Find research datasets worth reusing

opencc-by-4.0Jul 2021View details →

Predicted locations and nitrate pollution of groundwater discharge from D3pl karst aquifer in Latvia

Description A georeferenced raster data layer [5_predicted_D3pl_GW_discharge_zone.tif] showing predicted likelihood that groundwater polluted with nitrate (NO3-) is discharging as springs or diffuse seepage from the Upper Devonian Pļaviņas (D3pl) dolomite karst aquifer in Latvia is presented. The cell value indicates the likelihood (0 – low, 1 - high) that groundwater with nitrate contamination is discharging from the D3pl aquifer at this location. Value of 0 means that no groundwater is discharging there. The BalticTM 93 (EPSG:25884) references system is used. The rationale and methodology for elaborating the map of groundwater discharge as springs or diffuse seepage from the D3pl dolomite karst aquifer is described in the main article (Kalvāns et al. under review). In short, a 3D regional geological model (Popovs et al. 2015), land surface elevation model and bedrock surface elevation model (Popovs et al. under review) were combined to identify locations where aquitard at the base of D3pl aquifer is outcropping at bedrock surface and in the nearby depressions (in a distance up to 0.25 km) the land surface was below the surface of this aquitard. The likely contamination with NO3- was estimated from proportion of arable land (European Environment Agency 2018) within 4.75 km window. It is assumed that the NO3- contamination in the D3pl karst aquifer is likely only close to its distribution margins, where groundwater table is deeper than the top of the aquifer. This work was supported by the EU Interreg Est–Lat program project GroundEco No. Est-Lat62, and base funding grant from the Latvian Ministry of Education and Science to the University of Latvia, No. ZD2016/AZ03. References European Environment Agency (2018) Corine Land Cover 2018. https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=download (CLC). Accessed 1 Jun 2020 Popovs K, Kalvāns A, Jemeljanova M, et al (under review) Bedrock surface topography map of Latvia. J Maps Popovs K, Saks T, Jātnieks J (2015) A comprehensive approach to the 3D geological modelling of sedimentary basins: example of Latvia, the central part of the Baltic Basin. Est J Earth Sci 64:173–188. https://doi.org/10.3176/earth.2015.25

opencc-by-4.0Mar 2014View details →

Data sources for the groundwater depletion manuscript in Water Resources Research

Here, you can access the source files for the figures (and tables) of the publication (see reference). Basically, you find the model output (WaterGAP 2.2a) for global scaled groundwater storage, total water storage, baseflow, groundwater recharge (diffuse and below surface water bodies) and a table where location of grid cell and belonging continental area (e.g. to convert values into km³) is given. In addition, an Excel-File for the diagram of HPA (Figure 2) is accessible. First part of the file name represents the model variant (IRR100, IRR100_S, IRR70_S, NOUSE_S, for details see the manuscript), then the variable name and unit is given (Total Water Storages [mm], groundwater storage [mm], Qb (baseflow) [mm], Rg (diffuse groundwater recharge) [mm], Rg_swb (groundwater recharge below surface water bodies) [mm]). File format is a zipped netCDF. The table "lat_lon_cont_area.txt" contains the ArcID (internal grid cell number), coordinates and the continental area which is used for WaterGAP calculations. Original data description: https://www.uni-frankfurt.de/49903932/6__GW_depletion

opencc-by-4.0Jan 2023View details →

Water stable isotope, temperature and electrical conductivity dataset (snow, ice, rain, surface water, groundwater) from a high alpine catchment (2019-2021).

