The DOI matches its DataCite record.
USGS Water Data for the Nation
Open accessAbstract
This collection provides access to water-resources data collected at approximately 1.5 million sites in all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa and the Commonwealth of the Northern Mariana Islands. Online access to this data is organized around the categories surface water, groundwater, water quality, and water use.\r\n\r\nSurface-water data includes more than 850,000 station years of time-series data that describe stream levels, streamflow (discharge), reservoir and lake levels, surface-water quality, and rainfall. The data are collected by automatic recorders and manual field measurements at installations across the Nation.\r\n\r\nGroundwater data consists of more than 850,000 records of wells, springs, test holes, tunnels,drains, and excavations in the United States. Available site descriptive information includes well location information such as latitude and longitude, well depth, and aquifer. The USGS annually monitors groundwater levels in thousands of wells in the United States. Groundwater level data are collected and stored as either discrete field-water-level measurements or as continuous time-series data from automated recorders. \r\n\r\nWater-quality data includes chemical, physical, and biological properties of water, sediment and tissue samples from across the Nation. The discrete sample data base is a compilation of over 4.4 million historical water quality analyses in the USGS district data bases through September 2005. At selected surface-water and groundwater sites, the USGS maintains instruments that continuously record physical and chemical characteristics of the water including pH, specific conductance, temperature, dissolved oxygen, and percent dissolved-oxygen saturation. Supporting data such as air temperature and barometric pressure are also available at some sites. At sites where this information is transmitted automatically, data are available from the current data system.\r\n\r\nWater use refers to water that is used for specific purposes. Water-use data is collected by area type (State, county, watershed or aquifer) and source such as rivers or groundwater, and category such as public supply or irrigation. Water-use data has been reported every five years since 1950, for years ending in "0" and "5". The USGS works in cooperation with local, State, and Federal agencies as well as academic and private organizations to collect and report total withdrawals.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Of particular interest, tetraconazole and fluometuron were detected at East Mustang Creek and West Mustang Creek.”
From Per- and Polyfluoroalkyl Substances in Surface Water and Fluvial Sediments of a Rural Gulf Coast Watershed: A Year-long Spatiotemporal Assessment (2026) · cites this paper as [50]
In the citing paper
“Sites were sampled under approximate base-flow conditions (3 days after ∼6 mm of precipitation) 21 and near long-term median mean daily streamflow values for those days of the year at nearby streamgages.22”
Citations
Cited by
Sorted by citations
A Rainfall‐Runoff Model With LSTM‐Based Sequence‐to‐Sequence Learning
Xiang, Z., Yan, J., & Demir, İ. (2020) · Water Resources Research · doi:10.1029/2019wr025326 · Cited by 791
Tarek, M., Brissette, F. P., & Arsenault, R. (2020) · Hydrology and earth system sciences · doi:10.5194/hess-24-2527-2020 · Cited by 766
Sahoo, S., Russo, T. A., Elliott, J. W., & Foster, I. T. (2017) · Water Resources Research · doi:10.1002/2016wr019933 · Cited by 428
Bradley, P. M., Journey, C. A., Romanok, K. M., Barber, L. B., Buxton, H. T., Foreman, W. T., Furlong, E. T., Glassmeyer, S. T., Hladik, M. L., Iwanowicz, L. R., et al. (2017) · Environmental Science & Technology · doi:10.1021/acs.est.7b00012 · Cited by 330
