AndreaBozzo/ceres-open-data-index huggingface dataset:
Depth rasters in aquifers of the Mississippi embayment

Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including specific conductance (SC), total dissolved solids (TDS), and chloride (Cl) concentrations—across three drinking-water aquifers of the Mississippi embayment. A ML approach was used because it accommodates a large and diverse set of explanatory variables, does not assume monotonic relations between predictors and response data, and results can be extrapolated to areas of the aquifer not sampled. These aspects of ML allowed potential drivers and sources of high salinity water that have been hypothesized in other studies to be included as explanatory variables. The ML approach integrated output from a groundwater-flow model and water-quality data to predict salinity, and the approach can be applied to other aquifers to provide context for the long-term availability of groundwater resources.
The Mississippi embayment includes two principal regional aquifer systems; the surficial aquifer system, dominated by the Quaternary Mississippi River Valley Alluvial aquifer (MRVA), and the Mississippi embayment aquifer system, which includes deeper Tertiary aquifers and confining units. Based on the distribution of groundwater use for drinking water, the modeling focused on the MRVA, middle Claiborne aquifer (MCAQ), and lower Claiborne aquifer (LCAQ). Boosted regression tree (BRT) models (Elith and others, 2008; Kuhn and Johnson, 2013) were developed to predict SC and Cl to 1-kilometer (km) raster grid cells of the National Hydrologic Grid (Clark and others, 2018) for 7 aquifer layers (1 MRVA, 4 MCAQ, 2 LCAQ) following the hydrogeologic framework of Hart and others (2008). TDS maps were created using the correlation between SC and TDS. Explanatory variables for the BRT models included attributes associated with well location and construction, surficial variables (such as soils and land use), and variables extracted from a MODFLOW groundwater flow model for the Mississippi embayment (Haugh and others, 2020a; Haugh and others, 2020b). Prediction intervals were calculated for SC and Cl by bootstrapping raster-cell predictions following methods from Ransom and others (2017). For a full description of modeling workflow and final model selection see Knierim and others (2020).

Tags: alabama, aquifer, arkansas, boosted-regression-tree, groundwater, groundwater-quality, illinois, kentucky, louisiana, machine-learning, mathematical-modeling, mississippi, tennessee, usgs-5df7ef29e4b0cdded7393f97
Organization: Department of the Interior
Lake Ontario Nearshore Nutrient Study (LONNS), 2018, Lake Ontario, New York

From April through September of 2018, water-quality data were collected at 35 locations from select tributaries, embayments, and nearshore lake locations along New York's portion of Lake Ontario in support of the 2018 Cooperative Science and Monitoring Initiative, the Great Lakes Restoration Initiative, and the Lakewide Action Management Plan. 
These data include environmental, replicate, and blank samples of nutrients, suspended solids, sodium, and chloride, as well as field measurements of physical parameters (temperature, specific conductance, dissolved oxygen, pH, turbidity, phycocyanin relative fluorescence, chlorophyll relative fluorescence, photosynthetically active radiation, and phycocyanin:cholorphyll ratio).

Tags: cayuga-county, jefferson-county, lake-ontario, monroe-county, new-york, niagara-county, nutrients, orleans-county, oswego-county, united-states, usgs-5df7a8d6e4b0cdded7393e55, water-quality, wayne-county
Organization: Department of the Interior
Prediction grids of pH for the Mississippi River Valley Alluvial and Claiborne Aquifers

Groundwater is a vital resource to the Mississippi embayment region of the central United States. Regional and integrated assessments of water availability that link physical flow models and water quality in principal aquifer systems provide context for the long-term availability of these water resources. An innovative approach using machine learning was employed to predict groundwater pH across drinking water aquifers of the Mississippi embayment. The region includes two principal regional aquifer systems; the Mississippi River Valley alluvial (MRVA) aquifer and the Mississippi embayment aquifer system that includes several regional aquifers and confining units. Based on the distribution of groundwater use for drinking water, the modeling effort was focused on the MRVA, Middle Claiborne aquifer (MCAQ), and Lower Claiborne aquifer (LCAQ)of the Mississippi embayment aquifer system. Boosted regression tree (BRT) models (Elith and others, 2008; Kuhn and Johnson, 2013) were used to predict pH to 1-km raster grid cells of the National Hydrologic Grid (Clark and others, 2018). Predictions were made for 7 aquifer layers (1 MRVA, 4 MCAQ, 2 LCAQ) following the hydrogeologic framework used in a regional groundwater flow model (Hart and others, 2008). Explanatory variables for the BRT models included attributes associated with well position and construction, surficial variables, and variables extracted from a MODFLOW groundwater flow model for the MISE (Haugh and others, 2020a,b). For a full description of modeling workflow see Knierim and others (2020).