Data collected in the Otemma forefield in Switzerland (45°56’03”N,7°24’42”) from July 2019 to October 2021. Data were collected by the research teams of Bettina Schaefli2 and Stuart N. Lane1. 1 Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland 2 Institute of Geography (GIUB), University of Bern, 3012 Bern, Switzerland For further information, please contact: <ul> <li>tom.muller.1@unil.ch</li> </ul> Description of the dataset This dataset contains water stable isotope (δ2H, δ17O, δ18O), water temperature and water electrical conductivity (EC) measurements collected from the Otemma glacier catchment. All water isotope samples were collected directly from the source and stored in 12 mL amber glass vials with an air-tight caps. River samples were first collected with an automatic ISCO 6712 portable water sampler with 1L open plastic bottles and transferred in 12 mL vials every one to two weeks. All isotope analysis were performed using a Wavelength-Scanned Cavity Ring Down Spectrometer (Picarro 2140-I, Santa Clara, California, USA) and expressed relative to the international Vienna Standard Mean Ocean Water (VSMOW) standards. All EC and water temperature measurements were performed with a WTW Multi 3510 IDS logger with a IDS TetraCon® 925 probe. The dataset contains measurements performed at various locations within the catchment. A total of approximately 1500 measurements are provided. In the dataset each point correspond to a measurement station (column "Station") which we classified in specific class of water (column "Type") as follows : <ul> <li>Stream : samples collected at three locations, from the glacier snout, after a small outwash plain and 2km downstream.</li> <li>Tributary : 5 hillslopes tributaries originating from small seasonal overland flow or small springs at the base of the morainic hillslope. Those tributaries were monitored weekly. In addition, a few other seasonal lateral streams were sampled in various locations (Type: Other tributaries).</li> <li>Bedrock : A few exfiltrations directly leaking out of the bedrock outcrop were sampled.</li> <li>Ice : Ice was sampled either as surface ice (small cores 5 cm deep), as deeper cores (5 to 8m deep) or as meltwater from supraglacial gullies. All solid ice samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials.</li> <li>Snow : The snowpack was sampled either at the surface (0 to 5cm) or at about 20 cm depth. Where possible, meltwater leaking from the snowpack was sampled. At 3 locations in 2021, we dug snowpits from which we sampled snow at different layers with depth. All solid snow samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials</li> <li>Rain : Rainwater was mostly sampled at our camp site at 2450 m. asl. Rainwater samples represent single rain events which are identified by dry periods of at least one day long.</li> <li>Groundwater : shallow (2 to 3 meters) fully-screened groundwater wells were installed in the outwash plain and water sampled monthly in the snow-free season.</li> </ul> - GPS coordinates are provided with each point (Swiss coordinate system CH1903+ / LV95  (EPSG: 2056)). - Dates are provided in local timezone (GMT+1 with daylight saving time) and in UTC date format. - Analyitcal error from the Picarro spectrometer is reported as 1 standard deviation. More information can be accessed in the corresponding publication by Müller et al. (to be published in 2023). Data files <ul> <li>Otemma_isotope_EC_T_2019_2021.csv : file containing all data with GPS coordinates</li> <li> isotope_locations_Otemma.jpg : an overview of the locations of each measurement point </li> <li> Otemma_Isotopes_2019-2020.html : interactive plots of all datasets (δ2H, EC, temperature), classified by Type. </li> </ul>

opencc-by-4.0Dec 2022View details →

Global groundwater recharge estimates

Groundwater recharge estimates have been presented in Berghuijs et al. (2022). The estimates exclude regions with mean temperatures below −2°C and regions with aridity below 1. The estimates consist of total groundwater recharge (units mm per year) and the fraction of precipitation becoming groundwater recharge (dimensionless).

opencc-by-4.0Apr 2022View details →

Large Ensemble Dataset for Discovering Global Peak Water Limit of Future Groundwater Withdrawals Using 900 GCAM Runs