Evaluating the performance of random forest for large-scale flood discharge simulation
Schoppa, L., Disse, M., & Bachmair, S. (2020) · Journal of Hydrology · doi:10.1016/j.jhydrol.2020.125531 · Cited by 240
Water quality data for national‐scale aquatic research: The Water Quality Portal
Read, E., Carr, L., Cicco, L. D. D., Dugan, H., Hanson, P., Hart, J. A., Kreft, J., Read, J., & Winslow, L. (2017) · Water Resources Research · doi:10.1002/2016wr019993 · Cited by 177
Landscape Drivers of Dynamic Change in Water Quality of U.S. Rivers
Stets, E. G., Sprague, L. A., Oelsner, G. P., Johnson, H. M., Murphy, J. C., Ryberg, K. R., Vecchia, A. V., Zuellig, R. E., Falcone, J. A., & Riskin, M. L. (2020) · Environmental Science & Technology · doi:10.1021/acs.est.9b05344 · Cited by 235
Burned forests impact water supplies
Hallema, D. W., Sun, G., Caldwell, P. V., Norman, S. P., Cohen, E. C., Liu, Y., Bladon, K. D., & McNulty, S. G. (2018) · Nature Communications · doi:10.1038/s41467-018-03735-6 · Cited by 193
McMahon, P. B., Belitz, K., Reddy, J. E., & Johnson, T. D. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.8b04055 · Cited by 177
McGuire, V. L. (2017) · Scientific investigations report · doi:10.3133/sir20175040 · Cited by 149
Zero or not? Causes and consequences of zero‐flow stream gage readings
Zimmer, M. A., Kaiser, K. E., Blaszczak, J. R., Zipper, S. C., Hammond, J. C., Fritz, K. M., Costigan, K. H., Hosen, J. D., Godsey, S. E., Allen, G. H., et al. (2020) · Wiley Interdisciplinary Reviews Water · doi:10.1002/wat2.1436 · Cited by 138
Erickson, M. L., Elliott, S. M., Brown, C. J., Stackelberg, P. E., Ransom, K. M., Reddy, J. E., & Cravotta, C. A. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.0c06740 · Cited by 118
Papenfus, M., Schaeffer, B. A., Pollard, A. I., & Loftin, K. A. (2020) · Environmental Monitoring and Assessment · doi:10.1007/s10661-020-08631-5 · Cited by 117
Integrating urban water fluxes and moving beyond impervious surface cover: A review
Oswald, C. J., Kelleher, C. A., Ledford, S. H., Hopkins, K. G., Sytsma, A., Tetzlaff, D., Toran, L. E., & Voter, C. B. (2023) · Journal of Hydrology · doi:10.1016/j.jhydrol.2023.129188 · Cited by 123
Ryberg, K. R., Hodgkins, G. A., & Dudley, R. W. (2019) · Journal of Hydrology · doi:10.1016/j.jhydrol.2019.124307 · Cited by 108
Low streamflow trends at human-impacted and reference basins in the United States
Dudley, R. W., Hirsch, R. M., Archfield, S. A., Blum, A. G., & Renard, B. (2019) · Journal of Hydrology · doi:10.1016/j.jhydrol.2019.124254 · Cited by 106
The metabolic regimes of 356 rivers in the United States
Appling, A., Read, J. S., Winslow, L., et al. (2018) · Scientific Data · doi:10.1038/sdata.2018.292 · Cited by 106
Blackwell, B. R., Ankley, G. T., Bradley, P. M., Houck, K. A., Makarov, S. S., Medvedev, A. V., Swintek, J., & Villeneuve, D. L. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.8b05304 · Cited by 99
Oelsner, G., Sprague, L., Murphy, J., Zuellig, R. E., Johnson, H. M., Ryberg, K. R., Falcone, J., Stets, E., Vecchia, A. V., Riskin, M. L., et al. (2017) · Scientific investigations report · doi:10.3133/sir20175006 · Cited by 81
Moore, J., Fanelli, R., & Sekellick, A. J. (2019) · Environmental Science and Technology · doi:10.1021/acs.est.9b04316 · Cited by 77
Zhang, Q., & Hirsch, R. M. (2019) · Water Resources Research · doi:10.1029/2019wr025338 · Cited by 93
Crow, W. T., Chen, F., Reichle, R. H., et al. (2017) · Geophysical Research Letters · doi:10.1002/2017gl073642 · Cited by 93
Mahler, B. J., Nowell, L. H., Sandstrom, M. W., Bradley, P. M., Romanok, K. M., Konrad, C. P., & Metre, P. C. V. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.0c06625 · Cited by 88
