{"pageNumber":"325","pageRowStart":"8100","pageSize":"25","recordCount":46619,"records":[{"id":70216334,"text":"70216334 - 2018 - Discontinuities and functional resilience of large river fish assemblages","interactions":[],"lastModifiedDate":"2020-11-12T14:50:43.846922","indexId":"70216334","displayToPublicDate":"2018-07-20T08:43:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Discontinuities and functional resilience of large river fish assemblages","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Functional composition of communities across scales is increasingly used to infer resilience of biotic communities to environmental change. To assess the relevance of these concepts to management of large rivers, analyses were applied to fish community data of the Upper Mississippi River. First, to evaluate whether there was evidence for structural patterns in fish size distributions, a discontinuity analysis was performed. Using long‐term fish data, consistent discontinuities were identified across 14 reaches, suggesting similar structuring processes occur throughout the nearly 1300 river kilometers represented by those reaches. Increased variability in species abundance in relation to proximity to edges of body size aggregations supports the discontinuity hypothesis that body size aggregations are structured by key processes. Functional richness and redundancy were quantified within and across identified scales for each of 14 river reaches. Diversity of trophic and spawning guilds was generally greater in the upstream reaches in comparison with downstream reaches, with the exception of the diversity of large‐bodied spawning guilds. Evidence of functional shifts in the composition of fishes occurred, but differed by size aggregations, likely reflecting scale‐specific resource availability. Redundancy of spawning and trophic groups across body size aggregations suggested downstream reaches of this system may be less resilient to disturbances and were weakly associated with reduced habitat diversity. These findings suggest that discontinuities in large river fish assemblages do occur and may provide indication of shifting resource availability. Further investigation of the underlying processes and scales that support resource availability will be critical to managing for resilience in large river ecosystems.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2351","usgsCitation":"Bouska, K.L., 2018, Discontinuities and functional resilience of large river fish assemblages: Ecological Applications, v. 9, no. 8, e02351, 15 p., https://doi.org/10.1002/ecs2.2351.","productDescription":"e02351, 15 p.","ipdsId":"IP-085142","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468572,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2351","text":"Publisher Index Page"},{"id":437821,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CU2U8Z","text":"USGS data release","linkHelpText":"Habitat diversity and longitudinal connectivity limit the functional diversity and redundancy of fishes in a large river: Data"},{"id":380452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.0869140625,\n              45.82879925192134\n            ],\n            [\n              -94.2626953125,\n              45.36758436884978\n            ],\n            [\n              -92.8564453125,\n              44.5278427984555\n            ],\n            [\n              -92.4169921875,\n              43.96119063892024\n            ],\n            [\n              -91.58203125,\n              43.100982876188546\n            ],\n            [\n              -91.0546875,\n              42.293564192170095\n            ],\n            [\n              -91.318359375,\n              41.672911819602085\n            ],\n            [\n              -92.10937499999999,\n              40.81380923056958\n            ],\n            [\n              -92.10937499999999,\n              40.17887331434696\n            ],\n            [\n              -91.4501953125,\n              39.13006024213511\n            ],\n            [\n              -90.966796875,\n              38.685509760012\n            ],\n            [\n              -90.966796875,\n              38.30718056188316\n            ],\n            [\n              -90.3076171875,\n              37.64903402157866\n            ],\n            [\n              -89.384765625,\n              37.020098201368114\n            ],\n            [\n              -89.20898437499999,\n              36.80928470205937\n            ],\n            [\n              -89.033203125,\n              37.33522435930639\n            ],\n            [\n              -89.912109375,\n              39.13006024213511\n            ],\n            [\n              -91.14257812499999,\n              39.9434364619742\n            ],\n            [\n              -90.65917968749999,\n              41.07935114946899\n            ],\n            [\n              -89.9560546875,\n              42.4234565179383\n            ],\n            [\n              -90.65917968749999,\n              43.644025847699496\n            ],\n            [\n              -91.8896484375,\n              45.120052841530544\n            ],\n            [\n              -94.0869140625,\n              45.82879925192134\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"8","noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":804732,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70198121,"text":"ofr20181114 - 2018 - Findings from a preliminary investigation of the effects of aquatic habitat (water) availability on giant gartersnake (Thamnophis gigas) demography in the Sacramento Valley, California, 2014–17","interactions":[],"lastModifiedDate":"2018-07-23T10:03:35","indexId":"ofr20181114","displayToPublicDate":"2018-07-20T00:00:00","publicationYear":"2018","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":"2018-1114","displayTitle":"Findings from a preliminary investigation of the effects of aquatic habitat (water) availability on giant gartersnake (<i>Thamnophis gigas</i>) demography in the Sacramento Valley, California, 2014–17","title":"Findings from a preliminary investigation of the effects of aquatic habitat (water) availability on giant gartersnake (Thamnophis gigas) demography in the Sacramento Valley, California, 2014–17","docAbstract":"<p>The giant gartersnake (<i>Thamnophis gigas</i>) is a semi-aquatic species of snake precinctive to the Central Valley of California. Because the Central Valley has experienced a substantial loss of wetland habitat, giant gartersnake populations are largely found in aquatic habitats associated with rice agriculture. In dry years, less water may be available for rice agriculture, resulting in less aquatic habitat, which could have cascading effects on giant gartersnake populations. We present 2 years of data intended to examine how the demography of giant gartersnakes is affected by the availability of aquatic habitat on the landscape (2016–17), along with 2 years of (sparse) preliminary data (2014–15) collected as part of an earlier radio-telemetry study on giant gartersnake movement behavior. We sampled agricultural canals near rice fields for giant gartersnakes at 8 sites distributed throughout the Sacramento Valley. Five sites were sampled from 2014–17, and 3 sites were sampled from 2015–17. In total, we made 2,995 captures of 1,011 snakes from 2014–17. We used these capture data to fit a multi-site Jolly-Seber model to estimate the abundance of giant gartersnakes as well as the daily and annual probability of capture at each site. We used remotely sensed Landsat data to characterize the extent of flooded rice fields surrounding each site in each year. In addition, we collected 175 females from 2014–17 and delivered them to the Sacramento Zoo for health assessments and reproductive exams.</p><p>The abundance of giant gartersnakes varied among sites, and abundance estimates were more precise in 2016 and 2017 when sampling effort was greatest. The probability of a giant gartersnake being captured at least once in a year was higher in 2016 and 2017 than 2014 and 2015, and recaptures of snakes marked the previous year were highest in 2016 and 2017 as well. Mean annual apparent survival was estimated to be 0.40 but varied among sites from a low of 0.14 to a high of 0.63. Five sites had diverse size distributions that included abundant sub-adult and large adult female snakes. One site had a truncated size distribution with few large adult female snakes, and 2 sites had mostly large adult-sized snakes and few small individuals. Both the probability a female was gravid and a female’s litter size were positively related to the female’s snout-vent length. Somatic growth rates varied more among years than among sites, and females grew faster (in millimeters per day) than male snakes.</p><p>The proportion of the landscape around each site under active rice cultivation fluctuated over time (generally between 60–90 percent of the landscape was active rice growing, although this proportion was lower for some sites in some years), and variation in rice growing was asynchronous among sites. This study demonstrates that intensive demographic sampling enables estimation of several key demographic variables at each study site. Continued sampling would allow for investigating potential relationships between the amount of rice growing at a site and demographic parameters such as growth, survival, and reproduction.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181114","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Rose, J.P., Ersan, J.S.M., Reyes, G.A., Gustafson, K.B., Fulton, A.M., Fouts, K.J., Wack, R.F., Wylie, G.D., Casazza, M.L., and Halstead, B.J., 2018, Findings from a preliminary investigation of the effects of aquatic habitat (water) availability on giant gartersnake (<i>Thamnophis gigas</i>) demography in the Sacramento Valley, California, 2014–17: U.S. Geological Survey Open-File Report 2018–1114, 48 p., https://doi.org/10.3133/ofr20181114.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-097068","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":355890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1114/coverthb.jpg"},{"id":355891,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1114/ofr20181114.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1114"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.33,\n              38.8333\n            ],\n            [\n              -121.5833,\n              38.8333\n            ],\n            [\n              -121.5833,\n              39.6667\n            ],\n            [\n              -122.33,\n              39.6667\n            ],\n            [\n              -122.33,\n              38.8333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/werc/connect\" target=\"_blank\" data-mce-href=\"https://www.usgs.gov/centers/werc/connect\">Director</a>,<br><a href=\"https://www.werc.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://www.werc.usgs.gov/\">Western Ecological Research Center</a><br><a href=\"https://usgs.gov\" target=\"_blank\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br> 3020 State University Drive East<br> Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Background</li><li>Purpose and Scope</li><li>Study Area</li><li>Goals and Objectives</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary and Conclusions</li><li>References Cited</li><li>Glossary</li><li>Appendix A. Details of Bayesian Models</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2018-07-20","noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","scienceBaseUri":"5b6fc3f5e4b0f5d57878e981","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":105624,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan P.","email":"jprose@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":740697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ersan, Julia S. M. 0000-0002-1549-7561 jersan@usgs.gov","orcid":"https://orcid.org/0000-0002-1549-7561","contributorId":200441,"corporation":false,"usgs":true,"family":"Ersan","given":"Julia","email":"jersan@usgs.gov","middleInitial":"S. M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":740698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reyes, Gabriel A. 0000-0001-9281-5300 greyes@usgs.gov","orcid":"https://orcid.org/0000-0001-9281-5300","contributorId":200440,"corporation":false,"usgs":true,"family":"Reyes","given":"Gabriel A.","email":"greyes@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":740699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gustafson, K. Benjamin 0000-0003-3530-0372 kgustafson@usgs.gov","orcid":"https://orcid.org/0000-0003-3530-0372","contributorId":5568,"corporation":false,"usgs":true,"family":"Gustafson","given":"K.","email":"kgustafson@usgs.gov","middleInitial":"Benjamin","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":740700,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fulton, Alexandria M. 0000-0002-1070-4605 afulton@usgs.gov","orcid":"https://orcid.org/0000-0002-1070-4605","contributorId":200445,"corporation":false,"usgs":true,"family":"Fulton","given":"Alexandria","email":"afulton@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":740701,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fouts, Kristen J. 0000-0003-1325-1709 kfouts@usgs.gov","orcid":"https://orcid.org/0000-0003-1325-1709","contributorId":200444,"corporation":false,"usgs":true,"family":"Fouts","given":"Kristen J.","email":"kfouts@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":740702,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wack, Raymund F.","contributorId":199344,"corporation":false,"usgs":false,"family":"Wack","given":"Raymund","email":"","middleInitial":"F.","affiliations":[{"id":35518,"text":"Sacramento Zoo and UC Davis","active":true,"usgs":false}],"preferred":false,"id":740703,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wylie, Glenn D. 0000-0002-7061-6658 glenn_wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-6658","contributorId":3052,"corporation":false,"usgs":true,"family":"Wylie","given":"Glenn","email":"glenn_wylie@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":740704,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":740705,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":740706,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70197939,"text":"ofr20181103 - 2018 - Quality-assurance plan for groundwater activities, U.S. Geological Survey Dakota Water Science Center","interactions":[],"lastModifiedDate":"2018-07-24T12:53:40","indexId":"ofr20181103","displayToPublicDate":"2018-07-20T00:00:00","publicationYear":"2018","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":"2018-1103","displayTitle":"Quality-assurance plan for groundwater activities, U.S. Geological Survey Dakota Water Science Center","title":"Quality-assurance plan for groundwater activities, U.S. Geological Survey Dakota Water Science Center","docAbstract":"<p>As the Nation’s principal earth-science information agency, the U.S. Geological Survey (USGS) is depended upon to collect accurate data and produce factual and impartial interpretive reports. Methods for data collection and analysis that were developed by the USGS have become standard techniques used by numerous Federal, State, and local agencies and by private enterprises. The USGS has implemented a program designed to ensure that all scientific work done by or for USGS Water Science Centers is done in accordance with a quality-assurance plan. The implementation of a groundwater quality-assurance plan will enhance groundwater data collected by the USGS. This report is a quality-assurance plan for groundwater activities conducted by the USGS Dakota Water Science Center and is meant to complement qualityassurance plans for surface-water and water-quality activities and similar plans for the Dakota Water Science Center and general project activities throughout the USGS.