<h2>Global Groundwater Withdrawals Peak Over the 21st Century </h2> The large ensemble dataset contains groundwater related model outputs from 900 scenarios modeled using <a href="http://jgcri.github.io/gcam-doc/toc.html">Global Change Analysis Model (GCAM)</a>. The scenario ensemble members include five Shared Socioeconomic Pathways (SSPs), four Representative Concentration Pathways (RCPs), five global climate model outputs, three groundwater depletion limits, two surface water storage expansion regimes, and two historical groundwater depletion trends. <h3>Journal Article</h3> Niazi, H., Wild, T.B., Turner, S.W.D., Graham, N.T., Hejazi, M., Msangi, S., Kim, S., Lamontagne, J.R., & Zhao, M. (2024). <a href="https://rdcu.be/dFpb5">Global peak water limit of future groundwater withdrawals</a>. Nature Sustainability, 7(4), 413–422. <a href="https://doi.org/10.1038/s41893-024-01306-w" rel="nofollow">https://doi.org/10.1038/s41893-024-01306-w</a> Read full-text here: <a href="https://rdcu.be/dFpb5">https://rdcu.be/dFpb5</a>  <h3>Data Repository </h3> This data repository is to be used in combination with the main <a href="https://github.com/JGCRI/niazi-etal_2024_nature-sustainability">meta-repository</a> containing all scripts and files for reproducing the experiment as well as the analysis and post-processing of the model outputs. Scripts and smaller files are provided in the <a href="https://github.com/JGCRI/niazi-etal_202X_xyz">GitHub meta-repository</a> whereas larger files are provided in this data repository. Please complete the repository by placing the files as described hereunder. Please find the GitHub meta-repository here: <a href="https://github.com/JGCRI/niazi-etal_2024_nature-sustainability">https://github.com/JGCRI/niazi-etal_2024_nature-sustainability</a> Descriptions of files: <ol> <li>gcam-5.7z contains the GCAM version used to simulate 900 scenarios of plausible futures. The model folder contains all necessary input files to reproduce the simulations. <ul> <li>The model is to be used in combination with the <a href="https://github.com/JGCRI/niazi-etal_2024_nature-sustainability">meta-repository</a> to setup batch runs on cluster.</li> <li>Please navigate to <a href="https://github.com/JGCRI/niazi-etal_202X_xyz/tree/main/model">model/</a> folder for other scenario-specific and model setup folders and files. gcam-5 is to be extracted in the same directory (./model/gcam-5/). </li> <li>For the first-time users of GCAM, please follow guidance on <a href="http://jgcri.github.io/gcam-doc/toc.html">GCAM wiki</a> to setup GCAM or for background knowledge. </li> </ul> </li> <li>crop_yeild.7z: This file contains inputs related to climate impacts on crop yields. This is to be downloaded and extracted in the <a href="https://github.com/JGCRI/niazi-etal_202X_xyz/tree/main/model/combined_impacts">model/combined_impacts/</a> folder. </li> <li>outputs-all.7z: Key model outputs queried and collated from 900 GCAM runs are explained hereunder. The files could be downloaded individually (.csv files) or all at once in .7z format (<a href="../api/files/80b237d3-b22f-499f-8b8e-76c3846720a0/outputs-all.7z">outputs-all.7z</a>). These files are to be placed in the <a href="https://github.com/JGCRI/niazi-etal_202X_xyz/tree/main/model/outputs">model/outputs</a> folder of the <a href="https://github.com/JGCRI/niazi-etal_2024_nature-sustainability">meta-repository</a>.  <ul> <li>ag_prod_all_GW_scenarios.csv - Agricultural production across all scenario for 2050 and 2100 (tonnes)</li> <li>prices_water_withdrawal_all.csv - Water prices across all scenarios and years ($/km3)</li> <li>global_irrigated_prod_by_crop.csv - All irrigated agricultural production for each crop across and scenarios all years (tonnes)</li> <li>surface_water_production_all.csv - Runoff across all scenarios and years (km3)</li> <li>groundwater_production_FINAL.csv - Groundwater withdrawals across all scenarios and years (km3)</li> <li>water_withdrawals_desal_all.csv - Water withdrawals from desalination plants across all scenarios and years (km3)</li> </ul> </li> </ol> <h3>Short introduction to the study</h3> Using 900 GCAM runs, this study finds that global groundwater withdrawals are expected to peak around mid-century, followed by a decline through 21st century, exposing about half of the population living in one-third of basins to groundwater stress, with cost and availability of surface water storage being the most significant driver of future groundwater withdrawals. This first-ever robust, quantitative confirmation of the peak-and-decline pattern for groundwater, previously only known for fossil fuels and minerals, raises concerns for basins heavily dependent on groundwater. Niazi, H., Wild, T.B., Turner, S.W.D., Graham, N.T., Hejazi, M., Msangi, S., Kim, S., Lamontagne, J.R., & Zhao, M. (2024). <a href="https://rdcu.be/dFpb5">Global peak water limit of future groundwater withdrawals</a>. Nature Sustainability, 7(4), 413–422. <a href="https://doi.org/10.1038/s41893-024-01306-w" rel="nofollow">https://doi.org/10.1038/s41893-024-01306-w</a> Read full-text here: <a href="https://rdcu.be/dFpb5">https://rdcu.be/dFpb5</a> <h3>Contact </h3> Please reach out to Hassan Niazi at <a href="mailto:hassan.niazi@pnnl.gov">hassan.niazi@pnnl.gov</a> for any questions.

