Contaminants found in treated wastewater discharged to streams, including pharmaceuticals and per- and polyfluoroalkyl substances (PFAS), are of global concern due to their deleterious effects on aquatic ecosystems and potential impacts to human health. Hyporheic zones have strong potential for contaminant attenuation. Assessing this potential requires collection of physical and biogeochemical data within the hyporheic zone. This study tested the applicability of a novel drive-point multilevel system (DP-MLS) for quantifying head profiles and characterizing contaminant concentrations in the hyporheic zone of a temperate region effluent dominated stream (EDS). DP-MLS, each with 4 ports, were installed in the stream bed at two sites, DS-1 and DS-2, 0.2 and 4.7 km downstream of the effluent outfall, respectively. Head profiles were measured and groundwater collected for analysis of pharmaceuticals and PFAS temporally over two years. The DP-MLS withstood rapid changes in stage, ice formation, and floating debris. Vertical hydraulic gradients (VHG) were generally upward but varied in magnitude indicating heterogeneity in hydraulic conductivity and variability in flow conditions. Upward VHG were also about 2X larger at DS-1 than at DS-2. Contaminant concentration profiles consistently showed penetration of pharmaceuticals and PFAS to 1 m below the bed at DS-2 while there was less penetration, lower groundwater concentrations, and more temporal variability in concentrations at DS-1. Integration of the physical and chemical data suggests weaker upwelling conditions at DS-2 are more easily reversed during periods of high stream stage, which could facilitate migration of wastewater contaminants into the bed. However, further studies incorporating other transport processes and reach scale dynamics are required to fully characterize these exchanges. Overall, this study demonstrates the efficacy of these novel DP-MLSs for characterization of the hyporheic zone and provides new insights into the occurrence, composition, and persistence of wastewater derived contaminants in the hyporheic zone of a well-studied EDS.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70517","usgsCitation":"Meyer, J.R., Mianecki, A.L., Occhi, E., Kolpin, D., and LeFevre, G.H., 2026, A novel drive-point multilevel system to investigate PFAS and other contaminants of global concern in the hyporheic zone of a wastewater effluent dominated stream: Hydrological Processes, v. 40, no. 4, e70517, 20 p., https://doi.org/10.1002/hyp.70517.","productDescription":"e70517, 20 p.","ipdsId":"IP-182710","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":503777,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70517","text":"Publisher Index Page"},{"id":503619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United states","state":"Iowa","county":"Johnson County","otherGeospatial":"Muddy Creek","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-91.3677,41.8603],[-91.3673,41.7745],[-91.3675,41.6855],[-91.3671,41.5987],[-91.3679,41.5107],[-91.3687,41.4235],[-91.4839,41.4222],[-91.4843,41.4286],[-91.492,41.4405],[-91.5033,41.4493],[-91.5026,41.452],[-91.4989,41.4538],[-91.4988,41.4592],[-91.5145,41.4676],[-91.5156,41.4704],[-91.5136,41.4767],[-91.5038,41.4779],[-91.5029,41.4874],[-91.5039,41.4933],[-91.5076,41.4939],[-91.5107,41.4944],[-91.5112,41.4971],[-91.508,41.5016],[-91.5098,41.5034],[-91.5117,41.5016],[-91.5148,41.4985],[-91.5197,41.4981],[-91.5196,41.5027],[-91.5281,41.5078],[-91.528,41.511],[-91.5991,41.5107],[-91.7138,41.511],[-91.8291,41.5116],[-91.827,41.6001],[-91.8337,41.6006],[-91.8335,41.6865],[-91.8327,41.775],[-91.8318,41.8617],[-91.716,41.862],[-91.5989,41.8612],[-91.4836,41.8608],[-91.3677,41.8603]]]},\"properties\":{\"name\":\"Johnson\",\"state\":\"IA\"}}]}","volume":"40","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Meyer, J. 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H.","contributorId":370599,"corporation":false,"usgs":false,"family":"LeFevre","given":"G.","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":960564,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70275185,"text":"70275185 - 2026 - The role of groundwater in contributing to surface water salinization in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2026-04-21T15:13:37.377649","indexId":"70275185","displayToPublicDate":"2026-04-18T08:04:50","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The role of groundwater in contributing to surface water salinization in the Upper Colorado River Basin","docAbstract":"Freshwater salinization impacts the availability of water for human use and ecosystem needs worldwide. It has been estimated that total dissolved solids (TDS) in the Colorado River Basin cause $350 million/year in damages and substantial resources are devoted to reducing TDS loading to streams. This study describes the development and application of coupled watershed models that enable TDS source tracking through the subsurface and across the landscape at a seasonal timestep for 35 years in the Upper Colorado River Basin. Results indicate that, on average, 75% of TDS loading to streams originates as baseflow, and 50% of loading is lagged in delivery by longer than one season. Snowmelt was identified as a dominant process controlling the transport of lagged TDS to streams. This approach informs when and where TDS mitigation efforts may be effective in a watershed that serves as a critical water supply for the southwestern United States.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL118834","usgsCitation":"Miller, M.P., Miller, O.L., Longley, P.C., Wise, D.R., McDonnell, M.C., Schmadel, N.M., and Alder, J.R., 2026, The role of groundwater in contributing to surface water salinization in the Upper Colorado River Basin: Geophysical Research Letters, v. 53, no. 8, e2025GL118834, 10 p., https://doi.org/10.1029/2025GL118834.","productDescription":"e2025GL118834, 10 p.","ipdsId":"IP-179871","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":503440,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl118834","text":"Publisher Index Page"},{"id":503269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.90060995927905,\n 42.82938512458236\n ],\n [\n -110.90060995927905,\n 36.020335240877046\n ],\n [\n -107.09503766746343,\n 36.020335240877046\n ],\n [\n -107.09503766746343,\n 42.82938512458236\n ],\n [\n -110.90060995927905,\n 42.82938512458236\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"8","noUsgsAuthors":false,"publicationDate":"2026-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":219283,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Olivia L. 0000-0002-8846-7048","orcid":"https://orcid.org/0000-0002-8846-7048","contributorId":216556,"corporation":false,"usgs":true,"family":"Miller","given":"Olivia","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Longley, Patrick C. 0000-0001-8767-5577","orcid":"https://orcid.org/0000-0001-8767-5577","contributorId":268147,"corporation":false,"usgs":true,"family":"Longley","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wise, Daniel R. 0000-0002-1215-9612","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":217259,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDonnell, Morgan C. 0000-0001-6946-9286","orcid":"https://orcid.org/0000-0001-6946-9286","contributorId":359926,"corporation":false,"usgs":false,"family":"McDonnell","given":"Morgan","middleInitial":"C.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":959905,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmadel, Noah M. 0000-0002-2046-1694","orcid":"https://orcid.org/0000-0002-2046-1694","contributorId":219105,"corporation":false,"usgs":true,"family":"Schmadel","given":"Noah","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":959906,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":959907,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70275246,"text":"70275246 - 2026 - Hydrogeology, groundwater salinity distributions, and assessment of the effect of oil-production activities on groundwater in the Midway Valley area, western Kern County, San Joaquin Valley, California","interactions":[],"lastModifiedDate":"2026-04-24T14:10:27.768067","indexId":"70275246","displayToPublicDate":"2026-04-17T08:57:51","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11111,"text":"PLOS Water","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeology, groundwater salinity distributions, and assessment of the effect of oil-production activities on groundwater in the Midway Valley area, western Kern County, San Joaquin Valley, California","docAbstract":"This study seeks to determine the effects of oil field produced water disposal operations and well mechanical integrity issues on groundwater quality in oil fields in the southwest San Joaquin Valley, California. Whereas previous studies used groundwater wells to study shallow aquifers outside the oil fields, this study demonstrates that future approaches may use oil well geophysical logs to map groundwater head gradients, create salinity profiles and document changes in salinity over time in oil field areas with sparse groundwater well data and at depths greater than 330 m. We also incorporate an analysis of well histories to determine potential effects of compromised wellbore seals on changes in aquifer quality that cannot be explained by water disposal practices. Water quality in the aquifers is naturally brackish across most of the area, with better quality groundwater occurring in the eastern part. Geophysical logs are used to determine salinity variations within aquifers including the depth at which TDS exceeds 10,000 mg/L. This depth ranges from 366 m in the northwest to approximately 1,500 m in the southeast. Oil well porosity logs are used to determine water table elevations. These logs indicate the water table slopes south-southeast, showing the predominant groundwater flow direction is from oil field disposal areas toward better quality groundwater east of the oil fields. Geophysical logs show formation resistivity near some disposal facilities has decreased over time, indicating the salinity of the aquifer has increased due to disposal of saline produced water in injection wells and ponds. Oil well history analysis suggests that increased salinity over time in water-saturated sand intervals >1.5 km from disposal facilities may be caused by mechanical failures and/or incomplete borehole seals in poorly constructed or abandoned wellbores prevalent throughout the study area—particularly wells drilled prior to 1930.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pwat.0000450","usgsCitation":"Gillespie, J.M., Gannon, R., Ball, L.B., Warden, J.G., Everett, R.R., and Stephens, M.J., 2026, Hydrogeology, groundwater salinity distributions, and assessment of the effect of oil-production activities on groundwater in the Midway Valley area, western Kern County, San Joaquin Valley, California: PLOS Water, v. 5, no. 4, e0000450, 26 p., https://doi.org/10.1371/journal.pwat.0000450.","productDescription":"e0000450, 26 p.","ipdsId":"IP-180280","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":503759,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000450","text":"Publisher Index Page"},{"id":503509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Midway Valley area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120,\n 35.5\n ],\n [\n -119,\n 35.5\n ],\n [\n -119,\n 34.75\n ],\n [\n -120,\n 34.75\n ],\n [\n -120,\n 35.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":219675,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice","email":"","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gannon, Riley 0000-0002-1239-1083","orcid":"https://orcid.org/0000-0002-1239-1083","contributorId":205967,"corporation":false,"usgs":true,"family":"Gannon","given":"Riley","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":960229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warden, John G. 0000-0003-1384-458X","orcid":"https://orcid.org/0000-0003-1384-458X","contributorId":215846,"corporation":false,"usgs":true,"family":"Warden","given":"John","email":"","middleInitial":"G.