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181103","usgsCitation":"Valder, J.F., Carter, J.M., Robinson, S.M., Laveau, C.D., and Petersen, J.A., 2018, Quality-assurance plan for groundwater activities, U.S. Geological Survey Dakota Water Science Center: U.S. Geological Survey Open-File Report 2018–1103, 28 p., https://doi.org/10.3133/ofr20181103.","productDescription":"v, 28 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-097126","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":355869,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1103/ofr20181103.pdf","text":"Report","size":"1.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1103"},{"id":355868,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1103/coverthb.jpg"}],"contact":"<p><a href=\"mailto: dc_sd@usgs.gov\" data-mce-href=\"mailto: dc_sd@usgs.gov\">Director</a>,&nbsp;<a href=\"https://www.usgs.gov/centers/dakota-water\" data-mce-href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a> <br>U.S. Geological Survey<br>1608 Mountain View Road <br>Rapid City, SD 57702</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Organization and Responsibilities<br></li><li>Studies Project Planning and Reviews<br></li><li>Training<br></li><li>Safety<br></li><li>Basic Data Collection and Data Management Plan<br></li><li>Publications<br></li><li>Archiving<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix 1. Groundwater Technical Memorandums, Groundwater Technical Notes, Water Resources Policies, and the U.S. Geological Survey Survey Manual<br></li><li>Appendix 2. Groundwater Site Inventory (GWSI) Coding Forms<br></li><li>Appendix 3. Documentation of Field Procedures<br></li><li>Appendix 4. Dakota Water Science Center Groundwater Archive Plan<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-07-20","noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","scienceBaseUri":"5b6fc3f6e4b0f5d57878e985","contributors":{"authors":[{"text":"Valder, Joshua F. 0000-0003-3733-8868 jvalder@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":139256,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua","email":"jvalder@usgs.gov","middleInitial":"F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Janet M. 0000-0002-6376-3473","orcid":"https://orcid.org/0000-0002-6376-3473","contributorId":17637,"corporation":false,"usgs":true,"family":"Carter","given":"Janet M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, Steven M.","contributorId":206045,"corporation":false,"usgs":true,"family":"Robinson","given":"Steven M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laveau, Christopher D. 0000-0002-4009-1889","orcid":"https://orcid.org/0000-0002-4009-1889","contributorId":205320,"corporation":false,"usgs":true,"family":"Laveau","given":"Christopher D.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petersen, Joel A. 0000-0003-2560-7119","orcid":"https://orcid.org/0000-0003-2560-7119","contributorId":206047,"corporation":false,"usgs":true,"family":"Petersen","given":"Joel","email":"","middleInitial":"A.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739253,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70198116,"text":"ofr20181113 - 2018 - Coeur d’Alene Basin Environmental Monitoring Program, surface water, northern Idaho—Annual data summary, water year 2017","interactions":[],"lastModifiedDate":"2018-07-23T10:11:28","indexId":"ofr20181113","displayToPublicDate":"2018-07-20T00:00:00","publicationYear":"2018","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":"2018-1113","title":"Coeur d’Alene Basin Environmental Monitoring Program, surface water, northern Idaho—Annual data summary, water year 2017","docAbstract":"<p class=\"p1\">Streams within the Coeur d’Alene River drainage basin in northern Idaho have been extensively affected by historical mining activities and are subject to ongoing remedial actions as part of the Bunker Hill Mining &amp; Metallurgical Complex Superfund Site. The U.S. Geological Survey (USGS) operates 12 real-time streamgages and collects surface-water-quality samples two to four times annually at 20 sites in the Spokane River and Coeur d’Alene River drainage basins. These data are used by the U.S. Environmental Protection Agency (USEPA) to monitor cleanup progress and to support decisions related to implementing remedial actions throughout the basin. USGS data collection highlights from water year 2017 include: • A rain-on-snow event in March 2017 produced high streamflows and flooding in the basin. • The March event mobilized high concentrations of total metals (cadmium, lead, zinc, and others) in the Coeur d’Alene River near Cataldo, at Rose Lake, and near Harrison; these concentrations were among the highest that have been measured at these sites during flood events sampled by the USGS. • Total lead and dissolved zinc and cadmium concentrations decreased in Canyon Creek in 2017 when compared with water years 2007–16; in contrast, concentrations of dissolved zi</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181113","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Zinsser, L.M., 2018, Coeur d’Alene Basin Environmental Monitoring Program, surface water, northern Idaho—Annual data summary, water year 2017: U.S. Geological Survey Open-File Report 2018-1113, 15 p., https://doi.org/10.3133/ofr20181113.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-098458","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":355896,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1113/ofr20181113.pdf","text":"Report","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1113"},{"id":355895,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1113/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Coeur d’Alene Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117,\n              47.25\n            ],\n            [\n              -115.5,\n              47.25\n            ],\n            [\n              -115.5,\n              47.75\n            ],\n            [\n              -117,\n              47.75\n            ],\n            [\n              -117,\n              47.25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"http://id.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://id.water.usgs.gov\">Idaho Water Science Center</a><br> U.S. Geological Survey<br> 230 Collins Road<br> Boise, Idaho 83702</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Surface-Water Data, Water Year 2017<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-07-20","noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","scienceBaseUri":"5b6fc3f6e4b0f5d57878e983","contributors":{"authors":[{"text":"Zinsser, Lauren M. 0000-0002-8582-066X","orcid":"https://orcid.org/0000-0002-8582-066X","contributorId":206486,"corporation":false,"usgs":true,"family":"Zinsser","given":"Lauren M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":740084,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70197289,"text":"sir20185065 - 2018 - Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources","interactions":[],"lastModifiedDate":"2021-07-23T16:32:31.463125","indexId":"sir20185065","displayToPublicDate":"2018-07-20T00:00:00","publicationYear":"2018","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":"2018-5065","title":"Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources","docAbstract":"<p>The California State Water Resources Control Board initiated a regional monitoring program in July 2015 to determine where and to what degree groundwater quality may be adversely impacted by oil and gas development activities. A key issue in the implementation of the regional groundwater monitoring program is that each year, detailed characterization work can be done in only a few of California’s 487 onshore oil and gas fields. The first step in monitoring groundwater near petroleum development is to prioritize oil and gas fields using consistent statewide analysis of available data that indicate potential risk of groundwater to oil and gas development.</p><p>The U.S. Geological Survey compiled data for four factors that characterize the intensity of petroleum resource development and proximity to groundwater resources: petroleum-well density, volume of water injected in oil fields, vertical proximity of groundwater resources to oil and gas resource development, and water-well density. An overall priority ranking for each field was determined by computing summary metrics, analyzing statewide distributions of summary metrics for all oil and gas fields, using those distributions to define relative categories of potential risk for each factor, and combining relative risk rankings for different factors into an overall priority ranking. This preliminary assessment does not represent an evaluation of groundwater risk to oil and gas development, which needs to be based on detailed analysis and data related to development activities including well stimulation, well integrity issues, produced water ponds, and underground injection.</p><p>Based on the prioritization analysis, 22 percent (107 fields) of the total number of oil and gas fields in California were ranked as high priority, 23 percent (114 fields) as moderate priority, and 55 percent (266 fields) as low priority. These results indicate that between 100 and 200 oil fields are principal candidates for the next steps in the regional monitoring program. The land area of fields that ranked high priority accounted for 41 percent of the total field area (3,392 square miles). More than half of the high priority fields were in the southern San Joaquin Valley and the Los Angeles Basin. Some of the larger fields tended to have higher rankings because of greater intensity of petroleum development, sometimes coupled with proximity to groundwater resources.</p><p>The U.S. Geological Survey, in collaboration with the California State Water Resources Control Board and other agencies, has begun regional groundwater monitoring near oil and gas fields selected for study through the California Oil, Gas, and Groundwater cooperative program. Groundwater monitoring includes compiling, analyzing, and developing three-dimensional visualizations of existing data, including geological frameworks, salinity mapping, identification of surface features that could potentially affect groundwater quality, locations and depths of oil/gas and water wells, cataloging well-construction integrity issues, and evaluating the directions of groundwater flow. These analyses are required to determine where existing wells should be monitored and where new monitoring wells may need to be drilled.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185065","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Davis, T.A., Landon, M.K., and Bennett, G.L., 2018, Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources: U.S. Geological Survey Scientific Investigations Report 2018–5065, 115 p.,\nhttps://doi.org/10.3133/sir20185065.","productDescription":"Report: viii, 115 p.; Tables 1-6; Appendix Tables 1-7","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073272","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437823,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2DV3","text":"USGS data release","linkHelpText":"Data analyzed for the preliminary prioritization of California oil and gas fields for regional groundwater monitoring"},{"id":355611,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065_appendixtables_.xlsx","text":"Appendix Tables 1–7","size":"500 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5065"},{"id":355610,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065_tables_.xlsx","text":"Tables 1–6","size":"23 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5065"},{"id":355609,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065.pdf","text":"Report","size":"62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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 \"}}]}","contact":"<div><a href=\"mailto:dc_ca@usgs.gov\" target=\"_blank\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,</div><div><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a></div><div><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a></div><div>6000 J Street, Placer Hall</div><div>Sacramento, California 95819</div>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Results of the Preliminary Assessment of Factors for Prioritization<br></li><li>Results of the Prioritization Analysis<br></li><li>Summary<br></li><li>References Cited<br></li><li>Appendix 1. Statistical Summaries of Data used to Calculate Factors<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2018-07-20","noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","scienceBaseUri":"5b6fc3f6e4b0f5d57878e987","contributors":{"authors":[{"text":"Davis, Tracy 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":176921,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, George L. V V 0000-0002-6239-1604 georbenn@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-1604","contributorId":1373,"corporation":false,"usgs":true,"family":"Bennett","given":"George","suffix":"V","email":"georbenn@usgs.gov","middleInitial":"L. V","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736552,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70198036,"text":"ofr20181107 - 2018 - Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017","interactions":[],"lastModifiedDate":"2023-04-24T21:07:25.110741","indexId":"ofr20181107","displayToPublicDate":"2018-07-19T00:00:00","publicationYear":"2018","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":"2018-1107","title":"Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017","docAbstract":"<p>Trace-metal concentrations in sediment and in the clam <i>Macoma petalum</i> (formerly reported as <i>Macoma balthica</i>), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2017 to December 2017. These append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2017 data within the context of the longer, multi-decadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.</p><p>Significant reductions in silver and copper concentrations in sediment and <i>M. petalum</i> occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements appear to have stabilized at concentrations somewhat above silver (Ag) or near copper (Cu) regional background concentrations. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2017, concentrations of silver and copper in <i>M. petalum</i> varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. This record suggests that legacy contamination and regional-scale factors now largely control sedimentary and bioavailable concentrations of silver and copper, as well as other elements of regulatory interest, at the Palo Alto site.</p><p>Analyses of the benthic community structure of a mudflat in south San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, <i>M. petalum</i>, from the same area. Analysis of <i>M. petalum</i> shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2017), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (<i>Ampelisca abdita</i> and <i>Streblospio benedicti</i>) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2017. <i>Heteromastus filiformis</i> (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. <i>H. filiformis</i> abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2017. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like <i>M. petalum</i>. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or anoxia. The reproductive mode of most species that were present in 2017 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2017 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181107","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Parchaso, F., Pearson, S., Stewart, R., Turner, M., Barasch, D., Slabic, A., and Luoma, S.N., 2018, Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017: U.S. Geological Survey Open-File Report 2018–1107, 71 p., https://doi.org/10.3133/ofr20181107.","productDescription":"vi, 71 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-098497","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":416196,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"-  Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416195,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416197,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416194,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":416193,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"},{"id":355780,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1107/ofr20181107_.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1107"},{"id":355779,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1107/coverthb.jpg"}],"country":"United States","state":"California","city":"Palo Alto","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.27371215820312,\n              37.315567502511044\n            ],\n            [\n              -121.827392578125,\n              37.315567502511044\n            ],\n            [\n              -121.827392578125,\n              37.655557695625056\n            ],\n            [\n              -122.27371215820312,\n              37.655557695625056\n            ],\n            [\n              -122.27371215820312,\n              37.315567502511044\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://water.usgs.gov\" target=\"_blank\" data-mce-href=\"https://water.usgs.gov\">Hydro-Eco Interactions Branch</a><br><a href=\"https://usgs.gov\" target=\"_blank\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>345 Middlefield Road<br>Menlo Park, CA 94025<br></p>","tableOfContents":"<ul><li>Executive Summary of Past Findings</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Summary</li><li>Acknowledgment</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-07-18","noUsgsAuthors":false,"publicationDate":"2018-07-18","publicationStatus":"PW","scienceBaseUri":"5b6fc3f6e4b0f5d57878e98d","contributors":{"authors":[{"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":739732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":739733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parchaso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":150620,"corporation":false,"usgs":true,"family":"Parchaso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":739734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Sarah 0000-0002-0975-5173 spearson@usgs.gov","orcid":"https://orcid.org/0000-0002-0975-5173","contributorId":206185,"corporation":false,"usgs":true,"family":"Pearson","given":"Sarah","email":"spearson@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":739735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, A. Robin 0000-0003-2918-546X arstewar@usgs.gov","orcid":"https://orcid.org/0000-0003-2918-546X","contributorId":1482,"corporation":false,"usgs":true,"family":"Stewart","given":"A.","email":"arstewar@usgs.gov","middleInitial":"Robin","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40553,"text":"WMA - Office of the Chief Operating Officer","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":739736,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turner, Matthew A. 0000-0002-4472-7071","orcid":"https://orcid.org/0000-0002-4472-7071","contributorId":206186,"corporation":false,"usgs":true,"family":"Turner","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739737,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barasch, David","contributorId":199032,"corporation":false,"usgs":true,"family":"Barasch","given":"David","affiliations":[],"preferred":false,"id":740412,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Slabic, Ane","contributorId":206188,"corporation":false,"usgs":false,"family":"Slabic","given":"Ane","email":"","affiliations":[{"id":37275,"text":"none","active":true,"usgs":false}],"preferred":false,"id":740413,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":740414,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70197890,"text":"sir20185067 - 2018 - Geohydrology, geochemistry, and numerical simulation of groundwater flow and land subsidence in the Bicycle Basin, Fort Irwin National Training Center, California","interactions":[],"lastModifiedDate":"2018-07-20T10:09:20","indexId":"sir20185067","displayToPublicDate":"2018-07-19T00:00:00","publicationYear":"2018","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":"2018-5067","title":"Geohydrology, geochemistry, and numerical simulation of groundwater flow and land subsidence in the Bicycle Basin, Fort Irwin National Training Center, California","docAbstract":"<div>Groundwater pumping from Bicycle Groundwater Basin (referred to as Bicycle Basin) in the Fort Irwin National Training Center, California, began in 1967. From 1967 to December 2010, about 46,000 acre-feet of water had been pumped from the basin and transported to the Irwin Basin. During this time, not only did water levels in the basin decline by as much as 100 feet, the quality of the groundwater pumped from the basin also deteriorated in some wells. The U.S. Geological Survey collected geohydrologic data from existing wells, test holes, and 16 additional monitoring wells installed at 6 sites in Bicycle Basin during 1992–2011 to determine the quantity and quality of groundwater available in the basin. Geophysical surveys, including electrical, gravity, and seismic refraction surveys, were completed to help determine the geometry of the structural basin, delineate depths to the interface between Quaternary and Tertiary rocks, map the depth to the water table, and used to develop a geohydrologic framework and groundwater-flow model for Bicycle Basin. Water samples were used to determine the groundwater quality in the basin and to delineate potential sources of poor-quality groundwater. Analysis of stable isotopes of oxygen and hydrogen in groundwater indicated that presentday precipitation is not a major source of recharge to the basin. Tritium and carbon-14 data indicated that most of the groundwater in the basin was recharged prior to 1952 and had an apparent age of 15,625–39,350 years. Natural recharge to the basin was not sufficient to replenish the groundwater pumped from the basin. Interferograms from synthetic aperture radar data (InSAR), analyzed to evaluate land-surface subsidence between 1993 and 2010, showed 0.23 to 1.1 feet of subsidence during this period near one production well north of Bicycle Lake (dry) playa. A groundwater-flow model of Bicycle Basin was developed and calibrated using groundwater levels for 1964– 2010, and a subsidence model using land-surface deformation data for 1993–2010. Between January 1967 and December 2010, the simulated total recharge from precipitation runoff and underflow from adjacent basins was about 5,100 acre-feet and pumpage from the Bicycle Basin was about 47,000 acrefeet of water. Total outflows exceeded natural recharge during this period, resulting in a net loss of about 42,100 acre-feet of groundwater storage in the basin. The Fort Irwin National Training Center is considering various groundwater-management options in the Bicycle Basin. The groundwater-flow model was used to (1) evaluate changes in groundwater levels and subsidence with the addition of capture and recharge of simulated runoff in retention basins (scenario 1) for predevelopment through 2010; (2) simulate a base case (scenario 2) for reference; and (3) compare projections of alternative future pumping strategies for 2011–60 (scenarios 3–5). Model results from the runoff-capture simulation (scenario 1) indicated that total recharge, including runoff captured using retention basins, locally increased water levels, which partially offset, but did not mitigate, groundwater depletion associated with pumping. Groundwater-storage depletion in scenario 1 was about 14 percent less than without runoff capture. Simulated-drawdown results in model layer 1 in the eastern part of the basin indicated that, because of the captured runoff, simulated heads were as much as 100 feet higher in December 2010 than prior to the onset of development in 1967. In contrast, simulated drawdown for model without runoff capture indicated that, without captured runoff, simulated heads for December 2010 in this area were 80–90 feet lower than during the predevelopment period. Subsidence was mitigated slightly in scenario 1 compared to without runoff capture; the largest decrease in subsidence at observation sites was about 0.07 feet.</div><div><br data-mce-bogus=\"1\"></div>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185067","collaboration":"Prepared in cooperation with the Fort Irwin National Training Center","usgsCitation":"Densmore, J.N., Woolfenden L.R., Rewis, D.L., Martin, P.M., Sneed, M., Ellett, K.M., Solt, M., and Miller, D.M., 2018, Geohydrology, geochemistry, and numerical simulation of groundwater flow and land subsidence in the Bicycle Basin, Fort Irwin National Training Center, California: U.S. Geological Survey Scientific Investigations Report 2018–5067, 176 p., https://doi.org/10.3133/sir20185067.","productDescription":"xi, 176 p.","numberOfPages":"192","onlineOnly":"Y","ipdsId":"IP-077955","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355865,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5067/sir20185067.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5067"},{"id":355864,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5067/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bicycle Basin, Fort Irwin National Training Center","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.667,\n              35.2667\n            ],\n            [\n              -116.5667,\n              35.2667\n            ],\n            [\n              -116.5667,\n              35.3333\n            ],\n            [\n              -116.667,\n              35.3333\n            ],\n            [\n              -116.667,\n              35.2667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<div><a href=\"mailto:dc_ca@usgs.gov\" target=\"_blank\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,</div><div><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br data-mce-bogus=\"1\"></div><div><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br data-mce-bogus=\"1\"></div><div>6000 J Street, Placer Hall</div><div>Sacramento, California 95819</div>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Geohydrologic Framework</li><li>Geochemistry of Groundwater</li><li>Groundwater-Flow Model</li><li>Simulated Effects of Runoff Capture and Future Pumpage</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2018-07-19","noUsgsAuthors":false,"publicationDate":"2018-07-19","publicationStatus":"PW","scienceBaseUri":"5b6fc3f6e4b0f5d57878e98f","contributors":{"authors":[{"text":"Densmore, Jill N. 0000-0002-5345-6613 jidensmo@usgs.gov","orcid":"https://orcid.org/0000-0002-5345-6613","contributorId":1474,"corporation":false,"usgs":true,"family":"Densmore","given":"Jill","email":"jidensmo@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":738947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woolfenden, Linda R. 0000-0003-3500-4709 lrwoolfe@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-4709","contributorId":1476,"corporation":false,"usgs":true,"family":"Woolfenden","given":"Linda","email":"lrwoolfe@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rewis, Diane L.","contributorId":205953,"corporation":false,"usgs":false,"family":"Rewis","given":"Diane","email":"","middleInitial":"L.","affiliations":[{"id":37196,"text":"Retired USGS employee","active":true,"usgs":false}],"preferred":false,"id":738949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Peter M.","contributorId":205954,"corporation":false,"usgs":false,"family":"Martin","given":"Peter","email":"","middleInitial":"M.","affiliations":[{"id":37196,"text":"Retired USGS employee","active":true,"usgs":false}],"preferred":false,"id":738950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738951,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellett, Kevin M.","contributorId":205955,"corporation":false,"usgs":false,"family":"Ellett","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":37197,"text":"Indiana Geological and Water Survey, Indiana University","active":true,"usgs":false}],"preferred":false,"id":738952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Solt, Michael msolt@usgs.gov","contributorId":156,"corporation":false,"usgs":true,"family":"Solt","given":"Michael","email":"msolt@usgs.gov","affiliations":[],"preferred":true,"id":740642,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":131040,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":740643,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70197647,"text":"sir20185077 - 2018 - Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","interactions":[],"lastModifiedDate":"2018-07-20T10:23:35","indexId":"sir20185077","displayToPublicDate":"2018-07-18T12:30:00","publicationYear":"2018","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":"2018-5077","displayTitle":"Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","title":"Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","docAbstract":"<p>As the population of the Triangle area in central North Carolina increases, the demand for good quality drinking water from streams and lakes within the upper Neuse and upper Cape Fear River Basins also increases. The Triangle area includes Raleigh, Cary, Research Triangle Park, Durham, Chapel Hill, and the surrounding communities. The U.S. Geological Survey examined temporal trends in water quality for 13 stream and 8 reservoir sites in the two basins on the basis of data collected during 1989–2013. Trends were analyzed using a fitted time-series model that accommodated for shifting trends and variations in streamflow at multiple time scales. Seventeen water-quality properties and constituents were evaluated, including specific conductance and major ions, nutrients, and organic carbon. Suspended solids and suspended sediment were examined at stream sites; chlorophyll <i>a</i> and Secchi transparency were examined at lake sites.</p><p>The investigation identified considerable changes in population, land cover, streamflow, and selected water-quality characteristics in the study area over the 25-year period. Specific conductance and concentrations of calcium, magnesium, potassium, sodium, and chloride tended to increase throughout the study area. Area-wide increases were also observed for organic nitrogen. Trends for other water-quality constituents varied on a more site-specific basis because of local watershed influences such as changes to wastewater-treatment processes and substantial shifts from rural to urban land use. Water quality is influenced by multiple, often confounding factors, and thus may change in a non-uniform manner over time. Long-term monitoring is critical for tracking these trends and ensuring resiliency of water supplies for the future. Results from this study may promote the understanding of water-quality response to a growing population and land-cover changes and can assist water-resource managers in the Triangle area in tracking progress toward water-quality goals.