Tags: alabama, aquifer, arkansas, boosted-regression-tree, groundwater, groundwater-quality, kentucky, louisiana, machine-learning, mathematical-modeling, mississippi, tennessee, usgs-5e30b337e4b0a79317d627b1
Organization: Department of the Interior
Meteorological measurements from five locations within the Badger Wash study area near Mack, Colorado (ver. 3.0, September 2024)

These data are records collected from an automated weather station and four stand-alone tipping bucket rain gauges each with their own data logger that were in operation between February 2005 and December 2023 in the Badger Wash Study Area near Mack, Colorado as part of a larger project funded by the Bureau of Land Management. These files are hourly-interval data from the automated weather station with meteorological parameters of air temperature, relative humidity, wind speed, wind direction, wind gusts, photon flux density and rainfall as well as from a soil pit with temperature and soil moisture measurements at 5, 10, 20, 40, 60, 80 and 100 cm deep. The standalone tipping-bucket rain gauge data which records the time of each tip were processed to mimic the hourly interval records of the automated weather station and included rain intensity parameters as well. A separate table created by the data logger in the automated weather station recorded the time of each tip of the its tipping bucket rain gauge those data were processed in the same way as for the standalone tipping buckets. The Badger Wash study area contains paired grazed and ungrazed watersheds which were originally studied from 1954 to 1965 (Lusby 1979). Data collection was conducted using automated weather stations physically visited and maintained by scientists from the Southwest Biological Science Center. These data span the time period from 2005 through 2023.

Tags: air-temperature, badger-wash, badger-wash-met-station, badger-wash-study-area, bureau-of-land-management, climatologymeteorologyatmosphere, colorado, elevation, field-inventory-and-monitoring, land-ownership, leaf-wetness, mack, mesa-county, meteorology, meterological-measurements, micrometeorological-conditions, plot-data, precipitation, precipitation-atmospheric, precipitation-measurement, rain, rain-gauges, rain-intensity, rainfall-measurement, relative-humidity, soil-temperature, topography, usgs-5df7a102e4b0cdded7393e38, volumetric-water-content, water-content, watershed, weather, weather-observations, weather-station, wind, wind-direction, wind-speed
Organization: Department of the Interior
Estimated Wastewater Returns for the Coastal Carolinas Focus Area Study by Soil Water Assessment Tool Model Catchment Area, 2000, 2005, 2010, and 2015

The Pee Dee and Cape Fear River Basins in North Carolina and South Carolina were chosen as a focus area study (FAS) for the U.S. Geological Survey (USGS) National Water Census (NWC) in 2016. The objective of the NWC is to place technical information and tools in the hands of stake holders so that they can make decisions on water availability. The USGS South Atlantic Water Science Center, comprised of North Carolina, South Carolina, and Georgia, conducted a 3-year study of water use and availability to provide information related to the competing societal and ecological water needs in the Southeastern Atlantic Coastal Basins of the Carolinas. One task to meet this objective was compiling water withdrawal and return data by category from local, regional, and state-scale data sources so that those data could be utilized in surface-water models, a groundwater model, an ecological flow model, and for predictions of future water needs. This dataset presents wastewater-return estimates from years 2000, 2005, 2010, and 2015 which are aggregated to the Soil and Water Assessment Tool (SWAT) model catchment-area level developed for the Pee Dee and Cape Fear River Basins.

