AndreaBozzo/ceres-open-data-index huggingface dataset:
R script to create boxplots of change factors by NOAA Atlas 14 station, or for all stations in a Florida HUC-8 basin or county (create_boxplot.R)

The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the periods 2020-59 (centered in the year 2040) and 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period.  
An R script (create_boxplot.R) is provided which generates boxplots of change factors for a NOAA Atlas 14 station, or for all NOAA Atlas 14 stations in a Florida HUC-8 basin or county for durations of interest (1, 3, and 7 days, or combinations thereof) and return periods of interest (5, 10, 25, 50, 100, 200, and 500 years, or combinations thereof). The user also has the option of requesting that the script save the raw change factor data used to generate the boxplots, as well as the processed quantile and outlier data shown in the figure. The script allows the user to modify the percentiles used in generating the boxplots. A Microsoft Word file documenting code usage and available options is also provided within this data release (Documentation_R_script_create_boxplot.docx). As described in the documentation, the R script relies on some of the Microsoft Excel spreadsheets published as part of this data release.
The script uses basins defined in the "Florida Hydrologic Unit Code (HUC) Basins (areas)" from the Florida Department of Environmental Protection (FDEP;  https://geodata.dep.state.fl.us/datasets/FDEP::florida-hydrologic-unit-code-huc-basins-areas/explore) and their names are listed in the file basins_list.txt provided with the script. County names are listed in the file counties_list.txt provided with the script. NOAA Atlas 14 stations located in each Florida HUC-8 basin or county are defined in the Microsoft Excel spreadsheet Datasets_station_information.xlsx which is part of this data release. Instructions are provided in code documentation (see highlighted text on page 7 of Documentation_R_script_create_boxplot.docx) so that users can modify the script to generate boxplots for basins different from the FDEP "lorida Hydrologic Unit Code (HUC) Basins (areas).

Tags: climatologymeteorologyatmosphere, depth-duration-frequency, extremes, florida, florida-flood-hub-for-applied-research-and-innovation, precipitation-atmospheric, precipitation-extremes, usgs-64a2e6f8d34ef77fcb056b9a
Organization: Department of the Interior
Documentation of R scripts to create boxplots of change factors by NOAA Atlas 14 station, or for all stations in a Florida HUC-8 basin or county (Documentation_R_script_create_boxplot.docx)

The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the periods 2020-59 (centered in the year 2040) and 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period.   
An R script (create_boxplot.R) is provided which generates boxplots of change factors by NOAA Atlas 14 station, or for all NOAA Atlas 14 stations in a Florida HUC-8 basin or county. In addition, the R script basin_boxplot.R is provided as an example on how to create a wrapper function that will automate the generation of boxplots of change factors for all Florida HUC-8 basins. This Microsoft Word file (Documentation_R_script_create_boxplot.docx) serves as documentation on the code usage and available options for running the scripts. As described in the documentation, the R scripts rely on some of the Microsoft Excel spreadsheets published as part of this data release.
The script uses basins defined in the "Florida Hydrologic Unit Code (HUC) Basins (areas)" from the Florida Department of Environmental Protection (FDEP; https://geodata.dep.state.fl.us/datasets/FDEP::florida-hydrologic-unit-code-huc-basins-areas/explore) and their names are listed in the file basins_list.txt provided with the script. County names are listed in the file counties_list.txt provided with the script. NOAA Atlas 14 stations located in each Florida HUC-8 basin or county are defined in the Microsoft Excel spreadsheet Datasets_station_information.xlsx which is part of this data release. Instructions are provided in code documentation (see highlighted text on page 7 of Documentation_R_script_create_boxplot.docx) so that users can modify the script to generate boxplots for basins different from the FDEP "Florida Hydrologic Unit Code (HUC) Basins (areas)."

Tags: climatologymeteorologyatmosphere, depth-duration-frequency, extremes, florida, florida-flood-hub-for-applied-research-and-innovation, precipitation-atmospheric, precipitation-extremes, usgs-64a2e746d34ef77fcb056b9d
Organization: Department of the Interior
Shapefile of NOAA Atlas 14 stations in Florida (Atlas14_stations.shp)

The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in 2040) or to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period.  
Geospatial data provided in an ArcGIS shapefile are described herein. The shapefile shows the locations of NOAA Atlas 14 stations in Florida for which depth-duration-frequency curves and change factors of precipitation depths were developed as part of this project. For more information about the stations, see Table 1 of Datasets_station_information.xlsx.