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Everett, Rhett R. 0000-0001-7983-6270","orcid":"https://orcid.org/0000-0001-7983-6270","contributorId":208212,"corporation":false,"usgs":true,"family":"Everett","given":"Rhett","email":"","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960231,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephens, Michael J. 0000-0001-8995-9928","orcid":"https://orcid.org/0000-0001-8995-9928","contributorId":205895,"corporation":false,"usgs":true,"family":"Stephens","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960232,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70275178,"text":"70275178 - 2026 - Water volumes, heat flow, and solute discharge from Old Faithful Geyser eruptions, Yellowstone National Park, USA","interactions":[],"lastModifiedDate":"2026-04-21T15:01:47.79332","indexId":"70275178","displayToPublicDate":"2026-04-17T07:49:27","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Water volumes, heat flow, and solute discharge from Old Faithful Geyser eruptions, Yellowstone National Park, USA","docAbstract":"The iconic Old Faithful Geyser in Yellowstone National Park, USA, has attracted a significant amount of research because of the relative regularity and impressive size of its eruptions. Numerous studies have included observations, measurements, and analyses that informed models of geyser eruptions. However, fundamental quantities, including the associated mass and heat discharged, remain poorly constrained. In April 2025 we measured the volume of water from 45 Old Faithful Geyser eruptions using a portable flume in an outflow channel and specific conductance measurements in the Firehole River. We used high-speed video to perform velocimetry, measured changes in water chemistry to calculate the volume of water evaporated along the outflow channels, and used thermodynamic calculations to estimate the volume of water erupted as steam and to quantify the geyser's heat output. The calculated average volume of water discharged by Old Faithful Geyser in each eruption is 27.9 ± 9.4 m3, with no relation between eruption volume and the length of the preceding eruption interval. Video analysis of the eruption's liquid-dominated phase yields similar volumes of 21–30 m3. The calculated heat flow from the geyser is 2.2–2.4 MW and the average annual discharge of chloride, fluoride, and arsenic are 63 tons, 3.9 tons, and 241 kg, respectively. Average annual silica deposition rate on the geyser cone and along the outflow channels is 7 tons. This study provides a methodology for future studies at geysers worldwide and a baseline for monitoring future activity changes at Old Faithful.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2026.108624","usgsCitation":"Hurwitz, S., McCleskey, R., Rudolph, M.L., Peek, S., Roth, D.A., Schott-Atkins, M., Manga, M., Folz Donahue, K.F., Reed, M.H., and Hungerford, J.D., 2026, Water volumes, heat flow, and solute discharge from Old Faithful Geyser eruptions, Yellowstone National Park, USA: Journal of Volcanology and Geothermal Research, v. 474, 108624, 13 p., https://doi.org/10.1016/j.jvolgeores.2026.108624.","productDescription":"108624, 13 p.","ipdsId":"IP-185069","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":503750,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2026.108624","text":"Publisher Index Page"},{"id":503268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Old Faithful Geyser, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.05006455962126,\n 45.0129140640631\n ],\n [\n -111.05006455962126,\n 43.754298426623194\n ],\n [\n -109.3525348558879,\n 43.754298426623194\n ],\n [\n -109.3525348558879,\n 45.0129140640631\n ],\n [\n -111.05006455962126,\n 45.0129140640631\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"474","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":216321,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":959885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleskey, R. 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Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":959890,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Manga, Michael","contributorId":370162,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":33781,"text":"U.C. Berkeley","active":true,"usgs":false}],"preferred":false,"id":959891,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Folz Donahue, Kiernan F.","contributorId":370163,"corporation":false,"usgs":false,"family":"Folz Donahue","given":"Kiernan","middleInitial":"F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":959892,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reed, Mara H.","contributorId":370164,"corporation":false,"usgs":false,"family":"Reed","given":"Mara","middleInitial":"H.","affiliations":[{"id":33781,"text":"U.C. Berkeley","active":true,"usgs":false}],"preferred":false,"id":959893,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hungerford, Jefferson D.G.","contributorId":370165,"corporation":false,"usgs":false,"family":"Hungerford","given":"Jefferson","middleInitial":"D.G.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":959894,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70275076,"text":"ofr20261002 - 2026 - Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system","interactions":[{"subject":{"id":70273478,"text":"70273478 - 2026 - Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system","indexId":"70273478","publicationYear":"2026","noYear":false,"title":"Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system"},"predicate":"SUPERSEDED_BY","object":{"id":70275076,"text":"ofr20261002 - 2026 - Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system","indexId":"ofr20261002","publicationYear":"2026","noYear":false,"title":"Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system"},"id":1}],"lastModifiedDate":"2026-04-20T17:44:26.164652","indexId":"ofr20261002","displayToPublicDate":"2026-04-16T14:10:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1002","displayTitle":"Computation of Regional Groundwater Budgets for the Virginia Coastal Plain Aquifer System","title":"Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system","docAbstract":"Computation of detailed groundwater flow budgets for subdivisions of the Virginia Coastal Plain aquifer system has enabled quantification and more thorough understanding of groundwater flow within this important water resource. A zone budget analysis based on previously published groundwater models of the Virginia Coastal Plain and Virginia Eastern Shore indicates that groundwater conditions vary substantially throughout the Coastal Plain aquifer system because of local variations in hydrogeology and historical and ongoing variations in groundwater use and management. Decades of substantial groundwater withdrawal from the Coastal Plain aquifer system have altered groundwater flow from predevelopment conditions. Rates of sustainable withdrawal are limited because the downward groundwater flow rate into confined aquifers is a relatively small part of the total groundwater budget for the aquifer system compared to the rate of recharge at the land surface.
Analyses of groundwater budgets from the Virginia Coastal Plain model indicate that groundwater flow is generally outward from the surficial aquifer to rivers and coastal waterbodies and downward through a series of underlying aquifers and confining units to the Potomac aquifer, which is the deepest aquifer and the source of most groundwater withdrawals. Downward flow into the Potomac aquifer is estimated to be only 7 percent of total net precipitation-derived net recharge at the land surface but makes up about 66 percent of inflow to the aquifer in Virginia, with much of the remaining inflow occurring laterally from outside of defined groundwater budget regions in Virginia. For several decades prior to 2010, high rates of withdrawal from the Potomac aquifer resulted in substantial decline in groundwater storage in the aquifer and in most overlying aquifers and confining units. From 2010 to 2023, rates of withdrawal substantially lower than the historical maximum resulted in small net increases in groundwater storage in the confined aquifer system for most regions of the Virginia Coastal Plain. Nevertheless, for the same period, groundwater storage for the entire model domain continues to incrementally decline, indicating that storage recovery in Virginia is offset by a continued decrease in storage in areas beneath the Chesapeake Bay or adjacent areas of Maryland and North Carolina. Withdrawals from the Potomac aquifer have induced substantial downward flow which is a large part of groundwater budgets for confined aquifers such as the Potomac. For the most recent simulated conditions (2023) downward groundwater flow continues, but because vertical flow rates are a function of the difference between water pressure in the upper surficial systems and lower confined units, rates of downward flow are lower than those in earlier decades as the confined water levels partially recover from larger groundwater withdrawals in the past. Geographically, groundwater flow is generally inward from perimeter regions of the Virginia Coastal Plain toward central regions with the largest withdrawal rates. Groundwater inflow from coastal regions could be contributing to saltwater intrusion, even though that was not measured in this study.
Analyses of groundwater budgets from the Virginia Eastern Shore peninsula, a geographic region of the Virginia Coastal Plain, indicate that groundwater flow for that isolated aquifer system is generally outward from the surficial aquifer to coastal water bodies and downward into the confined Yorktown-Eastover aquifer system, which is the source of most withdrawals. Downward groundwater flow into the confined Yorktown-Eastover aquifer system is estimated to be less than 2 percent of total recharge and less than 9 percent of net recharge at the water table but makes up more than 93 percent of all inflow to the confined aquifer system. Decades of substantial but relatively consistent groundwater withdrawals have induced greater downward flow rates into the confined aquifer system but also have resulted in loss of groundwater from storage. For the most recent simulated period (2023), estimated storage loss accounts for slightly under 7 percent of withdrawals from the confined aquifer system. The reported withdrawal rate for this period from the confined Yorktown-Eastover system is near the highest reported rate for the Virginia Eastern Shore, which means that the storage depletion is expected to continue, even though groundwater levels appear to be relatively stable. Estimated groundwater flow rates upward from the confining unit underlying the Yorktown-Eastover system and low rates of inflow from coastal water bodies underscore ongoing concerns about up-coning and lateral intrusion of salty groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261002","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"Pope, J.P., Gordon, A.D., and Frederiks, R.S., 2026, Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system: U.S. Geological Survey Open-File Report 2026–1002, 48 p., https://doi.org/10.3133/ofr20261002. [Supersedes USGS Preprint https://doi.org/10.31223/X5HB5D.]","productDescription":"Report: viii, 48 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-185679","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":503256,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119369.htm","linkFileType":{"id":5,"text":"html"}},{"id":502777,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13GJEYW","text":"USGS data release","linkHelpText":"Input and output files from the Zonebudget program used with MODFLOW models to compute regional groundwater budgets for the Virginia Coastal Plain aquifer system"},{"id":502776,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1002/images/"},{"id":502775,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1002/ofr20261002.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1002 XML"},{"id":502772,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1002/coverthb.jpg"},{"id":502773,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1002/ofr20261002.pdf","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1002 PDF"},{"id":502774,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261002/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1002 HTML"}],"country":"United States","state":"Virginia","otherGeospatial":"Virginia Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.5,\n 38.5\n ],\n [\n -75,\n 38.5\n ],\n [\n -75,\n 36.55435844550527\n ],\n [\n -77.5,\n 36.55435844550527\n ],\n [\n -77.5,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
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Ice jams occur regularly at the southern outlet of Osoyoos Lake, which spans the border between the State of Washington and British Columbia, Canada. In recent winters, ice jams caused (1) decreases in downstream discharge that may adversely affect salmon spawning habitat and (2) short-duration lake-level rise that can interfere with lake level management agreements. In response, water managers sought to understand the environmental conditions associated with the historical ice-jam occurrences on Osoyoos Lake. Researchers compiled datasets of discharge, lake level, and air temperature from four meteorological and three hydrologic stations near Oroville, Washington, to determine “ice-jam” or “non-ice-jam” days from 1942 to 2024.