Tags: cape-fear-river, catchment, georgetown-sc, jacksonville-nc, modeling, nc, north-carolina, pee-dee-river, sc, south-carolina, subbasin, surface-water, swat, the-soil-and-water-assessment-tool, usgs-5df3f032e4b0cdded7372b2f, waccamaw-river, wastewater, wastewater-return, water-use, watershed, yadkin-river
Organization: Department of the Interior
Video data for trout abundance estimation

Rapid advances in video technology are enabling new strategies for species abundance estimation. Here we provide estimates of fish abundance derived from video data collected in a series of stream pools in Shenandoah National Park, Virginia (n=41). Two 360-degree cameras were simultaneously used at each pool site where 15-minutes of underwater footage was collected. Environmental data are provided describing pool morphology, canopy cover, and fish cover (boulders, large woody debris, and undercut banks).

Tags: aquatic-biology, field-sampling, freshwater-ecosystems, usgs-5e31d5e6e4b0a79317d80454, videography
Organization: Department of the Interior
Hawaii Volcanoes National Park Plant Trait, Percent Cover, and Environmental Data 2014

This data release includes data and metadata on 1) the coverage and composition of plants 2) species specific plant traits 3) sampling locations and 4) environmental data. All sites were within Hawaii Volcanoes National Park on Hawaii Island. Plant cover data were obtained from National Park Service Inventory and Monitoring Program. Plant trait data was collected for these plots in 2014. This study aims to evaluate how traits of native and exotic plant species change along environmental gradients and what this suggests for plant competition and invasion.

Tags: botany, bryophyte, ecology, forest-resources, forest-restoration, hawaii, hawaii-volcanoes-national-park, invasive-species, plant-ecology, seedling-recruitment, tropical-forest-dynamics, usgs-5dfad9fbe4b0b5e61c0534bc
Organization: Department of the Interior
Estimated Surface-Water Withdrawals for the Coastal Carolinas Focus Area Study by Soil Water Assessment Tool Model Catchment Area, Year, and Water-Use Category, 1983 - 2017

The Cape Fear and Pee Dee River Basins in North Carolina and South Carolina were chosen as a focus area study (FAS) for the U.S. Geological Survey (USGS) National Water Census (NWC) in 2016. The objective of the NWC is to place technical information and tools in the hands of stake holders so that they can make decisions on water availability. The USGS South Atlantic Water Science Center, comprised of North Carolina, South Carolina, and Georgia, conducted a 3-year study of water use and availability to provide information related to the competing societal and ecological water needs in the Southeastern Atlantic Coastal Basins of the Carolinas. One task to meet this objective was compiling water withdrawal and return data by water-use category from local, regional, and state-scale data sources and utilizing those data in Surface-water models, a Groundwater model, an Ecological flow model, and for predictions of future water needs. This data release presents surface-water withdrawals for the Pee Dee and Cape Fear HUC4 river basins in North and South Carolina.

Tags: cape-fear-river, catchment, georgetown-sc, huc4, jacksonville-nc, modeling, nc, north-carolina, pee-dee-river, sc, south-carolina, subregion, surface-water, swat, the-soil-and-water-assessment-tool, usgs-5df3efcbe4b0cdded7372b2d, waccamaw-river, water-use, water-use-category, watershed, yadkin-river
Organization: Department of the Interior
Estimated Groundwater Withdrawals for the Coastal Carolinas Focus Area Study by MODFLOW Model-Cell Area, Year, and Water-Use Category, 1974 - 2015

The coastal region which includes areas within the Pee Dee, Cape Fear, and Neuse-Pamlico River Basins in South Carolina and North Carolina was chosen as a focus area study (FAS) for the U.S. Geological Survey (USGS) National Water Census (NWC) in 2016. The objective of the NWC is to place technical information and tools in the hands of stake holders so that they can make informed decisions on water availability. The USGS South Atlantic Water Science Center, comprised of North Carolina, South Carolina, and Georgia, conducted a 3-year study of water use and availability, climate change, and population growth to provide information related to the competing societal and ecological water needs in the Southeastern Atlantic Coastal Basins of the Carolinas. One task to meet this objective was compiling water withdrawal and return data and other water use information from local, regional, and state-scale data sources. This information was used to develop water-use estimates used in a surface-water model, a groundwater model, and an ecological flow model. The simulations produced by these models were subsequently used to make predictions about future water availability and needs in the Coastal Carolina study area. This data release presents groundwater-withdrawals for Georgia, South Carolina, and North Carolina within the Atlantic Coastal Plain.