Tags: basins, boundaries, florida, florida-flood-hub-for-applied-research-and-innovation, hydrography, nexrad, rain, rain-areas, rainarea, rainareas, usgs-64a2e8e7d34ef77fcb056baf
Organization: Department of the Interior
Polycyclic aromatic hydrocarbon concentrations in soil, sediment, vegetation, and water samples collected from the Arctic National Wildlife Refuge during Summer 2019

This data set documents results of analysis of samples collected from the Arctic National Wildlife Refuge during Summer 2019. Data tables include: 1. The numeric and alphanumeric identifiers for samples collected for this study and the dates these samples were collected; 2. Results data containing concentration values of individual polycyclic aromatic hydrocarbon compounds in sediment, soil, and vegetation samples; 3. Results data containing concentration values of individual PAH compounds in water samples; 4. Results data containing concentration values of individual polycyclic aromatic hydrocarbon compounds in quality-control sample blanks for all four sample matrices (sediment, soil, vegetation, water); 5. Results data containing mass values of individual polycyclic aromatic hydrocarbon compounds detected in quality-control procedural spiked and purified water spiked samples that were spiked with mixture of polycyclic aromatic hydrocarbon compounds; 6. Results data containing concentration values of individual polycyclic aromatic hydrocarbon compounds in sediment, soil, and vegetation samples subsampled in triplicate; 7. Results data containing percent recovery values of deuterated polycyclic aromatic hydrocarbon surrogate compounds spiked into all processed samples at the beginning of the sample preparation procedure as a measure to determine recovery of targeted polycyclic aromatic hydrocarbon compounds subjected to the sample preparation procedure

Tags: arctic-national-wildlife-refuge, biota, columbia-environmental-research-center, contamination-and-pollution, mass-spectroscopy, polycyclic-aromatic-hydrocarbons, usgs-64a2f805d34ef77fcb056c0b
Organization: Department of the Interior
Estimated crop irrigation water use withdrawals in Willcox Groundwater Basin, Arizona for 2022

Observations of irrigated agricultural land within the Willcox Groundwater Basin in Arizona. Digitized field boundaries were used to locate crops for in situ verification twice in 2022; crop verification occurred first on May 17th and again on August 26th. Field boundaries were digitized from U.S. Department of Agriculture, National Agricultural Imagery Program County Mosaic 2021 imagery for Arizona and supplemented with Landsat and Sentinel2 imagery collections accessed via the Sentinel Hub, Sentinel Playground (https://apps.sentinel-hub.com/sentinel-playground). Satellite images were also used to identify the length of the growing season and crop condition. Water withdrawals were calculated using the modified Blaney-Criddle model of calculating consumptive use (U.S. Bureau of Reclamation, 1992 appendix A) using crop coefficients from Doorenbos and Pruitt (1975), the number of acres with active crops, crop condition, and irrigation system efficiency. The withdrawal equation was modified from "Water withdrawals for irrigation, municipal, mining, thermoelectric-power, and drainage uses in Arizona outside of active management areas, 1991-2000" (Tadayon, 2005) to account for variations in water application.

Tags: agricultural-sites, arizona, cochise, graham, groundwater, irrigation, usgs-64a32d17d34ef77fcb0570ba, water-use, willcox-groundwater-basin
Organization: Department of the Interior
Compilation of total dissolved solids concentrations and specific conductance measurements in the Upper Colorado River Basin, 1894 – 2022

This data release contains total dissolved solids (TDS) concentrations and specific conductance (SC) measurements collected at surface-water monitoring locations and groundwater monitoring wells within the Upper Colorado River Basin (UCRB) between 1894 and 2022. Discrete TDS and SC results were obtained from the Water Quality Portal (WQP). Continuous SC monitoring results were obtained from the USGS National Water Information System (NWIS). The data set includes 127,294 TDS results that were collected at 12,339 sites between 1900 and 2022, and 705,918 SC results that were collected at 19,630 sites between 1894 and 2022. The SC results represented 244,784 discrete measurements at 19,625 sites and 461,134 mean daily values from continuous monitoring at 193 sites. The data retrieved from the WQP were harmonized to create a standardized and readily usable dataset. The harmonization process included the synthesis of parameter names and fractions, the reconciliation of remarks and other data qualifiers, the resolution of duplicate records, and basic checks of the data quality. The harmonized results at 230 sites were selected for additional data processing because those sites were potential calibration targets for TDS watershed modeling for the UCRB using the USGS Spatially Referenced Regression on Watershed attributes (SPARROW) model. The 230 sites met the minimum criteria for the number and seasonal distribution of samples, the length of the sampling period, and the amount of overlap with the streamflow record at a nearby gage. The measured TDS concentrations at those sites were supplemented with estimated TDS concentrations that were determined from relations between measured TDS and SC results within the UCRB. A site-specific regression of TDS on SC was used to estimate TDS from SC at 143 sites, while a regional conversion factor between TDS and SC was used to estimate TDS from SC at 87 sites. The final TDS data for the 230 sites included 50,003 measured values from the WQP, 378,147 values estimated using the equation from a site-specific regression of TDS on SC (with 350,840 based on mean daily SC values), and 30,880 values estimated using a regional median ratio between TDS and SC.