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185077","collaboration":"Prepared in cooperation with the Triangle Area Water Supply Monitoring Project Steering Committee","usgsCitation":"Giorgino, M.J., Cuffney, T.F., Harden, S.L., and Feaster, T.D., 2018, Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013: U.S. Geological Survey Scientific Investigations Report 2018–5077, 67 p., https://doi.org/10.3133/sir20185077.","productDescription":"Report: viii, 67 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095343","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":355697,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5077/coverthb.jpg"},{"id":355698,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5077/sir20185077.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5077"},{"id":355835,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MS3S17","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets for trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989-2013"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Fear River basin, Neuse River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.79919433593749,\n              35.02099970111467\n            ],\n            [\n              -77.84912109375,\n              35.02099970111467\n            ],\n            [\n              -77.84912109375,\n              36.32397712011264\n            ],\n            [\n              -79.79919433593749,\n              36.32397712011264\n            ],\n            [\n              -79.79919433593749,\n              35.02099970111467\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/water/southatlantic/\" data-mce-href=\"https://www.usgs.gov/water/southatlantic/\">South Atlantic Water Science Center</a><br>U.S. Geological Survey<br> 720 Gracern Road<br> Suite 129<br> Columbia, SC 29210</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Area</li><li>Approach</li><li>Water-Quality Trends Related to Watershed Setting and&nbsp;Hydrologic Conditions</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-07-18","noUsgsAuthors":false,"publicationDate":"2018-07-18","publicationStatus":"PW","scienceBaseUri":"5b6fc3f6e4b0f5d57878e991","contributors":{"authors":[{"text":"Giorgino, Mary J. 0000-0001-7152-1856 giorgino@usgs.gov","orcid":"https://orcid.org/0000-0001-7152-1856","contributorId":205646,"corporation":false,"usgs":true,"family":"Giorgino","given":"Mary","email":"giorgino@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":205649,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harden, Stephen L. 0000-0001-6886-0099","orcid":"https://orcid.org/0000-0001-6886-0099","contributorId":205648,"corporation":false,"usgs":true,"family":"Harden","given":"Stephen L.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feaster, Toby D. 0000-0002-5626-5011","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":205647,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby","email":"","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738037,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195046,"text":"sir20185020 - 2018 - Monitoring the water-quality response of agricultural conservation practices in the Bucks Branch watershed, Sussex County, Delaware, 2014–16","interactions":[],"lastModifiedDate":"2018-07-19T10:53:47","indexId":"sir20185020","displayToPublicDate":"2018-07-18T12:00:00","publicationYear":"2018","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":"2018-5020","title":"Monitoring the water-quality response of agricultural conservation practices in the Bucks Branch watershed, Sussex County, Delaware, 2014–16","docAbstract":"<p>The purpose of this study was to evaluate the effects of irrigation and cover crops as conservation practices on water quality in groundwater and streams. Bucks Branch, a stream in the Nanticoke River watershed in southwestern Delaware, was identified as having one of the highest concentrations of nitrate in all surface-water sites sampled by the Delaware Department of Natural Resources and Environmental Control (DNREC). The study site is on two adjacent fields bordering Bucks Branch, one that has used irrigation since 2000 and one with dryland farming; both under conservation tillage and long-term rotation of corn, soybean, and small grain crops. A streamgage was installed near the study site fields to measure streamflow and water quality. The study area is typical of farming practices and environmental conditions throughout much of the intensively farmed agricultural land of the Coastal Plain of Delaware and surrounding parts of Maryland. Monitoring was conducted from January 2014 through June 2016. Corn was grown on both fields during the two growing seasons of the study period, and cover crops were planted before or shortly after harvest on both fields. During the second year of data collection, the effects of radish and rye grass cover crops on nutrient transport were studied.</p><p>The combined results from data collected for this study show that water and nitrate moved below the root zone year round when soil moisture was high, especially after significant rainfall and frequently after irrigation. Soil water sampled 2 to 3 weeks after nutrients were applied had nitrate concentrations greater than 50 milligrams per liter as nitrogen (mg/L as N) and may be a significant source of nitrate to groundwater. Whereas recharge containing elevated nitrate concentrations also occurred under the dryland field, it was less frequent and of lower concentration than recharge under the irrigated field.</p><p>Nitrate was present in all groundwater samples from these sites. Groundwater estimated to have recharged within 10 years or less had higher median concentrations of nitrate than in older water samples. The oldest groundwater encountered was over 30 years old, and had traveled along the longest, deep flowpaths from upland fields to the stream. The median nitrate concentration was 18 mg/L as N in younger water (less than 10 years old) beneath the irrigated field, compared to about 10 mg/L as N in younger water beneath the dryland field. Samples from the shallow upland wells in both study fields showed little, if any, evidence of denitrification. Several samples from deeper wells and from wells near forested riparian zone wetlands that border both fields did show partial denitrification.</p><p>A mixing model estimated that between 12 and 22 percent of the nitrate discharging to the stream was lost through uptake and denitrification upstream of the streamgage on Bucks Branch. Continuous data collected at this site and evidence of denitrification in the surface-water samples showed a greater potential for loss of nitrate during the warmer months than the colder months. This pattern was similar to that seen below the streamgage at the most downstream site in the watershed.</p><p>A mixed cover crop of radishes and rye was planted prior to removal (radishes) and just after harvest (rye) of the corn crop on the irrigated field. Rye grass was planted shortly after crop harvest on the dryland field. Cover crop biomass samples collected while radishes were growing and after they were killed by freezing temperatures indicates that the early planted radish crop effectively scavenged available nitrogen from the soil. Whereas radish biomass initially held more nitrogen than rye, at 55 to 8 pounds per acre, respectively, leaching of inorganic nitrate following radish die-off was minimal. Soil-water nitrate concentrations during the cover-crop growing period were lower than during the growing season prior to planting of the cover crop. There also was an increase in soil fertility and dissolved organic nitrate in samples of soil water that was likely related to increased soil microbial metabolism. Results indicate that cover crops stored plant nutrients over the winter and did not increase shallow groundwater concentrations of nitrate.</p><p>Although conservation practices such as cover crops and nutrient management have been applied to these fields, there was still significant leaching of nitrate to groundwater, especially under the irrigated field. This will likely continue to be a challenge in this area and other parts of the Coastal Plain where soil moisture capacity is relatively low and managing irrigation around rainfall is difficult. Cover crops, when planted in standing corn, are one practice that can effectively pull nitrate from below the root zone to the top layer of soil, thus limiting the amount of potential nitrate leaching to groundwater. Irrigation management that would lower average soil moisture conditions during the growing season also could potentially limit nitrogen transport.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185020","collaboration":"Prepared in cooperation with the Delaware Department of Natural Resources and Environmental Control and the Delaware Geological Survey","usgsCitation":"Denver, J.M., Soroka, A.M., Reyes, B., Lester, T.R., Bringman, D.A., and Brownley, M.S., 2018, Monitoring the water-quality response of agricultural conservation practices in the Bucks Branch watershed, Sussex County, Delaware, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5020, 43 p., https://doi.org/10.3133/sir20185020.","productDescription":"ix, 43 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088518","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":355731,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5020/sir20185020.pdf","text":"Report","size":"8.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5020"},{"id":355732,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77H1HK5","text":"USGS data release","description":"USGS data release","linkHelpText":"Chemistry analysis results for groundwater, soil-pore water, soil and plant material collected from two agricultural sites in the Nanticoke and Chester River watersheds on the Delmarva Peninsula from 2013 to 2016"},{"id":355730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5020/coverthb.jpg"}],"country":"United States","state":"Delaware","county":"Sussex County","otherGeospatial":"Bucks Branch Watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.6833,\n              38.6833\n            ],\n            [\n              -75.6167,\n              38.6833\n            ],\n            [\n              -75.6167,\n              38.7333\n            ],\n            [\n              -75.6833,\n              38.7333\n            ],\n            [\n              -75.6833,\n              38.6833\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_md@usgs.gov\" data-mce-href=\"mailto:dc_md@usgs.gov\">Director</a>, <a href=\"http://md.water.usgs.gov/\" data-mce-href=\"http://md.water.usgs.gov/\">MD-DE-DC Water Science Center</a><br> U.S. Geological Survey<br> 5522 Research Park Drive<br> Baltimore, MD 21228</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Network Design, Sampling, and Analytical Methods</li><li>The Water-Quality Response of Agricultural Conservation Practices at the Bucks Branch Study Site</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2018-07-18","noUsgsAuthors":false,"publicationDate":"2018-07-18","publicationStatus":"PW","scienceBaseUri":"5b6fc3f7e4b0f5d57878e993","contributors":{"authors":[{"text":"Denver, Judith M. 0000-0002-3272-5992 jmdenver@usgs.gov","orcid":"https://orcid.org/0000-0002-3272-5992","contributorId":181567,"corporation":false,"usgs":true,"family":"Denver","given":"Judith","email":"jmdenver@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":726740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soroka, Alexander M. 0000-0002-8002-5229","orcid":"https://orcid.org/0000-0002-8002-5229","contributorId":201664,"corporation":false,"usgs":true,"family":"Soroka","given":"Alexander","email":"","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reyes, Betzaida 0000-0002-1398-0824 breyes@usgs.gov","orcid":"https://orcid.org/0000-0002-1398-0824","contributorId":2250,"corporation":false,"usgs":true,"family":"Reyes","given":"Betzaida","email":"breyes@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lester, Todd R. 0000-0001-7938-6652","orcid":"https://orcid.org/0000-0001-7938-6652","contributorId":201665,"corporation":false,"usgs":true,"family":"Lester","given":"Todd","email":"","middleInitial":"R.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bringman, Deborah A. 0000-0002-7287-9136","orcid":"https://orcid.org/0000-0002-7287-9136","contributorId":27568,"corporation":false,"usgs":true,"family":"Bringman","given":"Deborah","email":"","middleInitial":"A.","affiliations":[{"id":375,"text":"Maryland, Delaware, and the District of Columbia Water Science Center","active":false,"usgs":true}],"preferred":false,"id":740234,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brownley, M.S. 0000-0003-0159-1247 msbrownl@usgs.gov","orcid":"https://orcid.org/0000-0003-0159-1247","contributorId":206369,"corporation":false,"usgs":false,"family":"Brownley","given":"M.S.","email":"msbrownl@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":740235,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70210391,"text":"70210391 - 2018 - Exploring viable geologic interpretations of gravity models using distance-based global sensitivity analysis and kernel methods","interactions":[],"lastModifiedDate":"2020-06-02T12:59:15.958554","indexId":"70210391","displayToPublicDate":"2018-07-18T07:53:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Exploring viable geologic interpretations of gravity models using distance-based global sensitivity analysis and kernel methods","docAbstract":"We have explored ways to integrate alternative geologic interpretations into the modeling of gravity data. These methods are applied to the Vaca Fault east of Fairfield, California, USA, where the structure across the fault is in question, and the Vaca Fault is used as a case study to demonstrate the method. The Vaca Fault is modeled using gravity data collected along a 10 km line perpendicular to the strike of the fault. Of particular interest is how the gravity data might inform on the dip of the Vaca Fault and thickness of the nonmarine section and whether spatial autocorrelation of density internal to the geologic units significantly influences the resulting gravity anomaly. We approach these questions by creating a suite of structural geologic models, which we then populate with geostatistically generated densities and from which the respective synthetic gravity anomalies are calculated. We perform distance-based generalized sensitivity analysis to identify which model inputs most leverage the calculated gravity anomaly. We then use multidimensional scaling to transform the gravity anomalies into a metric space and estimate the posterior probabilities of each structural geologic model using a Bayesian approach. We find that the gravity anomalies are particularly sensitive to zones of autocorrelated density values generated from geostatistical modeling. The structural geologic models most likely to produce gravity anomalies that match the observed data are the moderately dipping normal faults, 45° and 60°, although the probability that the fault dips more steeply, including in a strike slip or reverse fault orientation, is approximately 30%. The probability of a thicker nonmarine unit is 67%, more probable than a thinner nonmarine unit. This suggests that the Vaca Fault dips moderately to the east and truncates a thicker nonmarine unit, but that any further process modeling should include alternatives of the geologic structures.","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/geo2017-0742.1","usgsCitation":"Phelps, G., Scheidt, C., and Caers, J., 2018, Exploring viable geologic interpretations of gravity models using distance-based global sensitivity analysis and kernel