Spatiotemporally continuous estimates of the hydrologic cycle are often generated through hydrologic modeling, reanalysis, or remote sensing (RS) methods and are commonly applied as a supplement to, or a substitute for, in situ measurements when observational data are sparse or unavailable. This study compares estimates of precipitation (P), actual evapotranspiration (ET), runoff (R), snow water equivalent (SWE), and soil moisture (SM) from 87 unique data sets generated by 47 hydrologic models, reanalysis data sets, and remote sensing products across the conterminous United States (CONUS). Uncertainty between hydrologic component estimates was shown to be high in the western CONUS, with median uncertainty (measured as the coefficient of variation) ranging from 11 % to 21 % for P, 14 % to 26 % for ET, 28 % to 82 % for R, 76 % to 84 % for SWE, and 36 % to 96 % for SM. Uncertainty between estimates was lower in the eastern CONUS, with medians ranging from 5 % to 14 % for P, 13 % to 22 % for ET, 28 % to 82 % for R, 53 % to 63 % for SWE, and 42 % to 83 % for SM. Interannual trends in estimates from 1982 to 2010 show common disagreement in R, SWE, and SM. Correlating fluxes and stores against remote-sensing-derived products show poor overall correlation in the western CONUS for ET and SM estimates. Study results show that disagreement between estimates can be substantial, sometimes exceeding the magnitude of the measurements themselves. The authors conclude that multimodel ensembles are not only useful but are in fact a necessity for accurately representing uncertainty in research results. Spatial biases of model disagreement values in the western United States show that targeted research efforts in arid and semiarid water-limited regions are warranted, with the greatest emphasis on storage and runoff components, to better describe complexities of the terrestrial hydrologic system and reconcile model disagreement.
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0000-0003-1151-8908","orcid":"https://orcid.org/0000-0003-1151-8908","contributorId":215753,"corporation":false,"usgs":true,"family":"Saxe","given":"Samuel","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":814837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":223181,"corporation":false,"usgs":true,"family":"Farmer","given":"William H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":814838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":814839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":814840,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220458,"text":"70220458 - 2021 - Rapid-response unsaturated zone hydrology: Small-scale data, small-scale theory, big problems","interactions":[],"lastModifiedDate":"2021-05-14T12:15:26.478434","indexId":"70220458","displayToPublicDate":"2021-03-26T07:08:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7753,"text":"Frontiers in Earth Science","active":true,"publicationSubtype":{"id":10}},"title":"Rapid-response unsaturated zone hydrology: Small-scale data, small-scale theory, big problems","docAbstract":"The unsaturated zone (UZ) extends across the Earth’s terrestrial surface and is central to many problems related to land and water resource management. Flow of water through the UZ is typically thought to be slow and diffusive, such that it could attenuate fluxes and dampen variability between atmospheric inputs and underlying aquifer systems. This would reduce water resource vulnerability to contaminants and water-related hazards. Reducing or negating that effect, however, spatially concentrated and rapid flow and transport through the unsaturated zone is surprisingly common and becoming more so with the increasing frequency and magnitude of extreme hydroclimatic events. Arising from the wide range in the rates and complex modes of nonlinear flow processes, these effects are among the most poorly characterized hydrologic phenomena. Issues of scale present additional difficulties. Equations representing unsaturated processes have been developed and tested on the basis of field and laboratory measurements typically made at scales from pore size to plot size. In contrast, related problems of significant interest to society, including floods, aquifer recharge, landslides, and groundwater contamination, range from watershed to regional scales. The disparity between the scale of our understanding and the scale of interest for societal problems has spurred application of these model equations at increasingly coarse resolutions over larger areas than can be justified by existing measurements or theory. This mismatch in scales requires an assumption that spatially averaging slow diffusive flow and rapid preferential flow can effectively represent the influence of both processes across vast areas. Given the currently inadequate recognition and quantitative characterization of focused and rapid processes in unsaturated flow, these phenomena are critically in need of expanded attention and effort.
Methane is an important greenhouse gas with growing atmospheric concentrations. Freshwater lakes and reservoirs contribute substantially to atmospheric methane concentrations, but the magnitude of this contribution is poorly constrained. Uncertainty stems partially from whether the sites currently sampled represent the global population as well as incomplete knowledge of which environmental variables predict methane flux. Thus, determining the main drivers of methane flux across diverse waterbody types will inform more accurate upscaling approaches. Here we use a new database of total, diffusive, and ebullitive areal methane emissions from 313 lakes and reservoirs (ranging in surface area from 6 m2 to 5,400 km2) to identify the best predictors of methane emission. We found that the best predictors of methane emission differed by waterbody type (lakes vs. reservoirs), and that ecosystem morphometric variables (e.g., surface area and maximum depth) were more important predictors in lakes whereas metrics of autochthonous production (e.g., chlorophyll a) were more important in reservoirs. We also found that productivity strongly predicted methane ebullition, whereas ecosystem morphometry and waterbody type were more important predictors of diffusive methane flux. Finally, we identify several knowledge gaps that limit upscaling efforts. First, we need more methane emission measurements in small reservoirs, large lakes, and both natural and artificial ponds. Additionally, more accurate upscaling efforts require improved global information about waterbody surface area, waterbody type (lake vs. reservoir), ice phenology, and the distribution of productivity‐related predictor variables such as total phosphorus, DOC, and chlorophyll a.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JG005600","usgsCitation":"Deemer, B., and Holgerson, M.A., 2021, Drivers of methane flux differ between lakes and reservoirs, complicating global upscaling efforts: Journal of Geophysical Research-Biogeosciences, v. 126, no. 4, e2019JG005600, 15 p., https://doi.org/10.1029/2019JG005600.","productDescription":"e2019JG005600, 15 p.","ipdsId":"IP-112962","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":385017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holgerson, Meredith A.","contributorId":257243,"corporation":false,"usgs":false,"family":"Holgerson","given":"Meredith","email":"","middleInitial":"A.","affiliations":[{"id":51986,"text":"Departments of Biology and Environmental Studies, St. Olaf College, Northfield, Minnesota, USA","active":true,"usgs":false}],"preferred":false,"id":813863,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219125,"text":"sir20205140 - 2021 - Evaluation and application of the Purge Analyzer Tool (PAT) to determine in-well flow and purge criteria for sampling monitoring wells at the Stringfellow Superfund site in Jurupa Valley, California, in 2017","interactions":[],"lastModifiedDate":"2021-03-25T15:53:32.129298","indexId":"sir20205140","displayToPublicDate":"2021-03-25T09:45:00","publicationYear":"2021","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":"2020-5140","displayTitle":"Evaluation and Application of the Purge Analyzer Tool (PAT) To Determine In-Well Flow and Purge Criteria for Sampling Monitoring Wells at the Stringfellow Superfund Site in Jurupa Valley, California, in 2017","title":"Evaluation and application of the Purge Analyzer Tool (PAT) to determine in-well flow and purge criteria for sampling monitoring wells at the Stringfellow Superfund site in Jurupa Valley, California, in 2017","docAbstract":"The U.S. Geological Survey and U.S. Environmental Protection Agency are developing analytical tools to assess the representativeness of groundwater samples from fractured-rock aquifers. As part of this effort, monitoring wells from the Stringfellow Superfund site in Jurupa Valley in Riverside County, California, approximately 50 miles east of Los Angeles, were field tested to collect information to assist in the evaluation and application of in-well flow as computed by the analytical model called the Purge Analyzer Tool, which computes in-well groundwater travel times for simple piston transport of inflowing groundwater from open intervals of a monitoring well to the pump intake and can provide insight into optimal purging parameters (duration, rate, and pump position) needed for the collection of representative groundwater samples. Field testing of wells included hydraulic, chemistry, and dye tracer analysis to investigate travel times in wells under pumping conditions. The Purge Analyzer Tool was able to replicate dye velocities (travel times) for one of three wells that had appreciable inflow from the aquifer but not the other two wells, which are screened in low-permeability sediments and rock, where flow was dominated by borehole storage. A set of criteria was established to help assess the ability to collect representative groundwater chemistry from monitoring wells; criteria included understanding the height of the static well water column and relative exchange rate between the aquifer and the well.