AndreaBozzo/ceres-open-data-index huggingface dataset:
MODFLOW-NWT model used to simulate and assess groundwater flow and surface-water exchanges in lakes of the Northeast Twin Cities Metropolitan Area, Minnesota, 2003 through 2013

A three-dimensional, steady-state groundwater-flow model representing 2003-13 
mean hydrologic conditions was developed and calibrated to assess groundwater 
and lake-water exchanges and the effects of groundwater withdrawals and 
precipitation on water levels in lakes in the northeast Twin Cities Metropolitan 
Area, Minnesota.  The USGS groundwater-flow model program MODFLOW-NWT
version 1.0.8 was used to simulate groundwater flow in the approximately 
1,000-square-mile area of the northeast Twin Cities Metropolitan Area and 
western Wisconsin. Water levels were below normal for several lakes in the 
northeast Twin Cities Metropolitan Area during 2003 through 2013. Previous 
periods of low lake-water levels generally correlate with periods of below-normal 
precipitation but increases in groundwater withdrawals and land-use changes 
have put into question whether recent lake-water-level declines are due solely 
to declines in precipitation. The groundwater-flow model was developed to 
provide a thorough understanding of regional groundwater and surface-water 
exchanges under different groundwater withdrawal and precipitation scenarios.  
This USGS data release contains all of the input and output files for the 
simulations described in the associated U.S. Geological Survey Scientific 
Investigations Report 2016-5139B (https://doi.org/10.3133/sir20165139B).  
This data release also contains input and output data for ancillary soil-water 
balance (SWB) models used to simulate runoff to a subset of lakes and 
areal groundwater recharge.

Tags: anoka-county, aquifer-storage, chisago-county, dakota-county, environment, geoscientificinformation, groundwater, groundwater-availability, groundwater-depletion, groundwater-model, hennepin-county, inlandwaters, jordan-aquifer, minnesota, modflow-nwt, northeast-twin-cities-metropolitan-area, prairie-du-chien-aquifer, ramsey-county, st-peter-aquifer, usgs-5d6d0951-1929-48ac-97f4-fdd875fb7029, usgsgroundwatermodel, washington-county, white-bear-lake, wisconsin
Organization: Department of the Interior
Water-Quality Data Used in the Pecos River Salinity Assessment from Santa Rosa Lake, New Mexico to the Confluence of the Pecos River and the Rio Grande, Texas, 1900–2015

This part of the Data Release contains the water-quality data compiled and synthesized from various sources (including data from water-quality samples collected by the USGS in 2015 from 26 sites). This collection includes three main tables that contain (1) the list of site locations where water-quality data were collected, and information about those sites, such as the spatial coordinates of a well (Site_information); (2) the list of samples that were collected, and information about those samples, such as the date the sample was collected (Sample_information); and (3) the results of the measured constituent, and information about the result such as the concentration of a constituent that was measured in a sample (Water_quality_results). Additional tables in this collection include analysis completed on the data compiled in the three main tables such as instantaneous load computations computed from compiled dissolved solids concentration and streamflow data (Instantaneous_load_estimates). The collection also includes the results of quality-assurance tests performed on the data (Aggregated_water_quality_QAQC), and various lookup tables that describe codes and acronyms used. The data were used to complete a detailed salinity assessment of the Pecos River from Santa Rosa Lake, New Mexico to the confluence of the Pecos River and the Rio Grande, Texas.

Tags: andrews-county, aquifer, aquifer-base, aquifer-depth, avalon-lake, black-river, blue-hole, brantley-lake, brewster-county, chaves-county, crane-county, crockett-county, culberson-county, curry-county, debaca-county, delaware-river, ector-county, eddy-county, el-rito-creek, environment, geochemistry, geology, geoscientificinformation, geospatial-analysis, geospatial-datasets, groundwater, groundwater-quality, guadalupe-county, hydrogeology, independence-creek, inlandwaters, jeff-davis-county, lake-amistad, lake-sumner, lea-county, lincoln-county, lithology, live-oak-creek, loving-county, mora-county, new-mexico, north-seven-rivers, otero-county, pecos-county, pecos-river, presidio-county, quay-county, reagan-county, red-bluff-reservoir, reeves-county, rio-felix, rio-grande, rio-hondo, rio-penasco, roosevelt-county, salinity, salt-creek-n-mex, salt-creek-tex, san-miguel-county, santa-fe-county, santa-rosa-lake, south-seven-rivers, surface-water, surface-water-quality, taiban-creek, tecolote-creek, terrell-county, texas, torrance-county, upton-county, usgs-5d6a9e6fe4b0c4f70cf34123, val-verde-county, ward-county, water-quality, water-resources, winkler-county
Organization: Department of the Interior
Influenza A virus detected from bivalves in waterfowl habitat of the Delmarva Peninsula

