{"pageNumber":"29","pageRowStart":"700","pageSize":"25","recordCount":16440,"records":[{"id":70240728,"text":"sir20225125 - 2023 - Modeling flow and water quality in reservoir and river reaches of the Mahoning River Basin, Ohio","interactions":[],"lastModifiedDate":"2026-02-23T20:55:47.151064","indexId":"sir20225125","displayToPublicDate":"2023-02-27T16:09:05","publicationYear":"2023","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":"2022-5125","displayTitle":"Modeling Flow and Water Quality in Reservoir and River Reaches of the Mahoning River Basin, Ohio","title":"Modeling flow and water quality in reservoir and river reaches of the Mahoning River Basin, Ohio","docAbstract":"<h1>Executive Summary</h1><p>The U.S. Army Corps of Engineers (USACE) is considering changes to the management of water surface elevation in four lakes in the Mahoning River Basin. These changes would affect the timing and amounts of water released to the Mahoning River and could affect the water quality of those releases. To provide information on possible water-quality effects from these operational changes, flow and water-quality models were constructed for Berlin Lake, Lake Milton, Michael J Kirwan Reservoir, Mosquito Creek Lake, Mosquito Creek, and the Mahoning River from the dams downstream to Lowellville, Ohio.</p><p>The models were calibrated for two calendar years each, with model years selected depending on the availability of water-quality data. Models were developed with CE-QUAL-W2 version 4.2 (Wells, S.A., 2020, CE-QUAL-W2—A two-dimensional, laterally averaged, hydrodynamic and water quality model [version 4.2]: Portland State University, variously paged), a two-dimensional, laterally averaged hydrodynamic and water-quality model. Modeled constituents included flow, velocity, ice cover, water temperature, total dissolved solids (TDS), sulfate, chloride, inorganic suspended sediment, nitrate, ammonia, total Kjeldahl nitrogen, orthophosphate, total phosphorus, dissolved and particulate organic matter, algae, and dissolved oxygen. Iron was included for the lake models, but not the river.</p><p>A whole-basin model, with the four lake models and river model, was used to run model scenarios to examine the effects of altered lake water surface elevations on flow and water quality in the lakes, the lake outflows, and the Mahoning River. The initial whole-basin model, with calendar year 2013 hydrology and measured or typical water quality, was designated as scenario 0. Mahoning River flows for calendar year 2013 were close to a 20-year median flow. Four additional scenarios were constructed based on reservoir operations model (RES-SIM) model water surface elevations for the four lakes as provided by USACE. Scenario 1 was the RES-SIM base case, scenario 2 kept Berlin Lake water surface elevations higher in summer, scenario 3 allowed 25 percent of summer flood storage to extend the guide curve, and scenario 4 allowed more flexibility in lake management by removing any downstream Mahoning River minimum flow requirements. The Mahoning River model was not changed in any scenarios but received altered flows from the lakes. Significant findings from this study include the following:</p><ul><li>In two of the four lakes (Berlin and Mosquito Creek Lakes), development of lake model grids using recent bathymetric surveys suggests that sedimentation in these lakes has occurred since they were constructed, altering volume-elevation curves.</li><li>Tests of model parameter sensitivity showed that modeled water temperature, TDS, and dissolved oxygen were relatively insensitive to model parameter values. Modeled chlorophyll <i>a</i>, a measure of algal concentration, was most sensitive to parameter values; nitrate and total phosphorus concentrations were affected by a few of the parameters tested. As a group, the lake model results were more sensitive to model parameter values compared to the Mahoning River model.</li><li>Data gaps were identified for inflows, both for water quantity and water quality, that could be filled through future sampling programs. Ample data were available from within the waterbodies for model calibration.</li><li>The model simulated the general spatial and temporal patterns of water temperature, TDS, chloride, sulfate, nutrients, suspended sediment, organic matter, chlorophyll <i>a</i>, and dissolved oxygen in the lakes and Mahoning River.</li><li>From late spring to autumn in the years modeled (2006, 2013, 2017–19 depending on the lake), all lakes developed thermal stratification and periods of anoxia in bottom waters. Stratification was most stable in Michael J Kirwan Reservoir and least stable in Mosquito Creek Lake. The stratification and anoxia in Berlin Lake, Lake Milton, and Mosquito Creek Lake could be interrupted by high-flow inputs moving through those lakes.</li><li>The model predicted the release of ammonia and iron during anoxic periods in the lake hypolimnions.</li><li>Concentrations of TDS, nitrate, orthophosphate, and total phosphorus increased in the Mahoning River down to Lowellville, the end of the river model, in the years modeled. These concentrations were greater than those in upstream lake releases.</li><li>Chloride and sulfate concentrations were underpredicted in the Mahoning River, suggesting the presence of unreported chloride and sulfate inputs to the river, at least in the years modeled.</li><li>Model scenario 4 kept water surface elevations the highest in all lakes in the April to mid-December period, compared to scenarios 1–3. Model scenario 2 kept water surface elevations in Berlin Lake higher in summer and late autumn, compared to scenarios 1 and 3, but to satisfy downstream minimum flow requirements, water surface elevations in the other lakes had periods of lower water surface elevation.</li><li>As a group, scenarios 1–3 had largely similar effects on flow and water surface elevation in the Mahoning River because the lake releases in those scenarios still met downstream Mahoning River flow targets.</li><li>Modeling the removal of downstream flow targets, scenario 4 had periods of lower flow in the Mahoning River from April to mid-September as water was held in the lakes, and periods of higher Mahoning River flow from mid-September through November as the lakes were drawn down to prepare for winter flood-risk management.</li><li>In the four scenarios, all the lakes and lake outflows had generally similar seasonal cycles of water quality, though some differences were predicted. For instance, higher concentrations of iron and ammonia in the Lake Milton hypolimnion were modeled during a period of both low inflows from Berlin Lake and low outflows at Lake Milton dam. It is possible that those changes could be minimized by maintaining more flow or pulses of higher flow through the lake.</li><li>Compared to the scenario 1 base case, changes to Mahoning River water quality were relatively minor for scenarios 2 and 3, which maintained downstream flows but shifted the flow source among the upstream lakes.</li><li>The largest changes in Mahoning River water quality were predicted between Leavittsburg and Lowellville for scenario 4. The periods of lower lake outflows between April and mid-September led to correspondingly higher concentrations of TDS, orthophosphate, total phosphorus, and nitrate in the river, compared to the base case scenario 1. Conversely, the overall greater lake outflows from mid-September through November in scenario 4 led to periods of lower concentrations of TDS and nutrients in that portion of the river, at that time of year.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225125","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Sullivan, A.B., Georgetson, G.M., Urbanczyk, C.E., Gordon, G.W., Wherry, S.A., and Long, W.B., 2023, Modeling flow and water quality in reservoir and river reaches of the Mahoning River Basin, Ohio: U.S. Geological Survey Scientific Investigations Report 2022–5125, 101 p., https://doi.org/10.3133/sir20225125.","productDescription":"Report: xi, 101 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124907","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":413149,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5125/images"},{"id":413146,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5125/sir20225125.pdf","text":"Report","size":"38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5125"},{"id":413145,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5125/coverthb.jpg"},{"id":500467,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114425.htm","linkFileType":{"id":5,"text":"html"}},{"id":413150,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5125/sir20225125.XML"},{"id":413148,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IRZL8S","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 water-quality model and data for Berlin Lake, Lake Milton, Michael J Kirwan Reservoir, Mosquito Creek Lake, and the Mahoning River, Ohio"}],"country":"United States","state":"Ohio","otherGeospatial":"Mahoning River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.09848920357355,\n              40.83548711669414\n            ],\n            [\n              -80.46047172680031,\n              40.83548711669414\n            ],\n            [\n              -80.46047172680031,\n              41.777477506089326\n            ],\n            [\n              -81.09848920357355,\n              41.777477506089326\n            ],\n            [\n              -81.09848920357355,\n              40.83548711669414\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/or-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/or-water\">Oregon Water Science Center</a><br>U.S. Geological Survey<br>601 SW 2nd Avenue, Suite 1950<br>Portland, OR 97204</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Methods and Data</li><li>Model Development</li><li>Model Water Quality</li><li>Model Application</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2023-02-27","noUsgsAuthors":false,"publicationDate":"2023-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":79821,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett B.","email":"annett@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":864550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Georgetson, Gabrielle M.","contributorId":302498,"corporation":false,"usgs":false,"family":"Georgetson","given":"Gabrielle","email":"","middleInitial":"M.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":864551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Urbanczyk, Christina E.","contributorId":302499,"corporation":false,"usgs":false,"family":"Urbanczyk","given":"Christina","email":"","middleInitial":"E.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":864552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gordon, Gabriel W. 0000-0001-6866-0302 ggordon@usgs.gov","orcid":"https://orcid.org/0000-0001-6866-0302","contributorId":269773,"corporation":false,"usgs":true,"family":"Gordon","given":"Gabriel W.","email":"ggordon@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wherry, Susan A. 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":4952,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":864554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, William B. 0000-0002-9097-0603 wlong@usgs.gov","orcid":"https://orcid.org/0000-0002-9097-0603","contributorId":302501,"corporation":false,"usgs":true,"family":"Long","given":"William","email":"wlong@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864555,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240798,"text":"sir20225126 - 2023 - Estimating streamflow for base flow conditions at partial-record streamgaging stations at Acadia National Park, Maine","interactions":[],"lastModifiedDate":"2026-02-24T17:51:19.791819","indexId":"sir20225126","displayToPublicDate":"2023-02-23T12:15:00","publicationYear":"2023","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":"2022-5126","displayTitle":"Estimating Streamflow for Base Flow Conditions at Partial-Record Streamgaging Stations at Acadia National Park, Maine","title":"Estimating streamflow for base flow conditions at partial-record streamgaging stations at Acadia National Park, Maine","docAbstract":"<p>The objective of the work presented in this report is to develop equations that can be used to extend the base flow record at multiple partial-record streamgaging stations at Acadia National Park in eastern coastal Maine based on nearby continuous-record streamgaging stations. Daily mean streamflow values at U.S. Geological Survey continuous-record streamgaging station Otter Creek near Bar Harbor, Maine (station 01022840) had stronger correlations with instantaneous measurements during base flow conditions from 2006 to 2020 at 14 partial-record streamgaging stations at Acadia National Park than the other four continuous-record streamgaging stations tested for use as index stations. Index stations are continuous-record stations on hydrologically similar streams that have the potential to be used to extend the record at the partial-record station. Base flow is that part of streamflow that is sustained primarily by groundwater discharge. It is not attributable to direct precipitation or melting snow. Five of the partial-record stations had strong correlations with Otter Creek (correlation coefficient greater than 0.90) and relatively low root mean square errors (from 0.04 to 0.19). An additional four partial-record stations had fair correlations with Otter Creek (correlation coefficient from 0.79 to 0.9) and relatively low root mean square errors (from 0.05 to 0.19). For these 10 stations, maintenance of variance extension type 1 (MOVE.1) record extension equations computed in this report provide a reasonable method for extending the partial record, estimating summer monthly means and medians, and estimating daily mean streamflow values at these sites on days with no streamflow (discharge) measurements. Four of the partial-record stations have weak correlations (less than 0.78) or high root mean square error values (greater than 9) or both, indicating that record extension techniques are not appropriate for these partial-record stations using currently [2022] available data.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225126","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Lombard, P.J., 2023, Estimating streamflow for base flow conditions at partial-record streamgaging stations at Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report 2022–5126, 13 p., https://doi.org/10.3133/sir20225126.","productDescription":"Report: vi, 13 p.; Data Release","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-143769","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":413317,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZP8XHG","text":"USGS data release","linkHelpText":"Data and code to support MOVE.1 regression equations for streamflow at partial-record streamgaging stations at Acadia National Park, Maine:"},{"id":413315,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5126/sir20225126.XML"},{"id":413312,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5126/coverthb.jpg"},{"id":413313,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5126/sir20225126.pdf","text":"Report","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5126"},{"id":413316,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5126/images/"},{"id":413864,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225126/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5126"},{"id":500481,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114380.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -68.16726259768689,\n              44.32624433734378\n            ],\n            [\n              -68.17739845831488,\n              44.36973371484888\n            ],\n            [\n              -68.21954229987337,\n              44.38307924264697\n            ],\n            [\n              -68.23981402112935,\n              44.41090441296549\n            ],\n            [\n              -68.28035746364178,\n              44.41928748605292\n            ],\n            [\n              -68.29422758871185,\n              44.406712425764226\n            ],\n            [\n              -68.33050330043281,\n              44.35371506667144\n            ],\n            [\n              -68.38971806515461,\n              44.35562227826236\n            ],\n            [\n              -68.40305472387581,\n              44.31937464393428\n            ],\n            [\n              -68.39025153150348,\n              44.27890346604781\n            ],\n            [\n              -68.3390387620142,\n              44.21661505589944\n            ],\n            [\n              -68.3112985118746,\n              44.217762064180675\n            ],\n            [\n              -68.2883594588743,\n              44.24566571236582\n            ],\n            [\n              -68.30329651664208,\n              44.285396004838105\n            ],\n            [\n              -68.24514868461804,\n              44.281958867796675\n            ],\n            [\n              -68.1982036459197,\n              44.29532438221068\n            ],\n            [\n              -68.16726259768689,\n              44.32662596339111\n            ],\n            [\n              -68.16726259768689,\n              44.32624433734378\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ nweng@usgs.gov\" data-mce-href=\"mailto:dc_ nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods of Data Collection and Analysis</li><li>Extending the Records at Partial-Record Stations by Use of Continuous-Record Streamgages</li><li>Estimated Streamflow at Acadia National Park</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-02-23","noUsgsAuthors":false,"publicationDate":"2023-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":205225,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864860,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70240725,"text":"gip221 - 2023 - The water cycle","interactions":[],"lastModifiedDate":"2023-03-01T20:15:04.190572","indexId":"gip221","displayToPublicDate":"2023-02-22T14:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"221","displayTitle":"The Water Cycle","title":"The water cycle","docAbstract":"An illustrated diagram of the water cycle. This is a modern, updated version of the widely used diagram featured on the USGS Water Science School. Notably, this new water cycle diagram depicts humans and major categories of human water use as key components of the water cycle, in addition to the key pools and fluxes of the hydrologic cycle. This product targets an 8th grade audience and is designed to be printed as a poster.","language":"English, Spanish","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip221","usgsCitation":"Corson-Dosch, H.R., Nell, C.S., Volentine, R.E., Archer, A.A., Bechtel, E., Bruce, J.L., Felts, N., Gross, T.A., Lopez-Trujillo, D., Riggs, C.E., and Read, E.K., 2023, The water cycle: U.S. Geological Survey General Information Product 221, 1 sheet, https://doi.org/10.3133/gip221.","productDescription":"1 Sheet: 38.00 x 26.00 inches","numberOfPages":"1","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-146978","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":413134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/221/coverthb.jpg"},{"id":413137,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/special-topics/water-science-school/science/water-cycle","text":"The Water Cycle","linkFileType":{"id":5,"text":"html"}},{"id":413135,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/gip/221/gip221_english.pdf","text":"English version","size":"8.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 221 English"},{"id":413136,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/gip/221/gip221_spanish.pdf","text":"Spanish version","size":"9.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 221 Spanish"}],"publicComments":"The U.S. Geological Survey published the original manuscript in English as General Information Product 221 and underwent review and approval in English subject to USGS Fundamental Science Practices. The translated version is not the work of USGS and, therefore, does not carry the same approval by USGS as the original work. Translation errors are the sole responsibility of the author.","contact":"<p>Integrated Information Dissemination Division<br><a href=\"https://www.usgs.gov/mission-areas/water-resources\" data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources\">Water Resource Mission Area</a><br>U.S. Geological Survey<br>1 Gifford Pinchot Drive<br>Madison, WI 53726<br>Email: <a href=\"mailto:water-science-school@usgs.gov\" data-mce-href=\"mailto:water-science-school@usgs.gov\">water-science-school@usgs.gov</a></p>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-02-22","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Corson-Dosch, Hayley R. 0000-0001-8695-1584","orcid":"https://orcid.org/0000-0001-8695-1584","contributorId":244707,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Hayley","middleInitial":"R.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nell, Cee S. 0000-0003-2218-3971","orcid":"https://orcid.org/0000-0003-2218-3971","contributorId":244705,"corporation":false,"usgs":true,"family":"Nell","given":"Cee","middleInitial":"S.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Volentine, Rachel E. 0000-0002-4837-8075","orcid":"https://orcid.org/0000-0002-4837-8075","contributorId":302488,"corporation":false,"usgs":true,"family":"Volentine","given":"Rachel","email":"","middleInitial":"E.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Archer, Althea A. 0000-0003-1927-0783","orcid":"https://orcid.org/0000-0003-1927-0783","contributorId":302489,"corporation":false,"usgs":true,"family":"Archer","given":"Althea","email":"","middleInitial":"A.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864534,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bechtel, Ellen","contributorId":302490,"corporation":false,"usgs":false,"family":"Bechtel","given":"Ellen","email":"","affiliations":[{"id":65480,"text":"Gro Intelligence","active":true,"usgs":false}],"preferred":false,"id":864535,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bruce, Jennifer L. 0000-0003-4915-5567 jlbruce@usgs.gov","orcid":"https://orcid.org/0000-0003-4915-5567","contributorId":132,"corporation":false,"usgs":true,"family":"Bruce","given":"Jennifer","email":"jlbruce@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864536,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Felts, Nicole 0000-0002-9908-2370","orcid":"https://orcid.org/0000-0002-9908-2370","contributorId":302491,"corporation":false,"usgs":false,"family":"Felts","given":"Nicole","email":"","affiliations":[{"id":65481,"text":"Akima Systems Engineering","active":true,"usgs":false}],"preferred":false,"id":864537,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gross, Tara A. 0000-0003-0161-3434","orcid":"https://orcid.org/0000-0003-0161-3434","contributorId":213236,"corporation":false,"usgs":true,"family":"Gross","given":"Tara","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864538,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lopez-Trujillo, Dianne 0000-0002-1771-0725","orcid":"https://orcid.org/0000-0002-1771-0725","contributorId":207759,"corporation":false,"usgs":true,"family":"Lopez-Trujillo","given":"Dianne","email":"","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864539,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Riggs, Charlotte E. 0000-0002-3597-0328","orcid":"https://orcid.org/0000-0002-3597-0328","contributorId":302492,"corporation":false,"usgs":true,"family":"Riggs","given":"Charlotte","email":"","middleInitial":"E.