After confirming known ice jams since 1994 using Landsat 8–9 and Sentinel–2 satellite imagery along with discharge, lake level, and air temperature data, researchers designated ice-jam days. They conducted statistical analyses to examine environmental conditions associated with ice-jam occurrences on Osoyoos Lake. Statistical tests indicated significant differences in wind speed, wind direction, and air temperature between ice-jam and non-ice-jam days. A linear discriminant-analysis model correctly predicted 12 of 13 historical ice-jam days since 1994 and determined that ice jams are more likely under westerly and northwesterly winds near or above 10 kilometers per hour (km/h) and minimum temperatures near or below –9.4 degrees Celsius (°C). An analysis of historical discharge suggests that ice jams have occurred since at least the 1940s, but 13 ice jam days occurred in the past decade (2014–2024), exceeding any previous decade. The daily minimum air temperature in the Osoyoos Lake region has increased at a rate of 0.021 °C per year since the 1940s, but ice jams usually occur in winters with colder average temperatures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265003","collaboration":"Prepared in cooperation with the International Osoyoos Lake Board of Control","programNote":"Water Availability and Use Science Program","usgsCitation":"Sutfin, N.A., and Breen, S.J., 2026, Historical ice jams and associated environmental conditions on Osoyoos Lake: U.S. Geological Survey Scientific Investigations Report 2026–5003, 38 p., https://doi.org/10.3133/sir20265003.","productDescription":"vii, 38 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171288","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":503254,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119368.htm","linkFileType":{"id":5,"text":"html"}},{"id":502874,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5003/sir20265003.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5003 XML"},{"id":502873,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265003/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5003 HTML"},{"id":502872,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5003/sir20265003.pdf","size":"49.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5003 PDF"},{"id":502871,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5003/coverthb.jpg"},{"id":502875,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5003/images/"}],"country":"Canada, United States","state":"British Columbia, Washington","otherGeospatial":"Osoyoos Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.67443538186532,\n 49.11443094771283\n ],\n [\n -119.3142803507082,\n 49.11443094771283\n ],\n [\n -119.3142803507082,\n 48.87431047779373\n ],\n [\n -119.67443538186532,\n 48.87431047779373\n ],\n [\n -119.67443538186532,\n 49.11443094771283\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Washington Water Science Center
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Ice jams are accumulations of ice that partially block water from flowing downstream in rivers and lakes. Ice jams form at the shallow outlet of Osoyoos Lake, which drains into the Okanogan River at the border of the United States and Canada. These ice jams can temporarily reduce river flow downstream, which can harm salmon habitat and cause short lived increases in lake levels that complicate international agreements for managing water levels.
To better understand when and why these ice jams form, researchers from the U.S. Geological Survey examined historical records of river flow, lake level, and air temperature data from stations near Oroville, Washington (located just south of the lake outlet), for the years 1942–2024. Researchers used satellite images and environmental data during 1994–2024 to confirm known ice jams and then identified “ice jam days” for that period.
The team compared weather conditions on ice jam days and non-ice-jam days. They found that ice jams are more likely to form when winds blow from the west or northwest at speeds of about 10 kilometers per hour or more, and when minimum temperatures drop to –9.4 degrees Celsius or lower. A statistical model based on air temperature, wind speed, and wind direction correctly identified nearly all known ice jam days since 1994. While the statistical model identified some days without ice jams as ice-jam days, no ice-jam days occurred outside of the range of wind and temperature conditions identified.
Although ice jams have occurred since at least the 1940s, they have become more frequent in recent years: 13 ice jam days occurred during 2014–2024, more than in any previous decade. Even though winter temperatures in the Osoyoos Lake region have risen slightly over time, ice jams tend to occur during colder than average winters.
Understanding the conditions that lead to ice jams can help decision-makers better anticipate when ice jams may occur and plan for their potential effects on salmon habitat and lake level management.
","publicationDate":"2026-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sutfin, Nicholas A. 0000-0003-4429-7814","orcid":"https://orcid.org/0000-0003-4429-7814","contributorId":357883,"corporation":false,"usgs":true,"family":"Sutfin","given":"Nicholas","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breen, Stephen J. 0000-0002-2630-6206","orcid":"https://orcid.org/0000-0002-2630-6206","contributorId":369971,"corporation":false,"usgs":true,"family":"Breen","given":"Stephen","middleInitial":"J.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959462,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70275535,"text":"70275535 - 2026 - Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems","interactions":[],"lastModifiedDate":"2026-05-04T16:56:07.20148","indexId":"70275535","displayToPublicDate":"2026-04-16T09:50:08","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17103,"text":"Water Biology and Security","active":true,"publicationSubtype":{"id":10}},"title":"Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems","docAbstract":"In intermittent stream systems, including those occurring in Texas, USA, the severity of low-flow conditions, duration of seasonal disconnection, and frequency of no-flow events have been amplified by drought. Documentation of these no-flow events is necessary to evaluate ecosystem health. However, many intermittent reaches remain un-gauged given that perennial river sec-tions are often prioritized for gauge placement. Our objectives were to 1) document stream flow using Stream Temperature, Intermittency, and Conductivity (STIC) loggers to determine the frequency and duration of no-flow events in intermittent tributaries of the Colorado River, Texas and 2) compare logger data to publicly available data from streamflow discharge and precipitation gauge networks to understand differences among these data types for drying event characterization. We use these comparisons to summarize benefits and limitations of the application of in-stream data loggers. STIC loggers were deployed at 19 sites, one in each pool and riffle habitat of a stream reach. STIC loggers recorded a measurement of relative conductance every six hours from June 2022 to March 2024, which was used to determine the presence or absence of flow connectivity in a reach. No-flow duration among intermittent reaches varied between 37 and 270 days across tributaries during an ongoing drought in the study area. Overall, logger data was more precise than discharge data for characterizing no-flow events or precipitation data when documenting presence of water in the stream channel due to runoff. Lack of discharge gauges in intermittent tributaries left large sections of stream reaches undocumented and resulted in mischaracterization of flow patterns. Drought severity across the tributaries did not follow longitudinal patterns that would be expected by the climatic precipitation gradient of the study area. More research is needed to determine if factors such as population size affect severity. Likewise, precipitation data did not correlate well with logger water presence data, lacking consideration for groundwater recharge, soil hydrophobicity, and surface compaction. This study shows that to monitor no-flow events, detailed spatial datasets are necessary and that STIC loggers are useful tools that provide data to fill spatial information gaps and facilitate more accurate flow characterization and water presence data in intermittent systems.","language":"English","publisher":"Elsevier","doi":"10.1016/j.watbs.2026.100626","usgsCitation":"Cooper, C.R., Rogosch, J.S., Smith, N.G., Robertson, C.R., and Wilson, W.M., 2026, Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems: Water Biology and Security, 8 p., https://doi.org/10.1016/j.watbs.2026.100626.","productDescription":"8 p.","ipdsId":"IP-170052","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":504183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watbs.2026.100626","text":"Publisher Index Page"},{"id":503953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Colorado River tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.25288697239256,\n 32.83973386818306\n ],\n [\n -103.66787485319756,\n 31.396795472090005\n ],\n [\n -95.91239697047968,\n 27.731334360060373\n ],\n [\n -95.88841147436196,\n 29.31705583154367\n ],\n [\n -103.25288697239256,\n 32.83973386818306\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cooper, Cienna R.","contributorId":370959,"corporation":false,"usgs":false,"family":"Cooper","given":"Cienna","middleInitial":"R.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":960825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogosch, Jane S. 0000-0002-1748-4991","orcid":"https://orcid.org/0000-0002-1748-4991","contributorId":317717,"corporation":false,"usgs":true,"family":"Rogosch","given":"Jane","middleInitial":"S.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":960826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Nathan G.","contributorId":370961,"corporation":false,"usgs":false,"family":"Smith","given":"Nathan","middleInitial":"G.","affiliations":[{"id":62404,"text":"Texas Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":960827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robertson, Clinton R.","contributorId":370963,"corporation":false,"usgs":false,"family":"Robertson","given":"Clinton","middleInitial":"R.","affiliations":[{"id":62404,"text":"Texas Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":960828,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Wade M.","contributorId":370966,"corporation":false,"usgs":false,"family":"Wilson","given":"Wade","middleInitial":"M.","affiliations":[{"id":62404,"text":"Texas Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":960829,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70275256,"text":"70275256 - 2026 - Late Miocene Colorado River arrival in the Bidahochi basin supports spillover origin of Grand Canyon","interactions":[],"lastModifiedDate":"2026-04-24T14:51:49.560386","indexId":"70275256","displayToPublicDate":"2026-04-16T09:40:30","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Late Miocene Colorado River arrival in the Bidahochi basin supports spillover origin of Grand Canyon","docAbstract":"The timing and mechanism of the integration of the Colorado River and incision of the Grand Canyon remain among geology’s enduring controversies. A key question is the configuration of the upper Colorado River watershed between 11 and 6 million years ago. In this study, we present new evidence from zircon uranium-lead geochronology for the arrival of distinctive Colorado–Green River sediment in the Bidahochi basin by 6.6 million years ago derived from the Browns Park Formation. This is coeval with an order-of-magnitude increase in depositional rate, an increase in carbonate strontium isotope (87Sr/86Sr) ratios, the appearance of large fish species characteristic of fast-flowing waters, and other sedimentological changes. This evidence is consistent with the Colorado River supplying water and sediment to the Bidahochi basin before spillover integration of the river through the Grand Canyon.