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205140","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Harte, P.T., Perina, T., Becher, K., Levine, H., Rojas-Mickelson, D., Walther, L., and Brown, A., 2021, Evaluation and application of the Purge Analyzer Tool (PAT) to determine in-well flow and purge criteria for sampling monitoring wells at the Stringfellow Superfund site in Jurupa Valley, California, in 2017: U.S. Geological Survey Scientific Investigations Report 2020–5140, 54 p., https://doi.org/10.3133/sir20205140.","productDescription":"Report: ix, 54 p.; Data Release","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103064","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":384640,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191104","text":"Open-File Report 2019–1104","linkHelpText":"- Instructions for Running the Analytical Code PAT (Purge Analyzer Tool) for Computation of In-Well Time of Travel of Groundwater under Pumping Conditions"},{"id":384639,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CGINH0","text":"USGS data release","linkHelpText":"Data associated with the evaluation of the PAT (Purge Analyzer Tool), Stringfellow Superfund site, Jurupa Valley, California, 2017"},{"id":384641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5140/coverthb.jpg"},{"id":384642,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5140/sir20205140.pdf","text":"Report","size":"5.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5140"}],"country":"United States","state":"California","city":"Jurupa Valley","otherGeospatial":"Stringfellow Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.47066974639893,\n 34.019585556900935\n ],\n [\n -117.45178699493408,\n 34.019585556900935\n ],\n [\n -117.45178699493408,\n 34.03078943899101\n ],\n [\n -117.47066974639893,\n 34.03078943899101\n ],\n [\n -117.47066974639893,\n 34.019585556900935\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The United States (US) National Park Service (NPS) manages protected public lands to preserve biodiversity. Exposure to and effects of bioactive organic contaminants in NPS streams are challenges for resource managers. Recent assessment of pesticides and pharmaceuticals in protected-streams within the urbanized NPS Southeast Region (SER) indicated the importance of fluvial inflows from external sources as drivers of aquatic contaminant-mixture exposures. Great Smoky Mountains National Park (GRSM), lies within SER, has the highest biodiversity and annual visitation of NPS parks, but, in contrast to the previously studied systems, straddles a high-elevation hydrologic divide; this setting limits fluvial-inflows of contaminants but potentially increases visitation-driven contaminant deliveries. We leveraged the unique characteristics of GRSM to test further the importance of fluvial contaminant inflows as drivers of protected-stream exposures and to inform the relative importance of potential additional contaminant transport mechanisms, by comparing the estimated risks of 328 pesticides and pharmaceuticals in water at 16 GRSM stream locations to those estimated previously in SER streams. Extensive mixtures (31 compounds) were only observed in an atypical reach on the boundary of GRSM downstream of a wastewater discharge, while limited mixtures (2–5 compounds) were observed in one stream with elevated visitation pressure (recreational “tube floating”). The insecticide, imidacloprid, used to eradicate hemlock woolly adelgid, was detected in 8 (50%) streams. Infrequent exceedances of a cumulative ToxCast-based, exposure-activity ratio (ΣEAR) 0.001 screening-level of concern suggested limited risk to non-target, aquatic vertebrates, whereas exceedances of a cumulative benchmark-based, invertebrate toxicity quotient (ΣTQ) 0.1 screening level at 8 locations indicated generally high risk to invertebrates. The results are consistent with the importance of fluvial transport from extra-park sources as a driver of bioactive-contaminant mixture exposures in protected streams and illustrate the potential additional risks from visitation-driven and tactical-use-pesticides.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.146711","usgsCitation":"Bradley, P., Kulp, M.A., Huffman, B.J., Romanok, K., Smalling, K., Breitmeyer, S.E., Clark, J., and Journey, C., 2021, Reconnaissance of cumulative risk of pesticides and pharmaceuticals in Great Smoky Mountains National Park streams: Science of the Total Environment, v. 781, 146711, 9 p., https://doi.org/10.1016/j.scitotenv.2021.146711.","productDescription":"146711, 9 p.","onlineOnly":"N","ipdsId":"IP-117880","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":436436,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GUEIMD","text":"USGS data release","linkHelpText":"Pesticide and Pharmaceutical Exposure Data for Select Streams within Great Smoky Mountains National Park, 2019"},{"id":384693,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Great Smokey Mountains National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.166259765625,\n 35.03899204678081\n ],\n [\n -82.81494140625,\n 35.03899204678081\n ],\n [\n -82.81494140625,\n 35.782170703266075\n ],\n [\n -84.166259765625,\n 35.782170703266075\n ],\n [\n -84.166259765625,\n 35.03899204678081\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"781","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulp, Matt A.","contributorId":196801,"corporation":false,"usgs":false,"family":"Kulp","given":"Matt","email":"","middleInitial":"A.","affiliations":[{"id":35484,"text":"National Park Service, Great Smoky Mountains National Park","active":true,"usgs":false}],"preferred":false,"id":813009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huffman, Bradley J. 0000-0003-2827-8074","orcid":"https://orcid.org/0000-0003-2827-8074","contributorId":220344,"corporation":false,"usgs":true,"family":"Huffman","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Breitmeyer, Sara E. 0000-0003-0609-1559 sbreitmeyer@usgs.gov","orcid":"https://orcid.org/0000-0003-0609-1559","contributorId":172622,"corporation":false,"usgs":true,"family":"Breitmeyer","given":"Sara","email":"sbreitmeyer@usgs.gov","middleInitial":"E.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":813012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clark, Jimmy 0000-0002-3138-5738","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":221235,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813013,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Journey, Celeste A. 0000-0002-2284-5851","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":221232,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813014,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70262318,"text":"70262318 - 2021 - Suitability of an upper Mississippi River tributary for invasive carp reproduction","interactions":[],"lastModifiedDate":"2025-01-22T16:06:39.189719","indexId":"70262318","displayToPublicDate":"2021-03-25T00:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Suitability of an upper Mississippi River tributary for invasive carp reproduction","docAbstract":"Invasive carp are expanding throughout the upper Mississippi River basin and are of great concern due to their potential economic and ecological impacts. Identification of spawning locations provides critical information on recruitment sources to evaluate potential management strategies. Our objective was to create and validate a spawning habitat suitability model of the Des Moines River, Iowa, during low-, average-, and high-water-level conditions. Backwater availability, abundance of hardpoints (structures that create turbulence), river gradient and sinuosity, water temperature, and continuously free-flowing river lengths were used as model parameters. The model was compared to back-calculated spawning locations from invasive carp eggs collected in 2014–2015. Turbulent hardpoints, river sinuosity, and gradient were not significant predictors of invasive carp spawning locations, and backwater availability in the 25 river kilometers downstream of each reach was inversely correlated with invasive carp spawning locations. Invasive carp eggs were not caught in 2014 despite optimal spawning conditions, revealing that spawning may have high interannual variation. This study suggests that predicting invasive carp reproduction may require variables in addition to those currently proposed.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10551","usgsCitation":"Camacho, C., Sullivan, C., Weber, M., and Pierce, C., 2021, Suitability of an upper Mississippi River tributary for invasive carp reproduction: North American Journal of Fisheries Management, v. 43, no. 1, p. 12-24, https://doi.org/10.1002/nafm.10551.","productDescription":"13 p.","startPage":"12","endPage":"24","ipdsId":"IP-081177","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Des Moines 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Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5120","displayTitle":"Assessment of Water Quality and Discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017","title":"Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017","docAbstract":"The U.S. Geological Survey, Cape Cod National Seashore of the National Park Service, and Friends of Herring River cooperated from 2015 to 2017 to assess nutrient concentrations and fluxes across the ocean-estuary boundary at a dike on the Herring River in Wellfleet, Massachusetts. The purpose of this assessment was to characterize environmental conditions prior to a future removal of the dike, which has restricted saltwater inputs into the Herring River watershed for more than 100 years. Water temperature, dissolved oxygen, pH, and specific conductance were monitored continuously, and flow-weighted composite samples were collected approximately twice per month at the ocean-estuary boundary. Bidirectional discharge was computed for the U.S. Geological Survey Herring River at Chequessett Neck Road at Wellfleet, Massachusetts, streamgage (011058798) by using a stage-area rating and index-velocity ratings developed with acoustic Doppler current profile measurements made upstream and downstream from the dike. LOADEST regression modeling software was used to estimate nutrient fluxes (loads) from composite, paired nutrient concentration and discharge data in conjunction with continuous discharge data. Temperature, dissolved oxygen, pH, and specific conductance were also monitored continuously on two tributaries to the Herring River, Pole Dike Creek and Bound Brook, from late-May 2016 to mid-June 2017. Composite or discrete water samples were collected from the tributaries approximately twice per month in most months from late-May 2016 to mid-June 2017 and analyzed for total nitrogen, total phosphorus, and dissolved organic carbon.