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864540,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Read, Emily 0000-0002-9617-9433 eread@usgs.gov","orcid":"https://orcid.org/0000-0002-9617-9433","contributorId":190110,"corporation":false,"usgs":true,"family":"Read","given":"Emily","email":"eread@usgs.gov","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":864541,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70244045,"text":"70244045 - 2023 - Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA)","interactions":[],"lastModifiedDate":"2023-05-31T14:30:11.069748","indexId":"70244045","displayToPublicDate":"2023-02-22T09:26:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA)","docAbstract":"<p><strong>Study region</strong></p><p>The Southern Hills aquifer system in the Louisiana Capital Area Groundwater Conservation District (CAGCD), USA.</p><p><strong>Study focus</strong></p><p>The Southern Hills aquifer system provides abundant groundwater for public and industrial supplies in the CAGCD. Groundwater depletion, saltwater intrusion, and land subsidence are potential concerns due to prolonged excessive groundwater withdrawals. This study develops a high-fidelity groundwater flow model utilizing a complex unstructured grid to investigate groundwater flow and storage responses to excessive groundwater withdrawals for the <span>Southern Hills aquifer system</span> in the CAGCD. The groundwater model incorporates the Mississippi River alluvial aquifer down to the Miocene sands extending to depths around 1 km.</p><p><strong>New hydrological insights</strong><br></p><p>Groundwater modeling results indicate large cones of depression in the Evangeline and Jasper formations in the Baton Rouge area due to prolonged groundwater withdrawals. Low-permeability faults are inferred by significant groundwater level difference across the faults. While local groundwater storage depletion in deeper aquifers is evident, overall estimated groundwater storage changes of the <span>Southern Hills aquifer system</span> in the CAGCD are close to zero in the past two decades, indicating insignificant groundwater storage changes. This is attributed to dominant interactions between the major rivers and the shallower alluvial aquifer. In addition, the simulated groundwater storage changes exhibit patterns similar to those derived by the Gravity Recovery and Climate Experiment (GRACE) model that has been used in evaluation of groundwater depletion in many regional studies.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2023.101342","usgsCitation":"Chen, Y., Vahdat-Aboueshagh, H., Tsai, F.T., Dausman, A., and Runge, M.C., 2023, Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA): Journal of Hydrology: Regional Studies, v. 46, 101342, 22 p., https://doi.org/10.1016/j.ejrh.2023.101342.","productDescription":"101342, 22 p.","ipdsId":"IP-137603","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2023.101342","text":"Publisher Index Page"},{"id":417579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Southern Hills aquifer system","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.91720564327883,\n              31.007470903702682\n            ],\n            [\n              -91.91720564327883,\n              30.261535321867598\n            ],\n            [\n              -90.71125532149338,\n              30.261535321867598\n            ],\n            [\n              -90.71125532149338,\n              31.007470903702682\n            ],\n            [\n              -91.91720564327883,\n              31.007470903702682\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"46","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Ye-Hong","contributorId":305936,"corporation":false,"usgs":false,"family":"Chen","given":"Ye-Hong","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vahdat-Aboueshagh, Hamid","contributorId":305937,"corporation":false,"usgs":false,"family":"Vahdat-Aboueshagh","given":"Hamid","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tsai, Frank T.-C.","contributorId":305938,"corporation":false,"usgs":false,"family":"Tsai","given":"Frank","email":"","middleInitial":"T.-C.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dausman, Alyssa","contributorId":223766,"corporation":false,"usgs":false,"family":"Dausman","given":"Alyssa","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":874256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":874257,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240838,"text":"70240838 - 2023 - Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation","interactions":[],"lastModifiedDate":"2023-02-24T13:08:09.195827","indexId":"70240838","displayToPublicDate":"2023-02-22T07:04:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation","docAbstract":"<div class=\"article-section__content en main\"><p>Wildfire is a growing concern as climate shifts. The hydrologic effects of wildfire, which include elevated hazards and changes in water quantity and quality, are increasingly assessed using numerical models. Post-wildfire application of physically based distributed models provides unique insight into the underlying processes that affect water resources after wildfire. This work reviews and synthesizes post-wildfire applications of physically based distributed models by examining the scales and geographic/ecohydrologic distribution of model applications, hydrologic response process representation, model parameterization, and model performance metrics. Highlighted gaps and opportunities for advancing physically based distributed hydrologic response modeling after wildfire include the following: (a) applying models in under-represented geographic (S. America, Africa, Asia) and ecohydrologic regions (arid or dry subhumid climates), (b) incorporating all four major streamflow generation mechanisms (infiltration excess, saturation excess, subsurface storm flow, and groundwater flow), (c) representing integrated vadose zone and saturated zone processes to better capture subsurface streamflow generation, (d) building new remotely sensed model parameterization methods for precipitation interception, infiltration, and overland flow that account for burn severity and recovery, (e) incorporating distributed state variables (e.g., soil moisture, groundwater levels) in model performance assessment, (f) designing model intercomparison studies, including field datasets specifically for post-wildfire model development and validation, (g) linking mechanistic vegetation regrowth models with hydrologic models to improve simulation of process shifts as ecosystems recover, and (h) creating a new community modeling framework to integrate modeling advances across the wildfire science community.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EF003038","usgsCitation":"Ebel, B., Shephard, Z.M., Walvoord, M.A., Murphy, S.F., Partridge, T.F., and Perkins, K., 2023, Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation: Earth's Future, v. 11, e2022EF003038, 23 p., https://doi.org/10.1029/2022EF003038.","productDescription":"e2022EF003038, 23 p.","ipdsId":"IP-142611","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444393,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ef003038","text":"Publisher Index Page"},{"id":413398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":222581,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Partridge, Trevor Fuess 0000-0003-1589-4783","orcid":"https://orcid.org/0000-0003-1589-4783","contributorId":302668,"corporation":false,"usgs":true,"family":"Partridge","given":"Trevor","email":"","middleInitial":"Fuess","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perkins, Kimberlie 0000-0001-8349-447X kperkins@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-447X","contributorId":138544,"corporation":false,"usgs":true,"family":"Perkins","given":"Kimberlie","email":"kperkins@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865029,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240761,"text":"70240761 - 2023 - Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows","interactions":[],"lastModifiedDate":"2023-11-07T14:56:20.584618","indexId":"70240761","displayToPublicDate":"2023-02-20T16:04:57","publicationYear":"2023","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":"Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows","docAbstract":"<h3 id=\"nafm10837-sec-1001-title\" class=\"article-section__sub-title section1\">Objective</h3><p>Regulation of river flow regimes by dams and diversions impacts aquatic biota and ecosystems globally. However, our understanding of the ecological consequences of flow alteration and ecological benefits of flow restoration lags behind our ability to manipulate flows, and there is a need for broader development of flow–ecology relationships. Approaches for establishing flow–ecology relationships have recently shifted away from state-based methods that analyze snapshots of ecological conditions and towards rate-based methods focused on mechanisms that link hydrology with dynamics of important ecological components and processes.</p><h3 id=\"nafm10837-sec-2002-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We used a rate-based approach to validate environmental flow standards developed for the lower Brazos River, Texas, by analyzing the relationship between flow regime components and recruitment strength of imperiled Shoal Chub<span>&nbsp;</span><i>Macrhybopsis hyostoma</i>, a fluvial specialist and pelagic-broadcast-spawning fish. We collected 254 age-0 Shoal Chub (9–40 mm total length), extracted their otoliths to estimate age in days, and used a generalized additive model to regress the number of captured recruits that hatched on a calendar date against flow regime metrics, such as pulse magnitude, flow rate of change, and pulse timing in relation to environmental flow standards proposed by a science advisory committee (Brazos Basin and Bay Area Expert Science Team).</p><h3 id=\"nafm10837-sec-3002-title\" class=\"article-section__sub-title section1\">Result</h3><p>The model revealed that flow magnitude, rate of change, and timing were all significant predictors that collectively explained 60% of variation in the recruitment strength index. Hindcasting for 1919–2020 showed a general reduction in recruitment strength following commencement of flow regulation in the lower Brazos River and revealed that high recruitment correlated with years in which most or all proposed flow tiers were attained, whereas low recruitment correlated with years when less than half of the targeted tiers were attained.</p><h3 id=\"nafm10837-sec-4002-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Our work represents an effective validation method for environmental flow recommendations and reveals specific flow regimes that benefit an imperiled fish species.</p>","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10837","usgsCitation":"Perkin, J., Acre, M.R., Ellard, J.K., Rodger, A.W., Trungale, J., Winemiller, K.O., and Yancy, L.E., 2023, Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows: North American Journal of Fisheries Management, v. 43, no. 5, p. 1260-1275, https://doi.org/10.1002/nafm.10837.","productDescription":"16 p.","startPage":"1260","endPage":"1275","ipdsId":"IP-137319","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":413226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Brazos River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -103.55664204856129,\n              34.891337132196966\n            ],\n            [\n              -103.67919574341136,\n              34.90431733940822\n            ],\n            [\n              -103.67460945809466,\n              33.88709425240866\n            ],\n            [\n              -100.07733765481305,\n              32.32672893624452\n            ],\n            [\n              -97.58389153733157,\n              30.525918073387786\n            ],\n            [\n              -96.49599579297191,\n              28.1805962671085\n            ],\n            [\n              -95.17251974775999,\n              28.869046167859096\n            ],\n            [\n              -96.08662137570019,\n              30.375252554772146\n            ],\n            [\n              -96.7579178547347,\n              31.664902948076772\n            ],\n            [\n              -99.43674912606912,\n              33.62884152650054\n            ],\n            [\n              -101.21968168739465,\n              34.14353705447044\n            ],\n            [\n              -103.55664204856129,\n              34.891337132196966\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Perkin, Joshuah S.","contributorId":238286,"corporation":false,"usgs":false,"family":"Perkin","given":"Joshuah S.","affiliations":[{"id":47708,"text":"Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX","active":true,"usgs":false}],"preferred":false,"id":864741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":864742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellard, Johnathan K.","contributorId":302585,"corporation":false,"usgs":false,"family":"Ellard","given":"Johnathan","email":"","middleInitial":"K.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":864743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodger, Anthony W.","contributorId":302586,"corporation":false,"usgs":false,"family":"Rodger","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":864744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trungale, Joe","contributorId":302587,"corporation":false,"usgs":false,"family":"Trungale","given":"Joe","email":"","affiliations":[{"id":65515,"text":"Texas Conservation Science","active":true,"usgs":false}],"preferred":false,"id":864745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winemiller, Kirk O.","contributorId":265134,"corporation":false,"usgs":false,"family":"Winemiller","given":"Kirk","email":"","middleInitial":"O.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":864746,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yancy, Lauren E.","contributorId":302588,"corporation":false,"usgs":false,"family":"Yancy","given":"Lauren","email":"","middleInitial":"E.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":864747,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70240754,"text":"70240754 - 2023 - Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region","interactions":[],"lastModifiedDate":"2023-02-20T22:04:07.85217","indexId":"70240754","displayToPublicDate":"2023-02-20T15:55:10","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region","docAbstract":"<p><span>Accurate mapping of streams that maintain surface flow during annual baseflow periods in mountain headwater streams is important for informing water availability for human consumption and is a fundamental determinant of in-channel conditions for stream-dwelling organisms. Yet accurate mapping that captures local spatial variability and associated local controls on surface flow presence is limited. An empirical random-forest model was developed to predict streamflow permanence (late summer surface-flow presence) for Mount Rainier National Park and the surrounding mountainous area in western Washington, USA. This model was developed to improve upon the existing multi-state, regional-scale probability of stream permanence developed for the greater Pacific Northwest Region (PROSPER</span><sub>PNW</sub><span>). The model was trained on 544 wet/dry observations collected during the late summer, baseflow period from 2018 to 2020 using the crowd-source mobile application, FLOwPER. Final model accuracy was 0.74 with drainage area and covariates describing geology, topography, and land cover as top predictors of streamflow permanence compared to coarser resolution climatic covariates. The prevalence of static covariates over climatic covariates as top ranked important covariates highlights the importance of scale when evaluating controls on streamflow permanence. Cross validation of the model indicates that streamflow permanence probabilities from this model is an improvement over the regional-scale PROSPER</span><sub>PNW</sub><span>&nbsp;model demonstrating the utility of relatively simple, crowd-sourced data to address water resource needs, and that determination of important predictors of streamflow permanence is influenced by the spatial and temporal resolution of analysis.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14813","usgsCitation":"Jaeger, K.L., Sando, R., Dunn, S., and Gendaszek, A.S., 2023, Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region: Hydrological Processes, v. 37, no. 2, e14813, 20 p., https://doi.org/10.1002/hyp.14813.","productDescription":"e14813, 20 p.","ipdsId":"IP-141066","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":444412,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14813","text":"Publisher Index Page"},{"id":435442,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P942QL23","text":"USGS data release","linkHelpText":"Supporting data for and predictions from streamflow permanence modeling in Mount Rainier National Park and surrounding area, Washington, 2018-2020"},{"id":413225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mt. Rainier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.91425095542269,\n              47.01752002020956\n            ],\n            [\n              -122.78795134745224,\n              46.62862820386181\n            ],\n            [\n              -122.55339493264981,\n              46.550098584041734\n            ],\n            [\n              -122.65563747243549,\n              46.34497384739839\n            ],\n            [\n              -122.89620815428425,\n              46.09474739160191\n            ],\n            [\n              -122.7909584809756,\n              45.92766699262768\n            ],\n            [\n              -122.74585147812789,\n              45.67282216496895\n            ],\n            [\n              -122.66766600652696,\n              45.61185277936909\n            ],\n            [\n              -122.30380285023114,\n              45.54239311283217\n            ],\n            [\n              -121.81664721948816,\n              45.70223191477319\n            ],\n            [\n              -121.67531194390217,\n              45.68332742209245\n            ],\n            [\n              -121.45879833023858,\n              45.69383070693286\n            ],\n            [\n              -121.1580849779278,\n              45.630781413305954\n            ],\n            [\n              -120.98066410006487,\n              45.679125555918176\n            ],\n            [\n              -121.06185670518839,\n              46.012189334319174\n            ],\n            [\n              -121.07388523928094,\n              46.11234505718508\n            ],\n            [\n              -120.77317188697053,\n              46.28718041984081\n            ],\n            [\n              -120.78219328754065,\n              46.50050734721816\n            ],\n            [\n              -120.60477240967734,\n              46.628693092975396\n            ],\n            [\n              -120.65589367957018,\n              46.69473497860815\n            ],\n            [\n              -120.90548576198775,\n              46.88004533998597\n            ],\n            [\n              -121.37760572511556,\n              47.1445446352175\n            ],\n            [\n              -122.05120363429107,\n              47.246711543948805\n            ],\n            [\n              -122.36695265421739,\n              47.369052224585346\n            ],\n            [\n              -122.54136639855736,\n              47.309956252224225\n            ],\n            [\n              -122.67368027357409,\n              47.14249929055501\n            ],\n            [\n              -122.9052295548532,\n              47.16294919605744\n            ],\n            [\n              -122.91425095542269,\n              47.01752002020956\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"37","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":864708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Sarah B. 0000-0003-4463-0074","orcid":"https://orcid.org/0000-0003-4463-0074","contributorId":291768,"corporation":false,"usgs":false,"family":"Dunn","given":"Sarah B.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":864709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864710,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70240844,"text":"70240844 - 2023 - Hydrologic compartmentalization and analytic-element groundwater-flow simulations for a draining mine tunnel","interactions":[],"lastModifiedDate":"2023-02-24T12:37:42.644166","indexId":"70240844","displayToPublicDate":"2023-02-18T06:32:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic compartmentalization and analytic-element groundwater-flow simulations for a draining mine tunnel","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section c-article-content-visibility\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Draining mine tunnels contribute contaminants to groundwater and surface water, but remediation strategies may be hindered as hydrogeologic characterization and modeling of these heterogeneous features generally relies on sparse data sets. The Captain Jack mine site in Colorado, USA, presents a unique data set allowing for temporal evaluation of groundwater connectivity in the vicinity of an abandoned mine, where a hydraulic bulkhead is impounding water within the mine workings. This study applied statistical analysis of system pressure responses to bulkheading and used an analytic-element modeling approach to characterize heterogeneity and groundwater flow. Groundwater-level elevation data collected over a period of 4 years, both prior to and after bulkheading, indicate that the mine workings act as a sink to the local groundwater system. Despite groundwater flow being generally oriented towards the mine workings, there are also large vertical and horizontal hydraulic gradients which persist through time. Although the groundwater system is highly compartmentalized, statistical analysis using Kendall’s Tau indicates correlations between hydraulic head changes in the mine workings and several wells completed in crystalline bedrock, indicating the influence of fracture flow. An analytic-element model was parameterized to account for uncertainty in hydraulic conductivity, recharge, and discharge. Model results reproduced the range of observed hydraulic heads in the mine workings and adjacent igneous dikes but failed to closely simulate hydraulic heads in several wells located distal from the mine workings in granitic bedrock. The modeling approach shows potential promise, however, for conducting preliminary modeling to guide data collection at other similar mine sites.