Johnson, Z. C., Johnson, B. G., Briggs, M. A., et al. (2020) · Journal of Hydrology · doi:10.1016/j.jhydrol.2020.124929 · Cited by 69
Robertson, D. M., & Saad, D. A. (2021) · JAWRA Journal of the American Water Resources Association · doi:10.1111/1752-1688.12905 · Cited by 73
Verkaik, J., Sutanudjaja, E. H., Essink, G. O., et al. (2024) · Geoscientific model development · doi:10.5194/gmd-17-275-2024 · Cited by 69
Rust, A. J., Saxe, S., McCray, J., Rhoades, C. C., & Hogue, T. S. (2019) · International Journal of Wildland Fire · doi:10.1071/wf18191 · Cited by 69
Hopkins, K. G., Bhaskar, A. S., Woznicki, S. A., & Fanelli, R. M. (2019) · Hydrological Processes · doi:10.1002/hyp.13593 · Cited by 64
DynQual v1.0: a high-resolution global surface water quality model
Jones, E. R., Bierkens, M. F. P., Wanders, N., et al. (2023) · Geoscientific model development · doi:10.5194/gmd-16-4481-2023 · Cited by 63
Lawrence, G. B., & Roy, K. M. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.142529 · Cited by 61
Zell, W. O., & Sanford, W. E. (2020) · Water Resources Research · doi:10.1029/2019wr026724 · Cited by 61
Pool, S., Vis, M. J. P., Knight, R. R., et al. (2017) · Hydrology and earth system sciences · doi:10.5194/hess-21-5443-2017 · Cited by 59
Patterns and magnitude of flow alteration in California, USA
Zimmerman, J. K. H., Carlisle, D. M., May, J. T., Klausmeyer, K. R., Grantham, T. E., Brown, L. R., & Howard, J. K. (2017) · Freshwater Biology · doi:10.1111/fwb.13058 · Cited by 58
Beyond model metrics: The perils of calibrating hydrologic models
Triana, J. S. A., Chu, M. L., Gúzman, J. A., Moriasi, D. N., & Steiner, J. L. (2019) · Journal of Hydrology · doi:10.1016/j.jhydrol.2019.124032 · Cited by 60
Marinos, R. E., Meter, K. J. V., & Basu, N. B. (2020) · Geophysical Research Letters · doi:10.1029/2020gl087051 · Cited by 59
Bank‐derived material dominates fluvial sediment in a suburban Chesapeake Bay watershed
Cashman, M. J., Gellis, A. C., Sanisaca, L. G., et al. (2018) · River Research and Applications · doi:10.1002/rra.3325 · Cited by 57
Zhang, Q., Harman, C. J., & Ball, W. P. (2016) · Geophysical Research Letters · doi:10.1002/2016gl069945 · Cited by 56
Feng, D., Beck, H. E., de Bruijn, J., Sahu, R. K., Satoh, Y., Wada, Y., Liu, J., Pan, M., Lawson, K., & Shen, C. (2024) · Geoscientific model development · doi:10.5194/gmd-17-7181-2024 · Cited by 75
Prediction and Inference of Flow Duration Curves Using Multioutput Neural Networks
Worland, S. C., Steinschneider, S., Asquith, W. H., Knight, R. R., & Wieczorek, M. (2019) · Water Resources Research · doi:10.1029/2018wr024463 · Cited by 57
A Classification of Streamflow Patterns Across the Coastal Gulf of Alaska
Sergeant, C. J., Falke, J. A., Bellmore, R. A., Bellmore, J. R., & Crumley, R. (2020) · Water Resources Research · doi:10.1029/2019wr026127 · Cited by 54
Hosen, J. D., Aho, K. S., Fair, J. H., Kyzivat, E. D., Matt, S., Morrison, J., Stubbins, A., Weber, L. C., Yoon, B., & Raymond, P. A. (2020) · Ecosystems · doi:10.1007/s10021-020-00514-7 · Cited by 51
Johnson, J. M., Fang, S., Sankarasubramanian, A., Rad, A. M., da Cunha, L. K., Jennings, K. S., Clarke, K., Mazrooei, A., & Yeghiazarian, L. (2023) · Journal of Geophysical Research Atmospheres · doi:10.1029/2023jd038534 · Cited by 62
Borchardt, M. A., Stokdyk, J. P., Kieke, B. A., Muldoon, M. A., Spencer, S. K., Firnstahl, A. D., Bonness, D. E., Hunt, R. J., & Burch, T. R. (2021) · Environmental Health Perspectives · doi:10.1289/ehp7813 · Cited by 53
Mize, S. V., Murphy, J. C., Diehl, T. H., et al. (2018) · Journal of Hydrology · doi:10.1016/j.jhydrol.2018.05.068 · Cited by 48
Anthropogenic basin closure and groundwater salinization (ABCSAL)
