{"pageNumber":"583","pageRowStart":"14550","pageSize":"25","recordCount":40783,"records":[{"id":70127794,"text":"70127794 - 2014 - Decomposition","interactions":[],"lastModifiedDate":"2017-12-15T14:45:36","indexId":"70127794","displayToPublicDate":"2014-09-29T09:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"title":"Decomposition","docAbstract":"A cornerstone of ecosystem ecology, decomposition was recognized as a fundamental process driving the exchange of energy in ecosystems by early ecologists such as Lindeman 1942 and Odum 1960). In the history of ecology, studies of decomposition were incorporated into the International Biological Program in the 1960s to compare the nature of organic matter breakdown in various ecosystem types. Such studies still have an important role in ecological studies of today. More recent refinements have brought debates on the relative role microbes, invertebrates and environment in the breakdown and release of carbon into the atmosphere, as well as how nutrient cycling, production and other ecosystem processes regulated by decomposition may shift with climate change. Therefore, this bibliography examines the primary literature related to organic matter breakdown, but it also explores topics in which decomposition plays a key supporting role including vegetation composition, latitudinal gradients, altered ecosystems, anthropogenic impacts, carbon storage, and climate change models. Knowledge of these topics is relevant to both the study of ecosystem ecology as well projections of future conditions for human societies.","largerWorkTitle":"Oxford Bibliographies","language":"English","publisher":"Oxford University Press","doi":"10.1093/OBO/9780199830060-0123","usgsCitation":"Middleton, B.A., 2014, Decomposition, HTML Document, https://doi.org/10.1093/OBO/9780199830060-0123.","productDescription":"HTML Document","ipdsId":"IP-053799","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":294893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542fba9ae4b092f17df61cf5","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":502542,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70161902,"text":"70161902 - 2014 - Global assessment of human losses due to earthquakes","interactions":[],"lastModifiedDate":"2017-04-24T09:42:26","indexId":"70161902","displayToPublicDate":"2014-09-29T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Global assessment of human losses due to earthquakes","docAbstract":"<p>Current studies have demonstrated a sharp increase in human losses due to earthquakes. These alarming levels of casualties suggest the need for large-scale investment in seismic risk mitigation, which, in turn, requires an adequate understanding of the extent of the losses, and location of the most affected regions. Recent developments in global and uniform datasets such as instrumental and historical earthquake catalogues, population spatial distribution and country-based vulnerability functions, have opened an unprecedented possibility for a reliable assessment of earthquake consequences at a global scale. In this study, a uniform probabilistic seismic hazard assessment (PSHA) model was employed to derive a set of global seismic hazard curves, using the open-source software OpenQuake for seismic hazard and risk analysis. These results were combined with a collection of empirical fatality vulnerability functions and a population dataset to calculate average annual human losses at the country level. The results from this study highlight the regions/countries in the world with a higher seismic risk, and thus where risk reduction measures should be prioritized.</p>","conferenceTitle":"Second European Conference on Earthquake Engineering","conferenceDate":"August 25-29, 2014","conferenceLocation":"Istanbul, Turkey","language":"English","usgsCitation":"Silva, V., Jaiswal, K.S., Weatherill, G., and Crowley, H., 2014, Global assessment of human losses due to earthquakes, Second European Conference on Earthquake Engineering, Istanbul, Turkey, August 25-29, 2014, 10 p.","productDescription":"10 p.","ipdsId":"IP-055949","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":340143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Earth","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0ea6e4b006455f2d61ee","contributors":{"authors":[{"text":"Silva, Vitor","contributorId":152129,"corporation":false,"usgs":false,"family":"Silva","given":"Vitor","email":"","affiliations":[{"id":18873,"text":"University of Aveiro","active":true,"usgs":false}],"preferred":false,"id":588079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":588078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weatherill, Graeme","contributorId":152130,"corporation":false,"usgs":false,"family":"Weatherill","given":"Graeme","email":"","affiliations":[{"id":18874,"text":"EUCENTRE","active":true,"usgs":false}],"preferred":false,"id":588080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crowley, Helen","contributorId":152131,"corporation":false,"usgs":false,"family":"Crowley","given":"Helen","email":"","affiliations":[{"id":18874,"text":"EUCENTRE","active":true,"usgs":false}],"preferred":false,"id":588081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70127155,"text":"70127155 - 2014 - Assessing the value of the Central Everglades Planning Project (CEPP) in Everglades restoration: an ecosystem service approach","interactions":[],"lastModifiedDate":"2014-10-02T09:58:44","indexId":"70127155","displayToPublicDate":"2014-09-26T09:33:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1453,"text":"Ecological Economics","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the value of the Central Everglades Planning Project (CEPP) in Everglades restoration: an ecosystem service approach","docAbstract":"This study identifies a full range of ecosystem services that could be affected by a restoration project in the central Everglades and monetizes the economic value of a subset of these services using existing data. Findings suggest that the project will potentially increase many ecosystem services that have considerable economic value to society. The ecosystem services monetized within the scope of this study are a subset of the difference between the future-with the Central Everglades Planning Project (CEPP) and the future-without CEPP, and they totaled ~ $1.8 billion USD at a 2.5% discount rate. Findings suggest that the use of ecosystem services in project planning and communications may require acknowledgment of the difficulty of monetizing important services and the limitations associated with using only existing data and models. Results of this study highlight the need for additional valuation efforts in this region, focused on those services that are likely to be impacted by restoration activities but were notably challenging to value in this assessment due to shortages of data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Economics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolecon.2014.09.011","usgsCitation":"Richardson, L.A., Keefe, K., Huber, C.C., Racevskis, L., Gregg, R., Thourot, S., and Miller, I., 2014, Assessing the value of the Central Everglades Planning Project (CEPP) in Everglades restoration: an ecosystem service approach: Ecological Economics, v. 107, p. 366-377, https://doi.org/10.1016/j.ecolecon.2014.09.011.","productDescription":"12 p.","startPage":"366","endPage":"377","numberOfPages":"12","ipdsId":"IP-054468","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":294571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294565,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolecon.2014.09.011"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.3932,25.8427 ], [ -81.3932,25.8735 ], [ -81.3792,25.8735 ], [ -81.3792,25.8427 ], [ -81.3932,25.8427 ] ] ] } } ] }","volume":"107","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54267207e4b0bb3382a4762c","contributors":{"authors":[{"text":"Richardson, Leslie A. lrichardson@usgs.gov","contributorId":4810,"corporation":false,"usgs":true,"family":"Richardson","given":"Leslie","email":"lrichardson@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":502301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keefe, Kelly","contributorId":94989,"corporation":false,"usgs":true,"family":"Keefe","given":"Kelly","email":"","affiliations":[],"preferred":false,"id":502307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huber, Christopher C. chuber@usgs.gov","contributorId":5491,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":502302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Racevskis, Laila","contributorId":12386,"corporation":false,"usgs":true,"family":"Racevskis","given":"Laila","email":"","affiliations":[],"preferred":false,"id":502303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gregg, Reynolds","contributorId":48888,"corporation":false,"usgs":true,"family":"Gregg","given":"Reynolds","email":"","affiliations":[],"preferred":false,"id":502305,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thourot, Scott","contributorId":18289,"corporation":false,"usgs":true,"family":"Thourot","given":"Scott","email":"","affiliations":[],"preferred":false,"id":502304,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Ian","contributorId":66573,"corporation":false,"usgs":true,"family":"Miller","given":"Ian","affiliations":[],"preferred":false,"id":502306,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70120910,"text":"sir20145157 - 2014 - Estimated monthly streamflows for selected locations on the Kabul and Logar Rivers, Aynak copper, cobalt, and chromium area of interest, Afghanistan, 1951-2010","interactions":[],"lastModifiedDate":"2017-10-12T20:10:22","indexId":"sir20145157","displayToPublicDate":"2014-09-25T11:31:00","publicationYear":"2014","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":"2014-5157","title":"Estimated monthly streamflows for selected locations on the Kabul and Logar Rivers, Aynak copper, cobalt, and chromium area of interest, Afghanistan, 1951-2010","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, used the stochastic monthly water-balance model and existing climate data to estimate monthly streamflows for 1951–2010 for selected streamgaging stations located within the Aynak copper, cobalt, and chromium area of interest in Afghanistan. The model used physically based, nondeterministic methods to estimate the monthly volumetric water-balance components of a watershed. A comparison of estimated and recorded monthly streamflows for the streamgaging stations Kabul River at Maidan and Kabul River at Tangi-Saidan indicated that the stochastic water-balance model was able to provide satisfactory estimates of monthly streamflows for high-flow months and low-flow months even though withdrawals for irrigation likely occurred. A comparison of estimated and recorded monthly streamflows for the streamgaging stations Logar River at Shekhabad and Logar River at Sangi-Naweshta also indicated that the stochastic water-balance model was able to provide reasonable estimates of monthly streamflows for the high-flow months; however, for the upstream streamgaging station, the model overestimated monthly streamflows during periods when summer irrigation withdrawals likely occurred. Results from the stochastic water-balance model indicate that the model should be able to produce satisfactory estimates of monthly streamflows for locations along the Kabul and Logar Rivers. This information could be used by Afghanistan authorities to make decisions about surface-water resources for the Aynak copper, cobalt, and chromium area of interest.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145157","collaboration":"In cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations","usgsCitation":"Vining, K.C., and Vecchia, A.V., 2014, Estimated monthly streamflows for selected locations on the Kabul and Logar Rivers, Aynak copper, cobalt, and chromium area of interest, Afghanistan, 1951-2010: U.S. Geological Survey Scientific Investigations Report 2014-5157, iv, 12 p., https://doi.org/10.3133/sir20145157.","productDescription":"iv, 12 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-053116","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":294503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145157.jpg"},{"id":294502,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5157/pdf/sir2014-5157.pdf"},{"id":294501,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5157/"}],"projection":"Mercator Auxillary Sphere projection","country":"Afghanistan","otherGeospatial":"Kabul River;Logar River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 65.00,30.00 ], [ 65.00,35.00 ], [ 70.00,35.00 ], [ 70.00,30.00 ], [ 65.00,30.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54252089e4b0e641df8a6d95","contributors":{"authors":[{"text":"Vining, Kevin C. 0000-0001-5738-3872 kcvining@usgs.gov","orcid":"https://orcid.org/0000-0001-5738-3872","contributorId":308,"corporation":false,"usgs":true,"family":"Vining","given":"Kevin","email":"kcvining@usgs.gov","middleInitial":"C.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":498599,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70122945,"text":"ofr20141183 - 2014 - User's manual for the upper Delaware River riverine environmental flow decision support system (REFDSS), Version 1.1.2","interactions":[],"lastModifiedDate":"2014-09-25T09:30:55","indexId":"ofr20141183","displayToPublicDate":"2014-09-25T09:22:00","publicationYear":"2014","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":"2014-1183","title":"User's manual for the upper Delaware River riverine environmental flow decision support system (REFDSS), Version 1.1.2","docAbstract":"<p>Between 2002 and 2006, the Fort Collins Science Center (FORT) at the U.S. Geological Survey (USGS) conducted field surveys, organized workshops, and performed analysis of habitat for trout and shad in the Upper Delaware River Basin. This work culminated in the development of decision support system software (the Delaware River DSS–DRDSS, Bovee and others, 2007) that works in conjunction with the Delaware River Basin Commission’s reservoir operations model, OASIS, to facilitate comparison of the habitat and water-delivery effects of alternative operating scenarios for the Basin. This original DRDSS application was developed in Microsoft Excel and is available to all interested parties through the FORT web site (<a href=\"http://www.fort.usgs.gov/Products/Software/DRDSS/\">http://www.fort.usgs.gov/Products/Software/DRDSS/</a>).