Flow-weighted concentrations of ammonium, nitrate, and total nitrogen on the Herring River at the dike on the ebb tide generally varied between 0.01 and 0.1, 0.003 and 0.03, and 0.3 and 0.7 milligram per liter as nitrogen, respectively. Flow-weighted concentrations of orthophosphate, total dissolved phosphorus, and total phosphorus generally varied between 0.002 and 0.02, 0.003 and 0.06, and 0.03 and 0.1 milligram per liter as phosphorus, respectively, on the ebb tide. Flow-weighted concentrations of silicate and dissolved organic carbon on the ebb tide generally varied between 0.08 and 3.0 milligrams per liter of silica (silicon dioxide), and 1.7 and 5.6 milligrams per liter of carbon, respectively. Ebb tide concentrations of nitrate were highest in winter and lowest in summer. By contrast, ebb tide concentrations of phosphorus species were highest in late summer and early fall and lowest in winter. Silica and dissolved organic carbon did not exhibit systematic variation in seasonal concentrations. There was uncertainty in estimates of nutrient fluxes, but the LOADEST-estimated fluxes indicated that annual (and in almost all cases seasonal) exports (ebb tides) exceeded inputs (flood tides). Ebb tide concentrations of ammonium, nitrate, total nitrogen, and silica were positively correlated with antecedent cumulative 7-day precipitation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205120","collaboration":"Prepared in cooperation with the National Park Service and Friends of Herring River","usgsCitation":"Huntington, T.G., Spaetzel, A.B., Colman, J.A., Kroeger, K.D., and Bradley, R.T., 2021, Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017: U.S. Geological Survey Scientific Investigations Report 2020–5120, 59 p., https://doi.org/10.3133/sir20205120.","productDescription":"Report: x, 59 p.; Data Release","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106718","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":384601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5120/coverthb.jpg"},{"id":384603,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BKW4BX","text":"USGS data release","linkHelpText":"Tidal daily discharge and quality assurance data supporting an assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015–September 2017"},{"id":384602,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5120/sir20205120.pdf","text":"Report","size":"3.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5120"}],"country":"United States","state":"Massachusetts","city":"Wellfleet","otherGeospatial":"Herring River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.07801055908203,\n 41.93318868195924\n ],\n [\n -69.99870300292969,\n 41.93318868195924\n ],\n [\n -69.99870300292969,\n 41.98833256890643\n ],\n [\n -70.07801055908203,\n 41.98833256890643\n ],\n [\n -70.07801055908203,\n 41.93318868195924\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Groundwater is the primary source of municipal water for Saipan. Nearly all groundwater for the municipal water supply is withdrawn from a freshwater-lens system with a limited amount of freshwater that is susceptible to saltwater intrusion. The status of Saipan’s groundwater resources has not been thoroughly assessed since 2003. The U.S. Geological Survey—in cooperation with the Office of Grants Management, Commonwealth of the Northern Mariana Islands, and in collaboration with the Commonwealth Utilities Corporation—assessed the status and characteristics of Saipan’s groundwater resources by (1) evaluating groundwater withdrawals from municipal production wells during 2014–19, (2) evaluating chloride concentrations of municipal groundwater withdrawals during 2009–19, and (3) collecting salinity profiles at selected groundwater-monitoring wells during 2018–19. At the time of preparation of this report (2019), the periods of groundwater-withdrawal and chloride-concentration data represent the only periods of data available since 2003.
During 2014–19, groundwater for the municipal water supply was withdrawn from about 143 production wells. Most of the wells are drilled into limestone formations in the southern plateau and the Kagman Peninsula and generally have withdrawal rates of about 40–60 gallons per minute. Records of monthly groundwater withdrawals from municipal production wells were available for May 2014–March 2019; during that period, monthly withdrawals ranged from 5.7 to 12.8 million gallons per day (Mgal/d) and averaged 9.3 Mgal/d, although records were unavailable for 9 months (May 2015–January 2016). Private wells, mainly located on the western coastal plain, currently are permitted to withdraw a total of about 7 Mgal/d of groundwater. Actual groundwater withdrawals from private wells, however, are uncertain because withdrawal records for private wells are not available.
The Commonwealth Utilities Corporation measured the chloride concentration of groundwater pumped from each of its production wells about twice a year from 2009–19; during this period, 146 production wells were active and sampled. Only 32 of the 146 (22 percent) municipal production wells had median chloride concentrations less than or equal to 250 milligrams per liter (mg/L), the secondary drinking water standard set by the U.S. Environmental Protection Agency. Eighty-one wells (55 percent) pumped water with median chloride concentrations above 500 mg/L.
The Mann-Kendall test was used to determine if chloride concentrations of groundwater withdrawals at 146 municipal production wells had statistically significant trends during December 2009–February 2019. Trends were considered statistically significant for probability values (p-values) less than or equal to 0.05. Test results indicate an upward trend at 9 wells, a downward trend at 52 wells, and no trend at 85 wells.
Salinity profiles were measured in 12 selected monitor wells during July–August 2018 and were measured in six of the twelve selected monitor wells during March 2019. The salinity profiles were used to estimate the thickness of the freshwater lens at 10 monitor wells; freshwater-lens thickness was greatest (46 ft) in a monitor well in the Dan Dan well field near the northern part of the southern plateau. Freshwater-lens-thickness estimates elsewhere were (1) between 0 and 28 ft for the remaining monitor wells on the southern plateau, (2) between 19 and 21 ft for monitor wells on the Kagman Peninsula, (3) 2 ft for a monitor well in the Sablan Quarry well field on west-central Saipan, and (4) 8 ft for a monitor well in the Marpi Quarry well field on northern Saipan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205129","collaboration":"Prepared in cooperation with the Office of Grants Management and in collaboration with the Commonwealth Utilities Corporation, Commonwealth of the Northern Mariana Islands","usgsCitation":"Mitchell, J.N., Presley, T.K., and Carruth, R.L., 2021, Groundwater conditions and trends, 2009–19, Saipan, Commonwealth of the Northern Mariana Islands: U.S. Geological Survey Scientific Investigations Report 2020–5129, 51 p., https://doi.org/10.3133/sir20205129.","productDescription":"vii, 51 p.","numberOfPages":"51","onlineOnly":"Y","ipdsId":"IP-111052","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":384606,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5129/sir20205129.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384605,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5129/covrthb.jpg"}],"country":"United States","otherGeospatial":"Commonwealth of the Norhtern Marianas Islands, Saipan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 145.67665100097656,\n 15.083394661897604\n ],\n [\n 145.83595275878906,\n 15.083394661897604\n ],\n [\n 145.83595275878906,\n 15.339153696147529\n ],\n [\n 145.67665100097656,\n 15.339153696147529\n ],\n [\n 145.67665100097656,\n 15.083394661897604\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
Proliferative kidney disease (PKD) is an emerging disease that recently resulted in a large mortality event of salmonids in the Yellowstone River (Montana, USA). Total PKD fish mortalities in the Yellowstone River were estimated in the tens of thousands, which resulted in a multi‐week river closure and an estimated economic loss of US$500,000. This event shocked scientists, managers, and the public, as this was the first occurrence of the disease in the Yellowstone River, the only reported occurrence of the disease in Montana in the past 25 yr, and arguably the largest wild PKD fish kill in the world. To understand why the Yellowstone River fish kill occurred, we used molecular and historical data to evaluate evidence for several hypotheses: Was the causative parasite Tetracapsuloides bryosalmonae a novel invader, was the fish kill associated with a unique parasite strain, and/or was the outbreak caused by unprecedented environmental conditions? We found that T. bryosalmonae is widely distributed in Montana and have documented occurrence of this parasite in archived fish collected in the Yellowstone River prior to the fish kill. T. bryosalmonae had minimal phylogeographic population structure, as the DNA of parasites sampled from the Yellowstone River and distant water bodies were very similar. These results suggest that T. bryosalmonae could be endemic in Montana. Due to data limitations, we could not reject the hypothesis that the fish kill was caused by a novel and more virulent genetic strain of the parasite. Finally, we found that single‐year environmental conditions are insufficient to explain the cause of the 2016 Yellowstone River PKD outbreak. Other regional rivers where we documented T. bryosalmonae had similar or even more extreme conditions than the Yellowstone River and similar or more extreme conditions have occurred in the Yellowstone River in the recent past, yet mass PKD mortalities have not been documented in either instance. We conclude by placing these results and unresolved hypotheses into the broader context of international research on T. bryosalmonae and PKD, which strongly suggests that a better understanding of bryozoans, the primary host of T. bryosalmonae, is required for better ecosystem understanding.