","language":"English","publisher":"AAAS","doi":"10.1126/science.adz6826","usgsCitation":"He, J.J., Crow, R.S., Douglass, J.R., Holm-Denoma, C., Vazquez, J.A., Gootee, B.F., Lidzbarski, M.I., Pianowski, L., Gray, H., Heitmann, E., Pearthree, P., House, K., and Dulin, S., 2026, Late Miocene Colorado River arrival in the Bidahochi basin supports spillover origin of Grand Canyon: Science, v. 395, no. 6795, p. 285-295, https://doi.org/10.1126/science.adz6826.","productDescription":"11 p.","startPage":"285","endPage":"295","ipdsId":"IP-179903","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":503513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada, Utah","otherGeospatial":"Bidahochi basin, Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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,{"id":70275748,"text":"70275748 - 2026 - Logical data model for hydrographic data based on HY_Features concepts","interactions":[],"lastModifiedDate":"2026-05-18T14:33:53.753123","indexId":"70275748","displayToPublicDate":"2026-04-16T09:24:17","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":24339,"text":"OCG Public Engineering Report","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"25-045","title":"Logical data model for hydrographic data based on HY_Features concepts","docAbstract":"This report describes background and design of the “hydrofabric data model” which defines logic for implementation of data schemas and software that deals with hydrologic geospatial data. As a “logical” data model, the hydrofabric data model specifies details necessary to support compatibility of data and software that satisfy diverse needs without unnecessarily restricting implementation details. The logic presented in this report is based on concepts defined in WaterML2 Part 3 Surface Hydrology Features Concepts and is designed to serve the needs of a range of hydroscience use cases.
Development of international community standards applicable to hydrofabrics began, prompted by the World Meteorological Organization Commission for Hydrology, in 2012 [5] . More than 10 years later, this report documents one aspect of a long-term research and development activity that traces its roots back that far.
This report describes terminology, use cases, and background as context preceding presentation of the logical model and discussion of its design. Three appendices document related data models, an example encoding of the hydrofabric data model, and an artificial schematic and tabular data example. The sections of the report can be accessed in the Clause 5 section.
","language":"English","publisher":"Open Geospatial Consortium","usgsCitation":"2026, Logical data model for hydrographic data based on HY_Features concepts: OCG Public Engineering Report 25-045, v, 76 p.","productDescription":"v, 76 p.","ipdsId":"IP-172082","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":504473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":504462,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://www.opengis.net/doc/PER/hydrofabric"}],"noUsgsAuthors":false,"publicationDate":"2026-04-16","publicationStatus":"PW","contributors":{"editors":[{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":961717,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}} ,{"id":70275100,"text":"sir20265140 - 2026 - Analyses of meteorological and hydrological records support Tribal members’ accounts of changing climate on the Fort Apache Reservation, east–central Arizona","interactions":[],"lastModifiedDate":"2026-04-20T17:40:45.285521","indexId":"sir20265140","displayToPublicDate":"2026-04-15T15:25:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5140","displayTitle":"Analyses of Meteorological and Hydrological Records Support Tribal Members’ Accounts of Changing Climate on the Fort Apache Reservation, East–Central Arizona","title":"Analyses of meteorological and hydrological records support Tribal members’ accounts of changing climate on the Fort Apache Reservation, east–central Arizona","docAbstract":"The Fort Apache Reservation in east–central Arizona, home to the White Mountain Apache Tribe of the Fort Apache Reservation, Arizona, contains several climate zones because of the large variation in surface elevation within the reservation. This study was carried out in cooperation with the White Mountain Apache Tribe of the Fort Apache Reservation, Arizona, to raise awareness of how the changing climate affects the Fort Apache Reservation. This report documents the evaluation of existing multidecadal meteorological and hydrological datasets for the Fort Apache Reservation, used to evaluate the effects of a changing climate on the reservation. In this evaluation, near-surface air temperature, snow depth, snow water equivalent, precipitation, and streamflow datasets were analyzed for monotonic trends indicative of changing climatic conditions during specified periods of time. The results of these trend analyses were then compared with the Tribal community's memories of the changing climate.
Trend analysis of near-surface air temperatures from a U.S. Historical Climatological Network station on the Fort Apache Reservation at Whiteriver, Arizona, indicated that mean annual air temperatures have increased by an average of 2.48 degrees Fahrenheit from 1980 to 2023. Records from the same station also indicated that average monthly maximum temperatures recorded for March increased by 5.39 degrees Fahrenheit for the same time period.
Annual precipitation at the five precipitation stations used in this study decreased greatly from the 1980s to 2023. The largest total decrease was 10.07 inches, or 34.7 percent. However, only one of the two precipitation stations with longer term data available prior to 1980 had a significant negative trend when data from the entire period of record, from 1901 to 2023, were analyzed.
Trend analyses show a decrease in the annual maximum snow water equivalent and an earlier disappearance of the snowpack at two Natural Resources Conservation Service snow telemetry stations in the mountainous region just east of the Fort Apache Reservation from 1981 to 2023. Based on the trend analyses, the average annual maximum snow water equivalent has decreased by more than 40 percent at both stations, and the average date when the snowpack was fully melted at the stations in the spring has moved earlier in time from late April to early April or late March. However, a statistically significant trend was not determined for the early April snow water equivalent measured at a nearby Natural Resources Conservation Service snow course across its period of record, indicating that the history of mountain snowpack in this area is not fully understood. Analysis of snowfall data from a National Oceanic and Atmospheric Administration Cooperative Observer Program network station on the Fort Apache Reservation at McNary 2N, AZ (station 025412) indicated that, on average, the measured total annual snowfall at the station decreased 42.4 percent from 1935 to 2023.
Streamflow data from six U.S. Geological Survey streamgages on the Fort Apache Reservation were analyzed for trends. For most streamflow gages, statistically significant trends were not determined for tested parameters when the entire streamflow period of record was used for stations with records going back to at least the 1960s. However, when the data from 1980 to 2023 was tested, most of the streamflow parameters had statistically significant negative trends. All six streamgages showed a decrease in average annual runoff of at least 50 percent from 1980 to 2023; one streamgage showed an 81.8 percent decrease.
A similar statistical finding was observed in the analysis of the annual spring snowmelt peak from one of the six streamgages used in the study and located in an area receiving measurable amounts of snowmelt runoff. When data from the entire period of record (1958–2023) was used, no trend in streamflow was determined; however, a significant negative trend was determined from 1980 to 2023, indicating a decrease in average annual springtime runoff of 62.6 percent. Statistical analysis on the timing of the annual spring snowmelt peak at the same streamgage indicated the snowmelt peak is happening on average about 12 days earlier now (2023) than it did in the past. The trend results for the timing of the annual spring snowmelt peak were the same and statistically significant for both periods tested (1958–2023 and 1980–2023). Two of the streamflow records from the Fort Apache Reservation were compared to the Palmer Hydrological Drought Index computed for Arizona Climate Division 4 (East Central) by the National Centers for Environmental Information. The comparison showed that the streamflow records generally tracked the Palmer Hydrological Drought Index.
In interviews, Tribal community members living on the Fort Apache Reservation described the changes in climate that they observed during their lifetimes. Common themes reported were that air temperatures have become warmer, and the weather is less predictable with changes in seasonal patterns. Drier conditions, lower snowfall, shorter winters, and lower river levels were also reported. These community member observations align with the results of this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265140","collaboration":"Prepared in cooperation with the White Mountain Apache Tribe of the Fort Apache Reservation, Arizona","usgsCitation":"Mason, J.P., 2026, Analyses of meteorological and hydrological records support Tribal members’ accounts of changing climate on the Fort Apache Reservation, east–central Arizona: U.S. Geological Survey Scientific Investigations Report 2026–5140, 58 p., https://doi.org/10.3133/sir20265140.","productDescription":"Report: x, 58 p.; Data Release","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-180087","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":503253,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119367.htm","linkFileType":{"id":5,"text":"html"}},{"id":502810,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P144FN7Q","text":"USGS data release","linkHelpText":"U.S. Historical Climatology Network version 2.5 dataset for station Whiteriver 1 SW, Arizona, from 1873 to 2024, used in Analysis of Meteorological and Hydrological Records Support Tribal Members’ Accounts of Changing Climate on the Fort Apache Reservation, east–central Arizona"},{"id":502808,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5140/sir20265140.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5140 XML"},{"id":502807,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265140/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5140 HTML"},{"id":502806,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5140/sir20265140.pdf","size":"24.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5140 PDF"},{"id":502805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5140/coverthb.jpg"},{"id":502809,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5140/images/"}],"country":"United States","state":"Arizona","otherGeospatial":"Fort Apache Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.75,\n 34.5\n ],\n [\n -109.45,\n 34.5\n ],\n [\n -109.45,\n 33.5\n ],\n [\n -110.75,\n 33.5\n ],\n [\n -110.75,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
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520 N. Park Avenue, Suite 221
Tucson, AZ 85719
There have been sporadic reports of aquatic, benthic Microcoleus proliferations in freshwater rivers, lakes, and reservoirs for four decades, with reports increasing in frequency over the last twenty years, suggesting a possible rise in their global distribution, frequency, and intensity. Microcoleus can produce anatoxins which are neurotoxic, and ingestion of toxic mats has caused hundreds of dog fatalities and raised serious human and ecological health concerns. This review synthesizes and evaluates current knowledge on Microcoleus distribution, taxonomy, toxin production, toxicity, ecology, environmental drivers, and biotic interactions. Toxin-producing Microcoleus have been reported in at least 18 countries, though many regions have not conducted toxin testing, suggesting a broader but under-reported distribution. Proliferations occur across diverse habitats, including cobble-bedded streams, large sandy rivers, reservoirs, and lakes. Microcoleus proliferations also occur on macrophytes, both in lakes and rivers. Genomic analyses currently classify anatoxin-producing Microcoleus into distinct species, with all known anatoxin-producers isolated from freshwater ecosystems. Anatoxin concentrations vary widely over space and time, within and among waterbodies. While studies on environmental drivers remain limited, research in cobble-bedded rivers suggests that moderate enrichment of dissolved inorganic nitrogen and low dissolved reactive phosphorus concentrations in the water column promote proliferation. Metagenomic approaches have revealed unique nutrient acquisition and storage strategies used by Microcoleus. Key knowledge gaps remain around the environmental and ecological triggers of proliferation, toxin production, genomic diversity and microbial interactions. Addressing these gaps through coordinated, global studies using robust datasets and consistent methods is critical to improve prediction, monitoring, and mitigation of this increasingly widespread public and ecological health threat.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2026.125441","usgsCitation":"Kelly, L.T., Beach, D.G., Blaszczak, J.R., Bouma-Gregson, K., Brown, S.M., Cheng, H., Davidson, J.L., Fastner, J., Francis, M., Garcia Jimenez, A., Genzoli, L., Goel, R., Gonzalez, D., Handley, K.M., Hilt, S., Humbert, J., Jamieson, R., Johnston, L., Junier, P., Lawrence, J., McCarron, P., Meissner, S., Mormando, J., Puddick, J., Quiblier, C., Rajpirathap, N., Schampera, C., Selwood, A., Shearer, K., Sohrab, A., Stancheva, R., Valadez-Cano, C., Zebrecky, J.M., and Wood, S.A., 2026, The global proliferation of aquatic, benthic Microcoleus: Taxonomy, distribution, toxin production, ecology, and future directions: Water Research, v. 294, 125441, 22 p., https://doi.org/10.1016/j.watres.2026.125441.","productDescription":"125441, 22 p.","ipdsId":"IP-183789","costCenters":[{"id":154,"text":"California Water Science 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Jordan M.","contributorId":366196,"corporation":false,"usgs":false,"family":"Zebrecky","given":"Jordan","middleInitial":"M.","affiliations":[],"preferred":false,"id":955405,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Wood, Susanna A.","contributorId":366197,"corporation":false,"usgs":false,"family":"Wood","given":"Susanna","middleInitial":"A.","affiliations":[],"preferred":false,"id":955406,"contributorType":{"id":1,"text":"Authors"},"rank":34}]}} ,{"id":70275000,"text":"gip265 - 2026 - Mount Rainier volcanic hazard information","interactions":[],"lastModifiedDate":"2026-04-20T17:37:33.148135","indexId":"gip265","displayToPublicDate":"2026-04-14T15:46:56","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"265","displayTitle":"Mount Rainier Volcanic Hazard Information","title":"Mount Rainier volcanic hazard information","docAbstract":"Eruptions at Mount Rainier produce lava flows, plumes of airborne volcanic ash, and avalanches of hot rock, ash, and gas—pyroclastic flows—that rush down the steep, ice-covered slopes of the volcano. Hot rock and ash ejected during an eruption can melt large quantities of snow and ice, forming huge, fast moving mudflows called lahars that travel 30+ miles, all the way to Puget Sound. Very large lahars can also form when weak and water-saturated rock high on the volcano collapses with or without volcanic activity. Learn more inside!