Pauloo, R. A., Fogg, G. E., Harter, T., et al. (2020) · Journal of Hydrology · doi:10.1016/j.jhydrol.2020.125787 · Cited by 48
Hydrologic Signals and Surprises in U.S. Streamflow Records During Urbanization
Bhaskar, A. S., Hopkins, K. G., Smith, B., Stephens, T. A., & Miller, A. J. (2020) · Water Resources Research · doi:10.1029/2019wr027039 · Cited by 49
An evaluation of methods for computing annual water-quality loads
Lee, C. J., Hirsch, R. M., & Crawford, C. G. (2019) · Scientific investigations report · doi:10.3133/sir20195084 · Cited by 48
McMahon, P. B., Vengosh, A., Davis, T. A., Landon, M. K., Tyne, R., Wright, M. T., Kulongoski, J. T., Hunt, A. G., Barry, P. H., Kondash, A. J., et al. (2019) · Environmental Science & Technology · doi:10.1021/acs.est.9b02395 · Cited by 46
Killian, C. D., Asquith, W. H., Barlow, J. R. B., et al. (2019) · Hydrogeology Journal · doi:10.1007/s10040-019-01981-6 · Cited by 47
Hosen, J. D., Allen, G. H., Amatulli, G., et al. (2021) · Hydrological Processes · doi:10.1002/hyp.14124 · Cited by 47
Subsurface Water Flux in California's Central Valley and Its Source Watershed From Space Geodesy
Argus, D. F., Martens, H. R., Borsa, A. A., et al. (2022) · Geophysical Research Letters · doi:10.1029/2022gl099583 · Cited by 45
Murphy, S. F., Stallard, R. F., Scholl, M. A., González, G., & Torres-Sánchez, A. J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0180987 · Cited by 47
Rey, D. M., Briggs, M. A., Walvoord, M. A., & Ebel, B. A. (2023) · Journal of Hydrology · doi:10.1016/j.jhydrol.2023.129272 · Cited by 44
Sensitivity of headwater streamflow to thawing permafrost and vegetation change in a warming Arctic
Koch, J. C., Sjöberg, Y., O’Donnell, J. A., et al. (2022) · Environmental Research Letters · doi:10.1088/1748-9326/ac5f2d · Cited by 43
Uncertainties in measuring and estimating water‐budget components: Current state of the science
Levin, S. B., Briggs, M. A., Foks, S. S., Goodling, P., Raffensperger, J. P., Rosenberry, D. O., Scholl, M. A., Tiedeman, C. R., & Webb, R. M. T. (2023) · Wiley Interdisciplinary Reviews Water · doi:10.1002/wat2.1646 · Cited by 43
Hutchins, P. R., Sepulveda, A. J., Hartikainen, H., Staigmiller, K. D., Opitz, S. T., Yamamoto, R. M., Huttinger, A., Cordes, R. J., Weiss, T., Hopper, L. R., et al. (2021) · Ecosphere · doi:10.1002/ecs2.3436 · Cited by 43
Groundwater Variations From Autocorrelation and Receiver Functions
Kim, D., & Lekic, V. (2019) · Geophysical Research Letters · doi:10.1029/2019gl084719 · Cited by 40
Domestic well locations and populations served in the contiguous U.S.: 1990
Johnson, T. D., & Belitz, K. (2017) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.07.018 · Cited by 39
Regionalization of Groundwater Residence Time Using Metamodeling
Starn, J. J., & Belitz, K. (2018) · Water Resources Research · doi:10.1029/2017wr021531 · Cited by 38
An Analysis of Streamflow Trends in the Southern and Southeastern US from 1950–2015
Rodgers, K., Roland, V. L., Hoos, A. B., Crowley-Ornelas, E. R., & Knight, R. R. (2020) · Water · doi:10.3390/w12123345 · Cited by 34
Managing nonperennial headwater streams in temperate forests of the United States
Kampf, S. K., Dwire, K. A., Fairchild, M. P., Dunham, J. B., Snyder, C. D., Jaeger, K. L., Luce, C. H., Hammond, J. C., Wilson, C., Zimmer, M. A., et al. (2021) · Forest Ecology and Management · doi:10.1016/j.foreco.2021.119523 · Cited by 33
Collins, M. J., Hodgkins, G. A., Archfield, S. A., et al. (2022) · Water Resources Research · doi:10.1029/2021wr030480 · Cited by 33
Willard, J., Varadharajan, C., Jia, X., & Kumar, V. (2025) · Environmental Data Science · doi:10.1017/eds.2024.14 · Cited by 49
McMahon, P. B., Lindsey, B. D., Conlon, M. D., et al. (2019) · Environmental Science & Technology · doi:10.1021/acs.est.9b01440 · Cited by 33