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3436","usgsCitation":"Hutchins, P., Sepulveda, A., Hartikainen, H., Staigmiller, K.D., Opitz, S.T., Yamamoto, R.M., Huttinger, A., Cordes, R.J., Weiss, T., Hopper, L.R., Purcell, M.K., and Okamura, B., 2021, Exploration of the 2016 Yellowstone River fish kill and proliferative kidney disease in wild fish populations: Ecosphere, v. 3, no. 12, e03436, 20 p., https://doi.org/10.1002/ecs2.3436.","productDescription":"e03436, 20 p.","ipdsId":"IP-120532","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":452955,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3436","text":"Publisher Index Page"},{"id":436440,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95XKXE1","text":"USGS data release","linkHelpText":"T. bryosalmonae detection in fish and water, DNA sequence, and simple sequence repeat data collected in the Inter-Mountain West from 2011 to 2019"},{"id":384695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Madison River, Yellowstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.423095703125,\n 45.40616374516014\n ],\n [\n -111.368408203125,\n 45.40616374516014\n ],\n [\n -111.368408203125,\n 46.27103747280261\n ],\n [\n -112.423095703125,\n 46.27103747280261\n ],\n [\n -112.423095703125,\n 45.40616374516014\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Hutchins, Patrick Ross 0000-0001-5232-0821","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":256658,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick Ross","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartikainen, Hanna","contributorId":256659,"corporation":false,"usgs":false,"family":"Hartikainen","given":"Hanna","email":"","affiliations":[{"id":39130,"text":"University of Nottingham","active":true,"usgs":false}],"preferred":false,"id":812993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staigmiller, Ken D.","contributorId":256661,"corporation":false,"usgs":false,"family":"Staigmiller","given":"Ken","email":"","middleInitial":"D.","affiliations":[{"id":40948,"text":"Montana Fish Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":812994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Opitz, Scott T.","contributorId":256663,"corporation":false,"usgs":false,"family":"Opitz","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":40948,"text":"Montana Fish Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":812995,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yamamoto, Renee M.","contributorId":256665,"corporation":false,"usgs":false,"family":"Yamamoto","given":"Renee","email":"","middleInitial":"M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":812996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huttinger, Amberly","contributorId":256668,"corporation":false,"usgs":false,"family":"Huttinger","given":"Amberly","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":812997,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cordes, Rick J.","contributorId":256670,"corporation":false,"usgs":false,"family":"Cordes","given":"Rick","email":"","middleInitial":"J.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":812998,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Weiss, Tammy","contributorId":256672,"corporation":false,"usgs":false,"family":"Weiss","given":"Tammy","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":812999,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hopper, Lacey R.","contributorId":206813,"corporation":false,"usgs":false,"family":"Hopper","given":"Lacey","email":"","middleInitial":"R.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":813000,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":813001,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Okamura, Beth","contributorId":256676,"corporation":false,"usgs":false,"family":"Okamura","given":"Beth","email":"","affiliations":[{"id":51827,"text":"Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":813002,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70218832,"text":"sir20205106 - 2021 - Assessment of contaminant trends in plumes and wells and monitoring network optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin","interactions":[],"lastModifiedDate":"2021-03-24T21:57:54.814314","indexId":"sir20205106","displayToPublicDate":"2021-03-24T09:50:00","publicationYear":"2021","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":"2020-5106","displayTitle":"Assessment of Contaminant Trends in Plumes and Wells and Monitoring Network Optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin","title":"Assessment of contaminant trends in plumes and wells and monitoring network optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin","docAbstract":"Soil and groundwater at the Badger Army Ammunition Plant (BAAP), Sauk County, Wisconsin, were affected by several contaminants as a result of production and waste disposal practices common during its operation from 1942 to 1975. Three distinct plumes of contaminated groundwater originate on BAAP property and extend off-site, as identified by previous studies. Routine sampling of groundwater quality from a network of monitoring wells and off-site private wells has been performed since 1990, although the number of wells monitored and the monitoring frequency have varied as the approved monitoring plan was modified. During the period of monitoring from 1990 to 2018, numerous site investigations and remedial actions were conducted to address the sources of contamination, contaminated soils, and groundwater. Concentrations of contaminants reportedly decreased between 2000 and 2012 within all three plumes. Five or six contaminants of concern (COCs) were identified for each of the three plumes. An independent assessment of the contaminant plumes and of the monitoring network was conducted using groundwater-quality data collected from more than 600 wells between 2000 and 2018.
In a study conducted by the U.S. Geological Survey (USGS), in cooperation with the Army Environmental Command, a consistent data aggregation and interpolation scheme was applied to derive the likely maximum groundwater plume extents in four 3-year time periods between 2000 and 2018. The plume extent was defined by the Enforcement Standard for each COC and represents the maximum concentration observed in each 3-year time period. The plume boundary analysis shows that the spatial extent of groundwater contamination decreased for most COCs during the study period. Some plume boundaries are not well delineated by the existing monitoring network, particularly the downgradient edge of the Propellant Burning Ground plume. Maps identify the plume boundary in each time period, the sampling well network used to delineate the plume, and wells that were sampled in the 2010–12 period but not sampled in the 2015–18 period.
A series of statistical analyses using the Monitoring and Remediation Optimization System, version 3.0, program were applied to the available COC concentration data for two distinct periods, 2000 to 2012 and 2013 to 2018, with the break between periods coinciding with changes to the monitoring network in 2013. Trends in the concentration of COCs in individual wells varied, although generally more wells had decreasing than had increasing concentrations for most COCs in both time periods. The exceptions were ethyl ether in the 2004–12 period and 2,6-dinitrotoluene in the 2013–18 period, for which more wells had an increasing trend. Spatial moment analysis of concentration data from the well network was used to assess the stability of each plume for the COCs. During the 2000–12 period, most of the contaminant plumes for which data were sufficient to complete the analysis were either decreasing or stable in mass and size. The exceptions were carbon tetrachloride (associated solely with the Propellant Burning Ground plume) and 2,4-dinitrotoluene and 2,6-dinitrotoluene (in the Deterrent Burning Ground plume), which showed an increasing trend in mass. No COCs showed an increasing trend in plume mass in the 2013–18 period. Some wells with increasing trends in concentration or with concentrations greater than the enforcement standard are near the tail of a plume, where increased monitoring may be of value to better define future plume boundaries. A spatial optimization analysis covering the 2013–18 period identified six wells that provided information redundant to that from other wells. A temporal optimization analysis identified optimal sampling frequencies for 125 wells. Remedial actions directed at the Propellant Burning Ground plume coincided with a general decrease in plume mass and size, although in specific areas and depths, the plume size for specific contaminants may still be increasing.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205106","collaboration":"Prepared in cooperation with the Army Environmental Command","usgsCitation":"Pajerowski, M., Goodling, P., and Metes, M., 2021, Assessment of contaminant trends in plumes and wells and monitoring network optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2020–5106, 80 p., https://doi.org/10.3133/sir20205106.","productDescription":"Report: x, 80 p.; Data Release; 16 Plates","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118955","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":384411,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2020/5106/sir20205106_plates.pdf","text":"Plates 1 through 16","size":"189 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384401,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5106/coverthb.jpg"},{"id":384402,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5106/sir20205106.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5106"},{"id":384403,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97UKYNR","text":"USGS data release","linkHelpText":"Groundwater quality and plume boundaries for select contaminants of concern at Badger Army Ammunition Plant, Wisconsin (2000–2018)"}],"country":"United States","state":"Wisconsin","county":"Sauk County","otherGeospatial":"Badger Army Ammunition Plant","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.77375030517578,\n 43.30694264971061\n ],\n [\n -89.67041015625,\n 43.30694264971061\n ],\n [\n -89.67041015625,\n 43.420634784134876\n ],\n [\n -89.77375030517578,\n 43.420634784134876\n ],\n [\n -89.77375030517578,\n 43.30694264971061\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
The Everglades wetland was once a river of grass, with water flowing slowly through the sawgrass, southward across the landscape. As developers took hold of south Florida, water was sent away from the heart of the Everglades through canals and levees to protect the former wetland for residential and agricultural development. In the 1990s, planning began to restore the Everglades in what is the largest hydrologic restoration undertaking in the world. With billions of taxpayer dollars at stake, restoration planners benefit from forecasting tools to inform restoration planning. To meet this need, scientists developed predictive ecological models and other decision support tools tailored to this dynamic ecosystem as well as to the needs of restoration planning teams. Predictive modeling has been able to take advantage of well-understood relationships between species of interest and hydrologic dynamics in the Everglades. Recent modeling advances include multi-species approaches that consider interactions among species as well as explicit consideration of trade-offs among species from potential water management actions. Scientists are also starting to look at ecosystem-wide vulnerabilities with explicit consideration of future change such as sea level rise. Modeling tools and approaches continue to be refined to meet decision making needs for Everglades restoration. However, more work is needed to consider additional complexities of this dynamic wetland as well as to consider the broader socio-environmental system.