</p>\n<br>\n<p>Initial user feedback on the original Excel-based DSS highlighted the need for a more user-friendly and powerful interface to effectively deliver the complex data and analyses encapsulated in the DSS. In order to meet this need, the USGS FORT and Northern Appalachian Research Branch (NARB) developed an entirely new graphical user interface (GUI) application. Support for this research was through the DOI WaterSmart program (<a href=\"http://www.doi.gov/watersmart/html/index.php\">http://www.doi.gov/watersmart/html/index.php</a>) of which the USGS component is the National Water Census (<a href=\"http://water.usgs.gov/watercensus/WaterSMART.html\">http://water.usgs.gov/watercensus/WaterSMART.html</a>). The content and methodology of the new GUI interface emulates those of the original DSS with a few exceptions listed below. Refer to Bovee and others (2007) for the original information. Significant alterations to the original DSS include:</p>\n<br>\n<p>• We moved from Excel-based data storage and processing to a more powerful database back end powered by SQLite. The most notable effect of this is that the previous maximum temporal extent of 10 years has been replaced by a dynamic extent that can now cover the entire period of record for which we have data (1928–2000).</p> \n<p>• We incorporated interactive geographic information system (GIS) visualization and dynamic data processing. Previous habitat maps were generated outside of the DSS in an ad hoc process that the end user could not update or investigate.</p> \n<p>• The original bathymetric data collected in 2005 at the three main stem reaches was augmented with a higher resolution dataset collected in 2010. This new dataset was collected in order to conduct higher resolution (finer pixel size) two-dimensional (2D) hydrodynamic modeling for evaluating dwarf wedgemussel (DWM, <i>Alasmidonta heterodon</i>) habitat.</p> \n<p>• Results charts are now substantially more interactive, dynamic, and accessible, which allows users to more easily focus on their particular topics of interest as well as drill down to the source data used to calculate given results.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141183","usgsCitation":"Talbert, C., Maloney, K.O., Holmquist-Johnson, C., and Hanson, L., 2014, User's manual for the upper Delaware River riverine environmental flow decision support system (REFDSS), Version 1.1.2: U.S. Geological Survey Open-File Report 2014-1183, iv, 23 p., https://doi.org/10.3133/ofr20141183.","productDescription":"iv, 23 p.","numberOfPages":"27","onlineOnly":"Y","ipdsId":"IP-052908","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":294459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141183.jpg"},{"id":294458,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1183/pdf/ofr2014-1183.pdf"},{"id":294457,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1183/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54252090e4b0e641df8a6dd3","contributors":{"authors":[{"text":"Talbert, Colin talbertc@usgs.gov","contributorId":4668,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":499778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":499777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmquist-Johnson, Chris","contributorId":27803,"corporation":false,"usgs":true,"family":"Holmquist-Johnson","given":"Chris","email":"","affiliations":[],"preferred":false,"id":499779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Leanne hansonl@usgs.gov","contributorId":3231,"corporation":false,"usgs":true,"family":"Hanson","given":"Leanne","email":"hansonl@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":499776,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70125642,"text":"sir20145184 - 2014 - Withdrawal and consumption of water by thermoelectric power plants in the United States, 2010","interactions":[],"lastModifiedDate":"2016-04-27T13:12:32","indexId":"sir20145184","displayToPublicDate":"2014-09-24T14:20:00","publicationYear":"2014","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":"2014-5184","title":"Withdrawal and consumption of water by thermoelectric power plants in the United States, 2010","docAbstract":"<p>Estimates of water use at thermoelectric plants were developed by the U.S. Geological Survey based on linked heat and water budgets, and complement reported thermoelectric water withdrawals and consumption. The heat- and water-budget models produced withdrawal and consumption estimates, including thermodynamically plausible ranges of minimum and maximum withdrawal and consumption, for 1,290 water-using plants in the United States for 2010. Total estimated withdrawal for 2010 was about 129 billion gallons per day (Bgal/d), and total estimated consumption was about 3.5 Bgal/d. In contrast, total withdrawal reported by the U.S. Department of Energy, Energy Information Administration (EIA), was about 24 percent higher than the modeled estimates, and total EIA-reported consumption was about 8 percent lower. Most thermoelectric generation in 2010 was not associated with thermodynamically plausible EIA-reported values of both withdrawal and consumption.</p>\n<p>&nbsp;</p>\n<p>An analysis of 2005 and 2010 EIA-reported water use indicated that withdrawal and consumption declined 18 percent and 34 percent, respectively. Alternative water types (types other than freshwater) accounted for approximately 25 percent of all withdrawals in 2010, most of which occurred at plants with once-through cooling systems using saline and brackish tidal waters. Differences among withdrawal and consumption coefficients based on EIA-reported water use for 2005 and 2010 and heat-budget model results for 2010 reveal opportunities for improving consistency and accuracy of reporting of water-use information at the plant scale.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145184","collaboration":"A product of the USGS National Water Census and the USGS National Streamflow Information Program","usgsCitation":"Diehl, T.H., and Harris, M.A., 2014, Withdrawal and consumption of water by thermoelectric power plants in the United States, 2010 (First posted September 24, 2014; Revised and reposted November 10, 2014, version 1.1): U.S. Geological Survey Scientific Investigations Report 2014-5184, Report: vi, 28 p.; Appendix, https://doi.org/10.3133/sir20145184.","productDescription":"Report: vi, 28 p.; Appendix","numberOfPages":"38","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057676","costCenters":[],"links":[{"id":294436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145184.jpg"},{"id":294435,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5184/"},{"id":294433,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5184/pdf/sir20145184.pdf"},{"id":294434,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5184/downloads/sir20145184_Appendix_1_UPDATED_20141107.xlsx"}],"country":"United 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mharris@usgs.gov","orcid":"https://orcid.org/0000-0003-2659-9763","contributorId":1903,"corporation":false,"usgs":true,"family":"Harris","given":"Melissa","email":"mharris@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70175228,"text":"70175228 - 2014 - Predicting foundation bunchgrass species abundances: Model-assisted decision-making in protected-area sagebrush steppe","interactions":[],"lastModifiedDate":"2016-08-03T08:57:14","indexId":"70175228","displayToPublicDate":"2014-09-24T10:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Predicting foundation bunchgrass species abundances: Model-assisted decision-making in protected-area sagebrush steppe","docAbstract":"<p><span>Foundation species are structurally dominant members of ecological communities that can stabilize ecological processes and influence resilience to disturbance and resistance to invasion. Being common, they are often overlooked for conservation but are increasingly threatened from land use change, biological invasions, and over-exploitation. The pattern of foundation species abundances over space and time may be used to guide decision-making, particularly in protected areas for which they are iconic. We used ordinal logistic regression to identify the important environmental influences on the abundance patterns of bluebunch wheatgrass (</span><i>Pseudoroegneria spicata</i><span>), Thurber's needlegrass (</span><i>Achnatherum thurberianum</i><span>), and Sandberg bluegrass (</span><i>Poa secunda</i><span>) in protected-area sagebrush steppe. We then predicted bunchgrass abundances along gradients of topography, disturbance, and invasive annual grass abundance. We used model predictions to prioritize the landscape for implementation of a management and restoration decision-support tool. Models were fit to categorical estimates of grass cover obtained from an extensive ground-based monitoring dataset. We found that remnant stands of abundant wheatgrass and bluegrass were associated with steep north-facing slopes in higher and more remote portions of the landscape outside of recently burned areas where invasive annual grasses were less abundant. These areas represented only 25% of the landscape and were prioritized for protection efforts. Needlegrass was associated with south-facing slopes, but in low abundance and in association with invasive cheatgrass (</span><i>Bromus tectorum</i><span>). Abundances of all three species were strongly negatively correlated with occurrence of another invasive annual grass, medusahead (</span><i>Taeniatherum caput-medusae</i><span>). The rarity of priority bunchgrass stands underscored the extent of degradation and the need for prioritization. We found no evidence that insularity reduced invasibility; annual grass invasion represents a serious threat to protected-area bunchgrass communities. Our study area was entirely within the Wyoming big sagebrush ecological zone, understood to have inherently low resilience to disturbance and resistance to weed invasion. However, our study revealed important variation in abundance of the foundation species associated with resilience and resistance along the topographic-soil moisture gradient within this zone, providing an important foothold for conservation decision-making in these steppe ecosystems. We found the foundation species focus a parsimonious strategy linking monitoring to decision-making via biogeographic modeling.</span></p>","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/ES14-00169.1","usgsCitation":"Rodhouse, T., Irvine, K.M., Sheley, R.L., Smith, B.S., Hoh, S., Esposito, D.M., and Mata-Gonzalez, R., 2014, Predicting foundation bunchgrass species abundances: Model-assisted decision-making in protected-area sagebrush steppe: Ecosphere, v. 5, no. 9, p. 1-19, https://doi.org/10.1890/ES14-00169.1.","startPage":"1","endPage":"19","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051059","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es14-00169.1","text":"Publisher Index Page"},{"id":326006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-24","publicationStatus":"PW","scienceBaseUri":"57a315cce4b006cb45558b43","contributors":{"authors":[{"text":"Rodhouse, Thomas J.","contributorId":127378,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas J.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":644426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheley, Roger L.","contributorId":167296,"corporation":false,"usgs":false,"family":"Sheley","given":"Roger","email":"","middleInitial":"L.","affiliations":[{"id":24676,"text":"USDA-ARS, Burns Oregon","active":true,"usgs":false}],"preferred":false,"id":644427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Brenda S.","contributorId":173370,"corporation":false,"usgs":false,"family":"Smith","given":"Brenda","email":"","middleInitial":"S.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":644428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoh, Shirley","contributorId":173371,"corporation":false,"usgs":false,"family":"Hoh","given":"Shirley","email":"","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":644429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Esposito, Daniel M.","contributorId":173372,"corporation":false,"usgs":false,"family":"Esposito","given":"Daniel","email":"","middleInitial":"M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":644430,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mata-Gonzalez, Ricardo","contributorId":173373,"corporation":false,"usgs":false,"family":"Mata-Gonzalez","given":"Ricardo","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":644431,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70169034,"text":"70169034 - 2014 - The effects of hydropattern and predator communities on amphibian occupancy","interactions":[],"lastModifiedDate":"2016-03-11T13:52:22","indexId":"70169034","displayToPublicDate":"2014-09-23T14:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"The effects of hydropattern and predator communities on amphibian occupancy","docAbstract":"<p><span>Complex, interactive ecological constraints regulate species distributions, and understanding these factors is crucial for predicting species persistence. We used occupancy analysis, which corrects for imperfect detection, to test the importance of abiotic and biotic habitat and landscape factors on probability of occupancy by Boreal Chorus Frog (</span><i>Pseudacris maculata</i><span>&nbsp;(Agassiz, 1850)) tadpoles. We hypothesized that hydropattern and predators are primarily important because they affect desiccation and predation risk and can interact in ways difficult to predict. We surveyed 62 wetland sites across an elevational gradient in Colorado, USA, and modeled patterns in&nbsp;</span><i>P.