openCC (other)Mar 2023View details →

Data Source: Synergistic effects of precipitation and groundwater extraction on freshwater wetland inundation

Wetlands provide essential ecosystem services, including nutrient cycling, flood protection, and biodiversity support, that are sensitive to changes in wetland hydrology. Wetland hydrological inputs come from precipitation, groundwater discharge, and surface run-off. Changes to these inputs via climate variation, groundwater extraction, and land development may alter the timing and magnitude of wetland inundation. Data were compiled for 152 wetlands in west-central Florida over 14 years to investigate the response of wetland inundation to the interactive effects of precipitation, groundwater extraction, surrounding land development, basin geomorphology, and wetland vegetation class. Further methods are defined in the Methods section of the journal article associated with this dataset (Synergistic effects of precipitation and groundwater extraction on freshwater wetland inundation, published in the Journal of Environmental Management, 2023).

openCC (other)Jan 2025View details →

Groundwater-derived nutrient fluxes and offshore mixing rates along the New Jersey coast 21-23

Radium isotopes are natural tracers useful for studying the magnitude of groundwater discharge and the transport and fate of nutrients in the coastal ocean. We collected radium and nutrient samples from groundwater and surface waters along the southern New Jersey coast to calculate the flux of groundwater-derived nutrients and coastal mixing rates. These data serve as baselines for assessing future changes in the magnitude and quality of groundwater discharge driven by human activity and climate change.

openCC0Sep 2020View details →

Nyack Floodplain RiverNet surface water and groundwater dissolved oxygen, conductivity, water level, and temperature Northwest Montana, USA, 2012-2020

Water dissolved oxygen, conductivity, temperature, and level from ten locations in the Nyack Floodplain of the Middle Fork of the Flathead River in Northwest Montana, USA. Measurements are made hourly for the period of 2012 to 2020. Six sensor are placed in groundwater wells and four are placed in surface water. Data up to June 26h, 2019 have been cleaned to remove bad data and flag potentially anomalous observations.

openCC (other)Oct 2025View details →

Baltimore Ecosystem Study: Long-Term Monitoring of Riparian Water Table Depth and Groundwater Chemistry

Long-term monitoring of riparian water tables and groundwater chemistry began in 2000 along four first or second order steams in and around the Gwynns Falls watershed in Baltimore City and County, MD. One site (Oregon Ridge) is in the completely forested Pond Branch catchment that serves as a ""reference"" study area for the Baltimore LTER (BES). Two sites (Glyndon, Gwynbrook) were in suburban areas of the watershed; one just upstream from the Glyndon BES long-term stream monitoring site in the headwaters of the Gwynns Falls, and one along a tributary that enters the Gwynns Falls just above the Gwynnbrook BES long-term stream monitoring site farther downstream. The final, urban site (Cahill) was along a tributary to the Gwynns Falls in Leakin Park in the urban core of the watershed. Water table data and more detailed descriptions of soils, vegetation, stream channel properties and microbial processes at these sites can be found in Groffman et al. (2002, Environmental Science and Technology 36:4547-4552) and Gift et al. (2010, Restoration Ecology 18:113-120).

openCC (other)Jan 2023View details →

Groundwater and surface water chemistry from the Hole-in-the-Donut and nearby Taylor Slough in Everglades National Park, Florida, USA: 2015-2016

This research investigated the effects of the vegetation and soil removal on the hydrologic conditions of the Hole-in-the-donut (HID) of Everglades National Park. Groundwater and surface water samples were collected from 2 wells within the HID (DO1,DO3) and two wells outside the HID in adjacent Taylor Slough (NP-67, TSB). Surface water was collected at each site if present.

openCustomJan 2020View details →

Groundwater well pressure, temperature, conductance, salinity and oxygen measurements for GCE-LTER study hammock HN_i_1 from 30-Oct-2008 to 03-Dec-2013