Brook Trout Salvelinus fontinalis have declined across their native range due to multiple anthropogenic factors, including landscape alteration and climate change. Although coldwater streams in Maryland (eastern United States) historically supported significant Brook Trout populations, only fragmented remnant populations remain, with the exception of the upper Savage River watershed in western Maryland. Using microsatellite data from 38 collections, we defined genetic relationships of Brook Trout populations in Maryland drainages. Microsatellite analyses of Brook Trout indicated the presence of five major discrete units defined as the Youghiogheny (Ohio), Susquehanna, Patapsco/Gunpowder, Catoctin, and Upper Potomac, with a distinct genetic subunit present in the Savage River (upper Potomac). We did not observe evidence for widespread hatchery introgression with native Brook Trout. However, genetic effects due to fragmentation were evident in several Maryland Brook Trout populations, resulting in erosion of diversity that may have negative implications for their future persistence. Our current study supplements an increasing body of evidence that Brook Trout populations in Maryland are highly susceptible to multiple anthropogenic stresses, and many populations may be extirpated in the near future. Future management efforts focused on habitat protection and potential stream restoration, coupled with a comprehensive assessment framework that includes genetic considerations, may provide the best outlook for Brook Trout populations in Maryland.
In the humid, temperate Delaware River Basin (DRB) where water availability is generally reliable, summer low flows can cause competition between various human and ecological water uses. As temperatures continue to rise, population increases and development expands, it is critical to understand historical low flow variability to anticipate and plan for future flows. Using a sample of 325 U.S. Geological Survey gages, we evaluated spatial patterns in several low flow metrics, the biophysical and climatic drivers of these metrics, and trends in low flows for two periods: 1950-2018 and 1980-2018. We calculated the annual 7-day low flow and date, low flow deficit as the departure below a long-term daily flow threshold and the number of discrete low flow periods below this threshold. We also aggregated several climate metrics to watershed scale and used existing watershed properties quantifying land cover, topography, soils, geology, and human activity. Random forest models were used to assess the hierarchy of variable importance in explaining mean-annual low flow variability for each low flow metric using all gages. We find muted regional patterns in mean-annual low flow and low flow variability, likely due to the myriad of anthropogenic, landscape, and flow modifications that obscure flow regimes from their natural characteristics. In contrast, individual years show markedly different spatial patterns in low flow magnitude and severity. Coincident with increases in precipitation, 7-day low flows have generally increased and low flow deficits decreased for both 1950-2018 and 1980-2018 periods. However, 7-day low flows have decreased in the Coastal Plain physiographic province where water use and impervious area have increased in recent decades, highlighting the effects of land and water management on low flows. With continued change expected in the DRB, additional research needs are highlighted to enable estimation of future low flows and to plan for periods of prolonged low flow.
A multi-component geochemical dataset was collected from groundwater and surface-water bodies associated with the urban Fountain Creek alluvial aquifer, Colorado, USA, to facilitate analysis of recharge sources, geochemical interactions, and groundwater-residence times. Results indicate that groundwater can be separated into three distinct geochemical zones based on location within the flow system and proximity to surface water, and these zones can be used to infer sources of recharge and groundwater movement through the aquifer. Rare-earth-element concentrations and detections of wastewater-indicator compounds indicate the presence of effluent from wastewater-treatment plants in both groundwater and surface water. Effluent presence in groundwater indicates that streams in the area lose to groundwater in some seasons and are a source of focused groundwater recharge. Distributions of pharmaceuticals and wastewater-indicator compounds also inform an understanding of groundwater–surface-water interactions. Noble-gas isotopes corroborate rare-earth-element data in indicating geochemical evolution within the aquifer from recharge area to discharge area and qualitatively indicate variable groundwater-residence times and mixing with pre-modern groundwater. Quantitative groundwater-residence times calculated from 3H/3He, SF6, and lumped-parameter modeling generally are less than 20 years, but the presence of mixing with older groundwater of an unknown age is also indicated at selected locations. Future investigations would benefit by including groundwater-age tracers suited to quantification of mixing for both young (years to decades) and old (centuries and millennia) groundwater. This multi-faceted analysis facilitated development of a conceptual model for the investigated groundwater-flow system and illustrates the application of an encompassing suite of analytes in exploring hydrologic and geochemical interactions in complex systems.
","language":"English","publisher":"MDPI","doi":"10.3390/w13060871","usgsCitation":"Newman, C.P., Paschke, S.S., and Keith, G.L., 2021, Natural and anthropogenic geochemical tracers to investigate residence times and groundwater–surface-water interactions in an urban alluvial aquifer: Water, v. 13, no. 6, 30 p., https://doi.org/10.3390/w13060871.","productDescription":"30 p.","ipdsId":"IP-118155","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":452974,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13060871","text":"Publisher Index Page"},{"id":436443,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99SPQM2","text":"USGS data release","linkHelpText":"Environmental-tracer modeling to support hydrogeochemical evaluation of the Fountain Creek Alluvial Aquifer, El Paso County, Colorado, 2018-2019"},{"id":384712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Colorado Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.2490234375,\n 38.61687046392973\n ],\n [\n -104.1888427734375,\n 38.61687046392973\n ],\n [\n -104.1888427734375,\n 39.16839998800286\n ],\n [\n -105.2490234375,\n 39.16839998800286\n ],\n [\n -105.2490234375,\n 38.61687046392973\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paschke, Suzanne S. 0000-0002-3471-4242 spaschke@usgs.gov","orcid":"https://orcid.org/0000-0002-3471-4242","contributorId":1347,"corporation":false,"usgs":true,"family":"Paschke","given":"Suzanne","email":"spaschke@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keith, Gabrielle L. 0000-0002-2304-8504 gkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-2304-8504","contributorId":256699,"corporation":false,"usgs":true,"family":"Keith","given":"Gabrielle","email":"gkeith@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813077,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220205,"text":"70220205 - 2021 - Measuring and interpreting multilayer aquifer-system compactions for a sustainable groundwater-system development","interactions":[],"lastModifiedDate":"2021-04-27T11:44:36.379671","indexId":"70220205","displayToPublicDate":"2021-03-23T06:40:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Measuring and interpreting multilayer aquifer-system compactions for a sustainable groundwater-system development","docAbstract":"Ever decreasing water resources and climate change have driven the increasing use of groundwater causing land subsidence in many countries. Geodetic sensors such as InSAR, GPS and leveling can detect surface deformation but cannot measure subsurface deformation. A single‐well, single‐depth extensometer can be used to measure subsurface deformation, but it cannot delineate the depths of major compaction and provide insight about the deformation mechanism throughout a complex aquifer system, unless man extensometers at different depths are used. We present a multilayer compaction well (MLCW), installed in a borehole, that uses magnetic rings to detect stratum compaction at 25 depths as deep as 300 m below land surface. Our laboratory and field assessments indicate 1 mm precision and accuracy for one single‐depth magnetic reading. We tested the performance of MLCW by measuring aquifer‐system compaction over the proximal, middle, and distal fans of the Choushui River Alluvial Fan (CRAF) that has long experienced severe land subsidence. The MLCW measurements were used to create time‐depth diagrams of compaction, showing different compaction rates at different layers of aquifers and aquitards to identify the depths of major compactions. The elastic (reversible) and inelastic (irreversible) compactions from MLCW were used in stress‐strain analyses to estimate skeletal specific storages and the safe groundwater levels, below which groundwater extractions have caused irreversible compactions. The hydrogeological parameters derived from MLCW measurements can help governmental agencies to determine effective land‐use and water‐use policies, and ascertain the best strategy for utilizing artificial recharge to prevent land subsidence and achieve sustainable groundwater management.