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip265","isbn":"978-1-4113-4657-4","usgsCitation":"Weiss-Racine, H.F., Bard, J.A., Ball, J.L, and Mastin, C.L., 2026, Mount Rainier volcanic hazard information: U.S. Geological Survey General Information Product 265, https://doi.org/10.3133/gip265.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-186867","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":503251,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119365.htm","linkFileType":{"id":5,"text":"html"}},{"id":502667,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/265/gip265.pdf","text":"Brochure","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 265"},{"id":502666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/265/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.09920525440018,\n 46.5\n ],\n [\n -122.7,\n 46.5\n ],\n [\n -122.7,\n 47.6\n ],\n [\n -121.09920525440018,\n 47.6\n ],\n [\n -121.09920525440018,\n 46.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
U.S. Geological Survey
David A. Johnston Cascades Volcano Observatory
1300 SE Cardinal Court, Building 10, Suite 100
Vancouver, Washington, 98683-9589
Coral bleaching events have become increasingly common across the Hawaiian Archipelago since 1996 because of more frequent and intense marine heatwaves. The most significant bleaching event to date occurred from 2014 to 2015, which resulted in catastrophic state-wide coral loss. Bleaching events with less severe effects also occurred in 1996 and 2019. To understand the long-term effects of repeated bleaching events, along with other anthropogenic factors such as water quality, storms, sewage runoff, and coastal development, on coral reefs on the Kona Coast of the Island of Hawaiʻi, the U.S. Geological Survey, in collaboration with the National Park Service, collected underwater imagery in the early 2000s (baseline survey) and again in 2022 (resurvey). These images were captured within and adjacent to the National Historic Parks (NHP) and National Historic Sites (NHS) of Kaloko-Honokōhau NHP (KAHO), Puʻuhonua o Hōnaunau NHP (PUHO), and Puʻukohola Heiau NHS (PUHE). Imagery was classified for live coral cover and dominant type (four coral types, rubble, macroalgae, and two bottom substrate types). Change of percent live coral cover was determined for all sites. Change of coral and non-coral dominant types were calculated by aggregating classifications for each park into coral and non-coral. Net coral cover decreased between the baseline and resurvey period across all three parks, though PUHE exhibited the greatest loss of live coral cover. Across all three parks, the occurrence of lower coral cover classes (0–20 percent) increased and higher coral cover classes (greater than 50 percent) decreased. Furthermore, the total occurrence of non-coral dominant type classifications (rubble, macroalgae, sand, and volcanic pavement) increased by approximately 25 percent across all three parks, with PUHE experiencing a nearly 90-percent increase in the occurrence of non-coral types. There was little to no effect of water depth on change of live coral cover, indicating that marine heatwave driven bleaching events and additional anthropogenic influences affected the entire reef across all water depths from the lower fore reef to the reef flat.
Because coral loss was more severe at PUHE and PUHO than KAHO, creating a monitoring framework that utilizes periodic underwater camera surveys and fixed diver transects by the National Park Service would contextualize the periodic spatial surveys to the fixed transects that have greater temporal resolution. Similarly, increased frequency of spatial surveys would allow for the National Park Service to continue monitoring changes to critical nearshore habitats and marine resources relevant to National Park jurisdiction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261061","collaboration":"Prepared in cooperation with the National Park Service","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"McPherson, M.L., Logan, J.B., Alkins, K.A., Groff, S., Hatcher, G.A., Gibbs, A.E., Cochran, S.A., and Storlazzi, C.D., 2026, Evaluation of benthic habitat change within the national historic sites of Hawaiʻi’s Kona Coast: U.S. Geological Survey Open-File Report 2026–1061, 28 p., https://doi.org/10.3133/ofr20261061.","productDescription":"Report: vii, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-178080","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":503252,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119366.htm","linkFileType":{"id":5,"text":"html"}},{"id":502799,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZPWNS","text":"USGS data release","linkHelpText":"Underwater imagery and classifications of the substrate and coral reef habitat on the Kona coast of the Island of Hawaiʻi, from 2003, 2004, and 2022"},{"id":502798,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1061/images"},{"id":502795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1061/ofr20261061.pdf","text":"Report","size":"8.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1061 PDF"},{"id":502794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1061/coverthb.jpg"},{"id":502796,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261061/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1061 HTML"},{"id":502797,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1061/ofr20261061.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1061 XML"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kona Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.77407070286742,\n 20.114961049183847\n ],\n [\n -156.2156728366818,\n 20.114961049183847\n ],\n [\n -156.2156728366818,\n 19.280147118202123\n ],\n [\n -155.77407070286742,\n 19.280147118202123\n ],\n [\n -155.77407070286742,\n 20.114961049183847\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
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Despite the extensive natural gas pipeline network in the United States that intersects streams and other sensitive habitats, few case studies use a comparative upstream-to-downstream approach to evaluate potential short- and long-term effects of pipeline stream crossings from pre-construction through post-restoration. In 2017, the U.S. Geological Survey, in cooperation with the Virginia Department of Environmental Quality, deployed real-time continuous stream monitoring stations upstream and downstream from six proposed Mountain Valley Pipeline stream crossings in southwestern Virginia. Water temperature and turbidity data collected at the upstream and downstream sites were compared across three periods—before stream crossing construction, during stream crossing construction, and after stream crossing construction—to determine potential influences from the pipeline stream crossing. Additionally, the monitoring network was used to notify regulators of potentially anomalous conditions throughout the entire monitoring period.