Groundwater pressure, temperature and other parameters (e.g. conductance, salinity, oxygen and pH) were measured using various instruments installed in PVC wells at the GCE-LTER HN_i_1 holocene study hammock from 30-Oct-2008 to 03-Dec-2013. Observations were logged continuously at 15 minute intervals, and accumulated data were downloaded from loggers using manufacturer-provided communications software semi-monthly, then imported into MATLAB for post-processing, quality control and documention. Raw, unvented pressure readings were corrected for atmospheric pressure and sensor height from the bottom of the well to generate corrected pressure readings. Separate data tables are provided for each combination of instrument and well due to differences in parameters measured and post-processing steps, but all tables include detailed information on location and well characteristics to support integration and analysis. These data were collected as part of the Georgia Coastal Ecosystems LTER Intensive Hammock Characterization and Hammock Groundwater Modeling projects, and will be used for groundwater modeling studies at two marsh hammocks on Sapelo Island, Georgia.

openCustomJan 2020View details →

Groundwater well pressure, temperature, conductance, salinity and oxygen measurements for GCE-LTER study hammock PC_i_29 from 15-Aug-2008 to 13-Dec-2013

Groundwater pressure, temperature and other parameters (e.g. conductance, salinity, oxygen and pH) were measured using various instruments installed in PVC wells at the GCE-LTER PC_i_29 pleistocene study hammock from 15-Aug-2008 to 13-Dec-2013. Observations were logged continuously at 15 minute intervals, and accumulated data were downloaded from loggers using manufacturer-provided communications software semi-monthly, then imported into MATLAB for post-processing, quality control and documention. Raw, unvented pressure readings were corrected for atmospheric pressure and sensor height from the bottom of the well to generate corrected pressure readings. Separate data tables are provided for each combination of instrument and well due to differences in parameters measured and post-processing steps, but all tables include detailed information on location and well characteristics to support integration and analysis. These data were collected as part of the Georgia Coastal Ecosystems LTER Intensive Hammock Characterization and Hammock Groundwater Modeling projects, and will be used for groundwater modeling studies at two marsh hammocks on Sapelo Island, Georgia.

openCC0Dec 2024View details →

AGW01 Long-term measurement of groundwater physical and chemical properties from wells on watersheds N04D and N01B at Konza Prairie

In 1988 and 1990, 31 wells were installed at 20 sites within watershed N04D at Konza Prairie Biological Station to allow long-term monitoring of groundwater physical and chemical properties. Subsequently, four additional wells were installed in N04D in 1997, and five wells were installed in an adjacent watershed, N01B, in 2020. Most of the wells are nested to include wells completed in alluvium/colluvium and two Permian limestone units, the Morrill Limestone and the Eiss Limestone. The wells are completed along transects perpendicular to the main drainage in each watershed. Every four to six weeks, water samples and water depth measurements have been collected at subsets of the wells in N04D since 1991 and in N01B since 2021. At the same time, stream samples are collected from the outlet in N04D and N01B when the stream is flowing, as well as two upstream locations in N04D. Moreover, since 2024, stream samples are also collected at the same time from the outlet of a third watershed, N02B, when the steam is flowing. Methodologies have evolved since 1991 as detailed in the method description, though the primary goal of assessing groundwater and surface water major ion composition, pH, temperature, and groundwater level has been constant since 1991.

openCC0May 2023View details →

AGW02 Measurement of groundwater physical and chemical properties from wells in contrasting land uses near Kings Creek, Konza Prairie

Wells were drilled in two sites on Konza Prairie Biological Station in April, 1993 approximately 100 m from Kings Creek. The two sites are located in a grassland and an agricultural area. The grassland site (K01A) is an old field that was planted with brome sometime prior to 1976. It has not been grazed for 25 years and is burned in spring every 1-2 years. The agricultural site is currently under a mix of cultivation and restoration plots. Historically, it was cultivated from sometime between 1939 and 1950 to the present. It is approximately 1 km downstream in an area geologically similar to K01A. The soil at both sites is mapped as Reading silt loam (fine, mixed, mesic Typic Arguidolls). Samples are taken monthly by PVC bailer following removal of 2 times the well volume. Samples are analyzed with same methods as used for LTER stream water chemistry.