Kreiling, R. M., Thoms, M. C., Bartsch, L. A., Larson, J. H., & Christensen, V. G. (2020) · Water Resources Research · doi:10.1029/2019wr026655 · Cited by 32
Bradley, P. M., Romanok, K. M., Duncan, J. R., Battaglin, W. A., Clark, J. M., Hladik, M. L., Huffman, B. J., Iwanowicz, L. R., Journey, C. A., & Smalling, K. L. (2019) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2019.135431 · Cited by 29
Shao, S., Driscoll, C. T., Sullivan, T. J., et al. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.137113 · Cited by 32
Hama, J. R., Kolpin, D. W., LeFevre, G. H., et al. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c01477 · Cited by 32
Clark, K. E., Stallard, R. F., Murphy, S. F., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29618-5 · Cited by 31
Rue, G., Rock, N. D., Gabor, R. S., Pitlick, J., Tfaily, M., & McKnight, D. M. (2017) · Water Resources Research · doi:10.1002/2016wr019708 · Cited by 31
Arnold, T. L., Bexfield, L. M., Musgrove, M., et al. (2017) · Data series · doi:10.3133/ds1063 · Cited by 31
Bias Correction of Airborne Thermal Infrared Observations Over Forests Using Melting Snow
Pestana, S., Chickadel, C. C., Harpold, A. A., et al. (2019) · Water Resources Research · doi:10.1029/2019wr025699 · Cited by 30
Knierim, K. J., Kingsbury, J. A., Haugh, C. J., et al. (2020) · JAWRA Journal of the American Water Resources Association · doi:10.1111/1752-1688.12879 · Cited by 30
Modelling surface‐water depression storage in a Prairie Pothole Region
Hay, L. E., Norton, P. A., Viger, R. J., Markstrom, S. L., Regan, R. S., & Vanderhoof, M. K. (2018) · Hydrological Processes · doi:10.1002/hyp.11416 · Cited by 31
Moore, J. F., Pine, W. E., Frederick, P. C., Beck, S., Moreno, M., Dodrill, M. J., Boone, M., Sturmer, L., & Yurek, S. (2020) · Marine and Coastal Fisheries · doi:10.1002/mcf2.10117 · Cited by 29
Risk‐Based Wellhead Protection Decision Support: A Repeatable Workflow Approach
Fienen, M. N., Corson‐Dosch, N., White, J. T., Leaf, A. T., & Hunt, R. J. (2021) · Ground Water · doi:10.1111/gwat.13129 · Cited by 29
Zhang, Q., & Ball, W. P. (2017) · Journal of Hydrology · doi:10.1016/j.jhydrol.2016.12.052 · Cited by 30
Solder, J. E., & Beisner, K. R. (2020) · Hydrogeology Journal · doi:10.1007/s10040-020-02194-y · Cited by 28
Effects of shifting snowmelt regimes on the hydrology of non-alpine temperate landscapes
Ford, C. M., Kendall, A. D., & Hyndman, D. W. (2020) · Journal of Hydrology · doi:10.1016/j.jhydrol.2020.125517 · Cited by 28
Climate change impacts and strategies for adaptation for water resource management in Indiana
Cherkauer, K. A., Bowling, L. C., Byun, K., Chaubey, I., Chin, N., Ficklin, D. L., Hamlet, A. F., Kines, S. J., Lee, C. I., Neupane, R. P., et al. (2021) · Climatic Change · doi:10.1007/s10584-021-02979-4 · Cited by 28
A Lagrangian particle-tracking approach to modelling larval drift in rivers
McDonald, R. R., & Nelson, J. M. (2020) · Journal of Ecohydraulics · doi:10.1080/24705357.2019.1709102 · Cited by 28
Yager, R. M., Kauffman, L. J., Soller, D. R., et al. (2018) · Scientific investigations report · doi:10.3133/sir20185091 · Cited by 28
Hydrodynamics structure plankton communities and interactions in a freshwater tidal estuary
Smits, A. P., Loken, L. C., Nieuwenhuyse, E. E. V., et al. (2023) · Ecological Monographs · doi:10.1002/ecm.1567 · Cited by 27
Espinoza, E. A., Loritz, R., Kratzert, F., Klotz, D., Gauch, M., Chaves, M. Á., Bäuerle, N., & Ehret, U. (2025) · Hydrology and earth system sciences · doi:10.5194/hess-29-1277-2025 · Cited by 37
Mapped Predictions of Manganese and Arsenic in an Alluvial Aquifer Using Boosted Regression Trees
Knierim, K. J., Kingsbury, J. A., Belitz, K., Stackelberg, P. E., Minsley, B. J., & Rigby, J. R. (2021) · Ground Water · doi:10.1111/gwat.13164 · Cited by 28