methods: Geophysics, v. 5, no. 83, p. G79-G92, https://doi.org/10.1190/geo2017-0742.1.","productDescription":"14 p.","startPage":"G79","endPage":"G92","ipdsId":"IP-089675","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":375240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.98071289062499,\n              36.721273880045004\n            ],\n            [\n              -118.3447265625,\n              36.721273880045004\n            ],\n            [\n              -118.3447265625,\n              39.791654835253425\n            ],\n            [\n              -123.98071289062499,\n              39.791654835253425\n            ],\n            [\n              -123.98071289062499,\n              36.721273880045004\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"5","issue":"83","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phelps, Geoffrey 0000-0003-1958-2736 gphelps@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-2736","contributorId":127489,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey","email":"gphelps@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":790143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scheidt, Celine","contributorId":225060,"corporation":false,"usgs":false,"family":"Scheidt","given":"Celine","email":"","affiliations":[{"id":41031,"text":"Stanford Center for Reservoir Forecasting","active":true,"usgs":false}],"preferred":false,"id":790144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caers, Jef","contributorId":225061,"corporation":false,"usgs":false,"family":"Caers","given":"Jef","email":"","affiliations":[{"id":41032,"text":"Dept of Geological Sciences Stanford University","active":true,"usgs":false}],"preferred":false,"id":790145,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197695,"text":"fs20183036 - 2018 - Idaho water use, 2015","interactions":[],"lastModifiedDate":"2025-03-17T15:57:23.564958","indexId":"fs20183036","displayToPublicDate":"2018-07-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3036","displayTitle":"Idaho Water Use, 2015","title":"Idaho water use, 2015","docAbstract":"<p>The ability to quantify water resources hinges on the understanding of water use by the population. The demand humans place on the water cycle varies across the United States, driven by both need and availability. The U.S. Geological Survey quantifies water use nationally, at the county scale, with estimates of water withdrawals and deliveries, by category of use (for example, irrigation, thermoelectric power, industrial, public supply, including domestic deliveries and self-supply domestic, livestock, mining, and aquaculture) and source (fresh and saline groundwater or surface water) every 5 years. Estimates of water use are an important component of the water budget to help manage water supplies and plan for the future. Understanding water use in Idaho is important not only at the local (county) and State scales, but also at the National level because Idaho ranked third in the Nation for total water use in 2015.</p><p>This fact sheet describes calendar year 2015 freshwater withdrawals by source and by each Idaho county. An associated data release provides the data discussed herein. Freshwater withdrawals totaled 17,737 million gallons per day during 2015. Surface water accounted for 70 percent of total withdrawals for all categories of use, mostly for irrigation of crops and aquaculture production. Withdrawals for mining activities were mostly from surface water, whereas the remaining categories of use—public supply, domestic, industrial, livestock, irrigation of golf courses, and thermoelectric power—relied largely on groundwater withdrawals. Most withdrawals occurred in southern Idaho counties to support irrigated agriculture.&nbsp;&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183036","usgsCitation":"Murray, E.M., 2018, Idaho water use, 2015: U.S. Geological Survey Fact Sheet 2018-3036, 4 p., https://doi.org/10.3133/fs20183036.","productDescription":"Report: 4 p.; Data release","onlineOnly":"Y","ipdsId":"IP-093323","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":355834,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92AXN0O","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water use by source and category in Idaho counties, 2015"},{"id":355822,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3036/fs20183036.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3036"},{"id":355821,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3036/coverthb.jpg"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/id-water\" target=\"blank\" data-mce-href=\"https://www.usgs.gov/centers/id-water\">Idaho Water Science Center</a><br> U.S. Geological Survey<br> 230 Collins Road<br> Boise, Idaho 83702</p>","tableOfContents":"<ul><li>Top Three Water Use<br></li><li>Trends, 1985-2015<br></li><li>Future Needs<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-07-18","noUsgsAuthors":false,"publicationDate":"2018-07-18","publicationStatus":"PW","scienceBaseUri":"5b6fc410e4b0f5d57878e9b9","contributors":{"authors":[{"text":"Murray, Erin M. 0000-0002-5007-3449","orcid":"https://orcid.org/0000-0002-5007-3449","contributorId":206449,"corporation":false,"usgs":true,"family":"Murray","given":"Erin","email":"","middleInitial":"M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":738195,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70198162,"text":"70198162 - 2018 - Towards coordinated regional multi-satellite InSAR volcano observations: Results from the Latin America pilot project","interactions":[],"lastModifiedDate":"2020-09-02T12:58:41.104845","indexId":"70198162","displayToPublicDate":"2018-07-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3841,"text":"Journal of Applied Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Towards coordinated regional multi-satellite InSAR volcano observations: Results from the Latin America pilot project","docAbstract":"Within Latin America, about 319 volcanoes have been active in the Holocene, but 202 of these volcanoes have no seismic, deformation or gas monitoring. Following the 2012 Santorini Report on satellite Earth Observation and Geohazards, the Committee on Earth Observation Satellites (CEOS) developed a 4-year pilot project (2013-2017) to demonstrate how satellite observations can be used to monitor large numbers of volcanoes cost-effectively, particularly in areas with scarce instrumentation and/or difficult access. The pilot aims to improve disaster risk management (DRM) by working directly with the volcano observatories that are governmentally responsible for volcano monitoring as well as with the international space agencies (ESA, CSA, ASI, DLR, JAXA, NASA, CNES). The goal is to make sure that the most useful data are collected at each volcano following the guidelines of the Santorini report that observation frequency is related to volcano activity, and to communicate the results to the local institutions in a timely fashion. Here we highlight how coordinated multi-satellite observations have been used by volcano observatories to monitor volcanoes and respond to crises. Our primary tool is measurements of ground deformation made by Interferometric Synthetic Aperture Radar (InSAR), which have been used in conjunction with other observations to determine the alert level at these volcanoes, served as an independent check on ground sensors, guided the deployment of ground instruments, and aided situational awareness. During this time period, we find 26 volcanoes deforming, including 18 of the 28 volcanoes that erupted - those eruptions without deformation were less than 2 on the VEI scale. Another 7 volcanoes were restless and the volcano observatories requested satellite observations, but no deformation was detected. We describe the lessons learned about the data products and information that are most needed by the volcano observatories in the different countries using information collected by questionnaires. We propose a practical strategy for regional to global satellite volcano monitoring for use by volcano observatories in Latin America and elsewhere to realize the vision of the Santorini report.","language":"English","publisher":"Springer","doi":"10.1186/s13617-018-0074-0","usgsCitation":"Pritchard, M., Biggs, J., Wauthier, C., Sansosti, E., Arnold, D.W., Delgado, F., Ebmeier, S., Henderson, S., Stephens, K., Cooper, C., Wnuk, K., Amelung, F., Aguilar, V.R., Mothes, P., Macedo, O., Lara, L.E., Poland, M.P., and Zoffoli, S., 2018, Towards coordinated regional multi-satellite InSAR volcano observations: Results from the Latin America pilot project: Journal of Applied Volcanology, v. 7, 5, 28 p., https://doi.org/10.1186/s13617-018-0074-0.","productDescription":"5, 28 p.","ipdsId":"IP-089702","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and 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,{"id":70197776,"text":"sir20185080 - 2018 - Simulation of potential groundwater recharge for the glacial aquifer system east of the Rocky Mountains, 1980–2011, using the Soil-Water-Balance Model","interactions":[],"lastModifiedDate":"2018-07-18T14:21:54","indexId":"sir20185080","displayToPublicDate":"2018-07-18T00:00:00","publicationYear":"2018","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":"2018-5080","title":"Simulation of potential groundwater recharge for the glacial aquifer system east of the Rocky Mountains, 1980–2011, using the Soil-Water-Balance Model","docAbstract":"<p>An understanding of the spatial and temporal extent of groundwater recharge is critical for many types of hydrologic assessments involving water quality, contaminant transport, ecosystem health, and sustainable use of groundwater. Annual potential groundwater recharge was simulated at a 1-kilometer resolution with the Soil-Water-Balance (SWB) model for the glacial aquifer system east of the Rocky Mountains, from central Montana east to Maine, for calendar years 1980–2011. The SWB model used high resolution meteorological, land cover, and soil hydrology datasets that are nationally consistent and publicly available. The SWB model computed daily potential groundwater recharge as precipitation in excess of interception, runoff, evapotranspiration, and soil-water storage capacity. Daily potential recharge values within each year of the simulation were summed to produce annual potential recharge rates. Potential recharge as described in this report is water that infiltrates vertically below the plant rooting zone and is assumed to reach the water table.</p><p>The calibrated SWB model in this report is called the glacial SWB model. Model calibration assumed that the area contributing to groundwater discharge equaled the surface watershed. The model was calibrated to stream base flows from 39 watersheds throughout the model domain that had hydrologic conditions appropriate for hydrograph separation. Base flows were calculated from daily streamflow records with the HYSEP local minimum hydrograph separation method The glacial SWB model reproduced the mean annual base-flow calibration targets well; the Nash-Sutcliffe efficiency coefficient was 0.94, and the root mean squared error was 1.28 inches per year.</p><p>The glacial SWB model provides insight into the spatial and temporal variability in potential annual recharge across the glacial aquifer system. About 20 percent of the active model area had an average potential recharge rate of less than 1 inch per year. Total precipitation, total recharge, and recharge as a percentage of precipitation increased from west to east. A substantial amount of the recharge water (39 percent) entering the glacial aquifer system travels through developed (urbanized) and agricultural landscapes, which are known to cause water-quality impairments. Regional climatic events, such as the 1988 to 1989 drought, are apparent in the potential recharge time series. Potential recharge generally increased across the glacial aquifer system between 2001 and 2011.</p><p>A comparison of the potential recharge from the glacial SWB model to previous broad-scale recharge estimates reveals several important considerations for future SWB modeling applications. Shifts in the overall distribution of potential recharge between separate models can be explained by methods used to generate base-flow calibration target datasets. Spatial patterns in potential recharge simulated by SWB models are strongly dependent on the data and assumptions used to assign model cells to hydrologic soil groups. A review of several SWB models used to estimate groundwater recharge (and not surface runoff) revealed that model results are most sensitive to input climatic data, followed by surface runoff (curve number) and root-zone depth parameters.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185080","collaboration":"Prepared as part of the Glacial Aquifer System Groundwater Availability Study, a cooperative effort between the U.S. Department of the Interior’s WaterSMART Initiative and the U.S. Geological Survey’s Water Availability and Use Science Program","usgsCitation":"Trost, J.J., Roth, J.L., Westenbroek, S.M., and Reeves, H.W., 2018, Simulation of potential groundwater recharge for the glacial aquifer system east of the Rocky Mountains, 1980–2011, using the Soil-Water-Balance model: U.S. Geological Survey Scientific Investigations Report 2018–5080, 51 p., 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href=\"mailto: dc_mn@usgs.gov\" data-mce-href=\"mailto: dc_mn@usgs.gov\">Director</a>, <a href=\"https://mn.water.usgs.gov\" data-mce-href=\"https://mn.water.usgs.gov\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>2280 Woodale Drive<br>Mounds View, MN 55112</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Simulation of Potential Groundwater Recharge<br></li><li>Sensitivity Analysis<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix. Model Archive<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-07-18","noUsgsAuthors":false,"publicationDate":"2018-07-18","publicationStatus":"PW","scienceBaseUri":"5b6fc410e4b0f5d57878e9b7","contributors":{"authors":[{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roth, Jason L. 0000-0001-5440-2775","orcid":"https://orcid.org/0000-0001-5440-2775","contributorId":191768,"corporation":false,"usgs":false,"family":"Roth","given":"Jason L.","affiliations":[],"preferred":false,"id":738464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":738466,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198126,"text":"70198126 - 2018 - The Future","interactions":[],"lastModifiedDate":"2020-08-19T20:20:29.321373","indexId":"70198126","displayToPublicDate":"2018-07-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"12","title":"The Future","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"GIS for surface water: Using the National Hydrography Dataset","largerWorkSubtype":{"id":13,"text":"Handbook"},"language":"English","publisher":"ESRI","isbn":"9781589484917","usgsCitation":"Blodgett, D.L., Rea, A.H., and Lieberman, J., 2018, The Future, chap. 12 <i>of</i> GIS for surface water: Using the National Hydrography Dataset, p. 427-448.","productDescription":"22 p.","startPage":"427","endPage":"448","ipdsId":"IP-087143","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination 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,{"id":70198151,"text":"70198151 - 2018 - Assessing the effectiveness of riparian restoration projects using Landsat and precipitation data from the cloud-computing application ClimateEngine.org","interactions":[],"lastModifiedDate":"2018-07-18T09:48:42","indexId":"70198151","displayToPublicDate":"2018-07-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the effectiveness of riparian