opencc-by-4.0Feb 2020View details →

S63 | UBADWGW | REACH Registered Substances Detected in Drinking (DW) or Groundwater (GW)

REACH Registered Substances Detected in Drinking (DW) or Groundwater (GW) This is a literature review and a subsequent persistent, mobile and toxic/very persistent and very mobile (PMT/vPvM) assessment published by the German Environment Agency (UBA) in 2019. All substances are reported in literature to have been detected in drinking water and groundwater. This list contains only those substance that are registered under REACH (EC No 1907/2006). It is assessed whether a substance meets the PMT/vPvM criteria as proposed by the German Environment Agency (UBA) in 2019 <a href="https://www.umweltbundesamt.de/publikationen/reach-improvement-of-guidance-methods-for-the">(UBA TEXTE 126/2019)</a>. Reference: Hans Peter H Arp and Sarah E Hale (2019). REACH: Improvement of guidance and methods for the identification and assessment of PMT/vPvM substances, Texte | 126/2019, German Environment Agency (⁠UBA⁠), Dessau-Roßlau, Germany. ISBN: 1862-4804, 131 pages. Acknowledgement: Environmental Research of the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety Project No. (FKZ) 3716 67 416 0 and Report No. FB000142/ENG This is the collection associated with list S63 UBADWGW on the <a href="https://www.norman-network.com/nds/SLE/">NORMAN Suspect List Exchange</a>.

opengpl-2.0Oct 2020View details →

Code and data for Mire microclimate: groundwater buffers temperature in waterlogged versus dry soils.

Version of record of the manuscript's code and data, as accepted by the International Journal of Climatology.

opencc-by-4.0Dec 2020View details →

Data pertaining to 'Can artesian groundwater and earthquake-induced aquifer leakage exacerbate the manifestation of liquefaction?'

Geodatabase (ArcGIS 10.5.1), Excel files and mp4 video to accompany:   Cox, S.C.; van Ballegooy, S.; Rutter, H.K.; Harte, D.S.; Holden, C.; Gulley, A.K.; Lacrosse, V.; Manga, M. (in press) Can artesian groundwater and earthquake-induced aquifer leakage exacerbate the manifestation of liquefaction? Engineering Geology Manuscript ENGEO 105982. Vast quantities of liquefaction ejecta repeatedly inundated properties during the 2010-2011 Canterbury earthquake sequence in New Zealand, resulting in differential ground surface subsidence and significant damage to buildings and urban infrastructure.  There are strong spatial correlations between the occurrence of ejected sediment with groundwater pressure in deep aquifers. When geotechnical testing sites are grouped according to liquefaction vulnerability indices (to control variance relating to shaking strength, water table depth, and soil profile strength), places where ‘minor’ and ‘moderate-severe’ liquefaction occurred during the Mw6.2 Christchurch earthquake had distinctly higher aquifer pressure than sites where liquefaction was not observed. Together with observations of earthquake-induced pressure changes and inferred transfer of groundwater from deep aquifers to shallower levels, an interpretation is that leakage from aquifers with artesian (above ground) pressure provided an additional driving mechanism for surface manifestation of water and sediment. It is surmised that above-ground aquifer pressures further promoted suffusion and piping along fractures, flow-pathways and liquefied horizons. The Mw6.2 Christchurch earthquake is presented as an example where leakage of artesian groundwater likely contributed to the near-surface liquefaction-induced ground damage. The process can result in underprediction of liquefaction vulnerability so needs to be considered when evaluating potential for earthquake-induced liquefaction and ground damage wherever groundwater is confined.

opencc-by-4.0Aug 2016View details →

Output files corresponding to "Continental patterns of submarine groundwater discharge reveal coastal vulnerabilities"