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s12665-023-10797-3","usgsCitation":"Newman, C.P., 2023, Hydrologic compartmentalization and analytic-element groundwater-flow simulations for a draining mine tunnel: Environmental Earth Sciences, v. 82, 117, 14 p., https://doi.org/10.1007/s12665-023-10797-3.","productDescription":"117, 14 p.","ipdsId":"IP-131194","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":435445,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NVBZXO","text":"USGS data release","linkHelpText":"Analytic-element groundwater-flow model of the Captain Jack Superfund Site, Boulder County, Colorado"},{"id":413393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.718234057508,\n              40.20731895041291\n            ],\n            [\n              -105.718234057508,\n              39.92577764315672\n            ],\n            [\n              -105.21856832600534,\n              39.92577764315672\n            ],\n            [\n              -105.21856832600534,\n              40.20731895041291\n            ],\n            [\n              -105.718234057508,\n              40.20731895041291\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2023-02-18","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":865033,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70240735,"text":"70240735 - 2023 - Declines in prey production during the collapse of a tailwater Rainbow Trout population are associated with changing reservoir conditions","interactions":[],"lastModifiedDate":"2023-02-17T13:06:18.673026","indexId":"70240735","displayToPublicDate":"2023-02-16T07:01:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13429,"text":"Transactions of American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Declines in prey production during the collapse of a tailwater Rainbow Trout population are associated with changing reservoir conditions","docAbstract":"<div class=\"article-section__content en main\"><h3 id=\"tafs10381-sec-0050-title\" class=\"article-section__sub-title section1\">Objective</h3><p>Understanding how energy moves through food webs and limits productivity at various trophic levels is a central question in aquatic ecology and can provide insight into drivers of fish population dynamics since many fish populations are food limited. In this study, we seek to better understand what factors drove a decline of &gt;85% in the number of Rainbow Trout<i>Oncorhynchus mykiss</i><span>&nbsp;</span>found in the tailwater portion of the Colorado River below Glen Canyon Dam during 2012–2016.</p><h3 id=\"tafs10381-sec-0051-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We estimate the production of dominant prey using data from previously published studies of Rainbow Trout abundance and growth alongside drift and diet samples. We test how prey production correlates to both proximate (e.g., nutrients) and distal (e.g., limnological conditions in the upriver reservoir) drivers.</p><h3 id=\"tafs10381-sec-0052-title\" class=\"article-section__sub-title section1\">Result</h3><p>Results suggest that gross consumption of invertebrate prey by the Rainbow Trout population declined from an annual mean of 423 to 69 kg/d. Daily production rates of dominant prey in aggregate declined from a high of 0.173 to 0.018 g·m<sup>−2</sup>·d<sup>−1</sup>. Chironomids accounted for 70% of the decline in prey production. Foraging efficiency by Rainbow Trout (range, 0.99–0.67) was high across the range of prey production rates. After the Rainbow Trout population had declined by ~90%, prey consumption saturated at higher rates of prey production and the gross quantity of daily drift exported from the reach increased from 8.9 to 12.7 kg/d.</p><h3 id=\"tafs10381-sec-0053-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Rainbow Trout population dynamics are largely influenced by changes in prey production, which is itself driven by soluble reactive phosphorus (<i>SRP</i>) concentrations in the reservoir. The<span>&nbsp;</span><i>SRP</i><span>&nbsp;</span>model predicted that prey production would increase by 32 kg/d (SE, 9) for each 1 μg/L increase in<span>&nbsp;</span><i>SRP</i>. These concentrations were indirectly influenced by reservoir hydrology and biogeochemistry, linkages that may extend far beyond the confines of this tailwater fishery and into the downstream reaches of the Grand Canyon's Colorado River ecosystem.</p></div><h2 id=\"d1855562\" class=\"article-section__header section__title short abstractlang_en short\">Impact Statement</h2><div class=\"article-section__content en short\"><p>We combined Rainbow Trout diet, growth, and abundance estimates with concentrations of drifting invertebrates to estimate the biomass of Rainbow Trout prey produced over time. Trends in prey biomass production track trends in phosphorous concentrations in the river.</p></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10381","usgsCitation":"Yard, M., Yackulic, C., Korman, J., Dodrill, M., and Deemer, B., 2023, Declines in prey production during the collapse of a tailwater Rainbow Trout population are associated with changing reservoir conditions: Transactions of American Fisheries Society, v. 152, no. 1, p. 35-50, https://doi.org/10.1002/tafs.10381.","productDescription":"16 p.","startPage":"35","endPage":"50","ipdsId":"IP-136012","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":444449,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10381","text":"Publisher Index Page"},{"id":435448,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UZTYPV","text":"USGS data release","linkHelpText":"Proximal and distal factors associated with the decline in secondary invertebrate prey production in the Colorado River, Glen Canyon, Arizona."},{"id":413166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.76609386826277,\n              36.969605706868535\n            ],\n            [\n              -112.76609386826277,\n              35.400882138821785\n            ],\n            [\n              -110.38307786825146,\n              35.400882138821785\n            ],\n            [\n              -110.38307786825146,\n              36.969605706868535\n            ],\n            [\n              -112.76609386826277,\n              36.969605706868535\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"152","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Yard, Michael D. 0000-0002-6580-6027","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":291738,"corporation":false,"usgs":false,"family":"Yard","given":"Michael D.","affiliations":[{"id":62744,"text":"Retired, US Geological Survey, Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":864590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":864591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Korman, Josh","contributorId":139960,"corporation":false,"usgs":false,"family":"Korman","given":"Josh","email":"","affiliations":[{"id":13333,"text":"Ecometric Research Inc.","active":true,"usgs":false}],"preferred":false,"id":864592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dodrill, Michael J. 0000-0002-7038-7170","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":206439,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":864593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":864594,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70242152,"text":"70242152 - 2023 - Groundwater recharge in northern New England: Meteorological drivers and relations with low streamflow","interactions":[],"lastModifiedDate":"2023-04-10T11:37:58.859573","indexId":"70242152","displayToPublicDate":"2023-02-16T06:33:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater recharge in northern New England: Meteorological drivers and relations with low streamflow","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Meteorological drivers of groundwater recharge for spring (February–June), fall (October–January), and recharge-year (October–June) recharge seasons were evaluated for northern New England and upstate New York from 1989 to 2018. Monthly groundwater recharge was computed at 21 observation wells by subtracting the water levels at the end of each month from the level of the previous month; only positive monthly values were used to compute seasonal recharge. Precipitation, temperature, sea-level pressure, 500-mb geopotential heights, and various teleconnection indices were tested as explanatory variables for the interannual variability of recharge using random forest machine learning models. Precipitation within recharge seasons was positively correlated with groundwater recharge for most wells in all seasons. In general, whilst groundwater recharge in the study area was generally highest during the months of March and April, October precipitation was an important month for explaining the interannual groundwater recharge variability. This is likely because the variability in recharge in October may be high or low for given years. Sea-level pressure and 500-mb heights were typically inversely correlated with groundwater recharge during the recharge-year and fall recharge seasons, as higher sea-level pressure and heights are usually associated with clearer skies and less precipitation. The North Atlantic Oscillation, Pacific-North American pattern, and Pacific Decadal Oscillation teleconnections affected groundwater recharge differently by well and season. The influence of groundwater recharge on minimum daily streamflows during the subsequent summer/fall was also analysed. Summer precipitation was the most important explanatory variable for study streams whilst groundwater recharge and summer air temperature were significant variables for a few streams.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14832","usgsCitation":"Crossett, C., Hodgkins, G.A., Menk, H., Dupigny-Giroux, L.L., Dudley, R., Lemcke-Stampone, M.D., and Hammond, J., 2023, Groundwater recharge in northern New England: Meteorological drivers and relations with low streamflow: Hydrological Processes, v. 37, no. 3, e14832, 13 p., https://doi.org/10.1002/hyp.14832.","productDescription":"e14832, 13 p.","ipdsId":"IP-141714","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":444457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14832","text":"Publisher Index Page"},{"id":415490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, New Hampshire, Vermont","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-70.152589,43.746794],[-70.157754,43.749818],[-70.145911,43.772119],[-70.128271,43.774009],[-70.152589,43.746794]]],[[[-70.171245,43.663498],[-70.205934,43.633633],[-70.211062,43.641842],[-70.188047,43.673762],[-70.171245,43.663498]]],[[[-70.186213,43.682655],[-70.21313,43.662973],[-70.201893,43.685483],[-70.186213,43.682655]]],[[[-70.163884,43.692404],[-70.135563,43.700658],[-70.168227,43.675136],[-70.173571,43.683734],[-70.163884,43.692404]]],[[[-70.087621,43.699913],[-70.115908,43.682978],[-70.095727,43.709278],[-70.097184,43.700929],[-70.087621,43.699913]]],[[[-70.119671,43.748621],[-70.097318,43.757292],[-70.108978,43.722312],[-70.124136,43.70832],[-70.138711,43.727559],[-70.119671,43.748621]]],[[[-68.499465,44.12419],[-68.491521,44.109833],[-68.502942,44.099722],[-68.51706,44.10341],[-68.511266,44.125082],[-68.499465,44.12419]]],[[[-68.358388,44.125082],[-68.346724,44.127749],[-68.330716,44.110598],[-68.338012,44.101473],[-68.365176,44.101464],[-68.376593,44.112207],[-68.358388,44.125082]]],[[[-68.453236,44.189998],[-68.416434,44.187047],[-68.384903,44.154955],[-68.438518,44.11618],[-68.456813,44.145268],[-68.502096,44.152388],[-68.474365,44.181875],[-68.453236,44.189998]]],[[[-68.680773,44.279242],[-68.623554,44.255622],[-68.605906,44.230772],[-68.612749,44.207722],[-68.624994,44.197637],[-68.618872,44.18107],[-68.643002,44.15766],[-68.670014,44.151537],[-68.671454,44.138572],[-68.681899,44.138212],[-68.692343,44.153698],[-68.720435,44.169185],[-68.714313,44.20376],[-68.722956,44.219607],[-68.700627,44.234013],[-68.680458,44.262105],[-68.680773,44.279242]]],[[[-68.355279,44.199096],[-68.333227,44.207308],[-68.31606,44.200244],[-68.332639,44.192131],[-68.339029,44.171839],[-68.347416,44.169459],[-68.378872,44.184222],[-68.355279,44.199096]]],[[[-68.472831,44.219767],[-68.453843,44.201683],[-68.48452,44.202886],[-68.482726,44.227058],[-68.470323,44.22832],[-68.472831,44.219767]]],[[[-68.792139,44.237819],[-68.769833,44.222787],[-68.780055,44.203129],[-68.829593,44.21689],[-68.839422,44.236547],[-68.827627,44.242838],[-68.792139,44.237819]]],[[[-68.23638,44.266254],[-68.211329,44.257074],[-68.23713,44.25343],[-68.248913,44.235443],[-68.274427,44.237099],[-68.274719,44.258675],[-68.246598,44.257836],[-68.23638,44.266254]]],[[[-68.498637,44.369686],[-68.478785,44.319563],[-68.489641,44.313705],[-68.530394,44.333583],[-68.518573,44.381022],[-68.501364,44.382281],[-68.498637,44.369686]]],[[[-68.618212,44.012367],[-68.635315,44.018886],[-68.652881,44.003845],[-68.659874,44.022758],[-68.650767,44.039908],[-68.661594,44.075837],[-68.6181,44.096706],[-68.584074,44.070578],[-68.601099,44.058362],[-68.610703,44.013422],[-68.618212,44.012367]]],[[[-68.785601,44.053503],[-68.818441,44.032046],[-68.862845,44.025037],[-68.889717,44.032516],[-68.913406,44.08519],[-68.907812,44.105518],[-68.943105,44.10973],[-68.935327,44.13038],[-68.917286,44.148239],[-68.825067,44.186338],[-68.818423,44.160978],[-68.780693,44.143274],[-68.818039,44.136852],[-68.820515,44.130198],[-68.815562,44.115836],[-68.806832,44.116339],[-68.772639,44.078439],[-68.77029,44.069566],[-68.785601,44.053503]]],[[[-67.619761,44.519754],[-67.582113,44.513459],[-67.590627,44.49415],[-67.562651,44.472104],[-67.574206,44.45173],[-67.588346,44.449754],[-67.604919,44.502056],[-67.614954,44.503576],[-67.619761,44.519754]]],[[[-68.942826,44.281073],[-68.919301,44.309872],[-68.919325,44.335392],[-68.90353,44.378613],[-68.87894,44.386584],[-68.868444,44.38144],[-68.860649,44.364425],[-68.896587,44.321986],[-68.88746,44.303094],[-68.916872,44.242866],[-68.95189,44.218719],[-68.94709,44.226792],[-68.965264,44.259332],[-68.942826,44.281073]]],[[[-70.353392,43.535405],[-70.379123,43.507202],[-70.385615,43.487031],[-70.380233,43.46423],[-70.349684,43.442032],[-70.370514,43.434133],[-70.39089,43.402607],[-70.421282,43.395777],[-70.424421,43.379656],[-70.460717,43.34325],[-70.517695,43.344037],[-70.553854,43.321886],[-70.593907,43.249295],[-70.575787,43.221859],[-70.587814,43.199858],[-70.618973,43.163625],[-70.638355,43.114182],[-70.665958,43.076234],[-70.703818,43.059825],[-70.704696,43.070989],[-70.718936,43.03235],[-70.759175,42.989475],[-70.810069,42.909549],[-70.817296,42.87229],[-70.848625,42.860939],[-70.886136,42.88261],[-70.914886,42.886564],[-71.031201,42.859089],[-71.047501,42.844089],[-71.064201,42.806289],[-71.132503,42.821389],[-71.165603,42.808689],[-71.186104,42.790689],[-71.181803,42.73759],[-71.223904,42.746689],[-71.245504,42.742589],[-71.294205,42.69699],[-73.276421,42.746019],[-73.290944,42.80192],[-73.285388,42.834093],[-73.278673,42.83341],[-73.241589,43.534973],[-73.258631,43.564949],[-73.293536,43.578518],[-73.293741,43.605203],[-73.306234,43.628018],[-73.371889,43.624489],[-73.372375,43.606014],[-73.39196,43.569915],[-73.430947,43.587036],[-73.417827,43.620586],[-73.426463,43.642598],[-73.415513,43.65245],[-73.402078,43.693106],[-73.370612,43.725329],[-73.370287,43.742269],[-73.350707,43.770463],[-73.390302,43.817371],[-73.390194,43.829364],[-73.372247,43.845337],[-73.381501,43.859235],[-73.37415,43.874163],[-73.407742,43.929887],[-73.407739,44.021312],[-73.43688,44.042578],[-73.411316,44.112686],[-73.41578,44.131523],[-73.403268,44.144295],[-73.390805,44.189072],[-73.362013,44.208545],[-73.349889,44.230356],[-73.324681,44.243614],[-73.313422,44.264199],[-73.334939,44.364441],[-73.315016,44.388513],[-73.293855,44.437556],[-73.306707,44.500334],[-73.342932,44.551907],[-73.374389,44.575455],[-73.381848,44.589316],[-73.376849,44.599598],[-73.38982,44.61721],[-73.361308,44.694523],[-73.365561,44.741786],[-73.333154,44.788759],[-73.335443,44.804602],[-73.381359,44.845021],[-73.360327,44.897236],[-73.338482,44.924112],[-73.337906,44.960541],[-73.353429,44.990165],[-73.343124,45.01084],[-73.059685,45.015869],[-72.67477,45.015459],[-72.310073,45.003822],[-71.502487,45.013367],[-71.491148,45.041774],[-71.505222,45.048791],[-71.497917,45.070589],[-71.467447,45.086851],[-71.427208,45.127364],[-71.437216,45.142333],[-71.39781,45.203553],[-71.403267,45.215348],[-71.443882,45.235462],[-71.420335,45.232719],[-71.406973,45.241516],[-71.38317,45.234904],[-71.357253,45.253336],[-71.362831,45.267617],[-71.336392,45.273066],[-71.284396,45.302434],[-71.266557,45.294589],[-71.262136,45.276098],[-71.231572,45.253472],[-71.196658,45.253594],[-71.180905,45.239858],[-71.158192,45.248746],[-71.13943,45.242958],[-71.097772,45.301906],[-71.00905,45.319022],[-71.002563,45.327819],[-71.01292,45.343297],[-71.004848,45.345419],[-70.985595,45.332188],[-70.950824,45.33453],[-70.921435,45.313867],[-70.912111,45.296197],[-70.9217,45.279445],[-70.898565,45.258502],[-70.892822,45.239172],[-70.857042,45.22916],[-70.84443,45.234513],[-70.83877,45.237555],[-70.848319,45.244707],[-70.848554,45.263325],[-70.812338,45.302006],[-70.807058,45.322464],[-70.819828,45.340109],[-70.802648,45.364933],[-70.826033,45.398408],[-70.798677,45.424146],[-70.755567,45.428361],[-70.712286,45.390611],[-70.677995,45.394362],[-70.651175,45.377123],[-70.634661,45.383608],[-70.635498,45.427817],[-70.717047,45.487732],[-70.723167,45.507606],[-70.687605,45.549099],[-70.688214,45.563981],[-70.644687,45.607083],[-70.592252,45.629865],[-70.5584,45.666671],[-70.525831,45.666551],[-70.469869,45.701639],[-70.400404,45.719834],[-70.383552,45.734869],[-70.388501,45.749717],[-70.406548,45.761813],[-70.417641,45.79377],[-70.395907,45.798885],[-70.387916,45.819043],[-70.34244,45.852192],[-70.284204,45.872034],[-70.253704,45.902981],[-70.263315,45.920152],[-70.24092,45.939095],[-70.252963,45.955234],[-70.280814,45.965211],[-70.31297,45.961856],[-70.309725,45.98021],[-70.287754,45.99182],[-70.317629,46.01908],[-70.278169,46.059671],[-70.306734,46.061344],[-70.284554,46.098713],[-70.254021,46.0996],[-70.239566,46.142762],[-70.292736,46.191599],[-70.272054,46.209833],[-70.248421,46.267072],[-70.205719,46.299865],[-70.208733,46.328961],[-70.191412,46.348072],[-70.141164,46.362669],[-70.11044,46.38611],[-70.096286,46.40943],[-70.057061,46.415036],[-69.997086,46.69523],[-69.22442,47.459686],[-69.146439,47.44886],[-69.082508,47.423976],[-69.061192,47.433052],[-69.043947,47.427634],[-69.039818,47.386309],[-69.053885,47.377878],[-69.050367,47.259821],[-69.033456,47.240984],[-68.96113,47.205582],[-68.942484,47.206386],[-68.90524,47.180919],[-68.717867,47.240919],[-68.687662,47.244215],[-68.664071,47.236762],[-68.607906,47.247497],[-68.582984,47.285493],[-68.546641,47.28298],[-68.507432,47.296636],[-68.470282,47.296804],[-68.448844,47.282547],[-68.376829,47.28852],[-68.384105,47.301506],[-68.380334,47.340242],[-68.355171,47.35707],[-68.234604,47.355035],[-68.217712,47.340847],[-68.15515,47.32542],[-68.137059,47.296068],[-68.019724,47.238036],[-67.991871,47.212042],[-67.955669,47.199542],[-67.935868,47.164843],[-67.893266,47.129943],[-67.883844,47.105834],[-67.789761,47.065744],[-67.781095,45.943032],[-67.750422,45.917898],[-67.803318,45.883718],[-67.796514,45.859961],[-67.755068,45.82367],[-67.780082,45.818194],[-67.806598,45.794723],[-67.806308,45.755405],[-67.793083,45.750559],[-67.781892,45.731189],[-67.809833,45.729274],[-67.803148,45.696127],[-67.817892,45.693705],[-67.805483,45.680241],[-67.720401,45.662522],[-67.729908,45.689012],[-67.710464,45.679372],[-67.675417,45.630959],[-67.64581,45.613597],[-67.644206,45.62322],[-67.631762,45.621409],[-67.606172,45.606533],[-67.499444,45.587014],[-67.476704,45.604157],[-67.455406,45.604665],[-67.429716,45.583773],[-67.420976,45.550029],[-67.435044,45.528783],[-67.416416,45.503515],[-67.462882,45.508691],[-67.503157,45.485367],[-67.482353,45.460825],[-67.473366,45.425328],[-67.418747,45.37726],[-67.434281,45.365438],[-67.430489,45.348751],[-67.453469,45.328246],[-67.460554,45.300379],[-67.485683,45.291433],[-67.489464,45.282653],[-67.46357,45.244097],[-67.43998,45.227047],[-67.428889,45.193213],[-67.407139,45.179425],[-67.404629,45.159926],[-67.345585,45.126392],[-67.298209,45.146672],[-67.299238,45.168937],[-67.283619,45.192022],[-67.246697,45.180765],[-67.227324,45.163652],[-67.203933,45.171407],[-67.161247,45.162879],[-67.112414,45.112323],[-67.090786,45.068721],[-67.117688,45.05673],[-67.082074,45.029608],[-67.033474,44.939923],[-66.984466,44.912557],[-66.990351,44.882551],[-66.978142,44.856963],[-66.996523,44.844654],[-66.986318,44.820657],[-66.950569,44.814539],[-66.97626,44.808315],[-67.02615,44.768199],[-67.062239,44.769543],[-67.073439,44.741957],[-67.098931,44.741311],[-67.103957,44.717444],[-67.139209,44.693849],[-67.155119,44.66944],[-67.181785,44.663699],[-67.191438,44.64775],[-67.213025,44.63922],[-67.24726,44.641664],[-67.274122,44.626345],[-67.273076,44.610873],[-67.293403,44.599265],[-67.314938,44.598215],[-67.32297,44.609394],[-67.293665,44.634316],[-67.292462,44.648455],[-67.309627,44.659316],[-67.299176,44.705705],[-67.308538,44.707454],[-67.355966,44.69906],[-67.376742,44.681852],[-67.381149,44.66947],[-67.363158,44.631825],[-67.377554,44.619757],[-67.386605,44.626974],[-67.405492,44.594236],[-67.428367,44.609136],[-67.457747,44.598014],[-67.492373,44.61795],[-67.505804,44.636837],[-67.530777,44.621938],[-67.551133,44.621938],[-67.575056,44.560659],[-67.562321,44.539435],[-67.568159,44.531117],[-67.648506,44.525403],[-67.656901,44.535896],[-67.685861,44.537155],[-67.702649,44.527922],[-67.698872,44.51575],[-67.71419,44.495238],[-67.733986,44.496252],[-67.743353,44.497418],[-67.742942,44.526453],[-67.753854,44.543661],[-67.774001,44.547438],[-67.781556,44.520577],[-67.79726,44.520685],[-67.808837,44.544081],[-67.839896,44.558771],[-67.856684,44.523934],[-67.851648,44.484901],[-67.868774,44.465272],[-67.851764,44.428695],[-67.855108,44.419434],[-67.878509,44.435585],[-67.887323,44.433066],[-67.899571,44.394078],[-67.913346,44.430128],[-67.92132,44.433066],[-67.930554,44.428869],[-67.931453,44.411848],[-67.955737,44.416278],[-67.961613,44.39907],[-67.978876,44.387034],[-68.006102,44.409562],[-68.034223,44.360456],[-68.044296,44.357938],[-68.049334,44.33073],[-68.067047,44.335692],[-68.077873,44.373047],[-68.090045,44.371369],[-68.11229,44.401588],[-68.117746,44.475038],[-68.150904,44.482383],[-68.17105,44.470211],[-68.194554,44.47189],[-68.189937,44.484901],[-68.213861,44.492456],[-68.227292,44.479865],[-68.224354,44.464335],[-68.261708,44.484062],[-68.270522,44.459718],[-68.298223,44.449225],[-68.299063,44.437893],[-68.247438,44.433276],[-68.24366,44.420685],[-68.249956,44.417747],[-68.21554,44.390466],[-68.20354,44.392365],[-68.184532,44.369145],[-68.173608,44.328397],[-68.191924,44.306675],[-68.233435,44.288578],[-68.289409,44.283858],[-68.298643,44.26665],[-68.290818,44.247673],[-68.317588,44.225101],[-68.339498,44.222893],[-68.377982,44.247563],[-68.401268,44.252244],[-68.430946,44.298624],[-68.430853,44.312609],[-68.411965,44.322262],[-68.409867,44.329397],[-68.421619,44.336113],[-68.396552,44.363941],[-68.398035,44.376191],[-68.360318,44.389674],[-68.359082,44.402847],[-68.3791,44.430049],[-68.387678,44.430936],[-68.392559,44.41807],[-68.427874,44.3968],[-68.433901,44.401534],[-68.429648,44.439136],[-68.455095,44.447498],[-68.46382,44.436592],[-68.461072,44.378504],[-68.47828,44.378084],[-68.483317,44.388157],[-68.472824,44.404106],[-68.480379,44.432647],[-68.494649,44.429709],[-68.499686,44.414179],[-68.51452,44.41334],[-68.529905,44.39907],[-68.565161,44.39907],[-68.545434,44.355],[-68.566936,44.317603],[-68.556236,44.300819],[-68.538595,44.299902],[-68.519516,44.265046],[-68.529802,44.249594],[-68.525302,44.227554],[-68.603385,44.27471],[-68.682979,44.299201],[-68.733004,44.328388],[-68.762021,44.329597],[-68.795063,44.30786],[-68.827197,44.31216],[-68.814811,44.362194],[-68.821767,44.40894],[-68.783679,44.473879],[-68.829153,44.462242],[-68.880271,44.428112],[-68.897104,44.450643],[-68.927452,44.448039],[-68.946582,44.429108],[-68.982449,44.426195],[-68.990767,44.415033],[-68.978815,44.38634],[-68.948164,44.355882],[-68.954465,44.32405],[-68.979005,44.296327],[-69.003682,44.294582],[-69.005071,44.274071],[-69.040193,44.233673],[-69.054546,44.171542],[-69.077776,44.165043],[-69.080331,44.117824],[-69.100863,44.104529],[-69.092,44.085734],[-69.056303,44.095162],[-69.031878,44.079036],[-69.048917,44.062506],[-69.064299,44.069911],[-69.079805,44.055256],[-69.073767,44.046135],[-69.125738,44.019623],[-69.124475,44.007419],[-69.170345,43.995637],[-69.193805,43.975543],[-69.203668,43.941806],[-69.259838,43.921427],[-69.280498,43.95744],[-69.31427,43.942951],[-69.319751,43.94487],[-69.305176,43.956676],[-69.331411,43.974311],[-69.351961,43.974748],[-69.366702,43.964755],[-69.398455,43.971804],[-69.421072,43.938261],[-69.423324,43.915507],[-69.459637,43.903316],[-69.483498,43.88028],[-69.50329,43.837673],[-69.514889,43.831298],[-69.520301,43.868498],[-69.543912,43.881615],[-69.552606,43.841347],[-69.575466,43.841972],[-69.578527,43.823316],[-69.588551,43.81836],[-69.604179,43.813551],[-69.604616,43.825793],[-69.592373,43.830895],[-69.594705,43.858878],[-69.604616,43.858004],[-69.621086,43.826814],[-69.634932,43.845907],[-69.649798,43.836287],[-69.653337,43.79103],[-69.664922,43.791033],[-69.692429,43.824336],[-69.705838,43.823024],[-69.719723,43.786685],[-69.752801,43.75594],[-69.780097,43.755397],[-69.778494,43.747089],[-69.835323,43.721125],[-69.838689,43.70514],[-69.851297,43.703581],[-69.858947,43.740531],[-69.868673,43.742701],[-69.862155,43.758962],[-69.869732,43.775656],[-69.903164,43.77239],[-69.927011,43.780174],[-69.953246,43.768806],[-69.982574,43.750801],[-70.001645,43.717666],[-69.998793,43.740385],[-70.041351,43.738053],[-70.034355,43.759041],[-69.99821,43.798684],[-70.002874,43.812093],[-70.026193,43.822587],[-70.023278,43.834247],[-70.002874,43.848239],[-70.009869,43.859315],[-70.019197,43.858733],[-70.064671,43.813259],[-70.080995,43.819672],[-70.107229,43.809178],[-70.142792,43.791688],[-70.176023,43.76079],[-70.172525,43.773615],[-70.190014,43.771866],[-70.194095,43.745632],[-70.217998,43.71998],[-70.215666,43.707737],[-70.251812,43.683251],[-70.254144,43.676839],[-70.211204,43.625765],[-70.217087,43.596717],[-70.20112,43.586515],[-70.196911,43.565146],[-70.206123,43.557627],[-70.231963,43.561118],[-70.244331,43.551849],[-70.272497,43.562616],[-70.307764,43.544315],[-70.353392,43.535405]]]]},\"properties\":{\"name\":\"Maine\",\"nation\":\"USA  \"}}]}","volume":"37","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-03-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Crossett, Caitlin","contributorId":304049,"corporation":false,"usgs":false,"family":"Crossett","given":"Caitlin","email":"","affiliations":[{"id":65957,"text":"Department of Geoscience, Hobart and William Smith Colleges, Geneva, NY 14456","active":true,"usgs":false}],"preferred":false,"id":869030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menk, Hadley","contributorId":304050,"corporation":false,"usgs":false,"family":"Menk","given":"Hadley","email":"","affiliations":[{"id":65958,"text":"Department of Geography & Sustainable Development, University of St Andrews, St Andrews, Scotland KY16 9AL","active":true,"usgs":false}],"preferred":false,"id":869032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dupigny-Giroux, Lesley-Ann L. 0000-0002-1992-5607","orcid":"https://orcid.org/0000-0002-1992-5607","contributorId":212158,"corporation":false,"usgs":false,"family":"Dupigny-Giroux","given":"Lesley-Ann","email":"","middleInitial":"L.