temperature time series, and Pressure_data.zip that contains raw observations of pressure from piezometers adjacent to vertical temperature profilers. Additionally, water pressure transducers (Onset HOBO model U20L) were suspended at two depths within 2" steel pipes with 20cm screen drivepoints that were driven vertically into bed sediments adjacent to locations TX129 and TX132.

Tags: bourne-ma, buzzards-bay-ma, cape-cod, electromagnetic-induction, environment, farming, geophysics, geoscientific-information, groundwater, location, massachusetts, oceans, pocasset-ma, temperature, usgs-6489d113d34ef77fcafe5b8a, water-borne
Organization: Department of the Interior
Monthly twelve-digit hydrologic unit code aggregations of the National Hydrologic Model Precipitation-Runoff Modeling System modeling application for Puerto Rico, 1950-2021 (ver. 2.0, June 2025)

This data release contains 16 variables from the National Hydrologic Model Infrastructure with the Precipitation-Runoff Modeling System (NHM-PRMS) modeling application forced with Daymet version 4 (LaFontaine and others, 2024) from January 1950 through December 2021 that are summarized to a monthly time step and a twelve-digit hydrologic unit code for the spatial extent of Puerto Rico and the U.S. Virgin Islands. The following fluxes and storages are included: total monthly precipitation, evapotranspiration, lateral flow, surface runoff, interflow, recharge, groundwater flow, and the average monthly snow water equivalent, interflow storage, groundwater storage, total storage, and soil moisture. These data can be found in the “PR_huc12_monthly_nhmprms_daymet_1950_2021.nc” file. 
Additionally, two supplementary files are also included in this data release. The first file (“PR_weights_hru_to_huc12_nhmprms_daymet.csv”) contains the spatial weights or fraction that is used to “weight” the modeling output in the area-weighting process. The second file (“PR_summed_weights_per_huc12_nhmprms_daymet.csv”) contains the total fractional area within each twelve-digit hydrologic unit code that is covered by the modeling output and is important for filtering results in the data file (where a fractional coverage may be less than one). 
In the version 2.0 data release update, a new variable was added to the “PR_huc12_monthly_nhmprms_daymet_1950_2021.nc” file and a new file, "PR_huc12_daily_soil_moisture_fraction_nhmprms_paymet_1950_2021.nc" was added that contains daily estimates of the soil moisture fraction at each twelve-digit hydrologic unit code for the spatial extent of Puerto Rico and the U.S. Virgin Islands. See the file, “revision_history_nhmprms_daymet_PR.txt” for a full description of revisions.

Tags: climatologymeteorologyatmosphere, national-hydrologic-model-precipitation-runoff-modeling-system, nhm-prms, usgs-6489d846d34ef77fcafe5bae
Organization: Department of the Interior
GIS Features of the Geospatial Fabric for the National Hydrologic Model, Hawaii Domain

The Geospatial Fabric is a dataset of spatial modeling units for use within the National Hydrologic Model that covers the conterminous United States (CONUS), Alaska, and most major river basins that flow in from Canada.  This U.S. Geological Survey (USGS) data release consists of the geospatial fabric features and other related datasets created to expand the National Hydrologic Model to Hawaii.
This page contains data and information related to the GIS features of the Geospaital Fabric for National Hydrologic Model, Hawaii domain. An Open Geospatial Consortium geopackage (GF_20.gpkg) contains 4 feature layers (layer names in parentheses): points of interest (poi), a stream network (nsegment), aggregated catchments (catchment), and hydrologic repsonse units (nhru). Features were derived from NHDPlus, version 2.0, and several hydroclimatic datasets representing domain-specific processes and key drainage basins within the Hawaii. 
All data cover the National Hydrologic Model's (NHM) Hawaiin domain. The NHM is a modeling infrastructure consisting of three main parts: 1) an underlying geospatial fabric of modeling units (hydrologic response units and stream segments) with an associated parameter database, 2) a model input data archive, and 3) a repository of the physical model simulation code bases (Regan and others, 2014). The pois represent hydro locations and points on the network. Segments are connected by the pois and are used to route streamflow and characterize upstream watershed conditions. The HRUs represent the spatial modeling units at which most of the physical processes (such as precipitation, runoff, evapotranspiration, and infiltration) are simulated. Some HRUs are connected to a corresponding segment, and may represent left and right-bank areas of each stream segment. See Regan and others (2018) and entities and attributes for more information.

Tags: biota, geographic-information-systems, geography, geoscientificinformation, geospatial-datasets, hawaii, hydrographic-datasets, hydrologic-modeling, hydrologic-response-units, hydrology, inlandwaters, kahoolawe, kauai, lanai, maui, molokai, niihau, oahu, points-of-interest, routing-network, usgs-6489dafcd34ef77fcafe5bc2
Organization: Department of the Interior
Biological and chemical data from laboratory toxicity exposures of wildland fire retardants to Rainbow Trout

We measured Survival endpoints for juvenile rainbow trout (Oncorhynchus mykiss) in response to exposure to wildland fire retardants. Exposures were &lt;24 hours. We documented time to mortality hourly through 12 hours of exposure and again at 24 hours.  This data set includes data for three current use fire retardants from the US Forest Service Qualified Products List (Phos-Chek 259-Fx, Phos-Chek MVP-Fx, and Phos-Chek LC-95A-R). Also included are water quality data measured in each treatment at the beginning of each assay and quality assurance/ quality control data which validates the accuracy of those water quality measurements.

Tags: ammonia, columbia-environmental-research-center, columbia-missouri, farming, fires, flame-retardants, oncorhynchus-mykiss, usgs-6489f729d34ef77fcafe5c5d, wildfires
Organization: Department of the Interior
Bathymetric data and grid of offshore Marconi Beach, Wellfleet, MA on March 20, 2023

The data in this release re-map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-014-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-02, which are two video cameras aimed at the beach. In March 2023, U.S. Geological Survey and Woods Hole Oceanographic Institute (WHOI) scientists conducted field surveys to collect topographic and bathymetric data. Images of the beach for use in structure-from-motion were taken with a camera (SONY a6000) and a post-processed kinematic (PPK) system attached to a helium powered balloon-kite (Helikite). High-precision GPS targets (AeroPoints) and numbered black and white tarps were used as ground control points. Bathymetry was collected in the nearshore using a single-beam echosounder mounted on a surf capable self-righting electric autonomous surface vehicle. Agisoft Metashape (v. 1.8.1) was used to create a digital surface model and orthomosaic with the collected imagery.

Tags: asv, autonomous-surface-vehicle, bathymetry, cape-cod, cmhrp, coastal-and-marine-hazards-and-resources-program, elevation, geoscientificinformation, geospatial-datasets, location, marconi-beach, massachusetts, national-seashore, oceans, remote-sensing, shoreline, single-beam-echo-sounder, u-s-geological-survey, united-states, usgs, usgs-648b6c33d34ef77fcafe68fc, wellfleet, whcmsc, whoi, woods-hole-coastal-and-marine-science-center, woods-hole-oceanographic-institution
Organization: Department of the Interior