The results of this study indicate that pipeline stream crossing did not affect long-term or short-term upstream-to-downstream water temperature conditions or long-term upstream-to-downstream turbidity conditions in any of the six monitored streams. Some short-term anomalously elevated turbidity conditions were observed and attributable to pipeline stream crossing; however, the magnitudes and durations were not sufficient to alter the long-term turbidity regimes of the streams in which they were observed. The application of the monitoring network as a real-time alert system successfully alerted regulators to potentially anomalous conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265011","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"Foster, B.M., Maas, C.M., and Flota, A.L., 2026, Assessment of natural gas pipeline construction on stream temperature and turbidity in southwestern Virginia, 2017–25: U.S. Geological Survey Scientific Investigations Report 2026–5011, 40 p., https://doi.org/10.3133/sir20265011. [Supersedes preprint https://doi.org/10.31223/X5XT9G.]","productDescription":"ix, 40 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-182747","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":503250,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119364.htm","linkFileType":{"id":5,"text":"html"}},{"id":502763,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5011/images"},{"id":502762,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5011/sir20265011.XML","description":"SIR 2026-5011 XML"},{"id":502764,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265011/full","text":"HTML Document","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5011 HTML"},{"id":502761,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5011/sir20265011.pdf","text":"Report","size":"12.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5011 PDF"},{"id":502760,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5011/coverthb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.75,\n 37.5\n ],\n [\n -80.75,\n 37\n ],\n [\n -79.75,\n 37\n ],\n [\n -79.75,\n 37.5\n ],\n [\n -80.75,\n 37.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
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In anticipation for increased funding made possible by the Water Resources Development Act of 2020, the Upper Mississippi River Restoration (UMRR) Program identified a need to conduct river-wide assessments of floodplain vegetation. In January 2025, we assembled a group of subject matter experts to perform the following tasks:
This document is a summarization of what occurred at the meeting and provides suggested next steps toward developing the capacity to conduct routine long-term monitoring and assessment of floodplain vegetation as part of the Upper Mississippi River Restoration Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261001","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program and the National Great Rivers Research and Education Center","usgsCitation":"Weiss, S.A., Trumper, M.L., De Jager, N.R., Guyon, L.J., and Van Appledorn, M., 2026, Proceedings of the Floodplain Vegetation Monitoring Workshop for the Long Term Resource Monitoring Element of the Upper Mississippi River Restoration Program, January 7–8, 2025, Moline, Illinois: U.S. Geological Survey Open-File Report 2026–1001, 29 p., https://doi.org/10.3133/ofr20261001.","productDescription":"viii, 29 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179749","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":502679,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261001/full"},{"id":502678,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1001/images/"},{"id":502675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1001/coverthb.jpg"},{"id":502676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1001/ofr20261001.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1001"},{"id":502677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1001/ofr20261001.XML"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.84995652179344,\n 47.38059349406069\n ],\n [\n -94.51879131555569,\n 45.1779196807436\n ],\n [\n -91.67435276851998,\n 43.23290915291983\n ],\n [\n -91.65945041845046,\n 38.647765678088035\n ],\n [\n -89.78655455017767,\n 38.796516838946786\n ],\n [\n -90.68564412568368,\n 40.42375517193139\n ],\n [\n -89.76470125204189,\n 42.49536202047\n ],\n [\n -92.0520195269138,\n 45.04310183668423\n ],\n [\n -94.84995652179344,\n 47.38059349406069\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
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Cyanobacterial toxins (cyanotoxins) represent a substantial threat to drinking water supplies and safe recreational uses of freshwater resources in watersheds worldwide. Monitoring cyanotoxins can be difficult because toxin events are variable in both space and time, are not always persistent, can be moved easily by wind and currents, and may be degraded biotically or abiotically. Thus, monitoring programs that collect discrete samples on a monthly or even bimonthly interval can miss key events and underestimate cyanotoxin risk or if they capture a high-concentration event, can give a false impression that cyanotoxins are a widespread health hazard. The use of Solid Phase Adsorption Toxin Tracking (SPATT) samplers helps address this issue by providing a time-weighted average estimate of dissolved cyanotoxin occurrence and relative concentrations. SPATT samplers have been used as a complement to traditional monitoring programs and can help elucidate cyanotoxin dynamics. SPATT samplers have been used by six U.S. Geological Survey (USGS) Water Science Centers (New York, California, Oregon, Upper Midwest, New Jersey, and Lower Mississippi-Gulf) to monitor various cyanotoxins in waterbodies such as streams, rivers, lakes, waterfalls, estuaries, and drinking-water intakes. Despite their use across the USGS, there is little guidance available to ensure consistent approaches and data quality across the Bureau. This report summarizes best practices for SPATT deployment and analysis, synthesizes data and describes lessons learned from USGS studies, identifies priority knowledge gaps, and offers considerations for future targeted experiments to help improve data collection and interpretation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255093","programNote":"Water Resources Mission Area—National Water Quality Program","usgsCitation":"Jaegge, A.C., Bouma-Gregson, K., Byl, T.D., Carpenter, K.D., Christensen, V.G., Gorney, R.M., Graham, J.L., Heckathorn, H.A., Olds, H.T., Reilly, P.A., Rosen, J.J., and Stouder, M.D., 2026, Opportunities and challenges in using Solid Phase Adsorption Toxin Tracking (SPATT) samplers for monitoring cyanotoxins in freshwater and estuarine environments: U.S. Geological Survey Scientific Investigations Report 2025–5093, 39 p., https://doi.org/10.3133/sir20255093.","productDescription":"Report: x, 39 p.; 6 Data Releases","numberOfPages":"39","onlineOnly":"Y","ipdsId":"IP-153043","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":503249,"rank":12,"type":{"id":36,"text":"NGMDB Index 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U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Geochemical data from sedimentary rocks are the primary source of information regarding Earth's surface evolution through time, including its air and water envelopes and interactions with life and deep Earth processes. The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.
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M.A., Knoll, A.H., Kreitsmann, T., Kulkarni, A., Kunert, A., Kunzmann, M., Lai, J., Lease, R.O., Li, C., Li, S., Lipp, A., Liu, Y., Loydell, D., Lu, X., Maloney, K., Mänd, K., Millikin, A.E., Mills, N.T., Motomura, K., Mwinde, C.N., Nelson, L., Nieminski, N.M., O'Connell, B., O'Sullivan, E., Okubo, J., Olah, J., Ossa Ossa, F., Ostrander, C., Paiste, K., Partin, C.A., Pereira, E., Peters, S., Playter, T.L., Porter, S.M., Poulton, S.W., Pruss, S.B., Qiu, Z., Quinn, D., Remirez, M., Richiano, S., Richoz, S., Rico, K., Ritzer, S.R., Roney, Z., Rooney, A.D., Rose, W.C., Rugen, E., Sahoo, S.K., Schoepfer, S.D., Sclafani, J.A., Sheldon, N.D., Shen, Y., Shields, G., Singh, P., Singh, A., Slotznick, S.P., Smith, E., Song, H., Spinks, S., Stockey, R.G., Strauss, J., Stüeken, E., Sun, Z., Tang, D., Tarhan, L., Thomson, D., Tosca, N., Tostevin, R., Tu, C., Vizcaíno, M., Wang, Y., Wang, C., Wang, X., Warren, L., Webb, L., Wilby, P.R., Woltz, C.R., Wood, R., Wu, Y., Yang, X., Yurchenko, I.A., Zhang, 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Cyanobacterial harmful algal blooms (HABs) are a documented problem along this freshwater-to-marine waterway where nutrient enrichment has been identified as a key factor in bloom occurrence but has not been experimentally tested in the river. This study is the first to test the effects of inorganic nutrient loading on phytoplankton assemblages in the Caloosahatchee River and the effects of different nutrient sources on phytoplankton dynamics at different times of the year. Three independent, in situ experiments were conducted to test the effects of daily, incrementally increased ammonium, nitrate, and phosphate loading on phytoplankton at different times of the year (summer, fall, winter). Over the 72-hour enclosure period, phytoplankton abundance metrics (cell concentration, chlorophyll-a, and phycocyanin), dissolved oxygen, and pH increased, and fluorescent dissolved organic matter and turbidity decreased in all treatments and controls. Increased phytoplankton abundance metrics relative to controls were observed after 72 hours of exposure to elevated ammonium and nitrate in summer and only ammonium in winter, suggesting periodic nitrogen limitation; however, no treatment effects on phytoplankton assemblage structure in terms of resemblance and diversity metrics were found. Increases in total cell concentrations were driven by elevated growth rates of already dominant taxa but not sufficiently to form a visible bloom. Cyanobacteria consistently dominated the phytoplankton, particularly Aphanocapsa and Merismopedia, whereas the common HAB-forming Microcystis maintained consistently low abundance. This study provides new information on the ecology of phytoplankton assemblages in the Caloosahatchee River and could be used by water resources managers to evaluate strategies for controlling cyanobacterial HABs in the river.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265141","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Nova Southeastern University, and Florida Gulf Coast University","programNote":"Environmental Health Program","usgsCitation":"Mazzei, V., Loftin, K.A., Karwacki, E., Lopez, J.V., Krausfeldt, L.E., Rosen, B.H., and Urakawa, H., 2026, Phytoplankton responses to experimental nitrogen and phosphorus loading in the eutrophic and colored Caloosahatchee River, Florida: U.S. Geological Survey Scientific Investigations Report 2026–5141, 32 p., https://doi.org/10.3133/sir20265141.","productDescription":"Report: x, 32 p.; 3 Data Releases","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146459","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":502717,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119361.htm","linkFileType":{"id":5,"text":"html"}},{"id":502324,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5141/sir20265141.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5141 XML"},{"id":502323,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JX9NA1","text":"USGS Data Release","linkHelpText":"Water-quality profiles within the Caloosahatchee River and twelve fiberglass tanks, during experimental nutrient addition treatments, 2021 (ver. 1.1, August 2024)"},{"id":502322,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99ELCEC","text":"USGS Data Release","linkHelpText":"Caloosahatchee River nutrient enrichment mesocosms—Phytoplankton taxonomic quantification September 2019, June 2020, September 2020, February 2021"},{"id":502321,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P900BQZR","text":"USGS Data Release","linkHelpText":"Water-quality profiles within the Caloosahatchee River and twelve fiberglass tanks, during experimental nutrient addition treatments, 2020"},{"id":502317,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5141/sir20265141.pdf","size":"10.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5141"},{"id":502309,"rank":1,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5141/images"},{"id":502310,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5141/coverthb4.jpg"},{"id":502325,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265141/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5141 HTML"}],"country":"United States","state":"Florida","otherGeospatial":"Caloosahatchee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80,\n 27.33\n ],\n [\n -82.5,\n 27.33\n ],\n [\n -82.5,\n 26.4\n ],\n [\n -80,\n 26.4\n ],\n [\n -80,\n 27.33\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Us- USGS Publications Warehouse