restoration projects using Landsat and precipitation data from the cloud-computing application ClimateEngine.org","docAbstract":"Riparian vegetation along streams provides a suite of ecosystem services in rangelands and thus is the target of restoration when degraded by over-grazing, erosion, incision, or other disturbances. Assessments of restoration effectiveness depend on defensible monitoring data, which can be both expensive and difficult to collect. We present a method and case study to evaluate the effectiveness of restoration of riparian vegetation using a web-based cloud-computing and visualization tool (ClimateEngine.org) to access and process remote sensing and climate data. Restoration efforts on an Eastern Oregon ranch were assessed by analyzing the riparian areas of four creeks that had in-stream restoration structures constructed between 2008 and 2011. Within each study area, we retrieved spatially and temporally aggregated values of summer (June, July, August) normalized difference vegetation index (NDVI) and total precipitation for each water year (October-September) from 1984 to 2017. We established a pre-restoration (1984–2007) linear regression between total water year precipitation and summer NDVI for each study area, and then compared the post-restoration (2012–2017) data to this pre-restoration relationship. In each study area, the post-restoration NDVI-precipitation relationship was statistically distinct from the pre-restoration relationship, suggesting a change in the fundamental relationship between precipitation and NDVI resulting from stream restoration. We infer that the in-stream structures, which raised the water table in the adjacent riparian areas, provided additional water to the streamside vegetation that was not available before restoration and reduced the dependence of riparian vegetation on precipitation. This approach provides a cost-effective, quantitative method for assessing the effects of stream restoration projects on riparian vegetation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2018.06.024","usgsCitation":"Hausner, M.B., Huntington, J., Nash, C., Morton, C., McEvoy, D.J., Pilliod, D.S., Hegewisch, K.C., Daudert, B., Abatzoglou, J.T., and Grant, G., 2018, Assessing the effectiveness of riparian restoration projects using Landsat and precipitation data from the cloud-computing application ClimateEngine.org: Ecological Engineering, v. 120, p. 432-440, https://doi.org/10.1016/j.ecoleng.2018.06.024.","productDescription":"9 p.","startPage":"432","endPage":"440","ipdsId":"IP-087503","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468582,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2018.06.024","text":"Publisher Index 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,{"id":70198147,"text":"70198147 - 2018 - Landscape-scale wildlife species richness metrics to inform wind and solar energy facility siting: An Arizona case study","interactions":[],"lastModifiedDate":"2018-07-17T15:43:38","indexId":"70198147","displayToPublicDate":"2018-07-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1510,"text":"Energy Policy","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-scale wildlife species richness metrics to inform wind and solar energy facility siting: An Arizona case study","docAbstract":"The juxtaposition of wildlife and wind or solar energy facility infrastructure can present problems for developers, planners, policy makers, and management agencies. Guidance on siting of these renewable energy facilities may help identify potential wildlife-facility conflicts with species of regulatory or economic concern. However, existing spatial guidance usually does not consider all wildlife that might use a potential facility location or corridors for its servicing infrastructure. We illustrate an approach toward assessing potential wildlife-facility conflicts using readily available vertebrate habitat models. The U.S. Geological Survey's Gap Analysis Program (GAP) has developed spatial models of potential habitat for vertebrate species across the entire nation. To illustrate their applicability, we used GAP models to estimate richness of all native, terrestrial vertebrates within Arizona and for those vertebrates grouped by class or by sensitivity to the type of facility infrastructure. We examined the spatial overlap of high species richness of each group with agency-developed guidance used to inform facility-siting decisions and found that GAP-based richness mappings augmented existing guidance. As the GAP vertebrate habitat models are publicly available for the entire USA, use of these data can provide a coarse view of potential wildlife-facility conflicts and inform facility planning early in the process.","language":"English","publisher":"Elsevier","doi":"10.1016/j.enpol.2018.01.052","usgsCitation":"Thomas, K.A., Jarchow, C., Arundel, T.R., Jamwal, P., Borens, A., and Drost, C.A., 2018, Landscape-scale wildlife species richness metrics to inform wind and solar energy facility siting: An Arizona case study: Energy Policy, v. 116, p. 145-152, https://doi.org/10.1016/j.enpol.2018.01.052.","productDescription":"8 p.","startPage":"145","endPage":"152","ipdsId":"IP-087101","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468584,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.enpol.2018.01.052","text":"Publisher Index Page"},{"id":437826,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4V08","text":"USGS data release","linkHelpText":"Landscape-scale wildlife species richness metrics"},{"id":355747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Amanda","contributorId":206372,"corporation":false,"usgs":false,"family":"Borens","given":"Amanda","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":740255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":740256,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70198145,"text":"70198145 - 2018 - Statistical approach to neural network imaging of karst systems in 3D seismic reflection data","interactions":[],"lastModifiedDate":"2018-07-18T09:53:59","indexId":"70198145","displayToPublicDate":"2018-07-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3906,"text":"Interpretation","active":true,"publicationSubtype":{"id":10}},"title":"Statistical approach to neural network imaging of karst systems in 3D seismic reflection data","docAbstract":"The current lack of a robust, standardized technique for geophysical mapping of karst systems can be attributed to both the complexity of the environment and prior technological limitations. Abrupt lateral variations in physical properties that are inherent to karst systems generate significant geophysical noise, challenging conventional seismic signal processing and interpretation. Modern application of neural networks to multi-attribute seismic interpretation now provide a semiautomated method for identifying and leveraging the nonlinear relationships exhibited among seismic attributes. The ambiguity generally associated with designing neural networks for seismic object detection can be reduced via statistical analysis of the extracted attribute data. A data-driven approach to selecting the appropriate set of input seismic attributes, as well as the locations and minimum number of training examples, provides a more objective and computationally efficient method for identifying karst systems using reflection seismology. This statistically optimized neural network technique is thoroughly demonstrated using three-dimensional seismic reflection data collected from the southeastern portion of the Florida carbonate platform. Several dimensionality reduction methods are applied and the resulting karst probability models are evaluated relative to one another based on both quantitative and qualitative criteria. Comparing the preferred model, using quadratic discriminant analysis, to previously available seismic object detection workflows demonstrates the karst-specific nature of the tool. Results suggest that the karst multi-attribute workflow presented is capable of approximating the structural boundaries of karst systems with more accuracy and efficiency than a human counterpart or previously presented seismic interpretation schemes. This objective technique, using solely three-dimensional seismic reflection data, likely represents the most practical approach to mapping karst systems for subsequent hydrogeological modeling.","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/int-2017-0197.1","usgsCitation":"Ebuna, D., Kluesner, J., Cunningham, K.J., and Edwards, J.H., 2018, Statistical approach to neural network imaging of karst systems in 3D seismic reflection data: Interpretation, v. 6, no. 3, p. B15-B35, https://doi.org/10.1190/int-2017-0197.1.","productDescription":"21 p.","startPage":"B15","endPage":"B35","ipdsId":"IP-090061","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":355752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc411e4b0f5d57878e9c1","contributors":{"authors":[{"text":"Ebuna, Daniel","contributorId":201729,"corporation":false,"usgs":true,"family":"Ebuna","given":"Daniel","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":740229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kluesner, Jared W. 0000-0003-1701-8832","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":206367,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":740228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cunningham, Kevin J. 0000-0002-2179-8686 kcunning@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-8686","contributorId":1689,"corporation":false,"usgs":true,"family":"Cunningham","given":"Kevin","email":"kcunning@usgs.gov","middleInitial":"J.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":740230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, Joel H.","contributorId":202599,"corporation":false,"usgs":false,"family":"Edwards","given":"Joel","email":"","middleInitial":"H.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":740231,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198118,"text":"70198118 - 2018 - Soil water dynamics at 15 locations distributed across a desert landscape: insights from a 27‐yr dataset","interactions":[],"lastModifiedDate":"2018-07-17T10:04:44","indexId":"70198118","displayToPublicDate":"2018-07-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Soil water dynamics at 15 locations distributed across a desert landscape: insights from a 27‐yr dataset","docAbstract":"<p><span>Desert ecosystems are primarily limited by water availability. Within a climatic regime, topography, soil characteristics, and vegetation are expected to determine how the combined effects of precipitation, temperature, and evaporative demand of the atmosphere shape the spatial and temporal patterns of water within the soil profile and across a landscape. To forecast how desert landscapes may respond to future climatic conditions, it is imperative to improve our understanding of these ecohydrologic processes. Here, we report on 27&nbsp;yr of monthly soil volumetric water content (VWC) measurements and associated soils data from a site in the northern Chihuahuan Desert of North America. The dataset includes VWC and soil properties measured to 3&nbsp;m in depth across 15 locations that encompass a range of Chihuahuan Desert vegetation types. We use this unique dataset (1) to generate insights into general temporal and depth patterns in VWC, (2) to analyze how VWC corresponds to measures of climatic conditions, and (3) to qualitatively evaluate the relative importance of soils, topographic setting, and vegetation type in mediating temporal patterns in VWC. Analyses of this unique dataset emphasize the importance of soil and topographic setting in determining depth and temporal patterns in VWC across time. Results emphasize the episodic nature of deep wetting events in our study system—essentially limited to three large events over the 27‐yr record driven primarily by wetter than normal winters. Comparison of soil water dynamics between mesquite shrub coppice dunes and interspace soils suggests the “island of fertility” concept does not extend to soil water. Median VWC was strongly coupled to climatic conditions over surprisingly long windows at most locations (6–18&nbsp;months), suggesting that soil water at depth is decoupled from short climatic pulses. However, VWC dynamics and VWC–climate relationships varied among locations, depths, and seasons, with unexpected similarities in ecohydrologic dynamics observed among very different vegetation types (e.g., an eroded creosote shrubland and a playa grassland). These results further underscore the importance of ecohydrological investigations in these ecosystems, given forecasts for a warmer and more variable climate in deserts globally.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2335","usgsCitation":"Duniway, M.C., Petrie, M., Peters, D., Anderson, J.P., Crossland, K., and Herrick, J.E., 2018, Soil water dynamics at 15 locations distributed across a desert landscape: insights from a 27‐yr dataset: Ecosphere, v. 9, no. 7, p. 1-36, https://doi.org/10.1002/ecs2.2335.","productDescription":"e02335; 36 p.","startPage":"1","endPage":"36","ipdsId":"IP-091071","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2335","text":"Publisher Index Page"},{"id":355722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-10","publicationStatus":"PW","scienceBaseUri":"5b6fc411e4b0f5d57878e9c5","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":740092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petrie, Matthew D.","contributorId":206328,"corporation":false,"usgs":false,"family":"Petrie","given":"Matthew D.","affiliations":[{"id":37312,"text":"Department of Plant & Environmental Sciences, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":740097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Debra P. C.","contributorId":36903,"corporation":false,"usgs":false,"family":"Peters","given":"Debra P. C.","affiliations":[{"id":25579,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM 88003","active":true,"usgs":false}],"preferred":false,"id":740096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, John P.","contributorId":206326,"corporation":false,"usgs":false,"family":"Anderson","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":37311,"text":"Jornada Experimental Range Department, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":740094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crossland, Keith","contributorId":206327,"corporation":false,"usgs":false,"family":"Crossland","given":"Keith","email":"","affiliations":[{"id":17659,"text":"Natural Resources Conservation Service","active":true,"usgs":false}],"preferred":false,"id":740095,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herrick, Jeffrey E.","contributorId":26054,"corporation":false,"usgs":false,"family":"Herrick","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":12627,"text":"USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, NM 88003-8003, USA","active":true,"usgs":false}],"preferred":false,"id":740093,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70210222,"text":"70210222 - 2018 - Effects of land use on summer thermal regimes in critical salmonid habitats of the Pacific Northwest","interactions":[],"lastModifiedDate":"2020-05-21T14:16:29.700544","indexId":"70210222","displayToPublicDate":"2018-07-16T09:06:03","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Effects of land use on summer thermal regimes in critical salmonid habitats of the Pacific Northwest","docAbstract":"The effect of climate change on stream temperature regimes is of significant concern to natural resource managers focused on protecting cold-water-dependent species. Nevertheless, understanding of how human land-use activities may act to exacerbate the effects of climate change on stream temperature regimes is limited. Using extensive stream temperature data with high-resolution climate and habitat data, we quantified how land management activities are related to summer stream temperatures across the Pacific Northwest, USA. We then described the distribution of land management practices influencing summer thermal regimes relative to the distribution of salmonid fish species of conservation concern. After accounting for climatic and geophysical variation, we detected a strong relationship between livestock grazing and summer thermal regimes. Maximum, average, and diel variation in water temperature was greater where livestock grazing was present. Livestock grazing was widespread, occurring in 43%–100% of sites supporting salmonid species of conservation concern. Thus, current land management practices may be intensifying the effects of ongoing climate change in freshwater habitats, acting to further threaten cold-water fishes of conservation concern.