Tags: arizona, colorado, environment, groundwater-quality, hydrology, inlandwaters, new-mexico, salinity, surface-water-quality, upper-colorado-river-basin, usgs-64a361d5d34ef77fcb0574fc, utah, water-chemistry, wyoming
Organization: Department of the Interior
Russian River Integrated Hydrologic Model (RRIHM): Rubber Dam Observations

This dataset provides a flow accumulation raster for the stream network. It displays the accumulated weight of all cells flowing into each downslope cell in a raster. The flow accumulation raster was generated using a flow direction raster, which was created from an elevation raster.

Tags: california, environment, groundwater, groundwater-and-surface-water-interaction, groundwater-level, hydrology, modeling, precipitation, russian-river, streamflow, surface-water-non-marine, united-states, usgs-64a38024d34ef77fcb0578f6, water-resources
Organization: Department of the Interior
Scanning electron microscopy data from sediments collected in ephemeral channels, Four Corners region, USA, 2021-2022

The San Juan River is a major water source for communities in the Four Corners region of the United States (parts of Colorado, Arizona, New Mexico, Utah) and is a vital source of water for the Navajo Nation. The Navajo Nation Environmental Protection Agency (NNEPA) periodically samples surface water on the Navajo Nation and has found that some elements exceed NNEPA surface water standards (the upper limits of an element for consumption or other use of water). Constituents of concern are substances that could be harmful if present in sufficient quantities, and it is important to monitor the concentrations of these substances in the environment. In the San Juan River, constituents of concern include metals detected in river water, such as arsenic, lead, and aluminum. These metals can come from natural sources or can result from anthropogenic (human) activities and can affect the health of people, plants, and animals.  The U.S. Geological Survey (USGS) is working with the NNEPA to identify sources of metals and trace elements entering the San Juan River from tributaries in the reach flowing through the Navajo Nation, and to quantify the contribution from each natural and human-caused source.
Sediments were collected in sediment traps in 33 ephemeral or perennial channels that flow into the San Juan River.  The sediment traps were placed in the apparent thalweg of the channel, and attached to a T-post.  Sites were checked every 2 to 3 weeks and sediment traps were collected if material accumulated.  If the traps were empty, they were left deployed.  The sediment traps filled during storm events.  This data release contains sediment electron microscopy back scatter images and energy-dispersive X-ray spectroscopy (EDS) spectra to identify general chemistry, mineralogy, and grain size from sediments mobilized during high-flow events in the tributaries to the San Juan River. Images and EDS spectra from four locations at 33 sample sites and a sample database file are included.  The database file includes the name of each site, names of associated images, grain size and rounding, and elements identified in each image.  Images are provided in .zip folders by sample location.

Tags: arizona, biota, colorado, four-corners, geochemistry, mineralogy, new-mexico, scanning-electron-microscopy, usgs-64a59bd5d34ef77fcb06203c, utah
Organization: Department of the Interior
Brewer's sparrow distribution in the Wyoming Basins Ecoregional Assessment area

Map of Brewer's sparrow distribution developed from an abundance map created using multi-scale vegetation, abiotic, and anthropogenic features.

Tags: biota, brewers-sparrow, colorado, distribution, environment, environment-and-conservation, geoscientificinformation, geospatial-datasets, idaho, modeling, montana, scientific-interpretation, shrubland-ecosystems, united-states, usgs-64a5f0a1d34ef77fcb062553, utah, wyoming
Organization: Department of the Interior
Russian River Integrated Hydrologic Model (RRIHM):  Agricultural Direct Diversion

This dataset provides a shapefile of surface water diversions directly to agricultural fields in the Russian River Coupled Groundwater and Surface-Water Flow Model (GSFLOW) model.