Tags: atlantic-coastal-plain, brunswick-georgia, ga, georgia, greenville-north-carolina, ground-water, groundwater, model-cell, modflow-2000, nc, north-carolina, sc, south-carolina, usgs-5df3ef81e4b0cdded7372b2a, water-use
Organization: Department of the Interior
Estimated Use of Water for Coastal Carolinas Focus Area Study

The Cape Fear and Pee Dee River Basins in North Carolina and South Carolina were chosen as a focus area study (FAS) for the U.S. Geological Survey (USGS) National Water Census (NWC) in 2016. The objective of the NWC is to place technical information and tools in the hands of stake holders so that they can make decisions on water availability. The USGS South Atlantic Water Science Center, comprised of North Carolina, South Carolina, and Georgia, conducted a 3-year study of water use and availability to provide information related to the competing societal and ecological water needs in the Southeastern Atlantic Coastal Basins of the Carolinas. The Coastal Carolinas study area includes the Pee Dee and Cape Fear River Basins and the Atlantic Coastal Plain from Brunswick, Georgia, to near Greenville, North Carolina. The study is divided into 5 main components: 1) Societal Water-Use Data Compilation and Refinement, 2) Land-Use, Population, Water-Use and Climate Change Scenarios, 3) Surface-Water Modeling, 4) Ecological Response Modeling, and 5) Groundwater Modeling. One task to meet this objective was to compile water withdrawal and return data by water-use category from local, regional, and state-scale data sources in order to utilize those data in surface-water models, a groundwater model, an ecological flow model, and for predictions of future water needs.
This data release contains (1) Groundwater withdrawals for Georgia, South Carolina, and North Carolina aggregated by groundwater MODFLOW model cell area, year, and water-use category; (2) Surface-water withdrawal estimates for years 1983 – 2017 aggregated to the Soil and Water Assessment (SWAT) model catchment level developed for the Pee Dee and Cape Fear River Basins; (3) Wastewater return estimates from years 2000, 2005, 2010, and 2015 aggregated to the Soil and Water Assessment (SWAT) model catchment level developed for the Pee Dee and Cape Fear River Basins; and (4) Surface-water and groundwater off-stream water-use estimates in the Coastal Carolinas study area for selected water-use categories from years 2000, 2005, 2010, and 2015 aggregated to the 8-digit (subbasin) hydrologic unit level within state boundaries in the Coastal Carolinas study area.

Tags: atlantic-coastal-plain, biota, cape-fear, georgia, ground-water, groundwater, huc8, hydrologic-unit-code, north-carolina, pee-dee, south-carolina, surface-water, usgs-5df3eed1e4b0cdded7372b26, wastewater-return, water-use, withdrawal
Organization: Department of the Interior
Mean annual water-budget components for the Island of Maui, Hawaii, for a set of eight future climate and land-cover scenarios

These shapefiles represent the spatial distribution of mean annual water-budget components, in inches, for the Island of Maui, Hawaii for a set of eight future climate and land-cover scenarios. The future climate conditions used in the water-budget analyses were derived from two end-of-century downscaled climate projections including (1) a projected future climate condition representative of phase 3 of the Coupled Model Intercomparison Project (CMIP3) A1B 2080-99 scenario climate described in Zhang and others (2016a, 2016b) and (2) a projected future climate condition representative of phase 5 of the Coupled Model Intercomparison Project (CMIP5) Representative Concentration Pathway 8.5 (RCP8.5) 2080-99 scenario climate described in Elison Timm and others (2015). The four future land-cover scenarios developed by Brewington (2018) were used to define the land-cover conditions and model subareas. A unique set of water-budget components for each model subarea was computed for each combination of projected climate conditions and future land-cover using a water-budget model developed by Johnson and others (2018) and later modified by Mair and others (2019). The shapefile attribute information associated with each subarea (or polygon) present an estimate of mean annual rainfall, fog interception, irrigation, septic system leachate, seepage from reservoirs and cesspools, runoff, canopy evaporation, total evapotranspiration, and total recharge. These shapefiles also include select geographic and land-cover attributes of the model subareas. Brief descriptions of the water-budget components and attributes are included in this metadata file. Refer to Mair and others (2019) and Brewington and others (2019) for further details of the methods and sources used to determine these components and attributes.