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0165","usgsCitation":"Kovach, R., Muhlfeld, C.C., Al-Chokhachy, R., Ojala, J.V., and Archer, E., 2018, Effects of land use on summer thermal regimes in critical salmonid habitats of the Pacific Northwest: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 5, p. 753-761, https://doi.org/10.1139/cjfas-2018-0165.","productDescription":"9 p.","startPage":"753","endPage":"761","ipdsId":"IP-093115","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":374983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington, Oregon, Idaho, Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.92578125,\n              41.77131167976407\n            ],\n            [\n              -111.26953125,\n              41.77131167976407\n            ],\n            [\n              -111.26953125,\n              49.095452162534826\n            ],\n            [\n              -123.92578125,\n              49.095452162534826\n            ],\n            [\n              -123.92578125,\n              41.77131167976407\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"76","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kovach, Ryan 0000-0001-5402-2123 rkovach@usgs.gov","orcid":"https://orcid.org/0000-0001-5402-2123","contributorId":145914,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":216140,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ojala, Jeffrey V.","contributorId":224816,"corporation":false,"usgs":false,"family":"Ojala","given":"Jeffrey","email":"","middleInitial":"V.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":789621,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Archer, Eric","contributorId":167603,"corporation":false,"usgs":false,"family":"Archer","given":"Eric","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":789622,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70197877,"text":"sir20185084 - 2018 - Water budget of the upper Chehalis River Basin, southwestern Washington","interactions":[],"lastModifiedDate":"2018-07-17T10:32:26","indexId":"sir20185084","displayToPublicDate":"2018-07-16T00:00:00","publicationYear":"2018","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":"2018-5084","title":"Water budget of the upper Chehalis River Basin, southwestern Washington","docAbstract":"<p>Groundwater and surface water collectively supply the domestic, agricultural, and industrial needs of the 895-square mile upper Chehalis River Basin upstream of Grand Mound, Washington, while providing streamflow for fish and other aquatic species in the Chehalis River and its tributaries. To support sustainable water management decision-making, a water budget (including precipitation, interception, groundwater recharge, surface runoff, and groundwater pumping) was developed for the upper Chehalis River Basin during October 2001–September 2015. Water-budget components were estimated from the U.S. Geological Survey Soil-Water-Balance (SWB) model except for groundwater pumping, which was estimated from public water purveyor records, annual system data from the Washington State Department of Health, census population data, and water-use estimates. Groundwater recharge estimated from the SWB model was compared to base flow, a proxy for groundwater recharge, independently estimated from separation of the hydrograph recorded by the U.S. Geological Survey streamgage at the outlet of the basin. Mean annual precipitation for the basin was estimated at 72.6 inches, of which 35 percent was lost to evapotranspiration, 30 percent was recharged to groundwater, 30 percent was surface runoff, and 5 percent was lost to interception. SWB model estimates of groundwater recharge were 17 percent less than estimates of base flow from hydrograph separation. Groundwater pumpage in the basin was estimated at 1 percent of groundwater recharge estimated by SWB and 0.8 percent of base flow estimated by hydrograph separation. These estimates form a baseline for understanding future changes to components of water use and may be used to inform numerical groundwater models to support sustainable management of water resources in the upper Chehalis River Basin.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185084","collaboration":"Prepared in cooperation with the City of Centrailia","usgsCitation":"Gendaszek, A.S., and Welch, W.B., 2018, Water budget of the upper Chehalis River Basin, southwestern Washington: U.S. Geological Survey Scientific Investigations Report 2018-5084, 17 p., https://doi.org/10.3133/sir20185084.","productDescription":"v, 17 p.","onlineOnly":"Y","ipdsId":"IP-096130","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":437827,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8K1F","text":"USGS data release","linkHelpText":"Soil Water Balance Model of Upper Chehalis River Basin, Southwestern Washington"},{"id":355593,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5084/coverthb.jpg"},{"id":355594,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5084/sir20185084.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5084"}],"country":"United States","state":"Washington","otherGeospatial":"Chehalis River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.1667,\n              46.8333\n            ],\n            [\n              -122.3333,\n              46.8333\n            ],\n            [\n              -122.3333,\n              46.3333\n            ],\n            [\n              -123.1667,\n              46.3333\n            ],\n            [\n              -123.1667,\n              46.8333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_wa@usgs.gov\" data-mce-href=\"mailto:dc_wa@usgs.gov\">Director</a>, <a href=\"https://wa.water.usgs.gov\" target=\"blank\" data-mce-href=\"https://wa.water.usgs.gov\">Washington Water Science Center</a><br> U.S. Geological Survey<br> 934 Broadway, Suite 300<br> Tacoma, Washington 98402</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Purpose and Scope<br></li><li>Description of Study Area<br></li><li>Water Budget<br></li><li>Methods<br></li><li>Water Budget Results<br></li><li>Discussion<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-07-16","noUsgsAuthors":false,"publicationDate":"2018-07-16","publicationStatus":"PW","scienceBaseUri":"5b6fc415e4b0f5d57878e9cf","contributors":{"authors":[{"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":738895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welch, Wendy B. 0000-0003-2724-0808 wwelch@usgs.gov","orcid":"https://orcid.org/0000-0003-2724-0808","contributorId":140515,"corporation":false,"usgs":true,"family":"Welch","given":"Wendy","email":"wwelch@usgs.gov","middleInitial":"B.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":738896,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198105,"text":"70198105 - 2018 - Value of sample information in dynamic, structurally uncertain resource systems","interactions":[],"lastModifiedDate":"2018-07-16T11:02:00","indexId":"70198105","displayToPublicDate":"2018-07-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Value of sample information in dynamic, structurally uncertain resource systems","docAbstract":"Few if any natural resource systems are completely understood and fully observed. Instead, there almost always is uncertainty about the way a system works and its status at any given time, which can limit effective management. A natural approach to uncertainty is to allocate time and effort to the collection of additional data, on the reasonable assumption that more information will facilitate better understanding and lead to better management. But the collection of more data, either through observation or investigation, requires time and effort that often can be put to other conservation activities. An important question is whether the use of limited resources to improve understanding is justified by the resulting potential for improved management. In this paper we address directly a change in value from new information collected through investigation. We frame the value of information in terms of learning through the management process itself, as well as learning through investigations that are external to the management process but add to our base of understanding. We provide a conceptual framework and metrics for this issue, and illustrate them with examples involving Florida scrub-jays (Aphelocoma coerulescens).","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0199326","usgsCitation":"Williams, B.K., and Johnson, F.A., 2018, Value of sample information in dynamic, structurally uncertain resource systems: PLoS ONE, v. 13, no. 6, e0199326; 16 p., https://doi.org/10.1371/journal.pone.0199326.","productDescription":"e0199326; 16 p.","ipdsId":"IP-093487","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468589,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0199326","text":"Publisher Index Page"},{"id":355688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-29","publicationStatus":"PW","scienceBaseUri":"5b6fc413e4b0f5d57878e9c9","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":740038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":740037,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198100,"text":"70198100 - 2018 - Using earthquakes, T waves, and infrasound to investigate the eruption of Bogoslof Volcano, Alaska","interactions":[],"lastModifiedDate":"2018-08-30T14:56:06","indexId":"70198100","displayToPublicDate":"2018-07-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using earthquakes, <i>T</i> waves, and infrasound to investigate the eruption of Bogoslof Volcano, Alaska","title":"Using earthquakes, T waves, and infrasound to investigate the eruption of Bogoslof Volcano, Alaska","docAbstract":"<p><span>The 2016‐2017 eruption of Bogoslof volcano, a submarine stratovolcano in the Bering Sea, produced 70 discrete explosive eruptions over 8 months. With no local monitoring data, activity was seismically recorded on nearby islands 50‐100 km away, limiting the detection and resolution of seismic observations. We construct a matched filter catalog of 3199 events from 49 earthquake families, many of which occurred with hydroacoustic</span><i>T</i><span><span>&nbsp;</span>waves of varying strength. We then use a 2D finite difference model to show that hydroacoustic amplitudes should decrease with increased source depth beneath the edifice and leverage each family's seismically recorded<span>&nbsp;</span></span><i>T</i><span><span>&nbsp;</span>wave amplitude as a proxy for source depth, which we compare to regional infrasound data. This unique combination of using<span>&nbsp;</span></span><i>P</i><span><span>&nbsp;</span>and<span>&nbsp;</span></span><i>S</i><span><span>&nbsp;</span>waves to detect events,<span>&nbsp;</span></span><i>T</i><span><span>&nbsp;</span>waves as a proxy for depth, and infrasound for precise timing of emissions allows us to interpret the dynamics and evolution of the Bogoslof eruption.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL078457","usgsCitation":"Wech, A., Tepp, G., Lyons, J.J., and Haney, M.M., 2018, Using earthquakes, T waves, and infrasound to investigate the eruption of Bogoslof Volcano, Alaska: Geophysical Research Letters, v. 45, no. 14, p. 6918-6925, https://doi.org/10.1029/2018GL078457.","productDescription":"8 p.","startPage":"6918","endPage":"6925","ipdsId":"IP-097523","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":355679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -168.06129455566406,\n              53.92021282471509\n            ],\n            [\n              -168.01769256591797,\n              53.92021282471509\n            ],\n            [\n              -168.01769256591797,\n              53.95335826795407\n            ],\n            [\n              -168.06129455566406,\n              53.95335826795407\n            ],\n            [\n              -168.06129455566406,\n              53.92021282471509\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"45","issue":"14","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","scienceBaseUri":"5b6fc415e4b0f5d57878e9d1","contributors":{"authors":[{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":740022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tepp, Gabrielle 0000-0001-5388-5138","orcid":"https://orcid.org/0000-0001-5388-5138","contributorId":206305,"corporation":false,"usgs":true,"family":"Tepp","given":"Gabrielle","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":740023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":740024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":740025,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70197045,"text":"ofr20181084 - 2018 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2016","interactions":[],"lastModifiedDate":"2018-07-14T10:03:26","indexId":"ofr20181084","displayToPublicDate":"2018-07-13T14:00:00","publicationYear":"2018","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":"2018-1084","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2016","docAbstract":"<p>As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir watershed, the U.S. Geological Survey in cooperation with the Providence Water Supply Board collected streamflow and water-quality data at the Scituate Reservoir and tributaries. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance were used to calculate loads of chloride and sodium during water year (WY) 2016 (October 1, 2015, through September 30, 2016) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected by the Providence Water Supply Board at 34 sampling stations that also include 14 continuous-record streamgages maintained by the U.S. Geological Survey during WY 2016 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2016.</p><p>The largest tributary to the reservoir, the Ponaganset River, which was monitored by the U.S. Geological Survey, contributed a mean streamflow of 18 cubic feet per second to the reservoir during WY 2016. For the same period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.27 to about 12 cubic feet per second. Together, tributaries equipped with instrumentation capable of continuously monitoring specific conductance transported about 2,100,000 kilograms of chloride and 1,300,000 kilograms of sodium to the Scituate Reservoir during WY 2016; chloride and sodium yields for the tributaries ranged from 14,000 to 95,000 kilograms per square mile and from 8,600 to 56,000 kilograms per square mile, respectively.