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":869033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lemcke-Stampone, Mary D. 0000-0001-5445-0267","orcid":"https://orcid.org/0000-0001-5445-0267","contributorId":212160,"corporation":false,"usgs":false,"family":"Lemcke-Stampone","given":"Mary","email":"","middleInitial":"D.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":869035,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869036,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70240682,"text":"sir20225051 - 2023 - Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States","interactions":[],"lastModifiedDate":"2026-02-23T19:14:56.874467","indexId":"sir20225051","displayToPublicDate":"2023-02-15T12:00:00","publicationYear":"2023","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":"2022-5051","displayTitle":"Generalized Additive Model Estimation of No-Flow Fractions and L-Moments to Support Flow-Duration Curve Quantile Estimation Using Selected Probability Distributions for Bay and Estuary Restoration in the Gulf States","title":"Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States","docAbstract":"<p>Censored and uncensored generalized additive models (GAMs) were developed using streamflow data from 941 U.S.&nbsp;Geological Survey streamflow-gaging stations (streamgages) to predict decadal statistics of daily streamflow for streams draining to the Gulf of Mexico. The modeled decadal statistics comprise no-flow fractions and L-moments of logarithms of nonzero streamflow for six decades (1950–2009). These statistics represent metrics of decadal flow-duration curves (dFDCs) derived from about 10 million daily mean streamflows. The L-moments comprise the mean, coefficient of L-variation, and the third through fifth L-moment ratios. The GAMs were fit to the statistics from 941 streamgages and 2,750 streamgage-decades by using watershed properties such as basin area and slope, decadal precipitation and temperature, and decadal values of flood storage and urban development percentages. The GAMs then estimated decadal statistics for 9,220 prediction locations (stream reaches) coincident with outlets of level-12 hydrologic unit codes. Both entire dataset (whole model) and leave-one-watershed-out model results are reported. No-flow fractions are censored data, and Tobit extensions to GAMs were used to model ephemeral streamflow conditions. Conversely, uncensored GAMs were used for estimation of the L-moments. The GAMs are shown, by coverage probabilities, to construct reliable 95-percent prediction limits. An example shows how no-flow fractions and L-moments may be used to approximate dFDCs by using selected probability distributions (mathematical formulas) including the asymmetric exponential power, generalized normal, and kappa distributions.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225051","issn":"2328-0328 (online)","collaboration":"Prepared in cooperation with the Gulf Coast Ecosystem Restoration Council","usgsCitation":"Crowley-Ornelas, E.R., Asquith, W.H., and Worland, S.C., 2023, Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States: U.S. Geological Survey Scientific Investigations Report 2022–5051, 35 p., https://doi.org/​10.3133/​sir20225051.","productDescription":"Report: viii, 35 p.; 3 Data Releases; Dataset; Software Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-111999","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":500450,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114346.htm","linkFileType":{"id":5,"text":"html"}},{"id":413056,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P36GXZ","text":"USGS data release","linkHelpText":"Estimated daily mean streamflows for HUC12 pour points in the southeastern United States, 1950–2009"},{"id":413055,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z4PM55","text":"USGS data release","linkHelpText":"Summary of decadal no-flow fractions and decadal L-moments of nonzero streamflow flow-duration curves for National Hydrography Dataset, version 2 catchments in the southeastern United States, 1950–2010"},{"id":413054,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MV8BYR","text":"USGS data release","linkHelpText":"Estimated quantiles of decadal flow-duration curves using selected probability distributions fit to no-flow fractions and L-moments predicted for streamgages and for pour points of level-12 hydrologic unit codes in the southeastern United States, 1950–2010"},{"id":413057,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":413051,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5051/sir20225051.XML","size":"173 KB","linkFileType":{"id":8,"text":"xml"}},{"id":413050,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5051/sir20225051.pdf","text":"Report","size":"25.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":413049,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5051/coverthb.jpg"},{"id":413052,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5051/images"},{"id":413053,"rank":5,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P93CKH92","text":"USGS software release","linkHelpText":"—RESTORE/fdclmrpplo—Source code for estimation of L-moments and percent no-flow conditions for decadal flow-duration curves and estimation at level-12 hydro­logic unit codes"}],"country":"United States","state":"Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, Missouri, Oklahoma, Tennessee, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97.89327254512996,\n              27.152072126975185\n            ],\n            [\n              -97.4101612611709,\n              27.11298566570153\n            ],\n            [\n              -96.9270188922167,\n              27.73675500068198\n            ],\n            [\n              -95.43366975181324,\n              28.89671187134826\n            ],\n            [\n              -94.07208671203415,\n              29.586553878547065\n            ],\n            [\n              -92.40304943746548,\n              29.433658046438964\n            ],\n            [\n              -90.16302572686091,\n              29.088800565828734\n            ],\n            [\n              -89.37242912311773,\n              29.395398033775706\n            ],\n            [\n              -89.72380539144815,\n              30.119862988588224\n            ],\n            [\n              -88.05476811687946,\n              30.423326949660762\n            ],\n            [\n              -86.56141897647663,\n              30.347548955066515\n            ],\n            [\n              -85.59513423856824,\n              29.96777990591761\n            ],\n            [\n              -85.02414780253173,\n              29.739218407083584\n            ],\n            [\n              -84.10178509816538,\n              30.04385063198481\n            ],\n            [\n              -83.75040882983495,\n              29.586553878547065\n            ],\n            [\n              -82.87196815900944,\n              28.935158147470503\n            ],\n            [\n              -82.87196815900944,\n              27.81447761044616\n            ],\n            [\n              -82.52059189067963,\n              26.87816776899561\n            ],\n            [\n              -81.90568342110166,\n              26.603595988158816\n            ],\n            [\n              -81.51038511923038,\n              26.603595988158816\n            ],\n            [\n              -81.77391732047789,\n              27.581143448383173\n            ],\n            [\n              -81.64215121985414,\n              28.395618442604956\n            ],\n            [\n              -82.30095641007729,\n              30.347545664969232\n            ],\n            [\n              -82.38880047715959,\n              30.801329787871083\n            ],\n            [\n              -82.60841064486628,\n              31.92642149651786\n            ],\n            [\n              -83.22331911444428,\n              33.40534616259008\n            ],\n            [\n              -83.35508521506803,\n              34.8955498277159\n            ],\n            [\n              -83.61861741631554,\n              35.255005590134715\n            ],\n            [\n              -84.32136995297581,\n              35.36253317119305\n            ],\n            [\n              -84.84843435547089,\n              34.85951723970993\n            ],\n            [\n              -85.46334282504884,\n              34.49832406298901\n            ],\n            [\n              -86.21001739525062,\n              34.20823758612808\n            ],\n            [\n              -87.30806823378218,\n              34.09919664343096\n            ],\n            [\n              -88.31827500523205,\n              34.42589658874546\n            ],\n            [\n              -88.40611907231438,\n              35.29086399681957\n            ],\n            [\n              -88.14258687106684,\n              35.79121142775928\n            ],\n            [\n              -88.18650890460766,\n              36.71210914809927\n            ],\n            [\n              -88.97710550835089,\n              37.06340209145981\n            ],\n            [\n              -90.03123431334161,\n              37.098442418155315\n            ],\n            [\n              -90.64614278291896,\n              36.182146271919535\n            ],\n            [\n              -91.6124275208274,\n              35.57715908257363\n            ],\n            [\n              -93.28146479539548,\n              35.21913131313332\n            ],\n            [\n              -95.03834613704649,\n              34.751324757546385\n            ],\n            [\n              -96.35600714328474,\n              34.02642451422544\n            ],\n            [\n              -96.44384543826796,\n              33.47864830609991\n            ],\n            [\n              -98.50818101470793,\n              32.3355627017998\n            ],\n            [\n              -99.51838778615716,\n              30.423324887376182\n            ],\n            [\n              -99.86976405448763,\n              29.24221202688979\n            ],\n            [\n              -98.99132338366213,\n              27.77562113086519\n            ],\n            [\n              -97.89327254512996,\n              27.152072126975185\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\" href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>640 Grassmere Park, Suite 100<br>Nashville, TN 37211<br></p><p><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Data Sources and Statistical Methods</li><li>Summary of Generalized Additive Model Computations for No-Flow Fractions and L-Moments</li><li>Results of Generalized Additive Models for No-Flow Fractions and L-Moments</li><li>Flow-Duration Curve Quantile Estimation Using Selected Probability Distributions</li><li>Summary</li><li>References Cited</li><li>Glossary</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-02-15","noUsgsAuthors":false,"publicationDate":"2023-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Crowley-Ornelas, Elena 0000-0002-1823-8485","orcid":"https://orcid.org/0000-0002-1823-8485","contributorId":211970,"corporation":false,"usgs":true,"family":"Crowley-Ornelas","given":"Elena","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864288,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70241542,"text":"70241542 - 2023 - High-frequency time series comparison of Sentinel-1 and Sentinel-2 for open and vegetated water across the United States (2017-2021)","interactions":[],"lastModifiedDate":"2023-03-23T13:55:48.119874","indexId":"70241542","displayToPublicDate":"2023-02-15T08:41:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"High-frequency time series comparison of Sentinel-1 and Sentinel-2 for open and vegetated water across the United States (2017-2021)","docAbstract":"<p><span>Frequent observations of surface water at fine spatial scales will provide critical data to support the management of aquatic habitat, flood risk and water quality. Sentinel-1 and Sentinel-2 satellites can provide such observations, but algorithms are still needed that perform well across diverse climate and vegetation conditions. We developed surface inundation algorithms for Sentinel-1 and Sentinel-2, respectively, at 12 sites across the conterminous United States (CONUS), covering a total of &gt;536,000&nbsp;km</span><sup>2</sup><span>&nbsp;and representing diverse hydrologic and vegetation landscapes. Each scene in the 5-year (2017–2021) time series was classified into open water, vegetated water, and non-water at 20&nbsp;m resolution using variables from Sentinel-1 and Sentinel-2, as well as variables derived from topographic and weather datasets. The Sentinel-1 algorithm was developed distinct from the Sentinel-2 model to explore if and where the two time series could potentially be integrated into a single high-frequency time series. Within each model, open water and vegetated water (vegetated palustrine, lacustrine, and riverine wetlands) classes were mapped. The models were validated using imagery from WorldView and PlanetScope. Classification accuracy for open water was high across the 5-year period, with an omission and commission error of only 3.1% and 0.9% for the Sentinel-1 algorithm and 3.1% and 0.5% for the Sentinel-2 algorithm, respectively. Vegetated water accuracy was lower, as expected given that the class represents mixed pixels. The Sentinel-2 algorithm showed higher accuracy (10.7% omission and 7.9% commission error) relative to the Sentinel-1 algorithm (28.4% omission and 16.0% commission error). Patterns over time in the proportion of area mapped as open or vegetated water by the Sentinel-1 and Sentinel-2 algorithms were charted and correlated for a subset of all 12 sites. Our results showed that the Sentinel-1 and Sentinel-2 algorithm open water time series can be integrated at all 12 sites to improve the temporal resolution, but sensor-specific differences, such as sensitivity to vegetation structure versus pixel color, complicate the data integration for mixed-pixel, vegetated water. The methods developed here provide inundation at 5-day (Sentinel-2 algorithm) and 12-day (Sentinel-1 algorithm) time steps to improve our understanding of the short- and long-term response of surface water to climate and land use drivers in different ecoregions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2023.113498","usgsCitation":"Vanderhoof, M.K., Alexander, L., Christensen, J.R., Solvik, K., Nieuwlandt, P.J., and Prentiss, M.A., 2023, High-frequency time series comparison of Sentinel-1 and Sentinel-2 for open and vegetated water across the United States (2017-2021): Remote Sensing of Environment, v. 288, 113498, 28 p., https://doi.org/10.1016/j.rse.2023.113498.","productDescription":"113498, 28 p.","ipdsId":"IP-142670","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":444461,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2023.113498","text":"Publisher Index Page"},{"id":435452,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RSXQ2U","text":"USGS data release","linkHelpText":"Sentinel-1 and Sentinel-2 based frequency of open and vegetated water across the United States (2017-2021)"},{"id":414610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"continental United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                48.27\n              ],\n              [\n                -89.6,\n                48.01\n              ],\n              [\n                -89.27292,\n                48.01981\n              ],\n              [\n                -88.37811,\n                48.30292\n              ],\n              [\n                -87.43979,\n                47.94\n              ],\n              [\n                -86.46199,\n                47.55334\n              ],\n              [\n                -85.65236,\n                47.22022\n              ],\n              [\n                -84.87608,\n                46.90008\n              ],\n              [\n                -84.77924,\n                46.6371\n              ],\n              [\n                -84.54375,\n                46.53868\n              ],\n              [\n                -84.6049,\n                46.4396\n              ],\n              [\n                -84.3367,\n                46.40877\n              ],\n              [\n                -84.14212,\n                46.51223\n              ],\n              [\n                -84.09185,\n                46.27542\n              ],\n              [\n                -83.89077,\n                46.11693\n              ],\n              [\n                -83.61613,\n                46.11693\n              ],\n              [\n                -83.46955,\n                45.99469\n              ],\n              [\n                -83.59285,\n                45.81689\n              ],\n              [\n                -82.55092,\n                45.34752\n              ],\n              [\n                -82.33776,\n                44.44\n              ],\n              [\n                -82.13764,\n                43.57109\n              ],\n              [\n                -82.43,\n                42.98\n              ],\n              [\n                -82.9,\n                42.43\n              ],\n              [\n                -83.12,\n                42.08\n              ],\n              [\n                -83.142,\n                41.97568\n              ],\n              [\n                -83.02981,\n                41.8328\n              ],\n              [\n                -82.69009,\n                41.67511\n              ],\n              [\n                -82.43928,\n                41.67511\n              ],\n              [\n                -81.27775,\n                42.20903\n              ],\n              [\n                -80.24745,\n                42.3662\n              ],\n              [\n                -78.93936,\n                42.86361\n              ],\n              [\n                -78.92,\n                42.965\n              ],\n              [\n                -79.01,\n                43.27\n              ],\n              [\n                -79.17167,\n                43.46634\n              ],\n              [\n                -78.72028,\n                43.62509\n              ],\n              [\n                -77.73789,\n                43.62906\n              ],\n              [\n                -76.82003,\n                43.62878\n              ],\n              [\n                -76.5,\n                44.01846\n              ],\n              [\n                -76.375,\n                44.09631\n              ],\n              [\n                -75.31821,\n                44.81645\n              ],\n              [\n                -74.867,\n                45.00048\n              ],\n              [\n                -73.34783,\n                45.00738\n              ],\n              [\n                -71.50506,\n                45.0082\n              ],\n              [\n                -71.405,\n                45.255\n              ],\n              [\n                -71.08482,\n                45.30524\n              ],\n              [\n                -70.66,\n                45.46\n              ],\n              [\n                -70.305,\n                45.915\n              ],\n              [\n                -69.99997,\n                46.69307\n              ],\n              [\n                -69.23722,\n                47.44778\n              ],\n              [\n                -68.905,\n                47.185\n              ],\n              [\n                -68.23444,\n                47.35486\n              ],\n              [\n                -67.79046,\n                47.06636\n              ],\n              [\n                -67.79134,\n                45.70281\n              ],\n              [\n                -67.13741,\n                45.13753\n              ],\n              [\n                -66.96466,\n                44.8097\n              ],\n              [\n                -68.03252,\n                44.3252\n              ],\n              [\n                -69.06,\n                43.98\n              ],\n              [\n                -70.11617,\n                43.68405\n              ],\n              [\n                -70.64548,\n                43.09024\n              ],\n              [\n                -70.81489,\n                42.8653\n              ],\n              [\n                -70.825,\n                42.335\n              ],\n              [\n                -70.495,\n                41.805\n              ],\n              [\n                -70.08,\n                41.78\n              ],\n              [\n                -70.185,\n                42.145\n              ],\n              [\n                -69.88497,\n                41.92283\n              ],\n              [\n                -69.96503,\n                41.63717\n              ],\n              [\n                -70.64,\n                41.475\n              ],\n              [\n                -71.12039,\n                41.49445\n              ],\n              [\n                -71.86,\n                41.32\n              ],\n              [\n                -72.295,\n                41.27\n              ],\n              [\n                -72.87643,\n                41.22065\n              ],\n              [\n                -73.71,\n                40.9311\n              ],\n              [\n                -72.24126,\n                41.11948\n              ],\n              [\n                -71.945,\n                40.93\n              ],\n              [\n                -73.345,\n                40.63\n              ],\n              [\n                -73.982,\n                40.628\n              ],\n              [\n                -73.95232,\n                40.75075\n              ],\n              [\n                -74.25671,\n                40.47351\n              ],\n              [\n                -73.96244,\n                40.42763\n              ],\n              [\n                -74.17838,\n                39.70926\n              ],\n              [\n                -74.90604,\n                38.93954\n              ],\n              [\n                -74.98041,\n                39.1964\n              ],\n              [\n                -75.20002,\n                39.24845\n              ],\n              [\n                -75.52805,\n                39.4985\n              ],\n              [\n                -75.32,\n                38.96\n              ],\n              [\n                -75.07183,\n                38.78203\n              ],\n              [\n                -75.05673,\n                38.40412\n              ],\n              [\n                -75.37747,\n                38.01551\n              ],\n              [\n                -75.94023,\n                37.21689\n              ],\n              [\n                -76.03127,\n                37.2566\n              ],\n              [\n                -75.72205,\n                37.93705\n              ],\n              [\n                -76.23287,\n                38.31921\n              ],\n              [\n                -76.35,\n                39.15\n              ],\n              [\n                -76.54272,\n                38.71762\n              ],\n              [\n                -76.32933,\n                38.08326\n              ],\n              [\n                -76.99,\n                38.23999\n              ],\n              [\n                -76.30162,\n                37.91794\n              ],\n              [\n                -76.25874,\n                36.9664\n              ],\n              [\n                -75.9718,\n                36.89726\n              ],\n              [\n                -75.86804,\n                36.55125\n              ],\n              [\n                -75.72749,\n                35.55074\n              ],\n              [\n                -76.36318,\n                34.80854\n              ],\n              [\n                -77.39763,\n                34.51201\n              ],\n              [\n                -78.05496,\n                33.92547\n              ],\n              [\n                -78.55435,\n                33.86133\n              ],\n              [\n                -79.06067,\n                33.49395\n              ],\n              [\n                -79.20357,\n                33.15839\n              ],\n              [\n                -80.30132,\n                32.50935\n              ],\n              [\n                -80.86498,\n                32.0333\n              ],\n              [\n                -81.33629,\n                31.44049\n              ],\n              [\n                -81.49042,\n                30.72999\n              ],\n              [\n                -81.31371,\n                30.03552\n              ],\n              [\n                -80.98,\n                29.18\n              ],\n              [\n                -80.53558,\n                28.47213\n              ],\n              [\n                -80.53,\n                28.04\n              ],\n              [\n                -80.05654,\n                26.88\n              ],\n              [\n                -80.08801,\n                26.20576\n              ],\n              [\n                -80.13156,\n                25.81677\n              ],\n              [\n                -80.38103,\n                25.20616\n              ],\n              [\n                -80.68,\n                25.08\n              ],\n              [\n                -81.17213,\n                25.20126\n              ],\n              [\n                -81.33,\n                25.64\n              ],\n              [\n                -81.71,\n                25.87\n              ],\n              [\n                -82.24,\n                26.73\n              ],\n              [\n                -82.70515,\n                27.49504\n              ],\n              [\n                -82.85526,\n                27.88624\n              ],\n              [\n                -82.65,\n                28.55\n              ],\n              [\n                -82.93,\n                29.1\n              ],\n              [\n                -83.70959,\n                29.93656\n              ],\n              [\n                -84.1,\n                30.09\n              ],\n              [\n                -85.10882,\n                29.63615\n              ],\n              [\n                -85.28784,\n                29.68612\n              ],\n              [\n                -85.7731,\n                30.15261\n              ],\n              [\n                -86.4,\n                30.4\n              ],\n              [\n                -87.53036,\n                30.27433\n              ],\n              [\n                -88.41782,\n                30.3849\n              ],\n              [\n                -89.18049,\n                30.31598\n              ],\n              [\n                -89.59383,\n                30.15999\n              ],\n              [\n                -89.41373,\n                29.89419\n              ],\n              [\n                -89.43,\n                29.48864\n              ],\n              [\n                -89.21767,\n                29.29108\n              ],\n              [\n                -89.40823,\n                29.15961\n              ],\n              [\n                -89.77928,\n                29.30714\n              ],\n              [\n                -90.15463,\n                29.11743\n              ],\n              [\n                -90.88022,\n                29.14854\n              ],\n              [\n                -91.62678,\n                29.677\n              ],\n              [\n                -92.49906,\n                29.5523\n              ],\n              [\n                -93.22637,\n                29.78375\n              ],\n              [\n                -93.84842,\n                29.71363\n              ],\n              [\n                -94.69,\n                29.48\n              ],\n              [\n                -95.60026,\n                28.73863\n              ],\n              [\n                -96.59404,\n                28.30748\n              ],\n              [\n                -97.14,\n                27.83\n              ],\n              [\n                -97.37,\n                27.38\n              ],\n              [\n                -97.38,\n                26.69\n              ],\n              [\n                -97.33,\n                26.21\n              ],\n              [\n                -97.14,\n                25.87\n              ],\n              [\n                -97.53,\n                25.84\n              ],\n              [\n                -98.24,\n                26.06\n              ],\n              [\n                -99.02,\n                26.37\n              ],\n              [\n                -99.3,\n                26.84\n              ],\n              [\n                -99.52,\n                27.54\n              ],\n              [\n                -100.11,\n                28.11\n              ],\n              [\n                -100.45584,\n                28.69612\n              ],\n              [\n                -100.9576,\n                29.38071\n              ],\n              [\n                -101.6624,\n                29.7793\n              ],\n              [\n                -102.48,\n                29.76\n              ],\n              [\n                -103.11,\n                28.97\n              ],\n              [\n                -103.94,\n                29.27\n              ],\n              [\n                -104.45697,\n                29.57196\n              ],\n              [\n                -104.70575,\n                30.12173\n              ],\n              [\n                -105.03737,\n                30.64402\n              ],\n              [\n                -105.63159,\n                31.08383\n              ],\n              [\n                -106.1429,\n                31.39995\n              ],\n              [\n                -106.50759,\n                31.75452\n              ],\n              [\n                -108.24,\n                31.75485\n              ],\n              [\n                -108.24194,\n                31.34222\n              ],\n              [\n                -109.035,\n                31.34194\n              ],\n              [\n                -111.02361,\n                31.33472\n              ],\n              [\n                -113.30498,\n                32.03914\n              ],\n              [\n                -114.815,\n                32.52528\n              ],\n              [\n                -114.72139,\n                32.72083\n              ],\n              [\n                -115.99135,\n                32.61239\n              ],\n              [\n                -117.12776,\n                32.53534\n              ],\n              [\n                -117.29594,\n                33.04622\n              ],\n              [\n                -117.944,\n                33.62124\n              ],\n              [\n                -118.4106,\n                33.74091\n              ],\n              [\n                -118.51989,\n                34.02778\n              ],\n              [\n                -119.081,\n                34.078\n              ],\n              [\n                -119.43884,\n                34.34848\n              ],\n              [\n                -120.36778,\n                34.44711\n              ],\n              [\n                -120.62286,\n                34.60855\n              ],\n              [\n                -120.74433,\n                35.15686\n              ],\n              [\n                -121.71457,\n                36.16153\n              ],\n              [\n                -122.54747,\n                37.55176\n              ],\n              [\n                -122.51201,\n                37.78339\n              ],\n              [\n                -122.95319,\n                38.11371\n              ],\n              [\n                -123.7272,\n                38.95166\n              ],\n              [\n                -123.86517,\n                39.76699\n              ],\n              [\n                -124.39807,\n                40.3132\n              ],\n              [\n                -124.17886,\n                41.14202\n              ],\n              [\n                -124.2137,\n                41.99964\n              ],\n              [\n                -124.53284,\n                42.76599\n              ],\n              [\n                -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                45.52341\n              ],\n              [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"288","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":867161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Laurie C.","contributorId":138989,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":867162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Jay R.","contributorId":238115,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","middleInitial":"R.","affiliations":[],"preferred":false,"id":867163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solvik, Kylen 0000-0001-6537-1791","orcid":"https://orcid.org/0000-0001-6537-1791","contributorId":303316,"corporation":false,"usgs":false,"family":"Solvik","given":"Kylen","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":867164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nieuwlandt, Peter Joseph 0000-0002-8245-2873","orcid":"https://orcid.org/0000-0002-8245-2873","contributorId":303317,"corporation":false,"usgs":true,"family":"Nieuwlandt","given":"Peter","email":"","middleInitial":"Joseph","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":867165,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prentiss, Mallory Annelle 0000-0002-0010-0744","orcid":"https://orcid.org/0000-0002-0010-0744","contributorId":303318,"corporation":false,"usgs":true,"family":"Prentiss","given":"Mallory","email":"","middleInitial":"Annelle","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":867166,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240750,"text":"70240750 - 2023 - Climate-driven mid- to late Holocene hydrologic evolution of arid wetlands documented by strontium, uranium, and oxygen isotopes from Lower Pahranagat Lake, southern Nevada, USA","interactions":[],"lastModifiedDate":"2023-05-25T15:40:53.773785","indexId":"70240750","displayToPublicDate":"2023-02-14T07:13:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Climate-driven mid- to late Holocene hydrologic evolution of arid wetlands documented by strontium, uranium, and oxygen isotopes from Lower Pahranagat Lake, southern Nevada, USA","docAbstract":"<div class=\"abstract-content\"><div class=\"abstract\" data-abstract-type=\"normal\"><p><span>Lacustrine carbonates in a 12.4-m-long core from Lower Pahranagat Lake (LPAH), southern Nevada, indicate that radiogenic isotopes of Sr and U (</span><sup><span class=\"sup\">87</span></sup><span>Sr/</span><sup><span class=\"sup\">86</span></sup><span>Sr and&nbsp;</span><sup><span class=\"sup\">234</span></sup><span>U/</span><sup><span class=\"sup\">238</span></sup><span>U) preserve evidence of past variations in water sources and evolving hydrologic conditions. Sr and U isotope compositions in LPAH carbonates fall within the range defined by the three primary groundwater sources in Pahranagat Valley and reflect variable mixtures of those sources since the mid-Holocene. Compositions in the oldest sample (5.78 ka) closely match modern compositions of modern discharge from nearby springs, indicating that LPAH water was derived almost exclusively from the local volcanic aquifer. By ca. 5.3–5.2 ka, LPAH water compositions shifted sharply towards isotopic compositions observed in groundwater from the regional carbonate aquifer, indicating a marked increase in surface flow from high-volume springs discharging from the carbonate aquifer to the north. Sediments deposited between 3.08–1.06 ka indicate reduced contributions from the regional aquifer. A comparison of uranium- and oxygen-isotope values in LPAH carbonates suggests that wetter climate conditions favor increased supply from deeper, regional carbonate aquifers compared to drier conditions when contributions from shallower, local volcanic aquifers were more important.</span></p></div></div>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2022.72","usgsCitation":"Theissen, K.M., and Paces, J., 2023, Climate-driven mid- to late Holocene hydrologic evolution of arid wetlands documented by strontium, uranium, and oxygen isotopes from Lower Pahranagat Lake, southern Nevada, USA: Quaternary Research, v. 113, p. 52-68, https://doi.org/10.1017/qua.2022.72.","productDescription":"17 p.","startPage":"52","endPage":"68","ipdsId":"IP-141669","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":435455,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96B7ABG","text":"USGS data release","linkHelpText":"Strontium and uranium isotopic compositions (87Sr/86Sr and 234U/238U) of mid- to late-Holocene lacustrine sediments from Lower Pahranagat Lake, Pahranagat National Wildlife Refuge, Lincoln County, Nevada"},{"id":413168,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Pahranagat Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.43523232398918,\n              37.66375328566663\n            ],\n            [\n              -115.43523232398918,\n              37.05452897208191\n            ],\n            [\n              -114.88855552446904,\n              37.05452897208191\n            ],\n            [\n              -114.88855552446904,\n              37.66375328566663\n            ],\n            [\n              -115.43523232398918,\n              37.66375328566663\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"113","noUsgsAuthors":false,"publicationDate":"2023-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Theissen, Kevin M. 0000-0002-6005-4380","orcid":"https://orcid.org/0000-0002-6005-4380","contributorId":298622,"corporation":false,"usgs":false,"family":"Theissen","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":6748,"text":"University of St. Thomas","active":true,"usgs":false}],"preferred":false,"id":864686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":118216,"corporation":false,"usgs":true,"family":"Paces","given":"James B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":864687,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70243039,"text":"70243039 - 2023 - Framework for facilitating mangrove recovery after hurricanes on Caribbean islands","interactions":[],"lastModifiedDate":"2023-09-06T16:08:19.597675","indexId":"70243039","displayToPublicDate":"2023-02-11T07:24:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Framework for facilitating mangrove recovery after hurricanes on Caribbean islands","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Mangrove ecosystems in the Caribbean are frequently exposed to hurricanes, leading to structural and regenerative change that elicit calls for recovery action. For those mangroves unaffected by human modifications, recovery can occur naturally. Indeed, observable natural recovery after hurricanes is the genesis of the “disturbance adaptation” classification for mangroves; while structural legacies exist, unaltered stands often regenerate and persist. However, among the &gt;7,000 islands, islets, and cays that make up the Caribbean archipelago, coastal alterations to support development affect mechanisms for regeneration, sediment distribution, tidal water conveyance, and intertidal mangrove transgression, imposing sometimes insurmountable barriers to natural post-hurricane recovery. We use a case study approach to suggest that actions to facilitate recovery of mangroves on Caribbean islands (and similar settings globally) may be more effective when focusing on ameliorating pre-existing anthropogenic stressors. Actions to clean debris, collect mangrove propagules, and plant seedlings are noble endeavors, but can be costly and fall short of achieving recovery goals in isolation without careful consideration of pre-hurricane stress. We update a procedural framework that considers six steps to implementing “Ecological Mangrove Restoration” (EMR), and we apply them specifically to hurricane recovery. If followed, EMR may expedite actions by suggesting immediate damage assessment focused on hydrogeomorphic mangrove type, hydrology, and previous anthropogenic (or natural) influence. Application of EMR may help to improve mangrove recovery success following catastrophic storms, and reduce guesswork, delays, and monetary inefficiencies.</p></div></div>","language":"English","publisher":"British Ecological Society","doi":"10.1111/rec.13885","usgsCitation":"Krauss, K., Whelan, K.R., Kennedy, J.P., Friess, D.A., Rogers, C., Stewart, H.A., Grimes, K.W., Trench, C.A., Ogurcak, D.E., Toline, C.A., Ball, L.C., and From, A., 2023, Framework for facilitating mangrove recovery after hurricanes on Caribbean islands: Restoration Ecology, v. 31, no. 7, e13885, https://doi.org/10.1111/rec.13885.","productDescription":"e13885","ipdsId":"IP-138477","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":416436,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219653,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":870760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whelan, Kevin R.T.","contributorId":225171,"corporation":false,"usgs":false,"family":"Whelan","given":"Kevin","email":"","middleInitial":"R.T.","affiliations":[{"id":41065,"text":"3U.S. National Park Service, Miami, FL 33157 USA","active":true,"usgs":false}],"preferred":false,"id":870761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, John Paul","contributorId":304505,"corporation":false,"usgs":false,"family":"Kennedy","given":"John","email":"","middleInitial":"Paul","affiliations":[{"id":25496,"text":"Manchester Metropolitan University","active":true,"usgs":false}],"preferred":false,"id":870762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friess, Daniel A.","contributorId":169072,"corporation":false,"usgs":false,"family":"Friess","given":"Daniel","email":"","middleInitial":"A.","affiliations":[{"id":25407,"text":"Department of Geography, National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":870763,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rogers, Caroline 0000-0001-9056-6961","orcid":"https://orcid.org/0000-0001-9056-6961","contributorId":223023,"corporation":false,"usgs":true,"family":"Rogers","given":"Caroline","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":870764,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Heather A.","contributorId":304507,"corporation":false,"usgs":false,"family":"Stewart","given":"Heather","email":"","middleInitial":"A.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":870765,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grimes, Kristin Wilson","contributorId":208051,"corporation":false,"usgs":false,"family":"Grimes","given":"Kristin","email":"","middleInitial":"Wilson","affiliations":[{"id":37691,"text":"Wells National Estuarine Research Reserve, Wells, Maine","active":true,"usgs":false}],"preferred":false,"id":870766,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Trench, Camilo A.","contributorId":304510,"corporation":false,"usgs":false,"family":"Trench","given":"Camilo","email":"","middleInitial":"A.","affiliations":[{"id":66090,"text":"Discovery Bay Marine Laboratory, Centre for Marine Studies, University of the West Indies","active":true,"usgs":false}],"preferred":false,"id":870767,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ogurcak, Danielle E.","contributorId":149171,"corporation":false,"usgs":false,"family":"Ogurcak","given":"Danielle","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":870768,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Toline, Catherine A.","contributorId":304511,"corporation":false,"usgs":false,"family":"Toline","given":"Catherine","email":"","middleInitial":"A.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":870769,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ball, Lianne C. 0000-0001-9331-0718 lball@usgs.gov","orcid":"https://orcid.org/0000-0001-9331-0718","contributorId":4274,"corporation":false,"usgs":true,"family":"Ball","given":"Lianne","email":"lball@usgs.gov","middleInitial":"C.