This data set includes information pertaining to 300 bivalve mollusk tissue samples collected from mollusk specimens from waters in eastern Maryland on the Delmarva Peninsula.  Data includes source location, species, morphometric data, and IAV matrix gene detection status for the bivalve samples collected and analyzed in the associated study.

Tags: avian-influenza, chesapeake-bay, delmarva-peninsula, mollusks, usgs-5d697cc3e4b0c4f70cf294de
Organization: Department of the Interior
Nitrogen sources to and export from the Chesapeake Bay watershed, 1950 to 2050

This U.S. Geological Survey data release contains datasets that combine past data with future projections of nitrogen sources and nitrogen export to the Chesapeake Bay watershed for the years 1950-2050. To help understand the effect of human and environmental changes over this time period, data for nitrogen sources from wastewater, agricultural fertilizer and manure, and atmospheric deposition are combined with datasets of population and land use. These datasets were used in conjunction with a previously calibrated SPAtially Referenced Regression On Watershed attributes (SPARROW) modeling tool to estimate the mean annual loads of total nitrogen to the Chesapeake Bay and nontidal stream reaches in the watershed at a decadal timestep from 1950-2050. SPARROW model output of incremental and total loads for each reach in the Chesapeake Bay watershed are reported in this data release.

Tags: agriculture, baseflow, chesapeake, chesapeake-bay-watershed, climate-change, delaware, district-of-columbia, effects-of-climate-change, environment, estuary, eutrophication, evaporation, fertilizer, geoscientificinformation, groundwater, groundwater-and-surface-water-interaction, groundwater-quality, land-cover-change, land-use-change, lower-chesapeake-bay, manure, maryland, mathematical-modeling, new-york, nitrate, nitrogen, pennsylvania, point-sources, runoff, sparrow, stormwater, streamflow, surface-water, surface-water-non-marine, surface-water-quality, tmdl, transpiration, upper-chesapeake-bay, urban-areas, usgs-5d692bdde4b0c4f70cf173d7, virginia, wastewater-discharge, water-quality, watershed, watershed-management, west-virginia
Organization: Department of the Interior
Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)

Tables are presented listing parameters used in logistic regression equations describing drought streamflow probabilities in the Northeastern United States. Streamflow daily data, streamflow monthly mean data, maximum likelihood logistic regression (MLLR) equation explanatory parameters, equation goodness of fit parameters, and Receiver Operating Characteristic (ROC) AUC values identifying the utility of each relation, describe each model of the probability (chance) of a particular streamflow daily value exceeding or not exceeding an identified drought streamflow threshold. These models are key inputs to drought forecasting web applications for the northeastern United states {https://usgs.maps.arcgis.com/apps/MapSeries/index.html?appid=b8c5da617a0e4d628e3e39f7dbd512da}

Tags: connecticut, decision-support-systems, delaware, district-of-columbia, drought, forecasting, maine, maryland, massachusetts, new-hampshire, new-jersey, new-york, pennsylvania, rhode-island, risk-assessment, streamflow, surface-water-hydrology, usgs-5d681d5de4b0c4f70cf15c9b, vermont, virginia, water-supply, watershed-management, west-virginia
Organization: Department of the Interior
Water Levels From Wells Used in the Columbia Plateau Regional Aquifer System Study, Idaho, Oregon, and Washington

These data describe the groundwater level elevations compiled for the Columbia Plateau Regional Aquifer Study (CPRAS). The data included are well ids used in the study, the date of each water-level measurement, the groundwater elevation, in feet, in the North American Vertical Datum of 1988 (NAVD 88), the status of each water-level measurement, and the agency that reported each water level.