Tags: canopy-evaporation, cesspool-seepage, direct-recharge, effects-of-climate-change, evaporation, fog-interception, groundwater, hawaii, inlandwaters, irrigation, land-use-change, maui, net-precipitation, pacific-islands, precipitation-atmospheric, recharge, reservoir-seepage, runoff, septic-system-leachate, total-evapotranspiration, transpiration, usgs-5df3db3de4b02caea0fbf2ba, water-budget, water-budget-model, water-cycle
Organization: Department of the Interior
PCR results from dreissenid mussel round robin assay analyses, 2018-2019

Real-time PCR results of a round robin evaluation of 5 assays that target dreissenid mussel DNA. Water samples collected from waters with and without dreissenid mussels were analyzed using these five assays in four USGS laboratories.  Samples from waters without dreissenid mussels were spiked with known amounts of dreissend DNA.

Tags: biota, california, environment, environmental-dna, invasive-species, jackson-lake, lake-mead, lake-michigan, lower-columbia, molecular-biology, new-york, upper-columbia, upper-yellowstone, usgs-5df2ab72e4b02caea0f95b47
Organization: Department of the Interior
Hawaii Island forest bird response to simulated nest predator 2015-2016

Hawaii forest birds nesting in Hakalau Forest National Wildlife Refuge were exposed to models of predators near their nests to measure behavioral responses. Responses to potential nest predators included vocalization rate, movement behavior, and nestling feeding. Predators were inert stick, introduced but abundant predator, a rat, and a novel predator, a snake, that does not occur on Hawaii.

Tags: biota, hawaii-forest-birds, nest-predation, usgs-5df2a595e4b02caea0f95b22
Organization: Department of the Interior
Landscape inputs and simulation output for the LANDIS-II model in the Greater Yellowstone Ecosystem

This data release provides inputs needed to run the LANDIS-II landscape change model, NECN and Base Fire extensions for the Greater Yellowstone Ecosystem (GYE), USA, and simulation results that underlie figures and analysis in the accompanying publication.  We ran LANDIS-II simulations for 112 years, from 1988-2100, using interpolated weather station data for 1988-2015 and downscaled output from 5 general circulation models (GCMs) for 2016-2100.  We also included a control future scenario with years drawn from interpolated weather station data from 1980-2015.  Model inputs include raster maps (250 × 250 m grid cells) of climate regions and tables of monthly temperature and precipitation for each climate region.  We provide initial conditions in 1987 as rasters and tables (i.e., species-age cohorts, aboveground biomass, soil carbon and nitrogen in surface litter 3 soil layers, soil percent sand, soil percent clay, soil wilting point, soil field capacity, soil drainage, soil storm flow and base flow fractions, and soil depth), historical fire data for model calibration, climate-inferred lognormal fire size distributions for each simulation year, and LANDIS-II control files including parameters for species and functional groups.  Outputs from 10 replicates for each of 5 GCMs and the control scenario are provided as rasters and tables.  Tables include spatially-weighted mean annual temperature and precipitation of the GYE for each GCM and the control scenario, summarize annual area burned by scenario, summarize biomass pools, and summarize changes in mean stand age.  Rasters include annual simulated fire severity for 2015-2100, simulated total aboveground biomass in 4-year timesteps, aboveground biomass of all species in 4-year timesteps, stand age in 4-year timesteps, maximum and minimum cohort age for three dominant species (Pinus contorta, Picea engelmannii, and Pseudotsuga menziesii) in 4-year timesteps, forest type in 1988 and 2100, net ecosystem exchange in 2040 and 2100, and total ecosystem carbon in 4-year timesteps.

Tags: aboveground-forest-biomass, ecosystem-carbon, forest-ecosystems, general-circulation-models, greater-yellowstone-ecoystem, idaho-usa, landis-ii, landsat, landscape-change-model, montana-usa, pinus-contorta, pseudotsuga-menziesii, rocky-mountains, usgs-5df294c8e4b02caea0f95add, vegetation-imputation, wildfire, wyoming-usa, yellowstone-national-park
Organization: Department of the Interior