Corresponding peer-reviewed publication This dataset corresponds to the output files that were produced for the study reported in: <ul> <li>Sawyer, Audrey H., Cédric H. David, and James S. Famiglietti, (2016), Continental patterns of submarine groundwater discharge reveal coastal vulnerabilities, Science, 353(6300), 705-707. DOI:10.1126/science.aag1058. </li> </ul>   When making use of any of the files in this dataset, please cite both the aforementioned article and the dataset herein.    Data sources The following sources were used to produce files in this dataset: <ul> <li>The National Hydrography Dataset Plus (NHDPlus) Version 2, obtained from http://www.horizon-systems.com/nhdplus/NHDplusV2_data.php.  Regions used are: Northeast (NE: 01), Mid-Atlantic (MA: 02), South-Atlantic North (SAN: 03N), South-Atlantic South (SAS: 03S), South-Atlantic West (SAW: 03W), Lower Mississippi (MS: 08), Texas (TX: 12), California (CA: 18), and Pacific Northwest (NW: 17).</li> <li>The second phase of the North American Land Data Assimilation System (NLDAS2), obtained from ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS.  Model outputs used are: NLDAS_MOS0125_MC.002, NLDAS_NOAH0125_MC.002, and NLDAS_VIC0125_MC.002.</li> <li>The United States 2010 Census dataset (CENSUS 2010), obtained from: http://www2.census.gov/geo/tiger/TIGER2010DP1/County_2010Census_DP1.zip.</li> <li>The United States 2011 National Land Cover Database (NLCD 2011), obtained from: http://www.mrlc.gov/nlcd2011.php.</li> </ul>   Description of files The files in this dataset contain are described below: <ul> <li>NHDFlowline_CONUS_coastline.zip.  This zip file contains a shapefile with the coastline of the Contiguous United States as described by NHDPlus V2, and was merged from a subsample of all river reaches available in regions used. </li> <li>Catchment_CONUS_coastline.zip.  This zip file contains a shapefile with the contributing catchments of NHDPlus V2 corresponding to the above coastline, and was merged from a subsample of all catchments available in regions used. </li> <li>Catchment_CONUS_coastline_centroid.zip.  This zip file contains a shapefile with the centroids of the above catchments. </li> <li>SGD_Coastal_Vulnerabilities.csv.  This .csv file contains the following data (units are in parentheses): <ul> <li>COMID. Unique feature identifier in NHDPlusV2 (-).</li> <li>LENGTHkm. Length of coastline feature (km).</li> <li>REACHCODE. Reach identifier in NHDPlusV2; reaches can include multiple features; Submarine Groundwater Discharge (SGD) is computed by reach, not feature (-).</li> <li>AREAsqkm. Area of coastal catchment feature (km2).</li> <li>REGION. NHDPlusV2 region: NE = Northeast, MA = Mid-Atlantic, SAN = South Atlantic North, SAS = South Atlantic South, SAW = South Atlantic West, TX = Texas, MS = Lower Mississippi, CA = California, PN = Pacific Northwest (-).</li> <li>RLENGTHkm. Total length of coastline accumulated by REACHCODE (km).</li> <li>RAREAsqkm. Total area of coastal catchment accumulated by REACHCODE (km2).</li> <li>BGRUNkgpsqm. Average annual infiltrating runoff for REACHCODE (kg/m2)</li> <li>SGDsqmpy. Average annual fresh SGD rate for REACHCODE (m2/y).</li> <li>RCOUNT. Number of features by REACHCODE (-).</li> <li>PDENpsqkm. Population density for coastal catchment feature (km-2).</li> <li>SWIVULN.  Vulnerability to saltwater intrusion: - 1 = vulnerable, 0 = not vulnerable (-).</li> <li>PCTDEV11.  Percentage of reach area with developed or agricultural land use in 2011 (%).</li> <li>CONTVULN. Vulnerability to offshore contamination associated with direct groundwater discharge: - 1 = vulnerable, 0 = not vulnerable (-).</li> </ul> </li> </ul>   Known bugs and limitations in this dataset or the associated manuscript. No bugs have been unveiled since publication of this dataset or the associated manuscript.  Vulnerability thresholds are subjective and could be adjusted for different applications, refer to published manuscript for approaches used here.   Funding This work was supported by the Ohio State University School of Earth Sciences, and NSF grant EAR-1446724 (A.H.S); the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA, and grants from the NASA SWOT and Sea Level Science Teams (C.H.D. and J.S.F.).

opencc-by-4.0May 2023View details →

Groundwater is a globally-threatened keystone ecosystem

Global maps of groundwater diversity, interactions between groundwater and surface water and global surface diversity linked into two maps.