</i><i>&nbsp;maculata</i><span>&nbsp;occupancy. Tadpoles were most frequently present in intermediate-length hydropattern systems with lower desiccation risk and no predatory fish because of occasional drying.&nbsp;</span><i>Pseudacris maculata</i><span>&nbsp;occupancy had a strong negative relationship with fish presence, while tadpoles, odonate larvae, and Barred Tiger Salamanders (</span><i>Ambystoma mavortium mavortium</i><span>&nbsp;Baird, 1850) frequently co-occurred. Dry seasonal conditions will likely result in fewer intermediate-length hydropattern ponds available for amphibian breeding. We hypothesize that this will force&nbsp;</span><i>P.</i><i>&nbsp;maculata</i><span>&nbsp;to breed in habitats with fish. As habitats shrink, predators that co-occur with&nbsp;</span><i>P.</i><i>&nbsp;maculata</i><span>&nbsp;are expected to concentrate in the remaining habitat and increase predation risk for developing tadpoles (assuming predators are similarly constricted in their habitat use as amphibians are).</span></p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Zoology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Research Council","publisherLocation":"Ottawa","doi":"10.1139/cjz-2014-0106","collaboration":"S.A. Amburgey; L.L. Bailey; M. Murphy; E. Muths; W.C. Funk","usgsCitation":"Amburgey, S., Bailey, L., Murphy, M., Muths, E.L., and Funk, W., 2014, The effects of hydropattern and predator communities on amphibian occupancy: Canadian Journal of Zoology, v. 92, no. 11, p. 927-937, https://doi.org/10.1139/cjz-2014-0106.","productDescription":"11 p.","startPage":"927","endPage":"937","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064686","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":318826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70115627,"text":"70115627 - 2014 - Acute sensitivity of white sturgeon (<i>Acipenser transmontanus</i>) and rainbow trout (<i>Oncorhynchus mykiss</i>) to copper, cadmium, or zinc in water-only laboratory exposures","interactions":[],"lastModifiedDate":"2016-10-17T10:36:44","indexId":"70115627","displayToPublicDate":"2014-09-23T14:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Acute sensitivity of white sturgeon (<i>Acipenser transmontanus</i>) and rainbow trout (<i>Oncorhynchus mykiss</i>) to copper, cadmium, or zinc in water-only laboratory exposures","docAbstract":"The acute toxicity of cadmium, copper, and zinc to white sturgeon (<i>Acipenser transmontanus</i>) and rainbow trout (<i>Oncorhynchus mykiss</i>) were determined for 7 developmental life stages in flow-through water-only exposures. Metal toxicity varied by species and by life stage. Rainbow trout were more sensitive to cadmium than white sturgeon across all life stages, with median effect concentrations (hardness-normalized EC50s) ranging from 1.47 µg Cd/L to 2.62 µg Cd/L with sensitivity remaining consistent during later stages of development. Rainbow trout at 46 d posthatch (dph) ranked at the 2nd percentile of a compiled database for Cd species sensitivity distribution with an EC50 of 1.46 µg Cd/L and 72 dph sturgeon ranked at the 19th percentile (EC50 of 3.02 µg Cd/L). White sturgeon were more sensitive to copper than rainbow trout in 5 of the 7 life stages tested with biotic ligand model (BLM)-normalized EC50s ranging from 1.51 µg Cu/L to 21.9 µg Cu/L. In turn, rainbow trout at 74 dph and 95 dph were more sensitive to copper than white sturgeon at 72 dph and 89 dph, indicating sturgeon become more tolerant in older life stages, whereas older trout become more sensitive to copper exposure. White sturgeon at 2 dph, 16 dph, and 30 dph ranked in the lower percentiles of a compiled database for copper species sensitivity distribution, ranking at the 3rd (2 dph), 5th (16 dph), and 10th (30 dph) percentiles. White sturgeon were more sensitive to zinc than rainbow trout for 1 out of 7 life stages tested (2 dph with an biotic ligand model–normalized EC50 of 209 µg Zn/L) and ranked in the 1st percentile of a compiled database for zinc species sensitivity distribution.","language":"English","publisher":"Wiley","doi":"10.1002/etc.2684","usgsCitation":"Calfee, R.D., Little, E.E., Puglis, H.J., Scott, E.L., Brumbaugh, W.G., and Mebane, C.A., 2014, Acute sensitivity of white sturgeon (<i>Acipenser transmontanus</i>) and rainbow trout (<i>Oncorhynchus mykiss</i>) to copper, cadmium, or zinc in water-only laboratory exposures: Environmental Toxicology and Chemistry, v. 33, no. 10, p. 2259-2272, https://doi.org/10.1002/etc.2684.","productDescription":"14 p.","startPage":"2259","endPage":"2272","ipdsId":"IP-056438","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":472749,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.2684","text":"Publisher Index Page"},{"id":294373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294372,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/etc.2684"}],"volume":"33","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-07-14","publicationStatus":"PW","scienceBaseUri":"5422bae8e4b08312ac7cee07","contributors":{"authors":[{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":495662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Little, Edward E. 0000-0003-0034-3639 elittle@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3639","contributorId":1746,"corporation":false,"usgs":true,"family":"Little","given":"Edward","email":"elittle@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":495661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":495664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, Erinn L. escott@usgs.gov","contributorId":4685,"corporation":false,"usgs":true,"family":"Scott","given":"Erinn","email":"escott@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":495663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":495660,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495659,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70118078,"text":"70118078 - 2014 - A generalization of the double-corner-frequency source spectral model and its use in the SCEC BBP validation exercise","interactions":[],"lastModifiedDate":"2014-10-10T16:23:32","indexId":"70118078","displayToPublicDate":"2014-09-23T13:38:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A generalization of the double-corner-frequency source spectral model and its use in the SCEC BBP validation exercise","docAbstract":"The stochastic method of simulating ground motions requires the specification of the shape and scaling with magnitude of the source spectrum.  The spectral models commonly used are either single-corner-frequency or double-corner-frequency models, but the latter have no flexibility to vary the high-frequency spectral levels for a specified seismic moment. Two generalized double-corner-frequency ω<sup>2</sup> source spectral models are introduced, one in which two spectra are multiplied together, and another where they are added.  Both models have a low-frequency dependence controlled by the seismic moment, and a high-frequency spectral level controlled by the seismic moment and a stress parameter.  A wide range of spectral shapes can be obtained from these generalized spectral models, which makes them suitable for inversions of data to obtain spectral models that can be used in ground-motion simulations in situations where adequate data are not available for purely empirical determinations of ground motions, as in stable continental regions.  As an example of the use of the generalized source spectral models, data from up to 40 stations from seven events, plus response spectra at two distances and two magnitudes from recent ground-motion prediction equations, were inverted to obtain the parameters controlling the spectral shapes, as well as a finite-fault factor that is used in point-source, stochastic-method simulations of ground motion.  The fits to the data are comparable to or even better than those from finite-fault simulations, even for sites close to large earthquakes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120140138","usgsCitation":"Boore, D.M., Di Alessandro, C., and Abrahamson, N., 2014, A generalization of the double-corner-frequency source spectral model and its use in the SCEC BBP validation exercise: Bulletin of the Seismological Society of America, v. 104, no. 5, p. 2387-2398, https://doi.org/10.1785/0120140138.","productDescription":"12 p.","startPage":"2387","endPage":"2398","numberOfPages":"12","ipdsId":"IP-057075","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":294349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294347,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120140138"}],"volume":"104","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-09-16","publicationStatus":"PW","scienceBaseUri":"5422bae7e4b08312ac7cedfa","contributors":{"authors":[{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":496235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Di Alessandro, Carola","contributorId":43436,"corporation":false,"usgs":true,"family":"Di Alessandro","given":"Carola","email":"","affiliations":[],"preferred":false,"id":496236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abrahamson, Norman A.","contributorId":45202,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman A.","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":496237,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70137955,"text":"70137955 - 2014 - Sea Level Affecting Marshes Model (SLAMM) ‐ New functionality for predicting changes in distribution of submerged aquatic vegetation in response to sea level rise","interactions":[],"lastModifiedDate":"2016-04-26T16:24:46","indexId":"70137955","displayToPublicDate":"2014-09-23T13:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Sea Level Affecting Marshes Model (SLAMM) ‐ New functionality for predicting changes in distribution of submerged aquatic vegetation in response to sea level rise","docAbstract":"<h1>Introduction</h1>\n<p>Submerged aquatic vegetation (SAV) is an ecologically important habitat world‐wide. In Pacific Northwest (PNW) estuaries, SAV in the lower intertidal and shallow subtidal habitats are dominated by the native seagrass, <i>Zostera marina</i> Linnaeus, 1753. Within this report, SAV and seagrass refer to <i>Z. marina</i> seagrass beds in PNW estuaries. <i>Z. marina</i> provides important habitat for juvenile salmon, dungeness crabs, migratory shore birds, and benthic assemblages (e.g., Philips, 1984; Williamson, 2006; Ferraro and Cole, 2007; Shaughnessy et al., 2012). <i>Z. marina</i> typically occurs in a narrow depth range. For example, in Oregon estuaries <i>Zostera marina</i> primarily occurs within the depth range of ‐1 to +1 m relative to Mean Lower Low Water (MLLW) (Young et al. 2012). Because of their narrow depth range, the distribution of these seagrass beds are potentially vulnerable to sea level rise (SLR) through increased water depths and associated reductions in underwater light levels, alterations in tidal variations, altered water movement and wave action, and increased seawater intrusion (Short and Neckles, 1999).</p>\n<p>The &ldquo;Sea‐Level Affecting Marshes Model&rdquo; (SLAMM) is a moderate resolution model used to predict the effects of sea level rise on marsh habitats (Craft et al. 2009). SLAMM has been used extensively on both the west coast (e.g., Glick et al., 2007) and east coast (e.g., Geselbracht et al., 2011) of the United States to evaluate potential changes in the distribution and extent of tidal marsh habitats. However, a limitation of the current version of SLAMM, (Version 6.2) is that it lacks the ability to model distribution changes in seagrass habitat resulting from sea level rise. Because of the ecological importance of SAV habitats, U.S. EPA, USGS, and USDA partnered with Warren Pinnacle Consulting to enhance the SLAMM modeling software to include new functionality in order to predict changes in <i>Zostera marina</i> distribution within Pacific Northwest estuaries in response to sea level rise. Specifically, the objective was to develop a SAV model that used generally available GIS data and parameters that were predictive and that could be customized for other estuaries that have GIS layers of existing SAV distribution. This report describes the procedure used to develop the SAV model for the Yaquina Bay Estuary, Oregon, appends a statistical script based on the open source R software to generate a similar SAV model for other estuaries that have data layers of existing SAV, and describes how to incorporate the model coefficients from the site‐specific SAV model into SLAMM to predict the effects of sea level rise on <i>Zostera marina</i> distributions. To demonstrate the applicability of the R tools, we utilize them to develop model coefficients for Willapa Bay, Washington using site‐specific SAV data.