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":870770,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"From, Andrew 0000-0002-6543-2627","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":223021,"corporation":false,"usgs":true,"family":"From","given":"Andrew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":870771,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70240478,"text":"sim3490 - 2023 - Geologic map and hydrogeologic investigations of the upper Santa Cruz River basin, southern Arizona","interactions":[],"lastModifiedDate":"2026-02-19T17:32:35.603934","indexId":"sim3490","displayToPublicDate":"2023-02-10T13:10:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3490","displayTitle":"Geologic Map and Hydrogeologic Investigations of the Upper Santa Cruz River Basin, Southern Arizona","title":"Geologic map and hydrogeologic investigations of the upper Santa Cruz River basin, southern Arizona","docAbstract":"<p>This report includes an updated geologic map and cross sections of the upper Santa Cruz River basin, southern Arizona. The map and cross sections describe the geometry, thickness, and structure of the Miocene to Holocene units which form the main aquifers in the basin. The report also includes results of new hydrogeologic studies including (1) mapping and defining depth to bedrock based on geophysical data in the map area to better define the geometry and structure of the basin aquifers, (2) describing newly recognized hydrologically significant faults in the Peck Canyon and Sopori Wash areas, and (3) evaluating groundwater sources and hydrogeology of the Potrero Creek wetlands.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3490","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"Page, W.R., Bultman, M.W., Berry, M.E., Turner, K.J., Menges, C.M., Gray, F., Paces, J.B., VanSistine, D.P., Morgan, L.E., and Havens, J.C., 2023, Geologic map and hydrogeologic investigations of the upper Santa Cruz River basin, southern Arizona: U.S. Geological Survey Scientific Investigations Map 3490, 2 sheets, scale 1:50,000, 73-p. pamphlet, https://doi.org/10.3133/sim3490.","productDescription":"Report: ix, 73 p.; 4 Data Releases; 3 Sheets: 40.89 × 35.83 inches or smaller","onlineOnly":"Y","ipdsId":"IP-123665","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":412895,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PGUZV0","text":"USGS data release","linkHelpText":"Database for the geologic map of the upper Santa Cruz River basin, southern Arizona"},{"id":412893,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94NR0D9","text":"USGS data release","linkHelpText":"Argon data for Santa Cruz Basin, Arizona (ver. 1.1, November 2022)"},{"id":412892,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MBNX4O","text":"USGS data release","linkHelpText":"Sopori Wash sub-basin gravity data, Pima and Santa Cruz Counties, Arizona"},{"id":412891,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3490/sim3490_sheet2.pdf","text":"Cross Sections","size":"292 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3490 cross sections"},{"id":412890,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3490/sim3490_sheet1_georeferenced.pdf","text":"Georeferenced Geologic Map","size":"106 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3490 Georeferenced Geologic Map"},{"id":412889,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3490/sim3490_sheet1.pdf","text":"Geologic Map","size":"27.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3490 Geologic Map"},{"id":412888,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3490/ReadMe.txt","text":"Read Me","size":"12.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3490 Read Me file"},{"id":500197,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114341.htm","linkFileType":{"id":5,"text":"html"}},{"id":412894,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XXW25T","text":"USGS data release","linkHelpText":"Sr-, U-, H- and O-isotope data used to evaluate water sources in the Potrero Creek wetlands, upper Santa Cruz basin, southern Arizona, USA"},{"id":412886,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3490/coverthb_pamphlet.jpg"},{"id":412887,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3490/sim3490_pamphlet.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3490 pamphlet"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.37611177853266,\n              31.882514371272933\n            ],\n            [\n              -111.37611177853266,\n              31.300216933285228\n            ],\n            [\n              -110.49757862424259,\n              31.300216933285228\n            ],\n            [\n              -110.49757862424259,\n              31.882514371272933\n            ],\n            [\n              -111.37611177853266,\n              31.882514371272933\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"http://www.usgs.gov/centers/gecsc/\" data-mce-href=\"http://www.usgs.gov/centers/gecsc/\"> Geosciences and Environmental Change Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-980<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methodology</li><li>Description of Map Units</li><li>Structural Geology</li><li>Hydrogeologic Investigations</li><li>New Hydrogeologic Investigations</li><li>Evaluating Water Sources in the Potrero Creek Wetlands Through Geologic, Geophysical and Isotopic Investigations</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2023-02-10","noUsgsAuthors":false,"publicationDate":"2023-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Page, William R. 0000-0002-0722-9911","orcid":"https://orcid.org/0000-0002-0722-9911","contributorId":204509,"corporation":false,"usgs":true,"family":"Page","given":"William R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":863903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bultman, Mark W. 0000-0001-8352-101X mbultman@usgs.gov","orcid":"https://orcid.org/0000-0001-8352-101X","contributorId":204510,"corporation":false,"usgs":true,"family":"Bultman","given":"Mark","email":"mbultman@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berry, Margaret E. 0000-0002-4113-8212","orcid":"https://orcid.org/0000-0002-4113-8212","contributorId":201560,"corporation":false,"usgs":true,"family":"Berry","given":"Margaret E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":863905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":863906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Menges, Christopher M. 0000-0002-8045-2933","orcid":"https://orcid.org/0000-0002-8045-2933","contributorId":204511,"corporation":false,"usgs":true,"family":"Menges","given":"Christopher M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gray, Floyd 0000-0002-0223-8966","orcid":"https://orcid.org/0000-0002-0223-8966","contributorId":201529,"corporation":false,"usgs":true,"family":"Gray","given":"Floyd","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":215864,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":863909,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Van Sistine, D. Paco 0000-0003-1166-2547","orcid":"https://orcid.org/0000-0003-1166-2547","contributorId":213647,"corporation":false,"usgs":true,"family":"Van Sistine","given":"D.","email":"","middleInitial":"Paco","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":863910,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":863911,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Havens, Jeremy C. 0000-0002-8685-2823","orcid":"https://orcid.org/0000-0002-8685-2823","contributorId":238719,"corporation":false,"usgs":false,"family":"Havens","given":"Jeremy","email":"","middleInitial":"C.","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":863912,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70240476,"text":"ofr20231006 - 2023 - Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm","interactions":[],"lastModifiedDate":"2026-02-10T21:32:15.228526","indexId":"ofr20231006","displayToPublicDate":"2023-02-08T13:48:38","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1006","displayTitle":"Improving Temporal Frequency of Landsat Surface Temperature Products Using the Gap-Filling Algorithm","title":"Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm","docAbstract":"<p>Remotely sensed surface temperature (ST) has been widely used to monitor and assess landscape thermal conditions, hydrologic modeling, and surface energy balance. Landsat thermal sensors have continuously measured the Earth surface thermal radiance since August 1982. The thermal radiance measurements are atmospherically compensated and converted to Landsat STs and delivered as part of the U.S. Geological Survey Landsat Collection 1 U.S. Analysis Ready Data; however, the low satellite revisit cycles combined with the presence of clouds and cloud shadows reduce the number of valid retrievals. This reduction can limit the ability to monitor annual or seasonal variations in the surface thermal budget. These factors reduce the ability to use the temperature data to fit time series for historical trend analysis to match background climate variations. In this study, we implemented an approach that uses linear harmonic least absolute shrinkage and selection operator regression models to fill gaps because of clouds, shadows, and coarse temporal resolution. The gap-filled data provide increased temporal density of Landsat ST records. The gap-filled Landsat ST, therefore, can allow for an improved monitoring of annual, seasonal, or even monthly landscape thermal conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231006","usgsCitation":"Xian, G., Shi, H., Arab, S., Mueller, C., Hussain, R., Sayler, K., and Howard, D., 2023, Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm: U.S. Geological Survey Open-File Report 2023–1006, 15 p., https://doi.org/10.3133/ofr20231006.","productDescription":"vi, 15 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-144337","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":412873,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1006/images"},{"id":412872,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1006/ofr20231006.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":412871,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1006/ofr20231006.pdf","text":"Report","size":"41.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1006"},{"id":412880,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231006/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412870,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1006/coverthb.jpg"},{"id":499732,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114340.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","city":"Atlanta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.9318883744094,\n              34.338976979151155\n            ],\n            [\n              -84.9318883744094,\n              33.376859208686255\n            ],\n            [\n              -83.70224614831253,\n              33.376859208686255\n            ],\n            [\n              -83.70224614831253,\n              34.338976979151155\n            ],\n            [\n              -84.9318883744094,\n              34.338976979151155\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eros\" data-mce-href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center</a><br>U.S. Geological Survey<br>47914 252nd Street<br>Sioux Falls, SD 57198</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Enhancement of Temporal Density of Landsat Surface Temperature Data</li><li>Results for Gap-Filled Surface Temperature Data</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-02-08","noUsgsAuthors":false,"publicationDate":"2023-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":863892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Hua 0000-0001-7013-1565","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":300281,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":863893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arab, Saeed 0000-0003-1602-8801","orcid":"https://orcid.org/0000-0003-1602-8801","contributorId":299964,"corporation":false,"usgs":false,"family":"Arab","given":"Saeed","email":"","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":863894,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Chase 0000-0002-9948-1304","orcid":"https://orcid.org/0000-0002-9948-1304","contributorId":302266,"corporation":false,"usgs":false,"family":"Mueller","given":"Chase","affiliations":[],"preferred":false,"id":863895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hussain, Reza 0000-0002-5445-3027","orcid":"https://orcid.org/0000-0002-5445-3027","contributorId":301245,"corporation":false,"usgs":false,"family":"Hussain","given":"Reza","affiliations":[{"id":65343,"text":"KBR, Contractor to U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":863896,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sayler, Kristi L. 0000-0003-2514-242X sayler@usgs.gov","orcid":"https://orcid.org/0000-0003-2514-242X","contributorId":2988,"corporation":false,"usgs":true,"family":"Sayler","given":"Kristi","email":"sayler@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":863897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Howard, Danny 0000-0002-7563-7538 danny.howard.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":176973,"corporation":false,"usgs":true,"family":"Howard","given":"Danny","email":"danny.howard.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":863898,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70240939,"text":"70240939 - 2023 - Increasing Alaskan river discharge during the cold season is driven by recent warming","interactions":[],"lastModifiedDate":"2023-03-02T13:22:05.643107","indexId":"70240939","displayToPublicDate":"2023-02-07T07:19:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Increasing Alaskan river discharge during the cold season is driven by recent warming","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Arctic hydrology is experiencing rapid changes including earlier snow melt, permafrost degradation, increasing active layer depth, and reduced river ice, all of which are expected to lead to changes in stream flow regimes. Recently, long-term (&gt;60 years) climate reanalysis and river discharge observation data have become available. We utilized these data to assess long-term changes in discharge and their hydroclimatic drivers. River discharge during the cold season (October–April) increased by 10% per decade. The most widespread discharge increase occurred in April (15% per decade), the month of ice break-up for the majority of basins. In October, when river ice formation generally begins, average monthly discharge increased by 7% per decade. Long-term air temperature increases in October and April increased the number of days above freezing (+1.1 d per decade) resulting in increased snow ablation (20% per decade) and decreased snow water equivalent (−12% per decade). Compared to the historical period (1960–1989), mean April and October air temperature in the recent period (1990–2019) have greater correlation with monthly discharge from 0.33 to 0.68 and 0.0–0.48, respectively. This indicates that the recent increases in air temperature are directly related to these discharge changes. Ubiquitous increases in cold and shoulder-season discharge demonstrate the scale at which hydrologic and biogeochemical fluxes are being altered in the Arctic.</p></div>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/acb661","usgsCitation":"Blaskey, D., Koch, J.C., Gooseff, M., Newman, A.C., Cheng, Y., O’Donnell, J.A., and Musselman, K., 2023, Increasing Alaskan river discharge during the cold season is driven by recent warming: Environmental Research Letters, v. 18, no. 2, 024042, 12 p., https://doi.org/10.1088/1748-9326/acb661.","productDescription":"024042, 12 p.","ipdsId":"IP-146328","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":444564,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/acb661","text":"Publisher Index Page"},{"id":413614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -140.80269683804968,\n              69.90708872520639\n            ],\n            [\n              -148.88520185751725,\n              71.02309718987036\n            ],\n            [\n              -155.5620538301211,\n              71.53067530491455\n            ],\n            [\n              -161.00895938671903,\n              71.02309718987036\n            ],\n            [\n              -166.9829848358909,\n              69.04477255284121\n            ],\n            [\n              -168.74005114447075,\n              65.596108528327\n            ],\n            [\n              -167.33439809760677,\n              64.78518663988115\n            ],\n            [\n              -166.45586494331695,\n              63.24598779081114\n            ],\n            [\n              -167.51010472846482,\n              61.284285987379945\n            ],\n            [\n              -167.51010472846482,\n              59.37133444177681\n            ],\n            [\n              -162.94173232615697,\n              58.464280389404564\n            ],\n            [\n              -163.99597211130484,\n              55.597485466387496\n            ],\n            [\n              -169.44287766790276,\n              53.561315965353174\n            ],\n            [\n              -169.0914644061869,\n              52.71814782604147\n            ],\n            [\n              -163.29314558787283,\n              53.97671165644215\n            ],\n            [\n              -153.6292808906832,\n              56.28627445825995\n            ],\n            [\n              -147.8309620723694,\n              59.72751943182155\n            ],\n            [\n              -142.55976314662954,\n              59.99219353855369\n            ],\n            [\n              -134.12584486544583,\n              55.398433011938096\n            ],\n            [\n              -132.01736529514983,\n              52.824449925968395\n            ],\n            [\n              -130.6117122482858,\n              54.997303115736514\n            ],\n            [\n              -131.13883214085976,\n              56.38367498879066\n            ],\n            [\n              -135.53149791230982,\n              59.99219353855369\n            ],\n            [\n              -136.5857376974577,\n              59.10171681014367\n            ],\n            [\n              -141.15411009976555,\n              60.68775388587548\n            ],\n            [\n              -140.80269683804968,\n              69.90708872520639\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Blaskey, D","contributorId":302754,"corporation":false,"usgs":false,"family":"Blaskey","given":"D","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":865371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":865372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gooseff, M.","contributorId":201026,"corporation":false,"usgs":false,"family":"Gooseff","given":"M.","email":"","affiliations":[],"preferred":false,"id":865373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newman, A. C. 0000-0001-6621-2717","orcid":"https://orcid.org/0000-0001-6621-2717","contributorId":211589,"corporation":false,"usgs":false,"family":"Newman","given":"A.","email":"","middleInitial":"C.","affiliations":[{"id":38269,"text":"Aarhus, Denmark","active":true,"usgs":false}],"preferred":false,"id":865374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cheng, Yang","contributorId":211352,"corporation":false,"usgs":false,"family":"Cheng","given":"Yang","email":"","affiliations":[],"preferred":false,"id":865375,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":865376,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Musselman, K","contributorId":302756,"corporation":false,"usgs":false,"family":"Musselman","given":"K","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":865377,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70240443,"text":"70240443 - 2023 - Integrating urban water fluxes and moving beyond impervious surface cover: A review","interactions":[],"lastModifiedDate":"2023-02-08T12:47:00.107874","indexId":"70240443","displayToPublicDate":"2023-02-06T06:44:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating urban water fluxes and moving beyond impervious surface cover: A review","docAbstract":"<div id=\"ab015\" class=\"abstract author\"><div id=\"as015\"><p id=\"sp0015\">Though urban areas represent a small fraction of global land cover, they have an outsized impact on hydrological processes. Within these areas, the pathways that water follows are fundamentally transformed by the disturbance of soils, land cover, vegetation, topography, and built infrastructure. While progress has been made across many cities to quantify interactions between hydrological processes and the urban environment, many fundamental questions remain unanswered. In this article, we review the state of urban hydrologic science, with an eye towards identifying gaps in our understanding of how water flows through built landscapes. Our review focuses on key topics within urban hydrology related to water quantity, including runoff and streamflow generation, soils and soil water, groundwater, vegetation, and climate. We also describe some of the challenges and opportunities within the field of urban hydrology that we envision will drive future work and collaboration.