Tags: groundwater, idaho, inlandwaters, oregon, usgs-5d680f48e4b0c4f70cf15c84, washington
Organization: Department of the Interior
Principal components of climate variation in the Desert Southwest for the future time period 2040-2070 (RCP 8.5)

Five principal components are used to represent the climate variation in an original set of 12 composite climate variables reflecting complex precipitation and temperature gradients. The dataset provides coverage for future climate (defined as the 2040-2070 normal period) under the RCP8.5 emission scenarios. Climate variables were chosen based on their known influence on local adaptation in plants, and include: mean annual temperature, summer maximum temperature, winter minimum temperature, annual temperature range, temperature seasonality (coefficient of variation in monthly average temperatures), mean annual precipitation, winter precipitation, summer precipitation, proportion of summer precipitation, precipitation seasonality (coefficient of variation in monthly precipitation totals), long-term winter precipitation variability, and long-term summer precipitation variability. The conversion to principal components both standardizes and accounts for covariation in climate variables, while emphasizing the most important climate gradients across the landscape. 
Raster layers representing each principal component form the input to Climate Distance Mapper (https://usgs-werc-shinytools.shinyapps.io/Climate_Distance_Mapper/), an interactive R Shiny application for matching seed sources with restoration sites. Plant populations are commonly adapted to local climate gradients and frequently exhibit a home-site advantage. For this reason, climate information may serve as a proxy for local adaptation in restoration designs. Climate Distance Mapper allows users to rank the suitability of seed sources for restoration sites by displaying multivariate climate distances (incorporating climate principal components) from user-supplied input points to the surrounding landscape. The application provides functions to match seed sources with current or future climate, guide sampling effort for large scale seed collections, and partition the landscape into suitable areas for different seed sources. 
These data support the following publication:
Shryock, D.F., DeFalco, L.A., and T.C. Esque. 2018. Spatial decision-support tools to guide restoration and seed sourcing in the Desert Southwest. Ecosphere 9(10):e02453.

Tags: arizona, atmospheric-and-climatic-processes, california, climatologymeteorologyatmosphere, colorado, colorado-plateau, geospatial-analysis, great-basin, mojave-desert, nevada, new-mexico, precipitation, sonoran-desert, united-states, usgs-5d670928e4b0c4f70cf10f24, utah
Organization: Department of the Interior
Principal components of climate variation in the Desert Southwest for the future time period 2010-2040 (RCP 4.5)

Five principal components are used to represent the climate variation in an original set of 12 composite climate variables reflecting complex precipitation and temperature gradients. The dataset provides coverage for future climate (defined as the 2010-2040 normal period) under the RCP4.5 emission scenario. Climate variables were chosen based on their known influence on local adaptation in plants, and include: mean annual temperature, summer maximum temperature, winter minimum temperature, annual temperature range, temperature seasonality (coefficient of variation in monthly average temperatures), mean annual precipitation, winter precipitation, summer precipitation, proportion of summer precipitation, precipitation seasonality (coefficient of variation in monthly precipitation totals), long-term winter precipitation variability, and long-term summer precipitation variability. The conversion to principal components both standardizes and accounts for covariation in climate variables, while emphasizing the most important climate gradients across the landscape. 
Raster layers representing each principal component form the input to Climate Distance Mapper (https://usgs-werc-shinytools.shinyapps.io/Climate_Distance_Mapper/), an interactive R Shiny application for matching seed sources with restoration sites. Plant populations are commonly adapted to local climate gradients and frequently exhibit a home-site advantage. For this reason, climate information may serve as a proxy for local adaptation in restoration designs. Climate Distance Mapper allows users to rank the suitability of seed sources for restoration sites by displaying multivariate climate distances (incorporating climate principal components) from user-supplied input points to the surrounding landscape. The application provides functions to match seed sources with current or future climate, guide sampling effort for large scale seed collections, and partition the landscape into suitable areas for different seed sources. 
These data support the following publication:
Shryock, D.F., DeFalco, L.A., and T.C. Esque. 2018. Spatial decision-support tools to guide restoration and seed sourcing in the Desert Southwest. Ecosphere 9(10):e02453.