</p>","language":"English","publisher":"U.S. Environmental Protection Agency","usgsCitation":"Lee II, H., Reusser, D.A., Frazier, M.R., McCoy, L.M., Clinton, P.J., and Clough, J.S., 2014, Sea Level Affecting Marshes Model (SLAMM) ‐ New functionality for predicting changes in distribution of submerged aquatic vegetation in response to sea level rise, iv, 50 p.","productDescription":"iv, 50 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059942","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":320579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Yaquina Bay Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.6,\n              45\n            ],\n            [\n              -124.6,\n              47\n            ],\n            [\n              -122.5,\n              47\n            ],\n            [\n              -122.5,\n              45\n            ],\n            [\n              -124.6,\n              45\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57209138e4b071321fe65694","contributors":{"authors":[{"text":"Lee II, Henry","contributorId":138672,"corporation":false,"usgs":false,"family":"Lee II","given":"Henry","affiliations":[{"id":12485,"text":"Pacific Coastal Ecology Branch, Western Ecology Division, United States Environmental Protection Agency, Newport, Oregon, 97365","active":true,"usgs":false}],"preferred":false,"id":538309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reusser, Deborah A. dreusser@usgs.gov","contributorId":2423,"corporation":false,"usgs":true,"family":"Reusser","given":"Deborah","email":"dreusser@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":538308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frazier, Melanie R","contributorId":138673,"corporation":false,"usgs":false,"family":"Frazier","given":"Melanie","email":"","middleInitial":"R","affiliations":[{"id":12486,"text":"National Center for Ecological Analysis and Synthesis, 735 State St. Suite 300, Santa Barbara, CA 93101","active":true,"usgs":false}],"preferred":false,"id":538310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCoy, Lee M","contributorId":138674,"corporation":false,"usgs":false,"family":"McCoy","given":"Lee","email":"","middleInitial":"M","affiliations":[{"id":12487,"text":"Agricultural Research Service, United States Department of Agriculture, Newport, OR","active":true,"usgs":false}],"preferred":false,"id":538311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clinton, Patrick J.","contributorId":138675,"corporation":false,"usgs":false,"family":"Clinton","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":12485,"text":"Pacific Coastal Ecology Branch, Western Ecology Division, United States Environmental Protection Agency, Newport, Oregon, 97365","active":true,"usgs":false}],"preferred":false,"id":538312,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clough, Jonathan S.","contributorId":138676,"corporation":false,"usgs":false,"family":"Clough","given":"Jonathan","email":"","middleInitial":"S.","affiliations":[{"id":12488,"text":"Warren Pinnacle Consulting, Inc., P.O. Box 351, Waitsfield VT, 05673","active":true,"usgs":false}],"preferred":false,"id":538313,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70122869,"text":"sir20145170 - 2014 - Concentrations, loads, and yields of total phosphorus, total nitrogen, and suspended sediment and bacteria concentrations in the Wister Lake Basin, Oklahoma and Arkansas, 2011-13","interactions":[],"lastModifiedDate":"2014-09-23T11:45:55","indexId":"sir20145170","displayToPublicDate":"2014-09-23T11:36:00","publicationYear":"2014","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":"2014-5170","title":"Concentrations, loads, and yields of total phosphorus, total nitrogen, and suspended sediment and bacteria concentrations in the Wister Lake Basin, Oklahoma and Arkansas, 2011-13","docAbstract":"<p>The Poteau Valley Improvement Authority uses Wister Lake in southeastern Oklahoma as a public water supply. Total phosphorus, total nitrogen, and suspended sediments from agricultural runoff and discharges from wastewater treatment plants and other sources have degraded water quality in the lake. As lake-water quality has degraded, water-treatment cost, chemical usage, and sludge production have increased for the Poteau Valley Improvement Authority.</p>\n<br/>\n<p>The U.S. Geological Survey (USGS), in cooperation with the Poteau Valley Improvement Authority, investigated and summarized concentrations of total phosphorus, total nitrogen, suspended sediment, and bacteria (Escherichia coli and Enterococcus sp.) in surface water flowing to Wister Lake. Estimates of total phosphorus, total nitrogen, and suspended sediment loads, yields, and flow-weighted mean concentrations of total phosphorus and total nitrogen concentrations were made for the Wister Lake Basin for a 3-year period from October 2010 through September 2013. Data from water samples collected at fixed time increments during base-flow conditions and during runoff conditions at the Poteau River at Loving, Okla. (USGS station 07247015), the Poteau River near Heavener, Okla. (USGS station 07247350), and the Fourche Maline near Leflore, Okla. (USGS station 07247650), water-quality stations were used to evaluate water quality over the range of streamflows in the basin. These data also were collected to estimate annual constituent loads and yields by using regression models.</p>\n<br/>\n<p>At the Poteau River stations, total phosphorus, total nitrogen, and suspended sediment concentrations in surface-water samples were significantly larger in samples collected during runoff conditions than in samples collected during base-flow conditions. At the Fourche Maline station, in contrast, concentrations of these constituents in water samples collected during runoff conditions were not significantly larger than concentrations during base-flow conditions. Flow-weighted mean total phosphorus concentrations at all three stations from 2011 to 2013 were several times larger than the Oklahoma State Standard for Scenic Rivers (0.037 milligrams per liter [mg/L]), with the largest flow-weighted phosphorus concentrations typically being measured at the Poteau River at Loving, Okla., station. Flow-weighted mean total nitrogen concentrations did not vary substantially between the Poteau River stations and the Fourche Maline near Leflore, Okla., station. At all of the sampled water-quality stations, bacteria (Escherichia coli and Enterococcus sp.) concentrations were substantially larger in water samples collected during runoff conditions than in water samples collected during base-flow conditions from 2011 to 2013.</p>\n<br/>\n<p>Estimated annual loads of total phosphorus, total nitrogen, and suspended sediment in the Poteau River stations during runoff conditions ranged from 82 to 98 percent of the total annual loads of those constituents. Estimated annual loads of total phosphorus, total nitrogen, and suspended sediment in the Fourche Maline during runoff conditions ranged from 86 to nearly 100 percent of the total annual loads.</p>\n<br/>\n<p>Estimated seasonal total phosphorus loads generally were smallest during base-flow and runoff conditions in autumn. Estimated seasonal total phosphorus loads during base-flow conditions tended to be largest in winter and during runoff conditions tended to be largest in the spring. Estimated seasonal total nitrogen loads tended to be smallest in autumn during base-flow and runoff conditions and largest in winter during runoff conditions. Estimated seasonal suspended sediment loads tended to be smallest during base-flow conditions in the summer and smallest during runoff conditions in the autumn. The largest estimated seasonal suspended sediment loads during runoff conditions typically were in the spring.</p>\n<br/>\n<p>The estimated mean annual total phosphorus yield was largest at the Poteau River at Loving, Okla., water-quality station. The estimated mean annual total phosphorus yield was largest during base flow at the Poteau River at Loving, Okla., water-quality station and at both of the Poteau River water-quality stations during runoff conditions. The estimated mean annual total nitrogen yields were largest at the Poteau River water-quality stations. Estimated mean annual total nitrogen yields were largest during base-flow and runoff conditions at the Poteau River at Loving, Okla., water-quality station. The estimated mean annual suspended sediment yield was largest at the Poteau River near Heavener, Okla., water-quality station during base-flow and runoff conditions.</p>\n<br/>\n<p>Flow-weighted mean concentrations indicated that total phosphorus inputs from the Poteau River Basin in the Wister Lake Basin were larger than from the Fourche Maline Basin. Flow-weighted mean concentrations of total nitrogen did not vary spatially in a consistent manner.</p>\n<br/>\n<p>The Poteau River and the Fourche Maline contributed estimated annual total phosphorus loads of 137 to 278 tons per year (tons/yr) to Wister Lake. Between 89 and 95 percent of the annual total phosphorus loads were transported to Wister Lake during runoff conditions. The Poteau River and the Fourche Maline contributed estimated annual total nitrogen loads of 657 to 1,294 tons/yr, with 86 to 94 percent of the annual total nitrogen loads being transported to Wister Lake during runoff conditions. The Poteau River and the Fourche Maline contributed estimated annual total suspended sediment loads of 110,919 to 234,637 tons/yr, with 94 to 99 percent of the annual suspended sediment loads being transported to Wister Lake during runoff conditions. Most of the total phosphorus and suspended sediment were delivered to Wister Lake during runoff conditions in the spring. The majority of the total nitrogen was delivered to Wister Lake during runoff conditions in winter.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145170","collaboration":"Prepared in cooperation with the Poteau Valley Improvement Authority","usgsCitation":"Buck, S.D., 2014, Concentrations, loads, and yields of total phosphorus, total nitrogen, and suspended sediment and bacteria concentrations in the Wister Lake Basin, Oklahoma and Arkansas, 2011-13: U.S. Geological Survey Scientific Investigations Report 2014-5170, viii, 39 p., https://doi.org/10.3133/sir20145170.","productDescription":"viii, 39 p.","numberOfPages":"50","ipdsId":"IP-055951","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":294325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145170.jpg"},{"id":294323,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5170/"},{"id":294324,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5170/pdf/sir2014-5170.pdf"}],"projection":"Albers Equal-Area Conic projection","datum":"North American Datum 1983","country":"United States","state":"Arkansas;Oklahoma","otherGeospatial":"Wister Lake Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.333333,34.666667 ], [ -95.333333,35.166667 ], [ -93.833333,35.166667 ], [ -93.833333,34.666667 ], [ -95.333333,34.666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5422baf0e4b08312ac7cee34","contributors":{"authors":[{"text":"Buck, Stephanie D. sbuck@usgs.gov","contributorId":4622,"corporation":false,"usgs":true,"family":"Buck","given":"Stephanie","email":"sbuck@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":499695,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70121906,"text":"sir20145162 - 2014 - Hydrologic conditions in urban Miami-Dade County, Florida, and the effect of groundwater pumpage and increased sea level on canal leakage and regional groundwater flow","interactions":[],"lastModifiedDate":"2016-08-03T12:15:25","indexId":"sir20145162","displayToPublicDate":"2014-09-23T08:41:00","publicationYear":"2014","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":"2014-5162","title":"Hydrologic conditions in urban Miami-Dade County, Florida, and the effect of groundwater pumpage and increased sea level on canal leakage and regional groundwater flow","docAbstract":"<p>The extensive and highly managed surface-water system in southeastern Florida constructed during the 20th Century has allowed for the westward expansion of urban and agricultural activities in Miami-Dade County. In urban areas of the county, the surface-water system is used to (1) control urban flooding, (2) supply recharge to production well fields, and (3) control seawater intrusion. Previous studies in Miami-Dade County have determined that on a local scale, leakage from canals adjacent to well fields can supply a large percentage (46 to 78 percent) of the total groundwater pumpage from production well fields. Canals in the urban areas also receive seepage from the Biscayne aquifer that is derived from a combination of local rainfall and groundwater flow from Water Conservation Area 3 and Everglades National Park, which are west of urban areas of Miami-Dade County.</p>\n<p>To evaluate the effects of groundwater pumpage on canal leakage and regional groundwater flow, the U.S. Geological Survey (USGS) developed and calibrated a coupled surface-water/groundwater model of the urban areas of Miami-Dade County, Florida. The model was calibrated by using observation data collected from January 1997 through December 2004. The model calibration was verified using observation data collected from January 2005 through December 2010. A 1-year warmup period (January 1996 through December 1996) was added prior to the start of the calibration period to reduce the effects of inaccurate initial conditions on model calibration. The model is designed to simulate surface-water stage and discharge in the managed canal system and dynamic canal leakage to the Biscayne aquifer as well as seepage to the canal from the aquifer. The model was developed using USGS MODFLOW&ndash;NWT with the Surface-Water Routing (SWR1) Process to simulate surface-water stage, surface-water discharge, and surface-water/groundwater interaction and the Seawater Intrusion (SWI2) Package to simulate seawater intrusion, respectively.</p>\n<p>Automated parameter estimation software (PEST) and highly parameterized inversion techniques were used to calibrate the model to observed surface-water stage, surface-water discharge, net surface-water subbasin discharge, and groundwater level data from 1997 through 2004 by modifying hydraulic conductivity, specific storage coefficients, specific yield, evapotranspiration parameters, canal roughness coefficients (Manning&rsquo;s&nbsp;<i>n</i>&nbsp;values), and canal leakance coefficients. Tikhonov regularization was used to produce parameter distributions that provide an acceptable fit between model outputs and observation data, while simultaneously minimizing deviations from preferred values based on field measurements and expert knowledge.