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129188","usgsCitation":"Oswald, C., Kelleher, C., Ledford, S., Hopkins, K.G., Sytsma, A., Tetzlaff, D., Toran, L., and Voter, C., 2023, Integrating urban water fluxes and moving beyond impervious surface cover: A review: Journal of Hydrology, v. 618, 129188, 25 p., https://doi.org/10.1016/j.jhydrol.2023.129188.","productDescription":"129188, 25 p.","ipdsId":"IP-144954","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":412867,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"618","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oswald, Claire","contributorId":302231,"corporation":false,"usgs":false,"family":"Oswald","given":"Claire","email":"","affiliations":[{"id":65447,"text":"Toronto Metropolitan University","active":true,"usgs":false}],"preferred":false,"id":863812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelleher, Christa","contributorId":242798,"corporation":false,"usgs":false,"family":"Kelleher","given":"Christa","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":863813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ledford, Sarah","contributorId":300624,"corporation":false,"usgs":false,"family":"Ledford","given":"Sarah","email":"","affiliations":[{"id":52554,"text":"Georgia State University","active":true,"usgs":false}],"preferred":false,"id":863814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":863815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sytsma, Anneliese","contributorId":302232,"corporation":false,"usgs":false,"family":"Sytsma","given":"Anneliese","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":863816,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tetzlaff, Doerthe","contributorId":302233,"corporation":false,"usgs":false,"family":"Tetzlaff","given":"Doerthe","email":"","affiliations":[{"id":65448,"text":"Humboldt University Berlin","active":true,"usgs":false}],"preferred":false,"id":863817,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Toran, Laura","contributorId":81622,"corporation":false,"usgs":false,"family":"Toran","given":"Laura","email":"","affiliations":[{"id":34225,"text":"Temple University, Philadelphia, Pa.","active":true,"usgs":false}],"preferred":false,"id":863818,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Voter, Carolyn","contributorId":302234,"corporation":false,"usgs":false,"family":"Voter","given":"Carolyn","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":863819,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70240465,"text":"70240465 - 2023 - Four decades of regional wet deposition, local bulk deposition, and stream-water chemistry show the influence of nearby land use on forested streams in Central Appalachia☆","interactions":[],"lastModifiedDate":"2023-02-08T12:39:04.453935","indexId":"70240465","displayToPublicDate":"2023-02-03T06:35:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Four decades of regional wet deposition, local bulk deposition, and stream-water chemistry show the influence of nearby land use on forested streams in Central Appalachia☆","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Hydrologic monitoring began on two headwater streams (&lt;1&nbsp;km<sup>2</sup>) on the University of Kentucky's Robinson Forest in 1971. We evaluated stream-water (1974–2013) and bulk-deposition (wet&nbsp;+&nbsp;dust) (1984–2013) chemistry in the context of regional wet-deposition patterns that showed decreases in both sulfate and nitrate concentrations as well as proximal surface-mine expansion. Decadal time steps (1974–83, 1984–93, 1994–2003, 2004–2013) were used to quantify change. Comparison of the first two decades showed similarly decreased sulfate (minimum flow-adjusted annual-mean concentration of ≈13.5&nbsp;mg/L in 1982 to 8.8&nbsp;mg/L in 1992) and increased pH (6.6–6.8) in both streams, reflecting contemporaneous changes in both bulk and wet deposition. In contrast, concentrations of nitrate (0.14 to &gt;0.25&nbsp;mg/L) and base cations increased between these two decades, coinciding with expansion of surface mining between 1985 and 1995. In 2004, stream-water pH (6.7 in 2004), sulfate (9.2&nbsp;mg/L), and nitrate (&gt;0.11&nbsp;mg/L) were similar to 1982, despite wet-deposition concentrations being lower. Base-cation concentrations were higher in the stream adjacent to ongoing surface mining relative to the stream situated near the middle of the experimental forest. However, pH decreased to approximately 5.7 by 2013 for both streams, which, combined with a shift in dominant cations from calcium to magnesium and potassium, indicates that the soil-buffering capacity of this landscape has been exceeded. Ratios of bulk deposition and stream-water concentrations indicate enrichment of sulfate (1.7–25.2) and cations (0.5–64.8), but not nitrogen (0.1–5.6), indicating that the Forest is not nitrogen saturated and that ongoing changes in water-quality are sulfate driven. When concentrations were adjusted to account for changes in streamflow (climate) over the 4 decades, external influences (land management/regulation) explained most change. The amount and direction of change differed among constituents, both between consecutive decades and between the first and last decades, reflecting the influence of localized surface mining even as regional wet deposition continued to improve due to the Clean Air Act. The implication is that localized stressors have the potential to out-pace the benefits of national environmental policies for communities that depend on local water-resources in similar environments.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2023.117392","usgsCitation":"Williamson, T.N., Sena, K., Shoda, M.E., and Barton, C.D., 2023, Four decades of regional wet deposition, local bulk deposition, and stream-water chemistry show the influence of nearby land use on forested streams in Central Appalachia☆: Journal of Environmental Management, v. 332, 117392, 12 p., https://doi.org/10.1016/j.jenvman.2023.117392.","productDescription":"117392, 12 p.","ipdsId":"IP-123382","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":412865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.96095899311437,\n              36.662738378060624\n            ],\n            [\n              -82.06179958395745,\n              36.662738378060624\n            ],\n            [\n              -82.06179958395745,\n              38.88459122444556\n            ],\n            [\n              -84.96095899311437,\n              38.88459122444556\n            ],\n            [\n              -84.96095899311437,\n              36.662738378060624\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"332","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":863867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":863868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":863870,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70239888,"text":"70239888 - 2023 - Characterizing historic streamflow to support drought planning in the upper Missouri River basin","interactions":[],"lastModifiedDate":"2026-03-18T16:13:50.675788","indexId":"70239888","displayToPublicDate":"2023-02-01T11:07:46","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"Characterizing historic streamflow to support drought planning in the upper Missouri River basin","docAbstract":"This project combined tree-ring based paleo and modern climate and hydrologic research aimed at understanding the primary influences on drought risk and water reliability in basins critical for western U.S. water resources. New paleohydrologic datasets and analyses were developed and applied to contextualize future streamflow projections and address specific water management questions. These questions centered around optimizing future water management protocols for numerous objectives ranging from improving agricultural water allocation during drought while maintaining instream flows for aquatic ecosystem health, to the testing of operations across large river systems with complex infrastructure critical for downstream flood control, navigation, and hydropower generation. USGS scientists worked closely with the Bureau of Reclamation to estimate both past and future drought risk at key management locations throughout the Missouri basin, the Milk and St. Mary River system, and across the major managed river systems in the western United States. These efforts provided a roadmap for future water management strategies under changing climate and water supply conditions, which are detailed in Reclamation’s newly completed Missouri Headwaters Basin Study, the 2021 SECURE Water Act Report, and the forthcoming update of the St. Mary and Milk Rivers Basin Study. Among the major scientific findings to emerge was a new understanding of the long-term (1200-year) history of drought variability for the Missouri River, which highlighted the unusual severity of the early 2000s drought across the Rocky Mountain headwaters and adjacent high plains. By combining the extended drought record with extensive modern and paleoclimate records, we document how warming exacerbates severities of naturally occurring droughts, with recent decades defined by “hot” droughts and the 2000s (2001-2010) drought ranking as the most severe event in 1200 years. Increasingly severe drought events such as this strain already over-allocated water resources that multiple sectors of society depend heavily upon.","language":"English","publisher":"North Central Climate Adaptation Science Center","usgsCitation":"Pederson, G.T., 2023, Characterizing historic streamflow to support drought planning in the upper Missouri River basin: Final Report, 33 p.","productDescription":"33 p.","ipdsId":"IP-148061","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":501261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501260,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f83509de4b0e84f60868124/63d1958bd34e06fef1500594","linkFileType":{"id":5,"text":"html"}}],"country":"Canada, United States","otherGeospatial":"upper Missouri River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.05224962042496,\n              50.08090362730903\n            ],\n            [\n              -117.05224962042496,\n              37.030824614225864\n            ],\n            [\n              -89.46041753932424,\n              37.030824614225864\n            ],\n            [\n              -89.46041753932424,\n              50.08090362730903\n            ],\n            [\n              -117.05224962042496,\n              50.08090362730903\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862279,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70240935,"text":"70240935 - 2023 - Agricultural conservation practices could help offset climate change impacts on cyanobacterial harmful algal blooms in Lake Erie","interactions":[],"lastModifiedDate":"2024-05-20T16:23:27.294825","indexId":"70240935","displayToPublicDate":"2023-02-01T06:36:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Agricultural conservation practices could help offset climate change impacts on cyanobacterial harmful algal blooms in Lake Erie","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab005\" class=\"abstract author\"><div id=\"as005\"><p id=\"sp0005\">Harmful algal blooms (HABs) are a recurring problem in many temperate large lake and coastal marine ecosystems, caused mainly by anthropogenic eutrophication. Implementation of agricultural conservation practices (ACPs) offers a means to reduce non-point source nutrient runoff and mitigate HABs. However, the effectiveness of ACPs in a changing climate remains uncertain. We used an integrated biophysical modeling approach to predict how Lake Erie cyanobacterial HAB severity (bloom biomass) may change under several climate and ACP implementation scenarios, using western Lake Erie and its largely agricultural watershed as our study system. An ensemble of general circulation model projections was used to drive spatially explicit land use and hydrology models of the Maumee River watershed, the output of which informed a predictive model of Lake Erie HAB severity. Results show that, in the absence of changes in ACPs, the frequency of severe HABs is projected to increase during coming decades, owing to increased inputs of nutrients from the watershed. These anticipated increases are due to increased total precipitation and more frequent higher-magnitude rainfall events. While further implementation of ACPs appears capable of reducing severe HAB events, widespread implementation would be necessary to reduce HAB severity below current management targets. This study highlights how continued climate change will only exacerbate the need for land management practices that can reduce nutrient runoff in agriculturally dominated ecosystems, such as Lake Erie. It also shows how interdisciplinary, biophysical modeling approaches can help identify strategies to mitigate HABs in the face of anthropogenic stressors.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.11.009","usgsCitation":"Fraker, M.E., Aloysius, N.R., Martin, J.F., Keitzer, S.C., Dippold, D.A., Yen, H., Arnold, J.G., Daggupati, P., Johnson, M.V., Robertson, D., Sowa, S.P., White, M.J., and Ludsin, S.A., 2023, Agricultural conservation practices could help offset climate change impacts on cyanobacterial harmful algal blooms in Lake Erie: Journal of Great Lakes Research, v. 49, no. 1, p. 209-219, https://doi.org/10.1016/j.jglr.2022.11.009.","productDescription":"11 p.","startPage":"209","endPage":"219","ipdsId":"IP-136384","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":444660,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2022.11.009","text":"Publisher Index Page"},{"id":413606,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.54931314843981,\n              41.61838726545028\n            ],\n            [\n              -82.86844995386474,\n              41.289162489225475\n            ],\n            [\n              -81.53966855800157,\n              41.47044290278254\n            ],\n            [\n              -80.15597883999482,\n              41.945939927238726\n            ],\n            [\n              -78.87112410184554,\n              42.6121865802632\n            ],\n            [\n              -78.76130745755944,\n              42.998913499774915\n            ],\n            [\n              -79.35431733670504,\n              43.0791772338647\n            ],\n            [\n              -80.36463046413846,\n              42.86222422480026\n            ],\n            [\n              -81.01254866542764,\n              42.83807110066172\n            ],\n            [\n              -81.84715516200271,\n              42.692954038490456\n            ],\n            [\n              -82.64881666529249,\n              42.2311751476457\n            ],\n            [\n              -83.02219325586584,\n              42.27181831635397\n            ],\n            [\n              -83.47244149743949,\n              42.28806825056833\n            ],\n            [\n              -83.54931314843981,\n              41.61838726545028\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fraker, Michael E. 0000-0002-1813-706X","orcid":"https://orcid.org/0000-0002-1813-706X","contributorId":150962,"corporation":false,"usgs":false,"family":"Fraker","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":865348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aloysius, Noel R","contributorId":302749,"corporation":false,"usgs":false,"family":"Aloysius","given":"Noel","email":"","middleInitial":"R","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":865349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Jay F. 0000-0002-1599-5931","orcid":"https://orcid.org/0000-0002-1599-5931","contributorId":254345,"corporation":false,"usgs":false,"family":"Martin","given":"Jay","email":"","middleInitial":"F.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":865350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keitzer, S. Conor 0000-0002-8164-4099","orcid":"https://orcid.org/0000-0002-8164-4099","contributorId":189196,"corporation":false,"usgs":false,"family":"Keitzer","given":"S.","email":"","middleInitial":"Conor","affiliations":[],"preferred":false,"id":865351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dippold, David A 0000-0002-4240-8704","orcid":"https://orcid.org/0000-0002-4240-8704","contributorId":254340,"corporation":false,"usgs":false,"family":"Dippold","given":"David","email":"","middleInitial":"A","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":865352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yen, Haw 0000-0002-5509-8792","orcid":"https://orcid.org/0000-0002-5509-8792","contributorId":169564,"corporation":false,"usgs":false,"family":"Yen","given":"Haw","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":865353,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arnold, Jeffrey G.","contributorId":172345,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":865354,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Daggupati, Prasad 0000-0002-7044-3435","orcid":"https://orcid.org/0000-0002-7044-3435","contributorId":189193,"corporation":false,"usgs":false,"family":"Daggupati","given":"Prasad","email":"","affiliations":[],"preferred":false,"id":865355,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, Mari-Vaughn Virginia 0000-0002-2944-2529","orcid":"https://orcid.org/0000-0002-2944-2529","contributorId":302751,"corporation":false,"usgs":true,"family":"Johnson","given":"Mari-Vaughn","email":"","middleInitial":"Virginia","affiliations":[{"id":63969,"text":"Pacific Islands Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":865356,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865357,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sowa, Scott P. 0000-0002-5425-2591 sowasp@missouri.edu","orcid":"https://orcid.org/0000-0002-5425-2591","contributorId":146672,"corporation":false,"usgs":false,"family":"Sowa","given":"Scott","email":"sowasp@missouri.edu","middleInitial":"P.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":865358,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"White, Michael J.","contributorId":172348,"corporation":false,"usgs":false,"family":"White","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":865359,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ludsin, Stuart A. 0000-0002-3866-2216","orcid":"https://orcid.org/0000-0002-3866-2216","contributorId":175425,"corporation":false,"usgs":false,"family":"Ludsin","given":"Stuart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":865360,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70241025,"text":"70241025 - 2023 - Can hydrological models benefit from using global soil moisture, evapotranspiration, and runoff products as calibration targets?","interactions":[],"lastModifiedDate":"2023-03-07T12:47:56.075162","indexId":"70241025","displayToPublicDate":"2023-01-31T06:40:31","publicationYear":"2023","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":"Can hydrological models benefit from using global soil moisture, evapotranspiration, and runoff products as calibration targets?","docAbstract":"<div class=\"article-section__content en main\"><p>Hydrological models are usually calibrated to in-situ streamflow observations with reasonably long and uninterrupted records. This is challenging for poorly gage or ungaged basins where such information is not available. Even for gaged basins, the single-objective calibration to gaged streamflow cannot guarantee reliable forecasts because, as has been documented elsewhere, the inverse problem is mathematically ill-posed. Therefore, the inclusion of other observations, and the reproduction of other hydrological variables beyond streamflow, become critical components of accurate hydrological forecasting. In this study, six single- and multi-objective model calibration schemes based on different combinations of gaged streamflow, global-scale gridded soil moisture, actual evapotranspiration (ET), and runoff products are used for the calibration of a process-based hydrological model for 20 catchments located within the Lake Michigan watershed, of the Laurentian Great Lakes. Results show that the addition of gridded soil moisture to gaged streamflow in model calibration improves the ET simulation performance for most of the catchments, leading to the overall best-performing models. The monthly streamflow simulation performance for the experiments using gridded runoff products to inform the model is outperformed by those using the gaged streamflow, but the discrepancy is mitigated with increasing catchment scale. A new visualization method that effectively synthesizes model performance for the simulations of streamflow, soil moisture, and ET was also proposed. Based on the method, it is revealed that the streamflow simulation performance is relatively weak for baseflow-dominated catchments; overall, the 20 catchment models simulate streamflow and ET better than soil moisture.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR032064","usgsCitation":"Mei, Y., Mai, J., Do, H.X., Gronewold, A., Reeves, H.W., Eberts, S.M., Niswonger, R.G., Regan, R.S., and Hunt, R., 2023, Can hydrological models benefit from using global soil moisture, evapotranspiration, and runoff products as calibration targets?: Water Resources Research, v. 59, no. 2, e2022WR032064, 19 p., https://doi.org/10.1029/2022WR032064.","productDescription":"e2022WR032064, 19 p.","ipdsId":"IP-137447","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":444667,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022wr032064","text":"External Repository"},{"id":435477,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DOVISZ","text":"USGS data release","linkHelpText":"PRMS Model Archive for Selected Catchments in the Lake Michigan Basin Used in Examination of Multi-Objective Model Calibration"},{"id":413758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.15070336490274,\n              46.27321789689552\n            ],\n            [\n              -85.89745654604944,\n              46.15163132762174\n            ],\n            [\n              -87.47881622377123,\n              45.93820704698675\n            ],\n            [\n              -88.44520269349022,\n              44.67158603626524\n            ],\n            [\n              -88.5330560089191,\n              43.91701689085704\n            ],\n            [\n              -88.2694960626324,\n              42.50847855309857\n            ],\n            [\n              -87.91808280091627,\n              41.59522078155692\n            ],\n            [\n              -86.81991635805396,\n              41.43075831670021\n            ],\n            [\n              -86.07316317690724,\n              42.443681530813166\n            ],\n            [\n              -85.23855668033163,\n              44.54649788311576\n            ],\n            [\n              -84.66751013004324,\n              45.47809222344057\n            ],\n            [\n              -85.15070336490274,\n              46.27321789689552\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Mei, Yiwen 0000-0002-3326-8287","orcid":"https://orcid.org/0000-0002-3326-8287","contributorId":302895,"corporation":false,"usgs":false,"family":"Mei","given":"Yiwen","email":"","affiliations":[{"id":65573,"text":"Connecticut Institute for Resilience and Climate Adaptation","active":true,"usgs":false}],"preferred":false,"id":865760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mai, Juliane 0000-0002-1132-2342","orcid":"https://orcid.org/0000-0002-1132-2342","contributorId":302896,"corporation":false,"usgs":false,"family":"Mai","given":"Juliane","email":"","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":865761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Do, Hong Xuan","contributorId":302897,"corporation":false,"usgs":false,"family":"Do","given":"Hong","email":"","middleInitial":"Xuan","affiliations":[{"id":65575,"text":"Nong Lam University","active":true,"usgs":false}],"preferred":false,"id":865762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gronewold, Andrew 0000-0002-3576-2529","orcid":"https://orcid.org/0000-0002-3576-2529","contributorId":302898,"corporation":false,"usgs":false,"family":"Gronewold","given":"Andrew","email":"","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":865763,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865764,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eberts, Sandra M. 0000-0001-5138-8293 smeberts@usgs.gov","orcid":"https://orcid.org/0000-0001-5138-8293","contributorId":127844,"corporation":false,"usgs":true,"family":"Eberts","given":"Sandra","email":"smeberts@usgs.gov","middleInitial":"M.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":865765,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865766,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Regan, R. Steve 0000-0003-4803-8596 rsregan@usgs.gov","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":196973,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"rsregan@usgs.gov","middleInitial":"Steve","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":865767,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865768,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70240042,"text":"sir20225124 - 2023 - Hydrologic change in the St. Louis River Basin from iron mining on the Mesabi Iron Range, northeastern Minnesota","interactions":[],"lastModifiedDate":"2026-02-23T20:52:37.679793","indexId":"sir20225124","displayToPublicDate":"2023-01-30T09:30:21","publicationYear":"2023","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":"2022-5124","displayTitle":"Hydrologic Change in the St. Louis River Basin from Iron Mining on the Mesabi Iron Range, Northeastern Minnesota","title":"Hydrologic change in the St. Louis River Basin from iron mining on the Mesabi Iron Range, northeastern Minnesota","docAbstract":"<p>This study compares the results of two regional steady-state U.S. Geological Survey Modular Three-Dimensional Finite-Difference Ground-Water Flow (MODFLOW) models constructed to quantify the hydrologic changes in the St. Louis River Basin from iron mining on the Mesabi Iron Range in northeastern Minnesota. The U.S. Geological Survey collaborated in this study with bands of the Minnesota Chippewa Tribe, and the Minnesota Pollution Control Agency to inform management decisions about aquatic resources in the St. Louis River Basin. A model constructed and calibrated to represent average 1995–2015 mining conditions produced regional groundwater heads and flows. A pre-mining scenario model was constructed from this mining model but had the land and bedrock surfaces restored to pre-mining topographies and had modeled mining features (mine pits, tailings basins, waste-rock piles, and mining-disturbed areas) eliminated to represent general pre-mining stratigraphy and hydrogeology. Many of the features important to the hydrology of this mining area (like individual mine pits) are difficult to represent in groundwater models and required the use of modeling tools to indirectly account for their effects. The difference between the results of these two models represents mining’s effects on the hydrology in the Mesabi Iron Range area of the St Louis River Basin. The mining and pre-mining regional models also can provide boundary conditions and initial properties for future local or site-specific groundwater-flow models in the area.