Tags: arizona, atmospheric-and-climatic-processes, california, climatologymeteorologyatmosphere, colorado, colorado-plateau, geospatial-analysis, great-basin, mojave-desert, nevada, new-mexico, precipitation, sonoran-desert, united-states, usgs-5d670752e4b0c4f70cf10dde, utah
Organization: Department of the Interior
Principal components of climate variation in the Desert Southwest for the time period 1980-2010

Five principal components are used to represent the climate variation in an original set of 12 composite climate variables reflecting complex precipitation and temperature gradients. The dataset provides coverage for current climate (defined as the 1980-2010 normal period). Climate variables were chosen based on their known influence on local adaptation in plants, and include: mean annual temperature, summer maximum temperature, winter minimum temperature, annual temperature range, temperature seasonality (coefficient of variation in monthly average temperatures), mean annual precipitation, winter precipitation, summer precipitation, proportion of summer precipitation, precipitation seasonality (coefficient of variation in monthly precipitation totals), long-term winter precipitation variability, and long-term summer precipitation variability. The conversion to principal components both standardizes and accounts for covariation in climate variables, while emphasizing the most important climate gradients across the landscape. 
Raster layers representing each principal component form the input to Climate Distance Mapper (https://usgs-werc-shinytools.shinyapps.io/Climate_Distance_Mapper/), an interactive R Shiny application for matching seed sources with restoration sites. Plant populations are commonly adapted to local climate gradients and frequently exhibit a home-site advantage. For this reason, climate information may serve as a proxy for local adaptation in restoration designs. Climate Distance Mapper allows users to rank the suitability of seed sources for restoration sites by displaying multivariate climate distances (incorporating climate principal components) from user-supplied input points to the surrounding landscape. The application provides functions to match seed sources with current or future climate, guide sampling effort for large scale seed collections, and partition the landscape into suitable areas for different seed sources. 
These data support the following publication:
Shryock, D.F., DeFalco, L.A., and T.C. Esque. 2018. Spatial decision-support tools to guide restoration and seed sourcing in the Desert Southwest. Ecosphere 9(10):e02453.

Tags: arizona, atmospheric-and-climatic-processes, california, climatologymeteorologyatmosphere, colorado, colorado-plateau, geospatial-analysis, great-basin, mojave-desert, nevada, new-mexico, precipitation, sonoran-desert, united-states, usgs-5d670543e4b0c4f70cf1046a, utah
Organization: Department of the Interior
Yellowstone Lake Vemco Positioning System 2012-2016

These data show triangulated results from Vemco Positioning Systems (VPS; https://vemco.com/products/vps/) set in Yellowstone Lake, WY. The data consist of transmissions from acoustic transmitters placed in fish to 69 kHz receivers. Field data were sent to Vemco for processing (proprietary software) and processed to determine the triangluated results shared within this data set. The data provided show triangulated positions of Lake Trout within suspected spawaning locations in Yellowstone Lake.  Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Tags: biota, ecology, fish, telemetry, usgs-5d66f818e4b0c4f70cf0cfbd, wyoming, yellowstone-national-park
Organization: Department of the Interior
Felsenthal National Wildlife Refuge green-tree reservoir 2016 forest plot measurements

A green-tree reservoir (GTR) is a stand of bottomland hardwoods that is intentionally flooded in the fall and winter to support migrating waterfowl. Bottomland hardwood forest plots in the GTR on Felsenthal National Wildlife Refuge (FNWR) are measured every 5-6 years to monitor tree survival, growth, and mortality. This dataset presents the measurements of all the trees in 54 plots during the year 2016. Parameters measured are species, diameter, vigor class, canopy class, whether or not the tree is a new recruit in 2016, whether the tree is a tip-up (windthrow) or a gap tree in 2016, and whether Hypoxylon canker fungus is present on the tree in 2016. These parameters are defined in the Entity and Attributes section of this metadata file.