Williamson, T. N., Dobrowolski, E. G., Meyer, S. S., et al. (2018) · Journal of Soil and Water Conservation · doi:10.2489/jswc.74.1.1 · Cited by 27
Huber, D. P., Lohse, K. A., Commendador, A. S., et al. (2019) · Ecosphere · doi:10.1002/ecs2.2655 · Cited by 27
Haugen, E., Jurgens, B. C., Arroyo‐Lopez, J. A., et al. (2021) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2021.145223 · Cited by 27
Bathymetry retrieval from CubeSat image sequences with short time lags
Niroumand-Jadidi, M., Legleiter, C. J., & Bovolo, F. (2022) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2022.102958 · Cited by 26
Zwart, J. A., Oliver, S. K., Watkins, W. D., Sadler, J. M., Appling, A., Corson-Dosch, H. R., Jia, X., Kumar, V., & Read, J. S. (2022) · JAWRA Journal of the American Water Resources Association · doi:10.1111/1752-1688.13093 · Cited by 33
Storb, M. B., Bussell, A. M., Eldridge, S. L. C., et al. (2023) · Environmental Science & Technology · doi:10.1021/acs.est.3c05090 · Cited by 26
Predicting Daily River Chlorophyll Concentrations at a Continental Scale
Savoy, P. R., & Harvey, J. W. (2023) · Water Resources Research · doi:10.1029/2022wr034215 · Cited by 23
Kent, R. H., Johnson, T. D., & Rosen, M. R. (2020) · Environmental Monitoring and Assessment · doi:10.1007/s10661-020-08504-x · Cited by 25
Linz, D. M., Sienkiewicz, N., Struewing, I. T., Stelzer, E. A., Graham, J. L., & Lu, J. (2023) · Scientific Reports · doi:10.1038/s41598-023-29037-6 · Cited by 26
Watson, K. M., Storm, J. B., Breaker, B. K., et al. (2017) · Scientific investigations report · doi:10.3133/sir20175005 · Cited by 25
Sprenger, M., Carroll, R. W. H., Marchetti, D. W., et al. (2024) · Hydrology and earth system sciences · doi:10.5194/hess-28-1711-2024 · Cited by 24
Li, C., Handwerger, A. L., Wang, J., Yu, W., Li, X., Finnegan, N. J., Xie, Y., Buscarnera, G., & Horton, D. E. (2022) · Natural hazards and earth system sciences · doi:10.5194/nhess-22-2317-2022 · Cited by 24
Development of a Coastal Drought Index Using Salinity Data
Conrads, P., & Darby, L. S. (2016) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-15-00171.1 · Cited by 24
Ryberg, K. R. (2017) · Journal of Environmental Quality · doi:10.2134/jeq2017.04.0131 · Cited by 24
Hammond, J. C., Anderson, B. J., Simeone, C. E., Brunner, M. I., Castro, E. M., Archfield, S. A., Magee, E., & Armitage, R. (2025) · Hydrological Processes · doi:10.1002/hyp.70113 · Cited by 26
Metadata
- Authors
- Survey, U. S. G.
- Corresponding author
- United States Geological Survey
- Venue
- U.S. Geological Survey
- Publisher
- U.S. Geological Survey
- Published
- 1994
- OpenAlex
- W6892160308
- Cited by
- 1,478
- References
- 0
- Citations by year
- 2026: 72 · 2025: 174 · 2024: 224 · 2023: 203 · 2022: 183 · 2021: 174 · 2020: 159 · 2019: 120 · 2018: 84 · 2017: 71 · 2016: 12 · 2013: 1
- Type
- other
- Language
- en
- Open access
- green
- doi.org
- Licence
- public-domain
- creativecommons.org/publicdomain/zero/1.0/legalcode
- Locations
- USGS DOI Tool Production Environment (public-domain)
- Topics
- Physical Sciences › Environmental Science › Water Science and Technology › Water Quality and Resources Studies
- Physical Sciences › Environmental Science › Management, Monitoring, Policy and Law › Environmental Monitoring and Data Management
- Physical Sciences › Environmental Science › Water Science and Technology › Environmental Science and Water Management
- Keywords
- water resources data, surface water, groundwater level, river discharge, surface water quality, rainfall, well data, springs, test holes, aquifers, water consumption, water abstraction, public water supply, irrigation, dissolved oxygen, specific conductance, time series
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review