</p>\n<p>Analytical and simulated water budgets for the period from 1996 through 2010 indicate that most of the water discharging through the salinity control structures is derived from within the urban parts of the study area and that, on average, the canals are draining the Biscayne aquifer. Simulated groundwater discharge from the urban areas to the coast is approximately 7 percent of the total surface-water inflow to Biscayne Bay and is consistent with previous estimates of fresh groundwater discharge to Biscayne Bay. Simulated groundwater budgets indicate that groundwater pumpage in some surface-water basins ranges from 13 to 27 percent of the sum of local sources of groundwater inflow. The largest percentage of groundwater pumpage to local sources of groundwater inflow occurs in the basins that have the highest pumping rates (C&ndash;2 and C&ndash;100 Basins). The ratio of groundwater pumpage to simulated local sources of groundwater inflow is less than values calculated in previous local-scale studies.</p>\n<p>The position of the freshwater-seawater interface at the base of the Biscayne aquifer did not change notably during the simulation period (1996&ndash;2010), consistent with the similar positions of the interface in 1984, 1995, and 2011 under similar hydrologic and groundwater pumping conditions. Landward movement of the freshwater-seawater interface above the base of the aquifer is more prone to occur during relatively dry years.</p>\n<p>The model was used to evaluate the effect of increased groundwater pumpage and (or) increased sea level on canal leakage, regional groundwater flow, and the position of the freshwater-seawater interface. Permitted groundwater pumping rates, which generally exceed historical groundwater pumping rates, were used for Miami-Dade County Water and Sewer Department groundwater pumping wells in the base-case future scenario. Base-case future and increased pumping scenario results suggest seawater intrusion may occur at the Miami-Springs well field if the Miami Springs, Hialeah, and Preston well fields are operated using current permitted groundwater pumping rates. Scenario simulations also show that, in general, the canal system limits the adverse effects of proposed groundwater pumpage increases on water-level changes and saltwater intrusion. Proposed increases (up to a 7 percent increase) in groundwater pumpage do not have a notable effect on movement of the freshwater-seawater interface. Increased groundwater pumpage increased lateral groundwater inflow into basins subject to additional groundwater pumpage; however, most (55 percent) of the additional groundwater extracted from pumping wells was supplied by changes in canal seepage and leakage in urban areas of the model. Increased sea level caused increased water-table elevations in urban areas and decreased hydraulic gradients across the system; the largest increases in water-table elevations occurred seaward of the salinity control structures. The extent of flood-prone areas and the percentage of time water-table elevations in flood-prone areas were less than 0.5 foot below land surface increased with increased sea level. Increased sea level also resulted in landward migration of the freshwater-seawater interface; the largest changes in the position of the interface occurred seaward of the salinity control structures except in parts of the model area that were inundated by increased sea level. Decreased water-table gradients reduced groundwater inflow, groundwater outflow, canal exchanges, surface-water inflow, and surface-water outflow through salinity control structures. Results for the scenario that evaluated the combination of increased groundwater pumpage and increased sea level did not differ substantially from the scenario that evaluated increased sea level alone. Groundwater inflow, groundwater outflow, and canal exchanges were reduced in urban areas of the study area as a result of decreased water-table gradients across the system, although reductions were less than those in the increased sea-level scenario. The decline in groundwater levels caused by increased groundwater pumpage was less under the increased sea-level scenario than under the increased groundwater-pumpage scenario. The largest reductions in surface-water outflow from the salinity control structures occurred with increased sea level and increased groundwater pumpage.</p>\n<p>The model was designed specifically to evaluate the effect of groundwater pumpage on canal leakage at the surface-water-basin scale and thus may not be appropriate for (1) predictions that are dependent on data not included in the calibration process (for example, subdaily simulation of high-intensity events and travel times) and (or) (2) hydrologic conditions that are substantially different from those during the calibration and verification periods. The reliability of the model is limited by the conceptual model of the surface-water and groundwater system, the spatial distribution of physical properties, the scale and discretization of the system, and specified boundary conditions. Some of the model limitations are manifested in model errors. Despite these limitations, however, the model represents the complexities of the interconnected surface-water and groundwater systems that affect how the systems respond to groundwater pumpage, sea-level rise, and other hydrologic stresses. The model also quantifies the relative effects of groundwater pumpage and sea-level rise on the surface-water and groundwater systems.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145162","collaboration":"Prepared in cooperation with the Miami-Dade Water and Sewer Department","usgsCitation":"Hughes, J.D., and White, J., 2014, Hydrologic conditions in urban Miami-Dade County, Florida, and the effect of groundwater pumpage and increased sea level on canal leakage and regional groundwater flow (Version 1.0: Originally posted September 23, 2014; Version 1.1: May 26, 2016; Version 1.2: August 1, 2016): U.S. Geological Survey Scientific Investigations Report 2014-5162, Report: xiii, 175 p.; Data Release, https://doi.org/10.3133/sir20145162.","productDescription":"Report: xiii, 175 p.; Data Release","numberOfPages":"194","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051842","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":321776,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F79P2ZRH","text":"Data Release"},{"id":321775,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5162/versionHist.txt"},{"id":294282,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5162/"},{"id":294283,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5162/pdf/sir2014-5162.pdf","text":"Report","size":"33.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":294284,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5162/images/coverthb.jpg"}],"scale":"2000000","country":"United States","state":"Florida","county":"Miami-Dade County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.11299133300781,\n              25.842539331357372\n            ],\n            [\n              -80.11917114257811,\n              25.961748853879143\n            ],\n            [\n              -80.85662841796875,\n              25.94075695601904\n            ],\n            [\n              -80.86898803710938,\n              25.17014505150313\n            ],\n            [\n              -80.76461791992188,\n              25.139068709030795\n            ],\n            [\n              -80.54901123046875,\n              25.187544344824484\n            ],\n            [\n              -80.36773681640625,\n              25.293129530136873\n            ],\n            [\n              -80.299072265625,\n              25.388697990350824\n            ],\n            [\n              -80.244140625,\n              25.332855459462515\n            ],\n            [\n              -80.16998291015625,\n              25.494107850705554\n            ],\n            [\n              -80.13290405273438,\n              25.728158254981707\n            ],\n            [\n              -80.11299133300781,\n              25.842539331357372\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: Originally posted September 23, 2014; Version 1.1: May 26, 2016; Version 1.2: August 1, 2016","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5422baf6e4b08312ac7cee62","contributors":{"authors":[{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":499318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Jeremy T. jwhite@usgs.gov","contributorId":3930,"corporation":false,"usgs":true,"family":"White","given":"Jeremy T.","email":"jwhite@usgs.gov","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":false,"id":499319,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70135282,"text":"70135282 - 2014 - Effects of seasonal operation on the quality of water produced by public-supply wells","interactions":[],"lastModifiedDate":"2018-09-13T13:45:07","indexId":"70135282","displayToPublicDate":"2014-09-23T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Effects of seasonal operation on the quality of water produced by public-supply wells","docAbstract":"<p><span>Seasonal variability in groundwater pumping is common in many places, but resulting effects of seasonal pumping stress on the quality of water produced by public-supply wells are not thoroughly understood. Analysis of historical water-quality samples from public-supply wells completed in deep basin-fill aquifers in Modesto, California (134 wells) and Albuquerque, New Mexico (95 wells) indicates that several wells have seasonal variability in concentrations of contaminants of concern. In Modesto, supply wells are more likely to produce younger groundwater with higher nitrate and uranium concentrations during the summer (high) pumping season than during the winter (low) pumping season. In Albuquerque, supply wells are more likely to produce older groundwater with higher arsenic concentrations during the winter pumping season than during the summer pumping season. Seasonal variability in contaminant concentrations in Modesto is influenced primarily by effects of summer pumping on vertical hydraulic gradients that drive migration of shallow groundwater through the aquifer to supply wells. Variability in Albuquerque is influenced primarily by the period of time that a supply well is idle, allowing its wellbore to act as a conduit for vertical groundwater flow and contaminant migration. However, both processes are observed in each study area. Similar findings would appear to be likely in other alluvial basins with stratified water quality and substantial vertical head gradients. Results suggest that even in aquifers dominated by old groundwater, changes to seasonal pumping patterns and/or to depth of well completion can help reduce vulnerability to selected contaminants of either natural or anthropogenic origin.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12174","usgsCitation":"Bexfield, L.M., and Jurgens, B., 2014, Effects of seasonal operation on the quality of water produced by public-supply wells: Groundwater, v. 52, no. S1, p. 10-24, https://doi.org/10.1111/gwat.12174.","productDescription":"15 p.","startPage":"10","endPage":"24","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053287","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":472751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.12174","text":"Publisher Index Page"},{"id":296633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"S1","noUsgsAuthors":false,"publicationDate":"2014-03-04","publicationStatus":"PW","scienceBaseUri":"548c1fcee4b0ca8c43c36964","chorus":{"doi":"10.1111/gwat.12174","url":"http://dx.doi.org/10.1111/gwat.12174","publisher":"Wiley-Blackwell","authors":"Bexfield Laura M., Jurgens Bryant C.","journalName":"Groundwater","publicationDate":"3/4/2014","auditedOn":"3/17/2016"},"contributors":{"authors":[{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":527007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":1503,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","email":"bjurgens@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":527008,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70125988,"text":"ofr20141204 - 2014 - Correlations of turbidity to suspended-sediment concentration in the Toutle River Basin, near Mount St. Helens, Washington, 2010-11","interactions":[],"lastModifiedDate":"2019-03-14T08:12:32","indexId":"ofr20141204","displayToPublicDate":"2014-09-22T20:51:00","publicationYear":"2014","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":"2014-1204","title":"Correlations of turbidity to suspended-sediment concentration in the Toutle River Basin, near Mount St. Helens, Washington, 2010-11","docAbstract":"Researchers at the U.S. Geological Survey, Cascades Volcano Observatory, investigated alternative methods for the traditional sample-based sediment record procedure in determining suspended-sediment concentration (SSC) and discharge. One such sediment-surrogate technique was developed using turbidity and discharge to estimate SSC for two gaging stations in the Toutle River Basin near Mount St. Helens, Washington. To provide context for the study, methods for collecting sediment data and monitoring turbidity are discussed. Statistical methods used include the development of ordinary least squares regression models for each gaging station. Issues of time-related autocorrelation also are evaluated. Addition of lagged explanatory variables was used to account for autocorrelation in the turbidity, discharge, and SSC data. Final regression model equations and plots are presented for the two gaging stations. The regression models support near-real-time estimates of SSC and improved suspended-sediment discharge records by incorporating continuous instream turbidity. Future use of such models may potentially lower the costs of sediment monitoring by reducing time it takes to collect and process samples and to derive a sediment-discharge record.