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR028194","usgsCitation":"Hung, W., Hwang, C., Sneed, M., Chen, Y., Chu, C., and Lin, S., 2021, Measuring and interpreting multilayer aquifer-system compactions for a sustainable groundwater-system development: Water Resources Research, v. 57, no. 4, e2020WR028194, 19 p., https://doi.org/10.1029/2020WR028194.","productDescription":"e2020WR028194, 19 p.","ipdsId":"IP-120150","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":452975,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr028194","text":"Publisher Index Page"},{"id":385313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hung, Wei-Chia","contributorId":172937,"corporation":false,"usgs":false,"family":"Hung","given":"Wei-Chia","email":"","affiliations":[{"id":27123,"text":"Green Environmental Engineering Consultant Co. LTD, Hsinchu, Taiwan","active":true,"usgs":false}],"preferred":false,"id":814749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hwang, Cheinway 0000-0002-3322-353X","orcid":"https://orcid.org/0000-0002-3322-353X","contributorId":172932,"corporation":false,"usgs":false,"family":"Hwang","given":"Cheinway","email":"","affiliations":[{"id":27120,"text":"Department of Civil Engineering, National Chiao Tung University, Taiwan","active":true,"usgs":false}],"preferred":false,"id":814750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Yi-An","contributorId":257631,"corporation":false,"usgs":false,"family":"Chen","given":"Yi-An","email":"","affiliations":[{"id":52072,"text":"Department of Earth Sciences, National Central University, Taiwan","active":true,"usgs":false}],"preferred":false,"id":814752,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chu, Chi-Hua","contributorId":257632,"corporation":false,"usgs":false,"family":"Chu","given":"Chi-Hua","email":"","affiliations":[{"id":52074,"text":"Green Environmental Engineering Consultant Co. LTD, Taiwan","active":true,"usgs":false}],"preferred":false,"id":814753,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lin, Shao-Hung","contributorId":257633,"corporation":false,"usgs":false,"family":"Lin","given":"Shao-Hung","email":"","affiliations":[{"id":52074,"text":"Green Environmental Engineering Consultant Co. LTD, Taiwan","active":true,"usgs":false}],"preferred":false,"id":814754,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219057,"text":"tm6H1 - 2021 - The basin characterization model—A regional water balance software package","interactions":[],"lastModifiedDate":"2021-03-25T18:39:35.720713","indexId":"tm6H1","displayToPublicDate":"2021-03-22T12:41:35","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-H1","displayTitle":"The Basin Characterization Model—A Regional Water Balance Software Package","title":"The basin characterization model—A regional water balance software package","docAbstract":"This report documents the computer software package, Basin Characterization Model, version 8 (BCMv8)—a monthly, gridded, regional water-balance model—and provides detailed operational instructions and example applications. After several years of many applications and uses of a previous version, CA-BCM, published in 2014, the BCMv8 was refined to improve the accuracy of the water-balance components, particularly the recharge estimate, which is the most difficult to accurately assess. The improvement of the various water-balance components targeted the actual evapotranspiration component, which, in turn, reduced the uncertainty of the recharge estimate. The improvement of this component was enabled by the availability of a national, gridded actual-evapotranspiration product from the U.S. Geological Survey that was unique in its scope to combine remotely sensed spatial variability and ground-based long-term water-balance constraints. This dataset provided the ability to assess monthly actual evapotranspiration for 62 vegetation types and to perform regional calibration in watersheds throughout California with the objective of closing the water balance using improved estimates for each component. The refinements, including vegetation-specific evapotranspiration, enabled the development of applications that could explore various aspects of landscape disturbance, such as wildfire, forest management, or urbanization. The improvements to BCMv8 also provided the ability to assess long-term sustainability of water resources under a variety of management applications or future climate projections.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6H1","collaboration":"Prepared in cooperation with California Department of Water Resources","usgsCitation":"Flint, L.E., Flint, A.L., and Stern, M.A., 2021, The basin characterization model—A regional water balance software package: U.S. Geological Survey Techniques and Methods 6–H1, 85 p., https://doi.org/10.3133/tm6H1.","productDescription":"x, 85 p.","numberOfPages":"85","onlineOnly":"Y","ipdsId":"IP-101075","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":436445,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K23J25","text":"USGS data release","linkHelpText":"Future Climate and Hydrology from Twenty Localized Constructed Analog (LOCA) Scenarios and the Basin Characterization Model (BCMv8)"},{"id":384554,"rank":4,"type":{"id":34,"text":"Image 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\"}}]}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Climate change has and is projected to continue to alter historical regimes of temperature, precipitation, and hydrology. To assess the vulnerability of climate change from a land management perspective and spatially identify where the most extreme changes are anticipated to occur, we worked in collaboration with land managers to develop a climate change vulnerability map for the midwestern United States with a focus on riparian systems. The map is intended for use by regional administrators to help them work across various program areas (e.g. fisheries, endangered species) to prioritize locations needing support for adaptation planning. The tool can also be utilized locally by managers to better understand the effects that projected climate scenarios have on the hydrology of management units as they develop adaptation strategies. The vulnerability map is watershed-based (360 watershed units within the region) and combines 15 climate change indicators that were selected by U.S. Fish and Wildlife Service natural resource managers based upon known and anticipated effects to species and habitats. The projected change in each of these indicators from the historical period (1986–2005) to the future period (2040–2059) was aggregated into a composite score for each watershed. Landscape-scale metrics reflective of a watershed’s adaptive capacity were combined with the climate change indicators to produce a vulnerability score. We found sub-regional variation in vulnerability to climate change with the greatest vulnerability in Iowa, central Illinois, and northwest Ohio. Greater vulnerability was seen in the higher greenhouse gas concentration scenario, Representative Concentration Pathway (RCP) 8.5 compared to the lower greenhouse gas concentration scenario RCP 4.5, when looking at the mean of the five downscaled climate models used in this study. By quantifying and mapping climate change vulnerability, natural resource managers can better understand the degree of vulnerability for individual watersheds and identify areas of prioritization in regional and local planning efforts.
The Navajo (N) aquifer is the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Availability of water is an important issue in the Black Mesa area because of continued water requirements for industrial and municipal use by a growing population and because of its arid climate. Precipitation in the area typically ranges from less than 6 to more than 16 inches per year depending on location.
The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from November 2016 to December 2018. The monitoring program includes measurements of (1) groundwater withdrawals (pumping), (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater and surface-water chemistry.
In calendar year 2017, total groundwater withdrawals were 3,710 acre-feet (acre-ft), industrial withdrawals were 1,110 acre-ft, and municipal withdrawals were 2,600 acre-ft. In calendar year 2018, total groundwater withdrawals were 3,670 acre-ft, industrial withdrawals were 1,170 acre-ft, and municipal withdrawals were 2,500 acre-ft. Total withdrawals during 2017 and 2018 were about 49 percent less than total withdrawals in 2005 because of Peabody Western Coal Company’s discontinued use of water to transport coal in a coal slurry pipeline.
From the prestress period (prior to 1965) to 2018, measured water levels available for comparison in wells completed in the unconfined areas of the N aquifer within the Black Mesa area declined in 8 of 14 wells, the changes ranged from +12.1 feet to −39.4 feet, and the median change was -0.6 feet. Water levels also declined in 15 of 18 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was −40.2 feet (ft), with changes ranging from +14.2 ft to −189.0 ft. From the prestress period to 2018, the median water-level change for all 32 wells in both the confined and unconfined areas was −9.4 ft.