</p><p>Total groundwater flow through the mining model is 171 million cubic feet per day. Areal recharge is the largest source of groundwater (78 and 81 percent of total groundwater flow in the mining and pre-mining scenario models, respectively). Seepage from streams and lakes provides another 17 percent of the total groundwater flow through both models. Water leaves aquifers through seepage to streams (discharge as base flow, 43 percent in both models) and areal seepage to the land surface (surface seepage), for example to wetlands (45 and 49 percent, mining and pre-mining scenario models respectively).</p><p>Comparison of the results from the mining and pre-mining scenario models shows that iron mining has produced measurable hydrologic changes in the St. Louis River Basin, but that most of those changes and the highest magnitude changes occur near the mining features. Flow changes to and from surface-water bodies like streams and wetlands were analyzed in detail because of their importance in sustaining surface waters and aquatic life. Overall, groundwater flow in the mining model was 3.62 million cubic feet per day (2.2 percent) greater than total pre-mining model groundwater flow. This was caused by an increase in recharge from tailings basins and a decrease in discharge from surface seepage. Groundwater discharge to mine pits was the largest change in groundwater flows between the models (a change representing 2.8 percent of total pre-mining model groundwater flow). Net recharge to groundwater from tailings basins (2.4 percent), net decrease in surface seepage from groundwater (2.7 percent), and net increase in seepage to streams (1.0 percent) were all in this same range of total pre-mining model groundwater flow. Groundwater lost through mine-pit withdrawals was nearly offset by groundwater gained through recharge from tailings basins. However, because losses and gains occurred in different areas, the effect of mining can have more substantial effects on local areas than the model-wide averages represent.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/sir20225124","collaboration":"Prepared in cooperation with bands of the Minnesota Chippewa Tribe, the Great Lakes Indian Fish & Wildlife Commission, and the Minnesota Pollution Control Agency","usgsCitation":"Cowdery, T.K., Baker, A.C., Haserodt, M.J., Feinstein, D.T., and Hunt, R.J., 2023, Hydrologic change in the St. Louis River Basin from iron mining on the Mesabi Iron Range, northeastern Minnesota: U.S. Geological Survey Scientific Investigations Report 2022–5124, 59 p., https://doi.org/10.3133/sir20225124.","productDescription":"Report: viii, 59 p.; 2 Data Releases","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-122102","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":412380,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5124/sir20225124.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":412376,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5124/images"},{"id":412373,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5124/coverthb.jpg"},{"id":412374,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5124/sir20225124.pdf","text":"Report","size":"18.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5124"},{"id":500466,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114303.htm","linkFileType":{"id":5,"text":"html"}},{"id":412504,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225124/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412378,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z60MJ0","text":"USGS data release","linkHelpText":"Soil-water-balance model data sets for the St. Louis River drainage basin, northeast Minnesota, 1995–2010"},{"id":412377,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U6KSBJ","text":"USGS data release","linkHelpText":"MODFLOW–NWT simulations of regional groundwater flow under mining and pre-mining scenarios near the Mesabi Iron Range within the St. Louis River Basin, northeastern Minnesota"}],"country":"United States","state":"Minnesota","otherGeospatial":"Mesabi Iron Range, St Louis River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.333,\n              48\n            ],\n            [\n              -93.3333,\n              47\n            ],\n            [\n              -91.666,\n              47\n            ],\n            [\n              -91.666,\n              48\n            ],\n            [\n              -93.333,\n              48\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/upper-midwest-water-science-center%20\" data-mce-href=\"https://www.usgs.gov/centers/upper-midwest-water-science-center%20\">Upper Midwest Water Science Center</a> <br>U.S. Geological Survey<br>1 Gifford Pinchot Drive <br>Madison, WI 53726</p><p><a href=\"https://pubs.er.usgs.gov/contactt\" data-mce-href=\"../contactt\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Geology, Groundwater Flow, and Interaction with Surface Waters</li><li>Mining Groundwater-Flow Model</li><li>Pre-Mining Scenario Model</li><li>Differences Between the Mining and Pre-Mining Model Results</li><li>Hydrologic Changes from Iron Mining</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-01-31","noUsgsAuthors":false,"publicationDate":"2023-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Cowdery, Timothy K. 0000-0001-9402-6575 cowdery@usgs.gov","orcid":"https://orcid.org/0000-0001-9402-6575","contributorId":456,"corporation":false,"usgs":true,"family":"Cowdery","given":"Timothy","email":"cowdery@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":862567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Anna C. 0000-0001-8194-7535 abaker@usgs.gov","orcid":"https://orcid.org/0000-0001-8194-7535","contributorId":4689,"corporation":false,"usgs":true,"family":"Baker","given":"Anna","email":"abaker@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haserodt, Megan J. 0000-0002-8304-090X mhaserodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-090X","contributorId":174791,"corporation":false,"usgs":true,"family":"Haserodt","given":"Megan","email":"mhaserodt@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862569,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":214256,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":862570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862571,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241176,"text":"70241176 - 2023 - Changes in suspended-sediment yields under divergent land-cover disturbance histories: A comparison of two large watersheds, Olympic Mountains, USA","interactions":[],"lastModifiedDate":"2023-06-27T16:41:52.717587","indexId":"70241176","displayToPublicDate":"2023-01-30T07:02:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Changes in suspended-sediment yields under divergent land-cover disturbance histories: A comparison of two large watersheds, Olympic Mountains, USA","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Improvements in timber harvest practices and reductions in harvest volumes over the past half&nbsp;century are commonly presumed to have reduced sediment loads in many western US rivers. However, direct assessments in larger watersheds are relatively sparse. Here, we compare 2019–21 sediment concentrations against those of the late 1970s in the Bogachiel and Calawah &nbsp;River watersheds, adjacent and similarly sized (~300 km<sup>2</sup>) basins in the western Olympic Mountains of Washington State. The Calawah River&nbsp;watershed has experienced significant land-cover disturbance, including a large 1951 fire, extensive post-fire salvage logging, and relatively high rates of timber harvest through the 1990s. In contrast, the Bogachiel&nbsp;River watershed did not burn, and experienced only modest timber harvest that largely post-dated 1970s sediment monitoring. Channel-width trends suggest the Calawah River was still recovering from 1950s disturbances in the late 1970s. We found that 2019–21 suspended-sediment loads in the Calawah River were 2.3–2.6 times lower than would have been expected based on 1970s sediment rating curves, while recent loads in the Bogachiel River were a factor of 1.4 ± 1.0 lower. We consider the plausibility and possible explanations of declining concentrations in the less-disturbed Bogachiel River. Suspended-sediment yields in the Bogachiel River were two times higher than yields in the Calawah River, which is attributed to a combination of modestly higher precipitation, more efficient runoff generation, and more extensive and erodible Quaternary valley fills in the Bogachiel River. Regional shifts in flood hydrology have also influenced suspended-sediment loads in both watersheds. Our results then document a significant decline in suspended-sediment concentrations in the Calawah River over the past half&nbsp;century. Reduced land-cover disturbance provides the simplest and most likely explanation for this decline, though the wide range of possible concentration changes in the Bogachiel River leaves open possibilities that other processes (human, natural, or methodologic) could be a factor.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/esp.5556","usgsCitation":"Jaeger, K.L., Anderson, S.W., and Dunn, S., 2023, Changes in suspended-sediment yields under divergent land-cover disturbance histories: A comparison of two large watersheds, Olympic Mountains, USA: Earth Surface Processes and Landforms, v. 48, no. 7, p. 1398-1413, https://doi.org/10.1002/esp.5556.","productDescription":"16 p.","startPage":"1398","endPage":"1413","ipdsId":"IP-144931","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":444679,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5556","text":"Publisher Index Page"},{"id":435479,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95L5ADD","text":"USGS data release","linkHelpText":"Supporting Spatial Data for Sediment Studies in the Bogachiel and Calawah River Watersheds, Washington"},{"id":414086,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.35640085378517,\n              48.1377522152041\n            ],\n            [\n              -124.35640085378517,\n              47.1761943193718\n            ],\n            [\n              -122.80798616934896,\n              47.1761943193718\n            ],\n            [\n              -122.80798616934896,\n              48.1377522152041\n            ],\n            [\n              -124.35640085378517,\n              48.1377522152041\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Sarah B. 0000-0003-4463-0074","orcid":"https://orcid.org/0000-0003-4463-0074","contributorId":291768,"corporation":false,"usgs":false,"family":"Dunn","given":"Sarah B.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":866350,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70239930,"text":"sir20225089 - 2023 - Interaction of a legacy groundwater contaminant plume with the Little Wind River from 2015 through 2017, Riverton Processing site, Wyoming","interactions":[],"lastModifiedDate":"2026-02-23T19:20:42.551781","indexId":"sir20225089","displayToPublicDate":"2023-01-26T12:30:05","publicationYear":"2023","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":"2022-5089","displayTitle":"Interaction of a Legacy Groundwater Contaminant Plume with the Little Wind River from 2015 Through 2017, Riverton Processing Site, Wyoming","title":"Interaction of a legacy groundwater contaminant plume with the Little Wind River from 2015 through 2017, Riverton Processing site, Wyoming","docAbstract":"<p>The Riverton Processing site was a uranium mill 4 kilometers southwest of Riverton, Wyoming, that prepared uranium ore for nuclear reactors and weapons from 1958 to 1963. The U.S. Department of Energy completed surface remediation of the uranium tailings in 1989; however, groundwater below and downgradient from the tailings site and nearby Little Wind River was not remediated. Beginning in 2010, a series of floods along the Little Wind River began to mobilize contaminants in the unsaturated zone, resulting in substantial increases of uranium and other contaminants of concern in monitoring wells completed inside the contaminant plume. In 2011, the U.S. Department of Energy started a series of university and Government agency retrospective and field investigations to understand the processes controlling contaminant increases in the groundwater plume. The goals of the field investigations described in this report were to (1) identify and quantify the contaminant flux and potential associated biological effects from groundwater associated with the legacy plume as it enters a perennial stream reach, and (2) assess chemical exposure and potential effects to biological receptors from the interaction of the contaminant plume and the river.</p><p>Field investigations along the Little Wind River were completed by the U.S. Geological Survey during 2015–17 in cooperation with the U.S. Department of Energy Office of Legacy Management to characterize: (1) seepage areas and seepage rates; (2) pore-water and bed sediment chemistry and hyporheic exchange and reactive loss; and (3) exposure pathways and biological receptors. All data collected during the study are contained in two U.S. Geological Survey data releases, available at <a href=\"https://doi.org/10.5066/F7BR8QX4\" data-mce-href=\"https://doi.org/10.5066/F7BR8QX4\">https://doi.org/10.5066/F7BR8QX4</a> and <a href=\"https://doi.org/10.5066/P9J9VJBR\" data-mce-href=\"https://doi.org/10.5066/P9J9VJBR\">https://doi.org/10.5066/P9J9VJBR</a>. A variety of tools and methods were used during the field characterizations. Streambed temperature mapping, electrical resistivity tomography, electromagnetic induction, fiber-optic distributed temperature sensing, tube seepage meters, vertical thermal sensor arrays, and an environmental tracer (radon) were used to identify areas of groundwater seepage and associated seepage rates along specific sections of the study reach of the river. Drive points, minipiezometers, diffusive equilibrium in thin-film/diffusive gradients in thin-film probes, bed-sediment samples, and equal discharge increment sampling methods were used to characterize pore-water chemistry, estimate hyporheic exchange and reactive loss of selected chemical constituents, and quantify contaminant loadings entering the study reach. Sampling and analysis of surface sediments, filamentous algae, periphytic algae, and macroinvertebrates were used to characterize biological exposure pathways, metal uptake, and receptors.</p><p>Areas of focused groundwater discharge identified by the fiber-optic distributed temperature sensing surveys corresponded closely with areas of elevated electrical conductivity identified by the electromagnetic induction survey results in the top 5 meters of sediment. During three monitoring periods in 2016, the mean vertical seepage rate measured with tube seepage meters was 0.45 meter per day, ranging from −0.02 to 1.55 meters per day. Five of the 11 locations where vertical thermal profile data were collected along the study reach during August 2017 indicated mean upwelling values ranging from 0.11 to 0.23 meter per day. Radon data collected from the Little Wind River during June, July, and August 2016 indicated a consistent inflow of groundwater to the central part of the study reach, in the area congruous with the center of the previously mapped groundwater plume discharge zone. During August 2017, the greatest attenuation of uranium from reactive loss in pore-water samples was observed at three locations along the study reach, at depths between 6 and 15 centimeters, and similar trends in molybdenum attenuation were also observed. Bed-sediment concentration profiles collected during 2017 also indicated attenuation of uranium and molybdenum from groundwater during hyporheic mixing of surface water with the legacy plume during groundwater upwelling into the river. Streamflow measurements combined with equal discharge increment water sampling along the study reach indicated an increase in dissolved uranium concentrations in the downstream direction during 2016 and 2017. Net uranium load entering the Little Wind River study reach was about 290 and 435 grams per day during 2016 and 2017, respectively. Biological samples indicated that low levels of uranium and molybdenum exposure were confined to the benthos in the Little Wind River within and immediately downstream from the perimeter of the groundwater plume. Concentrations of molybdenum and uranium in filamentous algae were consistently low at all sites in the study reach with no indication of increased exposure of dissolved bioavailable molybdenum or uranium at sites next to or downstream from the groundwater plume.</p><p>Comparison of the August 2017 results from electromagnetic induction, tube seepage meters, vertical thermal profiling, and pore-water chemistry surveys were in general agreement in identifying areas with upwelling groundwater conditions along the study reach. However, the electroconductivity values measured with electromagnetic induction in the top 100 centimeters of sediment did not agree with sodium concentrations measured in pore-water samples collected at similar streambed depths. Differences and similarities between multiple methods can result in additional insights into hydrologic and biogeochemical processes that may be occurring along a reach of a river system interacting with shallow groundwater inputs. It may be advantageous to apply a variety of geophysical, geochemical, hydrologic, and biological tools at other Uranium Mill Tailings Remedial Action (<a href=\"https://www.energy.gov/sites/prod/files/2014/10/f19/UMTRCA.pdf\" data-mce-href=\"https://www.energy.gov/sites/prod/files/2014/10/f19/UMTRCA.pdf\">https://www.energy.gov/sites/prod/files/2014/10/f19/UMTRCA.pdf</a>) sites during the investigation of legacy contaminant plume interactions with surface-water systems.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/sir20225089","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Naftz, D.L., Fuller, C.C., Runkel, R.L., Solder, J., Gardner, W.P., Terry, N., Briggs, M.A., Short, T.M., Cain, D.J., Dam, W.L., Byrne, P.A., and Campbell, J.R., 2023, Interaction of a legacy groundwater contaminant plume with the Little Wind River from 2015 through 2017, Riverton Processing site, Wyoming: U.S. Geological Survey Scientific Investigations Report 2022–5089, 66 p., https://doi.org/10.3133/sir20225089.","productDescription":"Report: xi, 66 p.; 3 Datasets; 2 Data Releases","numberOfPages":"82","onlineOnly":"Y","ipdsId":"IP-123760","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":412328,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BR8QX4","text":"USGS data release","linkHelpText":"Hydrologic, biogeochemical, and radon data collected within and adjacent to the Little Wind River near Riverton, Wyoming (ver. 1.1, January 2019)"},{"id":412329,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J9VJBR","text":"USGS data release","linkHelpText":"Geophysical data collected within and adjacent to the Little Wind River near Riverton, Wyoming"},{"id":412324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5089/coverthb.jpg"},{"id":412325,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5089/sir20225089.pdf","text":"Report","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5089"},{"id":412330,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://gems.lm.doe.gov/","text":"U.S. Department of Energy Office of Legacy Management Geospatial Environmental Mapping System database","linkHelpText":"—Riverton, WY, Processing site"},{"id":412331,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":412332,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":500452,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114285.htm","linkFileType":{"id":5,"text":"html"}},{"id":412327,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5089/images"},{"id":412326,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5089/sir20225089.XML"}],"country":"United States","state":"Wyoming","city":"Riverton","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -109,\n              43.5\n            ],\n            [\n              -109,\n              42.5\n            ],\n            [\n              -107.5,\n              42.5\n            ],\n            [\n              -107.5,\n              43.5\n            ],\n            [\n              -109,\n              43.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wy-mt-water/\" data-mce-href=\"https://www.usgs.gov/centers/wy-mt-water/\">Wyoming-Montana Water Science Center</a><br>U.S. Geological Survey<br>3162 Bozeman Avenue<br>Helena, MT 59601</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods Used to Determine the Interaction of a Legacy Groundwater Containment Plume</li><li>Riverton Processing Site Study Results and Discussion</li><li>Lessons Learned and Application to Other Sites</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-01-26","noUsgsAuthors":false,"publicationDate":"2023-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solder, John 0000-0002-0660-3326","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":222003,"corporation":false,"usgs":true,"family":"Solder","given":"John","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, W. Payton 0000-0003-0664-001X","orcid":"https://orcid.org/0000-0003-0664-001X","contributorId":206198,"corporation":false,"usgs":false,"family":"Gardner","given":"W.","email":"","middleInitial":"Payton","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":862408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":862413,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":862414,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Short, Terry M. 0000-0001-9941-4593 tmshort@usgs.gov","orcid":"https://orcid.org/0000-0001-9941-4593","contributorId":1718,"corporation":false,"usgs":true,"family":"Short","given":"Terry","email":"tmshort@usgs.gov","middleInitial":"M.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":862415,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":862416,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dam, William L","contributorId":248589,"corporation":false,"usgs":false,"family":"Dam","given":"William L","affiliations":[{"id":49955,"text":"Conserve-Prosper LLC","active":true,"usgs":false}],"preferred":false,"id":862417,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Byrne, Patrick A.","contributorId":247578,"corporation":false,"usgs":false,"family":"Byrne","given":"Patrick","email":"","middleInitial":"A.","affiliations":[{"id":49583,"text":"Liverpool John Moores University","active":true,"usgs":false}],"preferred":false,"id":862418,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Campbell, James R. 0000-0002-2760-3149","orcid":"https://orcid.org/0000-0002-2760-3149","contributorId":50156,"corporation":false,"usgs":true,"family":"Campbell","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":862419,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
]}