","tableOfContents":"Harmful algal blooms, particularly cyanobacteria harmful algal blooms (cyanoHABs), have emerged as a substantial global concern because of their detrimental effects on water quality and aquatic ecosystem health. CyanoHABs can produce cyanotoxins, which pose serious health risks to humans and wildlife, such as liver failure and respiratory distress. This is particularly concerning for water bodies that serve as drinking-water sources. Recent trends indicate an increase in the frequency and intensity of cyanoHABs globally. This study focuses on the Raritan Basin Water Supply Complex in New Jersey, where extensive monitoring was conducted from August 2020 to August 2021 to assess the presence of cyanobacteria and associated cyanotoxins. The research utilized a combination of discrete water-quality sampling, continuous monitoring, and solid phase adsorption toxin tracking (SPATT) to capture the dynamics of cyanotoxin occurrence and potential transport. Findings revealed a widespread presence of cyanobacteria and potential for cyanotoxin production, although actual cyanotoxin concentrations remained below drinking water and recreational thresholds. The study, conducted by the U.S. Geological Survey (USGS) in collaboration with the New Jersey Water Supply Authority (NJWSA) and the New Jersey Department of Environmental Protection (NJDEP), highlighted the limitations of traditional sampling methods and emphasized that continuous monitoring can support better understanding of how cyanoHAB conditions change over time and in different places. Genetic testing included quantitative polymerase chain reaction (qPCR) analyses, which demonstrated higher sensitivity, or increased findings of cyanobacteria compared to microscopy, indicating the potential for use in early warning systems. This research underscores that integrating various detection methods and hydrological data can enhance understanding of cyanotoxin dynamics in river systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265128","collaboration":"Prepared in cooperation with the New Jersey Water Supply Authority and the New Jersey Department of Environmental Protection","programNote":"Water Availability and Use Science Program","usgsCitation":"Gorney, R.M., Heckathorn, H.A., Clonan, K.R., Reilly, P.A., Cahalane, K., and Bjorklund, B.W., 2026, Occurrence of cyanobacteria and associated cyanotoxins in the Raritan Basin Water Supply Complex, New Jersey, August 2020 to August 2021: U.S. Geological Survey Scientific Investigations Report 2026–5128, 30 p., https://doi.org/10.3133/sir20265128.","productDescription":"Report, ix, 30 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":502716,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119360.htm","linkFileType":{"id":5,"text":"html"}},{"id":502326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5128/coverthb3.jpg"},{"id":502327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5128/sir20265128.pdf","text":"Report","size":"6.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5128 PDF"},{"id":502329,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5128/sir20265128.XML","description":"SIR 2026-5128 XML"},{"id":502330,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5128/images"},{"id":502328,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265128/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5128 HTML"},{"id":502331,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1S5DQ6A","text":"USGS Data Release","linkHelpText":"Cyanobacteria, other water-quality, and discharge data collected from the Raritan River Basin, New Jersey, August 2020 through August 2021"}],"country":"United States","state":"New Jersey","otherGeospatial":"Raritan Basin Water Supply Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.0833,\n 40.9167\n ],\n [\n -75.0833,\n 40.0167\n ],\n [\n -74.1667,\n 40.0167\n ],\n [\n -74.1667,\n 40.9167\n ],\n [\n -75.0833,\n 40.9167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, New Jersey 08648
The City of Lincoln, Nebraska, has been monitoring concentrations of arsenic in their source water and evaluating their options for treatment and removal since at least 2002. In 2022, the City of Lincoln, Nebr., with funding assistance from the Nebraska Water Sustainability Fund, began cooperating with the U.S. Geological Survey to examine arsenic concentrations in surface water and groundwater in the lower Platte River valley and the area around City of Lincoln Water System (LWS) well field. Arsenic data collected from the Platte River since 1974 were examined using the “weighted regression on time, discharge, and season” model, which compared the streamflow (also referred to as “discharge”), time of year, and season to estimate concentrations of arsenic. Annual mean arsenic concentrations modeled for more than 49 years at the Platte River at Louisville, Nebr., U.S. Geological Survey streamgage (station 06805500), indicated a significant increasing trend. Arsenic concentrations in the Platte River were seasonal, with the highest concentrations being observed during mid- to late summer. When seasonal patterns and streamflow were combined with arsenic concentrations in the Platte River during low streamflow conditions, groundwater contributions, which can have higher arsenic concentrations, make up a larger portion of the streamflow. Arsenic samples were collected from upstream rivers in 2022 and 2023 and were paired to analyze the arsenic contributions at the U.S. Geological Survey streamgage on the Platte River near Ashland, Nebr. (station 06801000), near the City of Lincoln well field. The arsenic concentrations from the streamgage on the Platte River near Ashland, Nebr., location, were higher than the U.S. Geological Survey streamgage on the Elkhorn River at Waterloo, Nebr. (station 06800500), and significantly lower than at the U.S. Geological Survey streamgage on the Platte River near Leshara, Nebr.(station 06796500), indicating that the Platte River usually contributes a higher concentration of arsenic than does the Elkhorn River as they join near Ashland, Nebr. During 1991–2023, six groundwater monitoring wells were analyzed to identify trends in arsenic concentrations. Two of the six wells had a positive trend during the 33-year period. One monitoring well did not reveal a long-term trend during this period but showed a trend during 2019–23, correlating to a period when the island in the middle of the Platte River was connected to the east bank of the river when manganese reducing conditions were present and groundwater levels were declining in the well. Across all wells the oxidation and reduction (redox) condition during the time of sampling was assessed. Mixed anoxic and (or) oxic redox condition was the most common redox process and the highest sampled arsenic concentrations in monitoring wells were observed in anoxic conditions driven by manganese reduction. Groundwater arsenic concentrations had seasonal variation around the City of Lincoln well field, with higher arsenic concentrations tending to be further south in comparison to samples collected further north. Isotope samples were collected and analyzed in surface water and groundwater around the LWS well field. The samples indicate that the proportion of surface water present in the LWS production wells can be higher in the spring and lower in the summer. With higher arsenic concentrations observed in the stream water during the summer period, the LWS source water can be affected by these elevated arsenic concentrations even though the proportion of surface water is lower.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265138","collaboration":"Prepared in cooperation with City of Lincoln, Nebraska","usgsCitation":"Moser, M.T., Cherry, M.L., and Hall, B.M., 2026, Arsenic and isotope concentrations in the lower Platte River valley of eastern Nebraska, early 1970s to 2023: U.S. Geological Survey Scientific Investigations Report 2026–5138, 23 p., https://doi.org/10.3133/sir20265138.","productDescription":"Report: vii; 23 p.; Data Release; Dataset","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-161400","costCenters":[{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":502306,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS data release"},{"id":502305,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5138/images"},{"id":502304,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265138/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5138 HTML"},{"id":502303,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5138/sir20265138.pdf","text":"Report","size":"5.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5138"},{"id":502302,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5138/coverthb.jpg"},{"id":502715,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119359.htm","linkFileType":{"id":5,"text":"html"}},{"id":502308,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5138/sir20265138.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5138 XML"},{"id":502307,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://www.usgs.gov/mission-areas/water-resources/science/usgs-national-water-quality-network","text":"USGS National Water Quality Network"}],"country":"United States","state":"Nebraska","otherGeospatial":"lower Platte River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.95,\n 41.667\n ],\n [\n -97,\n 41.667\n ],\n [\n -97,\n 40.667\n ],\n [\n -95.95,\n 40.667\n ],\n [\n -95.95,\n 41.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Plains Water Science Center
U.S. Geological Survey
1217 Biltmore Drive Lawrence, KS 66049
5231 South 19th Street Lincoln, NE 68512
Lake St. Clair Metropark Beach in Michigan has a history of closures because of elevated Escherichia coli (E. coli) concentrations in its recreational waters. To reduce closures, restoration projects were implemented in 2021 to deter waterfowl from congregating on the beach. In this study, the U.S. Geological Survey, in cooperation with the Michigan Department of the Environment, Great Lakes, and Energy and in collaboration with Huron-Clinton Metroparks and the Macomb County Health Department, monitored E. coli from 2022–23 in surface water, shallow groundwater, and sediment at Lake St. Clair Metropark Beach. Results were compared to data from a prerestoration (2018–19) study. A significant decrease in daily geometric mean E. coli concentrations in surface water was observed postrestoration, but the number of high concentration events increased. This resulted in more frequent beach closures postrestoration. Surface-sediment E. coli concentrations significantly decreased after restoration, and waterfowl populations generally decreased from 2021 to 2023, suggesting that the deterrence measures could be influencing E. coli concentrations in surface sediments and surface water. Groundwater E. coli concentrations were orders of magnitude higher than those in surface water and revealed no change correlated with restoration. Seepage measurements indicated that groundwater occasionally discharges into surface water, potentially providing a transport mechanism for E. coli to reach the lake. Continued monitoring and consideration of environmental factors could help to better understand the beach system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265134","issn":"2328-0328","collaboration":"Prepared in cooperation with Michigan Department of Environment, Great Lakes, and Energy","usgsCitation":"Lockmiller, H.A., Byers, V.C., and Fogarty, L.R., 2026, Escherichia coli monitoring and assessment in 2022 and 2023 after beach restoration at Lake St. Clair Metropark Beach, Macomb County, Michigan: U.S. Geological Survey Scientific Investigations Report 2026–5134, 24 p., https://doi.org/10.3133/sir20265134.","productDescription":"Report: viii, 24 p.; Data Release; Dataset","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-165989","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":502714,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119358.htm","linkFileType":{"id":5,"text":"html"}},{"id":502180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5134/coverthb.jpg"},{"id":502187,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","linkHelpText":"U.S. Geological Survey National Water Information System database"},{"id":502186,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13GGCXS","text":"USGS data release","linkHelpText":"Water flux and avian species data at Lake St. Clair Metropark in Macomb County, Michigan, collected during recreational seasons of 2021, 2022, and 2023"},{"id":502184,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5134/sir20265134.XML","description":"SIR 2026-5134 XML"},{"id":502183,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265134/full","text":"HTML","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5134 HTML"},{"id":502182,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5134/sir20265134.pdf","text":"Report","size":"4.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5134"},{"id":502181,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5134/images"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake St. Clair Metropark Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.7975,\n 42.57167\n ],\n [\n -82.7975,\n 42.570278\n ],\n [\n -82.794722,\n 42.570278\n ],\n [\n -82.794722,\n 42.57167\n ],\n [\n -82.7975,\n 42.57167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), have been detected at combined concentrations above 2,000 nanograms per liter (ng/L) at groundwater seep locations near the Coakley Landfill Superfund site, in North Hampton, New Hampshire. The landfill was active from 1972 to 1985. An impermeable cap was placed on the landfill in 1998. The adjacent area to the Coakley Landfill has many water supply wells, and transport of PFAS compounds to the wells is a concern. Fracture anisotropy in the underlying bedrock aquifer complicates the understanding of PFAS transport because groundwater preferentially travels along fractures that may not align with the prevailing groundwater flow direction. In 2018, the U.S Environmental Protection Agency and the U.S. Geological Survey began an investigation of the groundwater flow from the Coakley Landfill site. This report describes the modification of a numerical groundwater-flow model for the local area around the Coakley Landfill and summarizes findings of the investigation. In addition, this report includes a brief description of PFOA and PFOS occurrence, a discussion of model construction, evaluation of model performance through calibration, and discussion of simulation results for two periods (before and after capping). Limitations are also discussed. Results show that simulated groundwater flow moves from the Coakley Landfill to the west and north. Advective transport modeling using particle tracking shows that groundwater from the landfill discharges primarily to streams to the west and north, and a small amount is transported to distal wells. Dilution of contaminants through advection and dispersion likely plays a role in whether PFAS compounds from the landfill will be detected above laboratory reporting levels at distal wells.