Spring flow was measured at four springs in 2017 and 2018. Flow fluctuated during the period of record for Burro Spring and Pasture Canyon Spring, but a decreasing trend was statistically significant (p<0.05) at Moenkopi School Spring and Unnamed Spring near Dennehotso. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s and discharge at Pasture Canyon Spring has fluctuated for the period of record.
Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2018), Dinnebito Wash near Sand Springs 09401110 (1993 to 2018), Polacca Wash near Second Mesa 09400568 (1994 to 2018), and Pasture Canyon Springs 09401265 (2004 to 2018). Median winter flows (November through February) of each water year were used as an index of the amount of groundwater discharge at the above-named sites. For the period of record, the median winter flows have generally remained constant at Dinnebito Wash and Polacca Wash, whereas a decreasing trend was indicated at Moenkopi Wash and Pasture Canyon Springs.
In 2017 and 2018, water samples collected from two wells, four springs, and three streams in the Black Mesa area were analyzed for selected chemical constituents. The results from wells and springs were compared with previous analyses from the same wells and springs. At the Peabody 2 well, a significant (p<0.05) decreasing trend in dissolved solids over time was found, while concentrations of dissolved solids have not varied significantly (p>0.05) at the Kykotsmovi PM2 well. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 30 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly (p>0.05) since the early 1980s, and there is no increasing or decreasing trend in those data. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record, but there is no statistical trend in the data. Baseflow water chemistry samples were collected from Moenkopi, Dinnebito, and Polacca washes in 2017. Samples from all three washes had total-dissolved solids concentrations higher than is typically found in the N aquifer water.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211124","collaboration":"Prepared in cooperation with the Navajo Nation and Peabody Western Coal Company","usgsCitation":"Mason, J.P., 2021, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2016–2018: U.S. Geological Survey Open-File Report 2021–1124, 50 p., https://doi.org/10.3133/ofr20211124.","productDescription":"vii, 50 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-110021","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":384543,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181193","text":"Open-File Report 2018-1193","linkHelpText":"- Groundwater, Surface-Water, and Water-Chemistry Data, Black Mesa Area, Northeastern Arizona—2015–2016"},{"id":384455,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1124/ofr20211124.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384454,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1124/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.76391601562499,\n 35.32633026307483\n ],\n [\n -109.171142578125,\n 35.32633026307483\n ],\n [\n -109.171142578125,\n 36.99377838872517\n ],\n [\n -111.76391601562499,\n 36.99377838872517\n ],\n [\n -111.76391601562499,\n 35.32633026307483\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Groundwater models have evolved to encompass more aspects of the water cycle, but the incorporation of realistic boundary conditions representing surface water remains time-consuming and error-prone. We present two Python packages that robustly automate this process using readily available hydrography data as the primary input. SFRmaker creates input for the MODFLOW SFR package, while Linesink-maker creates linesink string input for the GFLOW analytic element program. These programs can reduce weeks or even months of manual effort to a few minutes of execution time, and carry the added advantages of reduced potential for error, improved reproducibility and facilitation of step-wise modeling through reduced dependency on a particular conceptual model or discretization. Two real-world examples at the county to multi-state scales are presented.
Top-down and bottom-up factors affecting invasive populations are rarely considered simultaneously, yet their interactive responses to disturbances and management interventions can be essential to understanding invasion patterns. We evaluated post-fire responses of the exotic perennial forb Chondrilla juncea (rush skeletonweed) and its biocontrol agents to landscape factors and a post-fire combined herbicide (imazapic) and bacteria (Pseudomonas fluorescens strain MB906) treatment that targeted invasive annual grasses in a sagebrush steppe ecosystem. Biocontrol agents released against C. juncea in previous decades included Cystiphora schmidti (gall midge), Aceria chondrillae (gall mite), and Puccinia chondrillina (rust fungus). C. juncea abundance was greater in sprayed than unsprayed plots, and where soils were coarser, slopes faced southwest, solar heat loads and topographic water accumulation were greater, and cover of deep-rooted native perennials was lower. Mite infestation was greater in unsprayed plots, midge infestation was greater at higher elevations on steeper slopes, and midges were more abundant while rust was less abundant on gravelly soils. Biocontrol infestation levels varied considerably between years and could not be predicted in 2019 from 2018 infestation levels. Multiple biocontrol species were often present at the same plots but were rarely present on the same C. juncea individuals. These results suggest that spatial patterns of invasion by C. juncea are related to deep-soil water availability, warmer conditions, and alleviation of competition. Treatments designed to reduce invasive annual grasses may inadvertently release C. juncea by both reducing plant competition for soil resources and affecting biocontrol agent (mite) abundance.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-021-02481-z","usgsCitation":"Lazarus, B., and Germino, M., 2021, Post-fire management targeting invasive annual grasses may have inadvertently released the exotic perennial forb Chondrilla juncea and suppressed its biocontrol agent: Biological Invasions, v. 23, p. 1915-1932, https://doi.org/10.1007/s10530-021-02481-z.","productDescription":"18 p.","startPage":"1915","endPage":"1932","onlineOnly":"N","ipdsId":"IP-120244","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":436452,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QFBHZ3","text":"USGS data release","linkHelpText":"Post-fire Chondrilla juncea and biocontrol at Boise River Wildlife Management Area 2018-2019"},{"id":384752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","city":"Boise","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.54296874999999,\n 43.51668853502906\n ],\n [\n -115.48828125000001,\n 43.51668853502906\n ],\n [\n -115.48828125000001,\n 43.96119063892024\n ],\n [\n -116.54296874999999,\n 43.96119063892024\n ],\n [\n -116.54296874999999,\n 43.51668853502906\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2021-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Lazarus, Brynne E. 0000-0002-6352-486X","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":242732,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813150,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70146231,"text":"sir20135225 - 2021 - Simulation of groundwater flow in the aquifer system of the Anacostia River and surrounding watersheds, Washington, D.C., Maryland, and Virginia","interactions":[],"lastModifiedDate":"2021-03-22T11:45:33.624013","indexId":"sir20135225","displayToPublicDate":"2021-03-19T13:45:00","publicationYear":"2021","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":"2013-5225","displayTitle":"Simulation of Groundwater Flow in the Aquifer System of the Anacostia River and Surrounding Watersheds, Washington, D.C., Maryland, and Virginia","title":"Simulation of groundwater flow in the aquifer system of the Anacostia River and surrounding watersheds, Washington, D.C., Maryland, and Virginia","docAbstract":"The U.S. Geological Survey, in cooperation with the District Department of Energy & Environment, Water Quality Division, is investigating the hydrogeology of the tidal Anacostia River watershed within Washington, D.C., with the goal of improving understanding of the groundwater-flow system and the interaction of groundwater and surface water in the watershed. To help meet this goal, a three-dimensional steady-state groundwater-flow model for the Anacostia River and surrounding watersheds in Washington, D.C., Maryland, and Virginia was constructed. The goal of the modeling study was to quantify the rate and pattern of groundwater flow to the tidal Anacostia River. The model domain includes weathered and unweathered rocks of the Piedmont Physiographic Province and the southeast-dipping sediments of the Atlantic Coastal Plain Physiographic Province. The model includes processes of recharge, evapotranspiration, withdrawals from wells, and base flow to streams, rivers, and tidal waters. Final model calibration was achieved by using the objective parameter estimation and sensitivity analysis capabilities of UCODE_2005. Simulated gradients in the surficial aquifer in the vicinity of the tidal Anacostia River indicate that flow is predominantly toward the river, with changes in the magnitude and direction of the gradients from the northeast, where the Anacostia River enters Washington, D.C., to the southwest, toward the confluence with the tidal Potomac River. Flow paths to the tidal Anacostia River from the north are largely horizontal through the surficial aquifer and Patuxent aquifer. From the south, the flow paths toward the river originate in the elevated topographic areas southeast of the river and pass through the surficial aquifer and Patapsco confining unit, lower Patapsco aquifer/Arundel Clay, and to some extent, the Patuxent aquifer. Groundwater-flow rates to and from the tidal rivers (Potomac and Anacostia) are generally greatest near the land-water boundary, where the gradient in the water table is greatest, and diminish toward the middle of the tidal river channels. The tidal rivers are predominantly areas of groundwater discharge, although there are areas where tidal waters are recharging the subsurface, typically where small variations or depressions in the topography produce small locally reversed gradients in the water table. Substantial recharge of tidal waters to the groundwater system is observed for the tidal Potomac where the upper Patapsco aquifer subcrops south of Washington, D.C. Water budget calculations indicate that inflows to the groundwater system beneath the tidal Anacostia River are predominantly from the land area of Washington, D.C., followed by tidal surface water and flows from lower layers. Outflows are largely to the tidal Anacostia River, with a smaller part going to the land area underlying Washington, D.C.