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141204","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Uhrich, M.A., Kolasinac, J., Booth, P.L., Fountain, R.L., Spicer, K.R., and Mosbrucker, A., 2014, Correlations of turbidity to suspended-sediment concentration in the Toutle River Basin, near Mount St. Helens, Washington, 2010-11: U.S. Geological Survey Open-File Report 2014-1204, Report: vi, 30 p.; Appendixes: A, B, https://doi.org/10.3133/ofr20141204.","productDescription":"Report: vi, 30 p.; Appendixes: A, B","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2010-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-051147","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":294281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141204.jpg"},{"id":294279,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1204/downloads/ofr2014-1204_appendixA.xlsx"},{"id":294270,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1204/"},{"id":294278,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1204/pdf/ofr2014-1204.pdf"},{"id":294280,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1204/downloads/ofr2014-1204_appendixB.xlsx"}],"projection":"Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens;Toutle River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.0,46.0 ], [ -123.0,46.45 ], [ -122.0,46.45 ], [ -122.0,46.0 ], [ -123.0,46.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54212c06e4b06fb4967a168a","contributors":{"authors":[{"text":"Uhrich, Mark A. 0000-0002-5202-8086 mauhrich@usgs.gov","orcid":"https://orcid.org/0000-0002-5202-8086","contributorId":1149,"corporation":false,"usgs":true,"family":"Uhrich","given":"Mark","email":"mauhrich@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":501857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolasinac, Jasna jkolasin@usgs.gov","contributorId":5599,"corporation":false,"usgs":true,"family":"Kolasinac","given":"Jasna","email":"jkolasin@usgs.gov","affiliations":[],"preferred":true,"id":501859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Booth, Pamela L.","contributorId":103974,"corporation":false,"usgs":true,"family":"Booth","given":"Pamela","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":501862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fountain, Robert L.","contributorId":42148,"corporation":false,"usgs":true,"family":"Fountain","given":"Robert","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":501861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":501858,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":33640,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":501860,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70123135,"text":"fs20143091 - 2014 - The 3D Elevation Program: Summary for New Jersey","interactions":[],"lastModifiedDate":"2016-08-10T15:56:45","indexId":"fs20143091","displayToPublicDate":"2014-09-22T20:44:00","publicationYear":"2014","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":"2014-3091","title":"The 3D Elevation Program: Summary for New Jersey","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of New Jersey, elevation data are critical for water supply and quality, flood risk management, natural resources conservation, agriculture and precision farming, infrastructure and construction management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143091","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: Summary for New Jersey: U.S. Geological Survey Fact Sheet 2014-3091, 2 p., https://doi.org/10.3133/fs20143091.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059180","costCenters":[{"id":423,"text":"National Geospatial 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":499842,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70137853,"text":"70137853 - 2014 - Strong influence of El Niño Southern Oscillation on flood risk around the world","interactions":[],"lastModifiedDate":"2015-01-14T09:27:58","indexId":"70137853","displayToPublicDate":"2014-09-22T09:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Strong influence of El Niño Southern Oscillation on flood risk around the world","docAbstract":"<p>El Ni&ntilde;o Southern Oscillation (ENSO) is the most dominant interannual signal of climate variability and has a strong influence on climate over large parts of the world. In turn, it strongly influences many natural hazards (such as hurricanes and droughts) and their resulting socioeconomic impacts, including economic damage and loss of life. However, although ENSO is known to influence hydrology in many regions of the world, little is known about its influence on the socioeconomic impacts of floods (i.e., flood risk). To address this, we developed a modeling framework to assess ENSO&rsquo;s influence on flood risk at the global scale, expressed in terms of affected population and gross domestic product and economic damages. We show that ENSO exerts strong and widespread influences on both flood hazard and risk. Reliable anomalies of flood risk exist during El Ni&ntilde;o or La Ni&ntilde;a years, or both, in basins spanning almost half (44%) of Earth&rsquo;s land surface. Our results show that climate variability, especially from ENSO, should be incorporated into disaster-risk analyses and policies. Because ENSO has some predictive skill with lead times of several seasons, the findings suggest the possibility to develop probabilistic flood-risk projections, which could be used for improved disaster planning. The findings are also relevant in the context of climate change. If the frequency and/or magnitude of ENSO events were to change in the future, this finding could imply changes in flood-risk variations across almost half of the world&rsquo;s terrestrial regions.</p>","language":"English","publisher":"National Academy of Sciences","publisherLocation":"Washington, D.C.","doi":"10.1073/pnas.1409822111","usgsCitation":"Ward, P.J., Jongman, B., Kummu, M., Dettinger, M., Sperna Weiland, F., and Winsemius, H., 2014, Strong influence of El Niño Southern Oscillation on flood risk around the world: Proceedings of the National Academy of Sciences, v. 111, no. 44, p. 15659-15664, https://doi.org/10.1073/pnas.1409822111.","productDescription":"6 p.","startPage":"15659","endPage":"15664","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057122","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":472753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1409822111","text":"Publisher Index Page"},{"id":297220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297187,"type":{"id":15,"text":"Index Page"},"url":"https://www.pnas.org/content/111/44/15659.full.pdf+html"}],"volume":"111","issue":"44","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-20","publicationStatus":"PW","scienceBaseUri":"54dd2c64e4b08de9379b377b","contributors":{"authors":[{"text":"Ward, Philip J.","contributorId":67434,"corporation":false,"usgs":true,"family":"Ward","given":"Philip","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":538185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jongman, B","contributorId":138641,"corporation":false,"usgs":false,"family":"Jongman","given":"B","email":"","affiliations":[{"id":6715,"text":"VU University Amsterdam","active":true,"usgs":false}],"preferred":false,"id":538186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kummu, M.","contributorId":39711,"corporation":false,"usgs":true,"family":"Kummu","given":"M.","email":"","affiliations":[],"preferred":false,"id":538187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dettinger, Mike 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":859,"corporation":false,"usgs":true,"family":"Dettinger","given":"Mike","email":"mddettin@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":538184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sperna Weiland, F.C","contributorId":138642,"corporation":false,"usgs":false,"family":"Sperna Weiland","given":"F.C","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":538188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winsemius, H.C","contributorId":138643,"corporation":false,"usgs":false,"family":"Winsemius","given":"H.C","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":538189,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70133425,"text":"70133425 - 2014 - Development and use of a basin-scale hydrologic model for the Onondaga Lake basin","interactions":[],"lastModifiedDate":"2017-06-05T15:32:36","indexId":"70133425","displayToPublicDate":"2014-09-22T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5049,"text":"Clear Waters","active":true,"publicationSubtype":{"id":10}},"title":"Development and use of a basin-scale hydrologic model for the Onondaga Lake basin","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"New York Water Environmental Association Inc.","usgsCitation":"Coon, W.F., 2014, Development and use of a basin-scale hydrologic model for the Onondaga Lake basin: Clear Waters, v. 44, p. 31-33.","productDescription":"3 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,{"id":70126236,"text":"70126236 - 2014 - Landscape alterations influence differential habitat use of nesting buteos and ravens within sagebrush ecosystem: implications for transmission line development","interactions":[],"lastModifiedDate":"2014-09-19T18:03:35","indexId":"70126236","displayToPublicDate":"2014-09-19T17:55:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Landscape alterations influence differential habitat use of nesting buteos and ravens within sagebrush ecosystem: implications for transmission line development","docAbstract":"A goal in avian ecology is to understand factors that influence differences in nesting habitat and distribution among species, especially within changing landscapes. Over the past 2 decades, humans have altered sagebrush ecosystems as a result of expansion in energy production and transmission. Our primary study objective was to identify differences in the use of landscape characteristics and natural and anthropogenic features by nesting Common Ravens (<i>Corvus corax</i>) and 3 species of buteo (Swainson's Hawk [<i>Buteo swainsoni</i>], Red-tailed Hawk [<i>B. jamaicensis</i>], and Ferruginous Hawk [<i>B. regalis</i>]) within a sagebrush ecosystem in southeastern Idaho. During 2007–2009, we measured multiple environmental factors associated with 212 nest sites using data collected remotely and in the field. We then developed multinomial models to predict nesting probabilities by each species and predictive response curves based on model-averaged estimates. We found differences among species related to nesting substrate (natural vs. anthropogenic), agriculture, native grassland, and edge (interface of 2 cover types). Most important, ravens had a higher probability of nesting on anthropogenic features (0.80) than the other 3 species (<0.10), and the probability of nesting near agriculture was greatest for ravens (0.55) followed by Swainson's Hawk (0.28). We also describe changes in nesting densities over 4 decades at this site as related to natural and anthropogenic disturbances. Since the 1970s, the composition of the raptor and raven nesting community has drastically changed with anthropogenic alterations and loss of continuous stands of sagebrush (<i>Artemisia</i> spp.), favoring increased numbers of nesting ravens and fewer nesting Ferruginous Hawks. Our results indicate that habitat alterations, fragmentation, and forthcoming disturbances anticipated with continued energy development in sagebrush steppe ecosystems can lead to predictable changes in raptor and raven communities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-13-126.1","usgsCitation":"Coates, P.S., Howe, K., Casazza, M.L., and Delehanty, D.J., 2014, Landscape alterations influence differential habitat use of nesting buteos and ravens within sagebrush ecosystem: implications for transmission line development: The Condor, v. 116, no. 3, p. 341-356, https://doi.org/10.1650/CONDOR-13-126.1.","productDescription":"16 p.","startPage":"341","endPage":"356","numberOfPages":"16","ipdsId":"IP-052050","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472754,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-13-126.1","text":"Publisher Index Page"},{"id":294254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294249,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1650/CONDOR-13-126.1"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.2001,43.4023 ], [ -113.2001,44.0507 ], [ -112.5008,44.0507 ], [ -112.5008,43.4023 ], [ -113.2001,43.4023 ] ] ] } } ] }","volume":"116","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d378ce4b0f68901ebd9a4","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howe, Kristy B.","contributorId":59354,"corporation":false,"usgs":true,"family":"Howe","given":"Kristy B.","affiliations":[],"preferred":false,"id":501973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":501971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Delehanty, David J.","contributorId":80811,"corporation":false,"usgs":true,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":501974,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70123759,"text":"sim3310 - 2014 - Base of principal aquifer for parts of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska","interactions":[],"lastModifiedDate":"2014-09-19T08:47:58","indexId":"sim3310","displayToPublicDate":"2014-09-19T08:36:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3310","title":"Base of principal aquifer for parts of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska","docAbstract":"<p>Water resources in the North and South Platte River valleys of Nebraska, including the valley of Lodgepole Creek, are critical to the social and economic health of the area, and for the recovery of threatened and endangered species in the Platte River Basin. Groundwater and surface water are heavily used resources, and uses are regulated in the study area. Irrigation is the dominant water use and, in most instances, is supplied by both groundwater and surface-water sources. The U.S. Geological Survey and its partners have collaborated to use airborne geophysical surveys for areas of the North and South Platte River valleys including the valley of Lodgepole Creek in western Nebraska. The objective of the surveys was to map the aquifers and underlying bedrock topography of selected areas to help improve the understanding of groundwater–surface-water relations to guide water-management decisions. This project was a cooperative study involving the North Platte Natural Resources District, the South Platte Natural Resources District, the Twin Platte Natural Resources District, the Conservation and Survey Division of the University of Nebraska-Lincoln, and the Nebraska Environmental Trust.