</p><p>At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were 27.9 milligrams per liter for chloride, 0.002 milligram per liter as nitrogen for nitrite, 0.13 milligrams per liter as nitrogen for nitrate, 0.07 milligram per liter as phosphate for orthophosphate, and 700 and 10 colony forming units per 100 milliliters for total coliform bacteria and <i>Escherichia coli</i> (<i>E. coli</i>), respectively. The medians of the median daily loads of chloride, nitrite nitrogen, nitrate nitrogen, orthophosphate, and total coliform and <i>E. coli</i> bacteria were 170 kilograms per day, 8.9 grams per day, 570 grams per day, 320 grams per day, 41,000 million colony forming units per day, and 680 million colony forming units per day. The medians of the median yields of chloride, nitrite nitrogen, nitrate nitrogen, orthophosphate, total coliform, and <i>E. coli</i> bacteria were 53 kilograms per day per square mile, 4.7 grams per day per square mile, 130 grams per day per square mile, 165 grams per day per square mile, 23,000 million colony forming units per day per square mile, and 340 million colony forming units per day per square mile, respectively.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181084","collaboration":"Prepared in cooperation with the Providence Water Supply Board ","usgsCitation":"Smith, K.P., 2018, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2016: U.S. Geological Survey Open-File Report 2018–1084, 23 p., https://doi.org/10.3133/ofr20181084.","productDescription":"v, 32 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088041","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":355643,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1084/ofr201810841.pdf","text":"Report","size":"3.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1084"},{"id":355642,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1084/coverthb22.jpg"},{"id":355644,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z60NC5","text":"USGS data release","description":"USGS data release","linkHelpText":"Water quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2016"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.79290771484375,\n              41.73237975329554\n            ],\n            [\n              -71.54296874999999,\n              41.73237975329554\n            ],\n            [\n              -71.54296874999999,\n              41.97786911170172\n            ],\n            [\n              -71.79290771484375,\n              41.97786911170172\n            ],\n            [\n              -71.79290771484375,\n              41.73237975329554\n            ]\n          ]\n        ]\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=\"http://newengland.water.usgs.gov\" data-mce-href=\"http://newengland.water.usgs.gov\">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>Streamflow Data Collection and Estimation</li><li>Water-Quality Data Collection and Analysis</li><li>Estimating Daily, Monthly, and Annual Loads and Yields</li><li>Streamflow</li><li>Water Quality and Constituent Loads and Yields</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2018-07-13","noUsgsAuthors":false,"publicationDate":"2018-07-13","publicationStatus":"PW","scienceBaseUri":"5b6fc416e4b0f5d57878e9d3","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":735362,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70226629,"text":"70226629 - 2018 - Accurate predictions of microscale oxygen barometry in basaltic glasses using V K-edge X-ray absorption spectroscopy: A multivariate approach","interactions":[],"lastModifiedDate":"2021-12-01T12:43:42.425767","indexId":"70226629","displayToPublicDate":"2018-07-13T06:39:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Accurate predictions of microscale oxygen barometry in basaltic glasses using V K-edge X-ray absorption spectroscopy: A multivariate approach","docAbstract":"<p>Because magmatic oxygen fugacity (<i>f</i><sub>O2</sub>) exerts a primary control on the discrete vanadium (V) valence states that will exist in quenched melts, V valence proxies for<span>&nbsp;</span><i>f</i><sub>O2</sub>, measured using X-ray absorption near-edge spectroscopy (XANES), can provide highly sensitive measurements of the redox conditions in basaltic melts. However, published calibrations for basaltic glasses primarily relate measured intensities of specific spectral features to V valence or oxygen fugacity. These models have not exploited information contained within the entire XANES spectrum, which also provide a measure of changes in V chemical state as a function of<span>&nbsp;</span><i>f</i><sub>O2</sub>. Multivariate analysis (MVA) holds significant promise for the development of calibration models that employ the full XANES spectral range. In this study, new calibration models are developed using MVA partial least-squares (PLS) regression and least absolute shrinkage and selection operator (Lasso) regression to predict the<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>of equilibration in glasses of basaltic composition directly. The models are then tested on a suite of natural glasses from mid-ocean ridge basalts and from Kilauea. The models relate the measured XANES spectral features directly to buffer-relative<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>as the predicted variable, avoiding the need for an external measure of the V valence in the experimental glasses used to train the models. It is also shown that by predicting buffer-relative<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>directly, these models also minimize temperature-relative uncertainties in the calibration. The calibration developed using the Lasso regression model, using a Lasso hyperparameter value of α = 0.0008, yields nickel-nickel oxide (NNO) relative<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>predictions with a root-mean-square-error of ±0.33 log units. When applied to natural basaltic glasses, the V MVA calibration model generally yields predicted NNO-relative<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>values that are within the analytical uncertainty of what is calculated using Fe XANES to predict Fe<sup>3+</sup>/ΣFe. When applied to samples of natural basaltic glass collected in 2014 from an active lava flow at Kilauea, a mean<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>of NNO-1.15 ± 0.19 (1σ) is calculated, which is generally consistent with other published<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>estimates for subaerial Kilauea lavas. When applied to a sample of pillow-rim basaltic glass dredged from the East Pacific Rise, calculated<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>varies from NNO-2.67 (±0.33) to NNO-3.72 (±0.33) with distance from the quenched pillow rim. Fe oxybarometry in this sample provides an<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>of NNO-2.54 ± 0.19 (1σ), which is in good agreement with that provided by the V oxybarometry within the uncertainties of the modeling. However, the data may indicate that V XANES oxybarometry has greater sensitivity to small changes in<span>&nbsp;</span><i>f</i><sub>O2</sub><span>&nbsp;</span>at these more reduced redox conditions than can be detected using Fe XANES.</p>","language":"English","publisher":"De Gruyter","doi":"10.2138/am-2018-6319","usgsCitation":"Lanzirotti, A., Dyar, M., Sutton, S., Newville, M., Head, E., Carey, C., McCanta, M., Lee, R.L., King, P., and Jones, J., 2018, Accurate predictions of microscale oxygen barometry in basaltic glasses using V K-edge X-ray absorption spectroscopy: A multivariate approach: American Mineralogist, v. 103, no. 8, https://doi.org/10.2138/am-2018-6319.","ipdsId":"IP-091620","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":392289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.4174041748047,\n              19.188623199306065\n            ],\n            [\n              -155.05760192871094,\n              19.188623199306065\n            ],\n            [\n              -155.05760192871094,\n              19.484718252643226\n            ],\n            [\n              -155.4174041748047,\n              19.484718252643226\n            ],\n            [\n              -155.4174041748047,\n              19.188623199306065\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"103","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lanzirotti, Antonio 0000-0002-7597-5924","orcid":"https://orcid.org/0000-0002-7597-5924","contributorId":223780,"corporation":false,"usgs":false,"family":"Lanzirotti","given":"Antonio","email":"","affiliations":[{"id":36705,"text":"University of Chicago","active":true,"usgs":false}],"preferred":false,"id":827539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyar, M. Darby","contributorId":269611,"corporation":false,"usgs":false,"family":"Dyar","given":"M. Darby","affiliations":[{"id":56007,"text":"Department of Astronomy, Mount Holyoke College, South Hadley, MA 01075, USA","active":true,"usgs":false}],"preferred":false,"id":827540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutton, Steve","contributorId":269612,"corporation":false,"usgs":false,"family":"Sutton","given":"Steve","email":"","affiliations":[{"id":56009,"text":"Center for Advanced Radiation Sources, The University of Chicago, Argonne, IL 60439, USA","active":true,"usgs":false}],"preferred":false,"id":827541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newville, Matthew","contributorId":269613,"corporation":false,"usgs":false,"family":"Newville","given":"Matthew","affiliations":[{"id":56009,"text":"Center for Advanced Radiation Sources, The University of Chicago, Argonne, IL 60439, USA","active":true,"usgs":false}],"preferred":false,"id":827542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Head, Elisabet","contributorId":269614,"corporation":false,"usgs":false,"family":"Head","given":"Elisabet","affiliations":[{"id":56010,"text":"Department of Earth Science, Northeastern Illinois University, Chicago, IL 60625, USA","active":true,"usgs":false}],"preferred":false,"id":827543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carey, CJ","contributorId":269615,"corporation":false,"usgs":false,"family":"Carey","given":"CJ","email":"","affiliations":[{"id":56011,"text":"College of Information and Computer Sciences, University of Massachusetts, Amherst, MA 01003, USA","active":true,"usgs":false}],"preferred":false,"id":827544,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCanta, Molly","contributorId":269616,"corporation":false,"usgs":false,"family":"McCanta","given":"Molly","affiliations":[{"id":56012,"text":"Department of Earth and Planetary Sciences, University of Tennessee, Knoxville, TN 37996, USA","active":true,"usgs":false}],"preferred":false,"id":827545,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lee, R. Lopaka 0000-0002-6352-0340","orcid":"https://orcid.org/0000-0002-6352-0340","contributorId":223777,"corporation":false,"usgs":true,"family":"Lee","given":"R.","email":"","middleInitial":"Lopaka","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":827546,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"King, Penelope L.","contributorId":269617,"corporation":false,"usgs":false,"family":"King","given":"Penelope L.","affiliations":[{"id":56013,"text":"Research School of Earth Sciences, Australian National University, Canberra, ACT 2601, Australia","active":true,"usgs":false}],"preferred":false,"id":827547,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, John","contributorId":269618,"corporation":false,"usgs":false,"family":"Jones","given":"John","affiliations":[{"id":56014,"text":"National Aeronautics and Space Administration/Johnson Space Center, Houston, TX 77058, USA","active":true,"usgs":false}],"preferred":false,"id":827548,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70198093,"text":"70198093 - 2018 - Icebergs in the Nordic Seas throughout the Late Pliocene","interactions":[],"lastModifiedDate":"2018-07-16T10:46:19","indexId":"70198093","displayToPublicDate":"2018-07-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3002,"text":"Paleoceanography","active":true,"publicationSubtype":{"id":10}},"title":"Icebergs in the Nordic Seas throughout the Late Pliocene","docAbstract":"The Arctic cryosphere is changing and making a significant contribution to sea level rise. The Late Pliocene had similar CO2 levels to the present and a warming comparable to model predictions for the end of this century. However, the state of the Arctic cryosphere during the Pliocene remains poorly constrained. For the first time we combine outputs from a climate model with a thermodynamic iceberg model to simulate likely source regions for ice‐rafted debris (IRD) found in the Nordic Seas from Marine Isotope Stage M2 to the mid‐Piacenzian Warm Period and what this implies about the nature of the Arctic cryosphere at this time. We compare the fraction of melt given by the model scenarios with IRD data from four Ocean Drilling Program sites in the Nordic Seas. Sites 911A, 909C, and 907A show a persistent occurrence of IRD that model results suggest is consistent with permanent ice on Svalbard. Our results indicate that icebergs sourced from the east coast of Greenland do not reach the Nordic Seas sites during the warm Late Pliocene but instead travel south into the North Atlantic. In conclusion, we suggest a continuous occurrence of marine‐terminating glaciers on Svalbard and on East Greenland (due to the elevation of the East Greenland Mountains during the Late Pliocene). The study has highlighted the usefulness of coupled climate model‐iceberg trajectory modeling for understanding ice sheet behavior when proximal geological records for Pliocene ice presence or absence are absent or are inconclusive.","language":"English","publisher":"AGU","doi":"10.1002/2017PA003240","usgsCitation":"Smith, Y.M., Hill, D., Dolan, A.M., Haywood, A.M., Dowsett, H.J., and Risebrobakken, B., 2018, Icebergs in the Nordic Seas throughout the Late Pliocene: Paleoceanography, v. 33, no. 3, p. 318-335, https://doi.org/10.1002/2017PA003240.","productDescription":"18 p.","startPage":"318","endPage":"335","ipdsId":"IP-091705","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":468590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017pa003240","text":"Publisher Index Page"},{"id":355676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-30","publicationStatus":"PW","scienceBaseUri":"5b6fc416e4b0f5d57878e9d5","contributors":{"authors":[{"text":"Smith, Yvonne M.","contributorId":206285,"corporation":false,"usgs":false,"family":"Smith","given":"Yvonne","email":"","middleInitial":"M.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":739980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Daniel","contributorId":206286,"corporation":false,"usgs":false,"family":"Hill","given":"Daniel","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":739981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dolan, Aisling M","contributorId":206287,"corporation":false,"usgs":false,"family":"Dolan","given":"Aisling","email":"","middleInitial":"M","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":739982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haywood, Alan M","contributorId":206288,"corporation":false,"usgs":false,"family":"Haywood","given":"Alan","email":"","middleInitial":"M","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":739983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":739979,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Risebrobakken, Bjorg","contributorId":206289,"corporation":false,"usgs":false,"family":"Risebrobakken","given":"Bjorg","email":"","affiliations":[{"id":37301,"text":"Bjerknes Centre for Climate Research, University of Norway","active":true,"usgs":false}],"preferred":false,"id":739984,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
]}