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135225","usgsCitation":"Raffensperger, J.P., Voronin, L.M., and Dieter, C.A., 2021, Simulation of groundwater flow in the aquifer system of the Anacostia River and surrounding watersheds, Washington, D.C., Maryland, and Virginia: U.S. Geological Survey Scientific Investigations Report 2013–5225, 59 p., https://doi.org/10.3133/sir20135225.","productDescription":"vii, 59 p.","numberOfPages":"59","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051429","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":384505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2013/5225/coverthb.jpg"},{"id":384506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5225/sir20135225.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5225"}],"country":"United States","state":"Delaware, Maryland, Washington D.C.","otherGeospatial":"Anacostia River and surrounding watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.70355224609375,\n 38.89958342598271\n ],\n [\n -76.44287109375,\n 38.1777509666256\n ],\n [\n -75.498046875,\n 39.14710270770074\n ],\n [\n -76.72027587890625,\n 39.715638134796336\n ],\n [\n -77.70355224609375,\n 38.89958342598271\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
Desert amphibians are limited to exploiting ephemeral resources and aestivating or to inhabiting scarce refuges of permanent water, such as springs. Understanding how amphibians use these resources is essential for their conservation. Dixie Valley Toads (Anaxyrus williamsi) are precinctive to a small system of cold and hot springs in the Dixie Valley, Nevada, USA. The toads have been petitioned for listing under the US Endangered Species Act, and information about how they use terrestrial and aquatic resources will help managers to conserve the toads and identify threats like geothermal energy development that might affect these toads. We used radiotelemetry to study the seasonal home ranges, movements, and habitat associations of Dixie Valley Toads in autumn 2018 and spring 2019. We found that toads were very closely associated with water in both seasons, with most observations occurring in water, especially for males in spring and all toads in the autumn. Even when found in terrestrial habitat, toads were a median distance of 4.2 m (95% credible interval = 3.3–5.3) from water; 95% of the time in spring and autumn, toads were within 14 m of water. Dixie Valley Toad habitat selection indicated a similar pattern, with selection in both spring and autumn for locations closer to water and for warmer water and substrates than at nearby available locations. In autumn, toads also avoided bare ground and terrestrial graminoids. Dixie Valley Toads selected brumation sites in, over (within dense vegetation), or near water, often near springs where water depths and temperatures are likely stable through the winter. The reliance of Dixie Valley Toads on water in spring, autumn, and during brumation suggests that alteration to historical flows and water temperatures are likely to affect the toads. Changes to the hydrothermal environment when toads are brumating could be particularly detrimental, potentially killing inactive toads.
The University of Kentucky (U KY) has owned Robinson Forest (37.460723° N, 83.158598° W) since 1923, conducting experiments crucial to understanding the environmental effects of land management in the region. Part of the management of Robinson Forest has been collection of environmental data, including precipitation quantity, bulk‐deposition chemistry, streamflow, stream‐water chemistry, and air and stream temperature. Over the years, these data have been collected and archived using various technologies and have been mostly inaccessible for research use – unedited and uncompiled, scattered across several spreadsheets and paper records. Through a partnership between the U.S. Geological Survey (USGS) and U KY, daily precipitation data for six stations and stream data from four watersheds in Robinson Forest have been compiled for 1971–2018, checked for transcription errors, and annotated for changes in methodologies. These data are available as a USGS data release at https://doi.org/10.5066/P9FPLG1O. Improved accessibility of this data set provides an important research resource for understanding water quality in minimally effected forests in the region. Preliminary results indicate that these data present a valuable opportunity to evaluate linkages among atmospheric deposition and stream chemistry, the effects of environmental policy, such as the Clean Air Act, and effects from nearby land disturbance in the form of surface mining. Furthermore, these data fill a geographic and physiographic gap in what is available to examine deposition and streamflow patterns over the last 45 years, supplementing those long‐term records of research sites in northern (e.g., Hubbard Brook Experimental Forest), central (e.g., Fernow Experimental Forest) and southern Appalachia (e.g., Coweeta Hydrologic Laboratory). As an oasis in the midst of significant surface mining activity, Robinson Forest presents a unique opportunity to understand environmental conditions characteristic of minimally disturbed forests similar to pre‐mining conditions in the Central Appalachian region.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14133","usgsCitation":"Sena, K., Barton, C.D., and Williamson, T.N., 2021, The Robinson Forest environmental monitoring network: Long‐term evaluation of streamflow and precipitation quantity and stream‐water and bulk deposition chemistry in eastern Kentucky watersheds: Hydrological Processes, v. 35, no. 4, e14133, 6 p., https://doi.org/10.1002/hyp.14133.","productDescription":"e14133, 6 p.","ipdsId":"IP-122607","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":385638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","otherGeospatial":"southeast Kentucky","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.27636718749999,\n 36.756490329505176\n ],\n [\n -81.36474609375,\n 36.756490329505176\n ],\n [\n -81.36474609375,\n 37.82280243352756\n ],\n [\n -83.27636718749999,\n 37.82280243352756\n ],\n [\n -83.27636718749999,\n 36.756490329505176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Sena, Kenton 0000-0003-1822-9375","orcid":"https://orcid.org/0000-0003-1822-9375","contributorId":258046,"corporation":false,"usgs":false,"family":"Sena","given":"Kenton","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":815604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barton, Chris D. 0000-0003-0692-3079","orcid":"https://orcid.org/0000-0003-0692-3079","contributorId":236883,"corporation":false,"usgs":false,"family":"Barton","given":"Chris","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":815605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219120,"text":"70219120 - 2021 - Public and private tapwater: Comparative analysis of contaminant exposure and potential risk, Cape Cod, Massachusetts, USA","interactions":[],"lastModifiedDate":"2021-05-28T14:11:19.896547","indexId":"70219120","displayToPublicDate":"2021-03-19T06:49:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7788,"text":"Environmental International","active":true,"publicationSubtype":{"id":10}},"title":"Public and private tapwater: Comparative analysis of contaminant exposure and potential risk, Cape Cod, Massachusetts, USA","docAbstract":"Humans are primary drivers of environmental contamination worldwide, including in drinking-water resources. In the United States (US), federal and state agencies regulate and monitor public-supply drinking water while private-supply monitoring is rare; the current lack of directly comparable information on contaminant-mixture exposures and risks between private- and public-supplies undermines tapwater (TW) consumer decision-making.
We compared private- and public-supply residential point-of-use TW at Cape Cod, Massachusetts, where both supplies share the same groundwater source. TW from 10 private- and 10 public-supply homes was analyzed for 487 organic, 38 inorganic, 8 microbial indicators, and 3 in vitro bioactivities. Concentrations were compared to existing protective health-based benchmarks, and aggregated Hazard Indices (HI) of regulated and unregulated TW contaminants were calculated along with ratios of in vitro exposure-activity cutoffs.
Seventy organic and 28 inorganic constituents were detected in TW. Median detections were comparable, but median cumulative concentrations were substantially higher in public supply due to 6 chlorine–disinfected samples characterized by disinfection byproducts and corresponding lower heterotrophic plate counts. Public-supply applicable maximum contaminant (nitrate) and treatment action (lead and copper) levels were exceeded in private-supply TW samples only. Exceedances of health-based HI screening levels of concern were common to both TW supplies.
These Cape Cod results indicate comparable cumulative human-health concerns from contaminant exposures in private- and public-supply TW in a shared source-water setting. Importantly, although this study’s analytical coverage exceeds that currently feasible for water purveyors or homeowners, it nevertheless is a substantial underestimation of the full breadth of contaminant mixtures documented in the environment and potentially present in drinking water.
Regardless of the supply, increased public engagement in source-water protection and drinking-water treatment, including consumer point-of-use treatment, is warranted to reduce risks associated with long-term TW contaminant exposures, especially in vulnerable populations.