</p>\n<br/>\n<p>This report presents the interpreted base-of-aquifer surface for part of the area consisting of the North Platte Natural Resources District, the South Platte Natural Resources District, and the Twin Platte Natural Resources District. The interpretations presented herein build on work done by previous researchers from 2008 to 2009 by incorporating additional airborne electromagnetic survey data collected in 2010 and additional test holes from separate, related studies. To make the airborne electromagnetic data useful, numerical inversion was used to convert the measured data into a depth-dependent subsurface resistivity model. An interpretation of the elevation and configuration of the base of aquifer was completed in a geographic information system that provided x, y, and z coordinates. The process of interpretation involved manually picking locations (base-of-aquifer elevations) on the displayed airborne electromagnetic-derived resistivity profile by the project geophysicist, hydrologist, and geologist. These locations, or picks, of the base-of-aquifer elevation (typically the top of the Brule Formation of the White River Group) were then stored in a georeferenced database. The pick was made by comparing the inverted airborne electromagnetic-derived resistivity profile to the lithologic descriptions and borehole geophysical logs from nearby test holes. The database of interpretive picks of the base-of-aquifer elevation was used to create primary input for interpolating the new base-of-aquifer contours.</p>\n<br/>\n<p>The automatically generated contours were manually adjusted based on the interpreted location of paleovalleys eroded into the base-of-aquifer surface and associated bedrock highs, many of which were unmapped before this study. When contours are overlain by the water-table surface, the saturated thickness of the aquifer can be computed, which allows an estimate of total water in storage. The contours of the base-of-aquifer surface presented in this report may be used as the lower boundary layer in existing and future groundwater-flow models. The integration of geophysical data into the contouring process facilitated a more continuous and spatially comprehensive view of the hydrogeologic framework.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3310","collaboration":"Prepared in cooperation with the North Platte Natural Resources District, South Platte Natural Resources District, Twin Platte Natural Resources District, Conservation and Survey Division of the University of Nebraska-Lincoln, and the Nebraska Environmental Trust","usgsCitation":"Hobza, C.M., Abraham, J., Cannia, J.C., Johnson, M., and Sibray, S.S., 2014, Base of principal aquifer for parts of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska: U.S. Geological Survey Scientific Investigations Map 3310, 2 Sheets: 53.0 x 36.0 inches and 36.5 x 36.0 inches; Downloads Directory, https://doi.org/10.3133/sim3310.","productDescription":"2 Sheets: 53.0 x 36.0 inches and 36.5 x 36.0 inches; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-054502","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":294201,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3310/GIS_files"},{"id":294199,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3310/pdf/sim3310_sheet1.pdf"},{"id":294200,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3310/pdf/sim3310_sheet2.pdf"},{"id":294194,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3310/"},{"id":294202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3310.jpg"}],"projection":"Universal Transverse Mercator projection, zone 13 north","datum":"North American Datum of 1983","country":"United States","state":"Nebraska","otherGeospatial":"Lodgepole Creek;North Platte River Valley;Platte River Basin;South Platte River Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.25,41.0 ], [ -104.25,42.25 ], [ -101.875,42.25 ], [ -101.875,41.0 ], [ -104.25,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d3786e4b0f68901ebd97e","contributors":{"authors":[{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":500220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abraham, Jared D.","contributorId":42630,"corporation":false,"usgs":true,"family":"Abraham","given":"Jared D.","affiliations":[],"preferred":false,"id":500221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannia, James C.","contributorId":94356,"corporation":false,"usgs":true,"family":"Cannia","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":500223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":500219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sibray, Steven S.","contributorId":88589,"corporation":false,"usgs":true,"family":"Sibray","given":"Steven","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":500222,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70120312,"text":"ofr20141174 - 2014 - 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: 2013","interactions":[],"lastModifiedDate":"2014-09-19T08:31:14","indexId":"ofr20141174","displayToPublicDate":"2014-09-19T08:18:00","publicationYear":"2014","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":"2014-1174","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: 2013","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 2013 to December 2013. These data serve as the basis for the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.</p>\n<br/>\n<p>Following significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and <i>M. petalum</i> appear to have stabilized. 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 2013, concentrations of Ag and Cu 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. In <i>M. petalum</i>, all observed elements showed annual maxima in January–February and minima in April, except for Zn, which was lowest in December. In sediments, annual maxima also occurred in January–February, and minima were measured in June and September. In 2013, metal concentrations in both sediments and clam tissue were among the lowest concentrations on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site.</p>\n<br/>\n<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 the <i>M. petalum</i> community shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2013), with almost all animals initiating reproduction in the fall and spawning the following spring. The 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. <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 2013. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for those deep-dwelling animals like <i>Macoma petalum</i>. Animals immediately returned to the mudflat in 2008, which was the first indication that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2013 is reflective of the 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 2013 benthic community data, which show 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 animals that consume the sediment, filter feed, have pelagic larvae that must survive landing on the sediment, and brood their young. USGS scientists continue to observe the community’s response to the 2008 defaunation event because it allows them to examine the response of the community to a natural disturbance (possible causes include sediment accretion or freshwater inundation) and compare this recovery to the long-term recovery observed in 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/ofr20141174","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Dyke, J., Cain, D.J., Thompson, J.K., Kleckner, A.E., Parcheso, F., Hornberger, M.I., and Luoma, S.N., 2014, 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: 2013: U.S. Geological Survey Open-File Report 2014-1174, Report: vii, 81 p.; Tables; Appendixes, https://doi.org/10.3133/ofr20141174.","productDescription":"Report: vii, 81 p.; Tables; Appendixes","numberOfPages":"90","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056078","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":294198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141174.jpg"},{"id":294195,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1174/pdf/ofr2014-1174.pdf"},{"id":294196,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1174/downloads/ofr2014-1174_tables.xlsx"},{"id":294197,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1174/downloads/ofr2014-1174_appendixes.xlsx"},{"id":294193,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1174/"}],"country":"United States","state":"California","city":"Palo Alto","otherGeospatial":"South San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.198736,37.359278 ], [ -122.198736,37.600546 ], [ -121.899568,37.600546 ], [ -121.899568,37.359278 ], [ -122.198736,37.359278 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d378ee4b0f68901ebd9bd","contributors":{"authors":[{"text":"Dyke, Jessica jldyke@usgs.gov","contributorId":1035,"corporation":false,"usgs":true,"family":"Dyke","given":"Jessica","email":"jldyke@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":498107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":498109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":498106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleckner, Amy E. kleckner@usgs.gov","contributorId":4258,"corporation":false,"usgs":true,"family":"Kleckner","given":"Amy","email":"kleckner@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":498112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parcheso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":2590,"corporation":false,"usgs":true,"family":"Parcheso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":498111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":498108,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":498110,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70126013,"text":"tm6A51 - 2014 - One-Water Hydrologic Flow Model (MODFLOW-OWHM)","interactions":[],"lastModifiedDate":"2014-09-19T08:13:45","indexId":"tm6A51","displayToPublicDate":"2014-09-18T16:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A51","title":"One-Water Hydrologic Flow Model (MODFLOW-OWHM)","docAbstract":"<p>The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, MF-OWHM has the unique set of capabilities to simulate and analyze historical, present, and future conjunctive-use conditions. MF-OWHM is especially useful for the analysis of agricultural water use where few data are available for pumpage, land use, or agricultural information. The features presented in this IHM include additional linkages with SFR, SWR, Drain-Return (DRT), Multi-Node Wells (MNW1 and MNW2), and Unsaturated-Zone Flow (UZF). Thus, MF-OWHM helps to reduce the loss of water during simulation of the hydrosphere and helps to account for “all of the water everywhere and all of the time.”</p>\n<br/>\n<p>In addition to groundwater, surface-water, and landscape budgets, MF-OWHM provides more options for observations of land subsidence, hydraulic properties, and evapotranspiration (ET) than previous models. Detailed landscape budgets combined with output of estimates of actual evapotranspiration facilitates linkage to remotely sensed observations as input or as additional observations for parameter estimation or water-use analysis. The features of FMP have been extended to allow for temporally variable water-accounting units (farms) that can be linked to land-use models and the specification of both surface-water and groundwater allotments to facilitate sustainability analysis and connectivity to the Groundwater Management Process (GWM).</p>\n<br/>\n<p>An example model described in this report demonstrates the application of MF-OWHM with the addition of land subsidence and a vertically deforming mesh, delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in demand caused by deficiency in supply, and changes in multi-aquifer pumpage caused by constraints imposed through the Farm Process and the MNW2 Package, and changes in surface water such as runoff, streamflow, and canal flows through SFR and SWR linkages.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Groundwater in Book 6 <i>Modeling Techniques</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A51","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation. This report is Chapter 51 of Section A: Groundwater in Book 6 <i>Modeling Techniques</i>.","usgsCitation":"Hanson, R.T., Boyce, S.E., Schmid, W., Hughes, J.D., Mehl, S.W., Leake, S.A., Maddock, T., and Niswonger, R., 2014, One-Water Hydrologic Flow Model (MODFLOW-OWHM): U.S. Geological Survey Techniques and Methods 6-A51, x, 120 p., https://doi.org/10.3133/tm6A51.","productDescription":"x, 120 p.","numberOfPages":"134","onlineOnly":"Y","ipdsId":"IP-040669","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438744,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C6F6C5","text":"USGS data release","linkHelpText":"MODFLOW One-Water Hydrologic Flow Model (MF-OWHM) Conjunctive Use and Integrated Hydrologic Flow Modeling Software with compiled windows executable, version 2.0.1"},{"id":294191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6A51.jpg"},{"id":294189,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/06/a51/"},{"id":294190,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a51/pdf/tm6-a51.