Tags: arkansas, biota, bottomland-hardwoods, environment, felsenthal-national-wildlife-refuge, forest-ecosystems, green-tree-reservoir, greentree-reservoir, long-term-ecological-monitoring, plot-sampling, usgs-5d66d656e4b0c4f70cf06470, wetland-ecosystems
Organization: Department of the Interior
Felsenthal National Wildlife Refuge green-tree reservoir 2011 forest plot measurements

A green-tree reservoir (GTR) is a stand of bottomland hardwoods that is intentionally flooded in the fall and winter to support migrating waterfowl. Bottomland hardwood forest plots in the GTR on Felsenthal National Wildlife Refuge (FNWR) are measured every 5-6 years to monitor tree survival, growth, and mortality. This dataset presents the measurements of all the trees in 54 plots during the year 2011. Parameters measured are species, diameter, vigor class, canopy class, whether or not the tree is a new recruit in 2011, and whether the tree is a tip-up (windthrow) or a gap tree in 2011. These parameters are defined in the Entity and Attributes section of this metadata file.

Tags: arkansas, biota, bottomland-hardwoods, environment, felsenthal-national-wildlife-refuge, forest-ecosystems, green-tree-reservoir, greentree-reservoir, long-term-ecological-monitoring, plot-sampling, usgs-5d66d503e4b0c4f70cf061bc, wetland-ecosystems
Organization: Department of the Interior
Felsenthal National Wildlife Refuge green-tree reservoir 2006 forest plot measurements

A green-tree reservoir (GTR) is a stand of bottomland hardwoods that is intentionally flooded in the fall and winter to support migrating waterfowl. Bottomland hardwood forest plots in the GTR on Felsenthal National Wildlife Refuge (FNWR) are measured every 5-6 years to monitor tree survival, growth, and mortality. This dataset presents the measurements of all the trees in 54 plots during the year 2006. Parameters measured are species, diameter, vigor class, canopy class, and whether or not the tree is a new recruit in 2006. These parameters are defined in the Entity and Attributes section of this metadata file.

Tags: arkansas, biota, bottomland-hardwoods, environment, felsenthal-national-wildlife-refuge, forest-ecosystems, green-tree-reservoir, greentree-reservoir, long-term-ecological-monitoring, plot-sampling, usgs-5d66d465e4b0c4f70cf05b8a, wetland-ecosystems
Organization: Department of the Interior
Felsenthal National Wildlife Refuge green-tree reservoir 1995 forest plot measurements

A green-tree reservoir (GTR) is a stand of bottomland hardwoods that is intentionally flooded in the fall and winter to support migrating waterfowl. Bottomland hardwood forest plots in the GTR on Felsenthal National Wildlife Refuge (FNWR) are measured every 5-6 years to monitor tree survival, growth, and mortality. This dataset presents the measurements of all the trees in 54 plots during the year 1995. Parameters measured are species, diameter, vigor class, canopy class, and whether or not the tree is a new recruit in 1995. These parameters are defined in the Entity and Attributes section of this metadata file.

Tags: arkansas, biota, bottomland-hardwoods, environment, felsenthal-national-wildlife-refuge, forest-ecosystems, green-tree-reservoir, greentree-reservoir, long-term-ecological-monitoring, plot-sampling, usgs-5d66d04fe4b0c4f70cf03eae, wetland-ecosystems
Organization: Department of the Interior
Felsenthal National Wildlife Refuge green-tree reservoir 1990 forest plot measurements

A green-tree reservoir (GTR) is a stand of bottomland hardwoods that is intentionally flooded in the fall and winter to support migrating waterfowl. Bottomland hardwood forest plots in the GTR on Felsenthal National Wildlife Refuge (FNWR) are measured every 5-6 years to monitor tree survival, growth, and mortality. This dataset presents the measurements of all the trees in 54 plots during the year 1990. Parameters measured are species, diameter, vigor class, and canopy class. These parameters are defined in the Entity and Attributes section of this metadata file.

Tags: arkansas, biota, bottomland-hardwoods, environment, felsenthal-national-wildlife-refuge, forest-ecosystems, green-tree-reservoir, greentree-reservoir, long-term-ecological-monitoring, plot-sampling, usgs-5d66cbcce4b0c4f70cf0176e, wetland-ecosystems
Organization: Department of the Interior