Tags: california, environment, groundwater, groundwater-and-surface-water-interaction, groundwater-level, hydrology, modeling, precipitation-atmospheric, russian-river, streamflow, surface-water-non-marine, united-states, usgs-64a5fb42d34ef77fcb062879, water-resources
Organization: Department of the Interior
Russian River Integrated Hydrologic Model (RRIHM): Agricultural Fields

This dataset provides a shapefile of the fraction of each Coupled Groundwater and Surface-Water Flow Model (GSFLOW) grid cell covered by agricultural fields.

Tags: california, environment, groundwater, groundwater-and-surface-water-interaction, groundwater-level, hydrology, modeling, precipitation-atmospheric, russian-river, streamflow, surface-water-non-marine, united-states, usgs-64a5fb84d34ef77fcb062953, water-resources
Organization: Department of the Interior
Russian River Integrated Hydrologic Model (RRIHM): Agricultural Water Use Package (AG)

This dataset is a comma separated file of agricultural fields, ponds, surface diversions and wells used to generate the Agricultural package (AG).

Tags: california, environment, groundwater, groundwater-and-surface-water-interaction, groundwater-level, hydrology, modeling, precipitation-atmospheric, russian-river, streamflow, surface-water-non-marine, united-states, usgs-64a5fc2dd34ef77fcb062955, water-resources
Organization: Department of the Interior
Russian River Integrated Hydrologic Model (RRIHM):  Crop Coefficients

This dataset provides crop coefficients from the Sonoma County water agency. Crop coefficients are used to estimate the water requirements of different crops and are essential for efficient irrigation management. The data in this dataset can be used by farmers and water managers to optimize water use and improve crop yields in Sonoma County.

Tags: california, environment, groundwater, groundwater-and-surface-water-interaction, groundwater-level, hydrology, modeling, precipitation-atmospheric, russian-river, streamflow, surface-water-non-marine, united-states, usgs-64a5fc62d34ef77fcb062957, water-resources
Organization: Department of the Interior
Russian River Integrated Hydrologic Model (RRIHM): Pond Diversions

This dataset provides a shapefile of the surface water diversions to agricultural ponds in the Russian River Coupled Groundwater and Surface-Water Flow Model (GSFLOW) model.

Tags: california, environment, groundwater, groundwater-and-surface-water-interaction, groundwater-level, hydrology, modeling, precipitation-atmospheric, russian-river, streamflow, surface-water-non-marine, united-states, usgs-64a5fcc8d34ef77fcb062959, water-resources
Organization: Department of the Interior
Limestone boulders and cobbles noted 2009 to 2017 that pertain to sea floods of the past 1,000 years on Anegada, British Virgin Islands

This part of the release provides an updated georeferenced catalog of limestone boulders and cobbles pertaining to extreme waves on Anegada, a low Caribbean island perched south of the Puerto Rico Trench. Tabulated are 660 limestone clasts, along with clast dimensions and long-axis trend in many instances. Fewer than one-fifth of the clasts were reported previously in https://doi.org/10.1007/s11069-011-9725-8 and https://doi.org/10.1130/GES01356.1. Most were surveyed in 2017.

Tags: biota, british-virgin-islands, carbon-14-analysis, caribbean-sea, corals, geoscientificinformation, hurricanes, limestone, tsunamis, usgs-64927da0d34ef77fcb005960
Organization: Department of the Interior
Russian River Integrated Hydrologic Model (RRIHM):  Ponds

This dataset provides a shapefile of agricultural ponds used in the Russian River Coupled Groundwater and Surface-Water Flow Model (GSFLOW) model.

Tags: california, environment, groundwater, groundwater-and-surface-water-interaction, groundwater-level, hydrology, modeling, precipitation-atmospheric, russian-river, streamflow, surface-water-non-marine, united-states, usgs-64a5fcf7d34ef77fcb06295b, water-resources
Organization: Department of the Interior
Fatty acid tissue concentrations of laboratory fed Lampsilis cardium mussels

The role of disease in freshwater mussel declines has been largely ignored due to the lack of appropriate diagnostic tools and metabolomic markers of stress. Mussels in this study were either fed a prepared diet or unfed and their condition was assessed with the observed changes in fatty acid content of their tissue.  This dataset contains quantitative fatty acid data from nonlethal (biopsy) sampling of foot tissue. These data may provide biomarkers  indicative of freshwater mussel’s metabolic status.

Tags: biota, diet, fatty-acid-profile, freshwater-mussel, lampsilis-cardium, usgs-64a6b6cdd34ef77fcb063926
Organization: Department of the Interior