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541be60de4b0e96537dda07d","contributors":{"authors":[{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Scott E. 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":501871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":501867,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mehl, Steffen W. swmehl@usgs.gov","contributorId":975,"corporation":false,"usgs":true,"family":"Mehl","given":"Steffen","email":"swmehl@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":501865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leake, Stanley A. 0000-0003-3568-2542 saleake@usgs.gov","orcid":"https://orcid.org/0000-0003-3568-2542","contributorId":1846,"corporation":false,"usgs":true,"family":"Leake","given":"Stanley","email":"saleake@usgs.gov","middleInitial":"A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501866,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maddock, Thomas III","contributorId":32983,"corporation":false,"usgs":true,"family":"Maddock","given":"Thomas","suffix":"III","affiliations":[],"preferred":false,"id":501869,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Niswonger, Richard G.","contributorId":45402,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","affiliations":[],"preferred":false,"id":501870,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70103642,"text":"sir20145080 - 2014 - Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change","interactions":[],"lastModifiedDate":"2017-05-22T14:49:07","indexId":"sir20145080","displayToPublicDate":"2014-09-18T14:44:00","publicationYear":"2014","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":"2014-5080","title":"Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change","docAbstract":"<p>A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia.</p>\n<br/>\n<p>The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling.</p>\n<br/>\n<p>The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the benefit of hydrological, soil erosion, and coarser ecological modeling. Reach attributes are summarized for each segment. In six subbasins segments are assigned additional attributes about barriers (usually impoundments) to fish migration and stream isolation. Segments in the six sub-basins are also attributed with percent urban area for the watershed upstream from the stream segment for each decade from 2010–2100 from models of urban growth.</p>\n<br/>\n<p>On a broader scale, for application in a coarse-scale species-response model, the stream-network information is aggregated and summarized by 256 drainage subbasins (Hydrologic Response Units) used for watershed hydrologic and stream-temperature models. A model of soil erodibility based on the Revised Universal Soil Loss Equation also was developed at this scale to parameterize a model to evaluate stream condition.</p>\n<br/>\n<p>The reach-scale network was classified using multivariate clustering based on modeled channel width, valley width, and mean reach gradient as variables. The resulting classification consists of a 6-cluster and a 12-cluster classification for every reach in the Apalachicola-Chattahoochee-Flint Basin. We present an example of the utility of the classification that was tested using the occurrence of two species of darters and two species of minnows in the Apalachicola-Chattahoochee-Flint River Basin, the blackbanded darter and Halloween darter, and the bluestripe shiner and blacktail shiner.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145080","collaboration":"Prepared in cooperation with the National Climate Change and Wildlife Science Center","usgsCitation":"Elliott, C.M., Jacobson, R.B., and Freeman, M., 2014, Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change: U.S. Geological Survey Scientific Investigations Report 2014-5080, ix, 79 p., https://doi.org/10.3133/sir20145080.","productDescription":"ix, 79 p.","numberOfPages":"94","onlineOnly":"Y","ipdsId":"IP-043137","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":294188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145080.jpg"},{"id":294187,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5080/pdf/sir2014-5080.pdf"},{"id":294186,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5080/"}],"country":"United States","state":"Alabama, Florida, Georgia, Virginia","otherGeospatial":"Apalachicola-Chattahoochee-Flint River System","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.333333,29.0 ], [ -85.333333,38.333333 ], [ -75.866667,38.333333 ], [ -75.866667,29.0 ], [ -85.333333,29.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541be610e4b0e96537dda095","contributors":{"authors":[{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":493431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":493430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":493432,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70125288,"text":"70125288 - 2014 - Insights for empirically modeling evapotranspiration influenced by riparian and upland vegetation in semiarid regions","interactions":[],"lastModifiedDate":"2014-09-18T13:41:59","indexId":"70125288","displayToPublicDate":"2014-09-18T13:36:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Insights for empirically modeling evapotranspiration influenced by riparian and upland vegetation in semiarid regions","docAbstract":"Water resource managers aim to ensure long-term water supplies for increasing human populations. Evapotranspiration (ET) is a key component of the water balance and accurate estimates are important to quantify safe allocations to humans while supporting environmental needs. Scaling up ET measurements from small spatial scales has been problematic due to spatiotemporal variability. Remote sensing products provide spatially distributed data that account for seasonal climate and vegetation variability. We used MODIS products [i.e., Enhanced Vegetation Index (EVI) and nighttime land surface temperatures (LST<sub>n</sub>)] to create empirical ET models calibrated using measured ET from three riparian-influenced and two upland, water-limited flux tower sites. Results showed that combining all sites introduced systematic bias, so we developed separate models to estimate riparian and upland ET. While EVI and LST<sub>n</sub> were the main drivers for ET in riparian sites, precipitation replaced LST<sub>n</sub> as the secondary driver of ET in upland sites. Riparian ET was successfully modeled using an inverse exponential approach (r<sup>2</sup> = 0.92) while upland ET was adequately modeled using a multiple linear regression approach (r<sup>2</sup> = 0.77). These models can be used in combination to estimate ET at basin scales provided each region is classified and precipitation data is available.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Arid Environments","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2014.06.007","usgsCitation":"Bunting, D.P., Kurc, S.A., Glenn, E.P., Nagler, P.L., and Scott, R.L., 2014, Insights for empirically modeling evapotranspiration influenced by riparian and upland vegetation in semiarid regions: Journal of Arid Environments, v. 111, p. 42-52, https://doi.org/10.1016/j.jaridenv.2014.06.007.","productDescription":"11 p.","startPage":"42","endPage":"52","numberOfPages":"11","ipdsId":"IP-036223","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":294179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294178,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jaridenv.2014.06.007"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.1,31.33 ], [ -113.1,34.0 ], [ -109.68,34.0 ], [ -109.68,31.33 ], [ -113.1,31.33 ] ] ] } } ] }","volume":"111","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541be60be4b0e96537dda063","contributors":{"authors":[{"text":"Bunting, Daniel P.","contributorId":21880,"corporation":false,"usgs":true,"family":"Bunting","given":"Daniel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":501140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kurc, Shirley A.","contributorId":21477,"corporation":false,"usgs":true,"family":"Kurc","given":"Shirley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":501139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":501138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":501137,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scott, Russell L.","contributorId":39875,"corporation":false,"usgs":false,"family":"Scott","given":"Russell","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":501141,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70125442,"text":"70125442 - 2014 - Frequency-dependent effects of rupture for the 2004 Parkfield mainshock, results from UPSAR","interactions":[],"lastModifiedDate":"2017-06-30T13:37:13","indexId":"70125442","displayToPublicDate":"2014-09-18T12:01:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Frequency-dependent effects of rupture for the 2004 Parkfield mainshock, results from UPSAR","docAbstract":"<p>The frequency-dependent effects of rupture propagation of the Parkfield, California earthquake (Sept. 28, 2004, M6) to the northwest along the San Andreas fault can be seen in acceleration records at UPSAR (USGS Parkfield Seismic Array) in at least two ways. First, we can see the effects of directivity in the acceleration traces at UPSAR, which is about 11.5 km from the epicenter. Directivity or the seismic equivalent of a Doppler shift has been documented in many cases by comparing short duration, high-amplitude pulses (P or S) in the forward direction with longer duration body waves in the backward direction. In this case we detect a change from a relatively large amplitude, coherent, high-frequency signal at the start of rupture to a low-amplitude, low-coherent, low-frequency signal at about the time the rupture front transfers from the forward azimuth to the back azimuth at about 34-36 s (time is UTC and are the seconds after day 272 and 17 hours and 15 minutes. S arrival is just after 30s) for rays leaving the fault and propagating to UPSAR. The frequency change is obvious in the band about 5 to 30 Hz, which is significantly above the corner frequency of the earthquake (about 0.11Hz). From kinematic source models, the duration of faulting is about 9.2 s and the change in frequency is during faulting as the rupture extends to the northwest. Understanding the systematic change in frequency and amplitude of seismic waves in relation to the propagation of the rupture front is important for predicting strong ground motion.</p>\n<br/>\n<p>Second, we can filter the acceleration records from the array to determine if the low frequency energy emerges from the same part of the fault as the high frequency signal (e.g. has the same back azimuth and apparent velocity at UPSAR) an important clue to the dynamics of rupture. Analysis of sources of strong motion (characterized by relatively high frequencies) compared to kinematic slip models (relatively low frequency) for the March 11, 2011 Tohoku earthquake as well as Maule (Feb. 27, 2010) and Chi-Chi (Sept. 20, 1999) earthquakes show that high- and low-frequency sources do not have the same locations on the fault. In this paper we filter the accelerograms from UPSAR for the 2004 mainshock in various passbands and then re-compute the cross correlations to determine the vector slowness of the incoming waves. At Parkfield, it appears that for seismic waves with frequencies above 1 Hz there is no discernible frequency-dependent difference in source position (up to 8 Hz) based on estimates of back azimuth and apparent velocity. However at lower frequencies, sources appear to be from shallower depths and trail the high frequencies as the rupture proceeds down the fault. This result is greater than one standard deviation of an estimate of error, based on a new method of estimating error that is a measure of how broad the peak in correlation is and an estimate of the variance of the correlation values. These observations can be understood in terms of a rupture front that is more energetic and coherent near the front of rupture (radiating higher frequencies) and less coherent and less energetic (radiating in a lower frequency band) behind the initial rupture front. This result is a qualitative assessment of changes in azimuth and apparent velocity with frequency and time and does not include corrections to find the source location on the fault.</p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014JB011007","usgsCitation":"Fletcher, J.B., 2014, Frequency-dependent effects of rupture for the 2004 Parkfield mainshock, results from UPSAR: Journal of Geophysical Research B: Solid Earth, v. 119, no. 9, p. 7195-7208, https://doi.org/10.1002/2014JB011007.","productDescription":"14 p.","startPage":"7195","endPage":"7208","numberOfPages":"14","ipdsId":"IP-057417","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472756,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014jb011007","text":"Publisher Index Page"},{"id":294154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294146,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2014JB011007"}],"country":"United States","state":"California","city":"Parkfield","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.518699,35.829432 ], [ -120.518699,35.959873 ], [ -120.348669,35.959873 ], [ -120.348669,35.829432 ], [ -120.518699,35.829432 ] ] ] } } ] }","volume":"119","issue":"9","noUsgsAuthors":false,"publicationDate":"2014-09-23","publicationStatus":"PW","scienceBaseUri":"541be608e4b0e96537dda050","contributors":{"authors":[{"text":"Fletcher, Jon B.","contributorId":65614,"corporation":false,"usgs":true,"family":"Fletcher","given":"Jon","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":501439,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
]}