","language":"English","publisher":"EarthArXiv","doi":"10.31223/X53761","usgsCitation":"Harte, P., and Collins, A.L., 2026, Simulation of groundwater flow to evaluate hydrogeologic controls on a PFAS plume, Coakley Landfill Superfund Site, Rockingham County, New Hampshire: EarthArXiv, preprint posted April 09, 2026, https://doi.org/10.31223/X53761.","productDescription":"72 p.","ipdsId":"IP-188248","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":502680,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2026-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Harte, Phil 0000-0002-7718-1204","orcid":"https://orcid.org/0000-0002-7718-1204","contributorId":369789,"corporation":false,"usgs":false,"family":"Harte","given":"Phil","affiliations":[{"id":63928,"text":"Former USGS (ret.)","active":true,"usgs":false}],"preferred":false,"id":959179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Andrew L. 0000-0003-4751-7333","orcid":"https://orcid.org/0000-0003-4751-7333","contributorId":332093,"corporation":false,"usgs":true,"family":"Collins","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959180,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70275750,"text":"70275750 - 2026 - Describing the seasonal abundance and growth rates of larval fishes across productivity gradients in Lake Huron in 2017","interactions":[],"lastModifiedDate":"2026-05-18T15:07:07.260384","indexId":"70275750","displayToPublicDate":"2026-04-09T07:57:51","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Describing the seasonal abundance and growth rates of larval fishes across productivity gradients in Lake Huron in 2017","docAbstract":"Several of the Laurentian Great Lakes, including Lake Huron, have undergone oligotrophication in the past decades and prey fish biomass has concomitantly declined. One potential mechanism to explain declines in prey fish is slower growth and lower survival at the larval stage. To determine whether reduced productivity affects the growth of larval fish, we sampled larval fishes and their environment approximately monthly from May through August 2017 at nine nearshore to offshore transects across Lake Huron that included North Channel, Georgian Bay, and the main basin. North Channel transects had the highest chlorophyll a concentrations and zooplankton densities. Rainbow smelt (Osmerus mordax), burbot (Lota lota), bloater (Coregonus hoyi), and shiners (Notropis spp.) were the most abundant larval fish taxa, peaking in June and July. We aged rainbow smelt and bloater using otoliths, and estimates of growth rate revealed rainbow smelt always grew faster. For both species, we explained variation in total length by comparing 16 candidate linear mixed-effects models, with age, chlorophyll a, zooplankton, water temperature, larval fish density, and interactions with age as predictor variables. For rainbow smelt, the full model was best; zooplankton had the greatest effect, but it was negative and opposite from our hypothesis. For bloater, four candidate models were most parsimonious; water temperature had the greatest effect, and it was positive as predicted from our hypothesis. To more effectively evaluate whether zooplankton can limit larval fish growth and survival, we recommend that future designs conduct more frequently sampling within a year even at the expense of fewer transects.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2026.102817","usgsCitation":"Bunnell, D.B., Eaton, L.A., Dieter, P.M., Collingsworth, P., Hoffman, J.C., Rowe, M.D., Stott, W., Ackiss, A.S., and Rutherford, E.S., 2026, Describing the seasonal abundance and growth rates of larval fishes across productivity gradients in Lake Huron in 2017: Journal of Great Lakes Research, 102817, 15 p., https://doi.org/10.1016/j.jglr.2026.102817.","productDescription":"102817, 15 p.","ipdsId":"IP-182655","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":504477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.58185200845517,\n 46.519644985424634\n ],\n [\n -84.58185200845517,\n 43.082049264308324\n ],\n [\n -79.6331783866257,\n 43.082049264308324\n ],\n [\n -79.6331783866257,\n 46.519644985424634\n ],\n [\n -84.58185200845517,\n 46.519644985424634\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bunnell, David B. 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":216545,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","middleInitial":"B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":961635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eaton, Lauren A.","contributorId":211815,"corporation":false,"usgs":false,"family":"Eaton","given":"Lauren","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":961636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dieter, Patricia M. 0000-0003-1686-2679","orcid":"https://orcid.org/0000-0003-1686-2679","contributorId":217345,"corporation":false,"usgs":true,"family":"Dieter","given":"Patricia","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":961637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collingsworth, Paris D.","contributorId":354643,"corporation":false,"usgs":false,"family":"Collingsworth","given":"Paris D.","affiliations":[{"id":84645,"text":"Illinois-Indiana SeaGrant","active":true,"usgs":false}],"preferred":false,"id":961638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoffman, Joel C.","contributorId":361653,"corporation":false,"usgs":false,"family":"Hoffman","given":"Joel","middleInitial":"C.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":961639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rowe, Mark D.","contributorId":208536,"corporation":false,"usgs":false,"family":"Rowe","given":"Mark","middleInitial":"D.","affiliations":[],"preferred":false,"id":961640,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stott, Wendylee 0000-0002-5252-4901","orcid":"https://orcid.org/0000-0002-5252-4901","contributorId":242990,"corporation":false,"usgs":false,"family":"Stott","given":"Wendylee","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":961641,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ackiss, Amanda Susanne 0000-0002-8726-7423","orcid":"https://orcid.org/0000-0002-8726-7423","contributorId":272165,"corporation":false,"usgs":true,"family":"Ackiss","given":"Amanda","email":"","middleInitial":"Susanne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":961642,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rutherford, Edward S.","contributorId":175426,"corporation":false,"usgs":false,"family":"Rutherford","given":"Edward","email":"","middleInitial":"S.","affiliations":[{"id":12789,"text":"NOAA Great Lakes Environmental Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":961643,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70275113,"text":"70275113 - 2026 - Natural language processing for groundwater insights","interactions":[],"lastModifiedDate":"2026-04-16T15:52:57.800537","indexId":"70275113","displayToPublicDate":"2026-04-08T10:51:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Natural language processing for groundwater insights","docAbstract":"No abstract available.
","language":"English","publisher":"National Grrundwater Association","doi":"10.1111/gwat.70067","usgsCitation":"Christenson, C., and McCoy, K., 2026, Natural language processing for groundwater insights: Groundwater, https://doi.org/10.1111/gwat.70067.","ipdsId":"IP-182736","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":502984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.70067","text":"Publisher Index Page"},{"id":502942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Christenson, Catherine 0000-0001-5944-2186 cchristenson@usgs.gov","orcid":"https://orcid.org/0000-0001-5944-2186","contributorId":200263,"corporation":false,"usgs":true,"family":"Christenson","given":"Catherine","email":"cchristenson@usgs.gov","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Kurt J. 0000-0002-9756-8238","orcid":"https://orcid.org/0000-0002-9756-8238","contributorId":216196,"corporation":false,"usgs":true,"family":"McCoy","given":"Kurt J.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959475,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274719,"text":"dr1224 - 2026 - Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2017–22","interactions":[],"lastModifiedDate":"2026-04-10T18:18:25.031448","indexId":"dr1224","displayToPublicDate":"2026-04-08T09:46:27","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1224","displayTitle":"Selected Water-Quality Data from the Cedar River and Cedar Rapids Well Fields, Cedar Rapids, Iowa, 2017–22","title":"Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2017–22","docAbstract":"The Cedar River alluvial aquifer is the source of drinking water in Cedar Rapids, Iowa. Production wells are completed in the alluvial aquifer approximately 40 to 80 feet below land surface. The City of Cedar Rapids and the U.S. Geological Survey have studied the groundwater-flow system and water quality of the aquifer in the vicinity of Cedar Rapids since 1992. Results of these studies documented hydrologic conditions, water quality, and geochemistry of the alluvial aquifer and interactions with the Cedar River. Water-quality samples were collected for studies involving well field monitoring, trends, source-water protection, groundwater geochemistry, surface-water–groundwater interaction, and pesticides in groundwater and surface water. Water quality was analyzed for dissolved major ions (boron, bromide, calcium, chloride, fluoride, iron, magnesium, manganese, potassium, silica, sodium, sulfate, and total dissolved solids), dissolved nutrients (ammonia as nitrogen, ammonia plus organic nitrogen as nitrogen, nitrite plus nitrate as nitrogen, nitrite as nitrogen, orthophosphate as phosphorus, and phosphorus), dissolved organic carbon, and selected pesticides. Physical characteristics (alkalinity, dissolved oxygen, pH, specific conductance, and water temperature) were measured on site and recorded for each water sample collected. This report presents the results of routine water-quality data-collection activities from October 2017 through September 2022. Methods of data collection, quality assurance, water-quality analyses, and statistical procedures are presented. Data include the results of water-quality analyses from quarterly sampling from monitoring wells, production wells, two water treatment plants, and the Cedar River at Blairs Ferry Road at Palo, Iowa, streamgage (U.S. Geological Survey station number 05464420), as well as monthly nutrient sampling from the Cedar River and Morgan Creek near Covington, Iowa, streamgage (U.S. Geological Survey station number 05464475).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1224","collaboration":"Prepared in cooperation with City of Cedar Rapids Utilities Water Division","usgsCitation":"Meppelink, S.M., and Kalkhoff, S.J., 2026, Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2017–22: U.S. Geological Survey Data Report 1224, 34 p., https://doi.org/10.3133/dr1224.","productDescription":"Report: vii, 34 p.; Dataset","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171718","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":502710,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119355.htm","linkFileType":{"id":5,"text":"html"}},{"id":502244,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1224/dr1224.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1224"},{"id":502243,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1224/coverthb.jpg"},{"id":502245,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1224/dr1224.XML"},{"id":502246,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1224/images/"},{"id":502247,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1224/full"},{"id":502248,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"}],"country":"United States","state":"Iowa","city":"Cedar Rapids","otherGeospatial":"Cedar Rapids Well Fields, Cedar River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.80773266985493,\n 42.032866361741156\n ],\n [\n -91.80773266985493,\n 41.90007413791929\n ],\n [\n -91.50986519614662,\n 41.90007413791929\n ],\n [\n -91.50986519614662,\n 42.032866361741156\n ],\n [\n -91.80773266985493,\n 42.032866361741156\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240