{"pageNumber":"1284","pageRowStart":"32075","pageSize":"25","recordCount":165309,"records":[{"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":70155948,"text":"70155948 - 2014 - Coastal subsidence and relative sea level rise","interactions":[],"lastModifiedDate":"2019-12-11T09:38:50","indexId":"70155948","displayToPublicDate":"2014-09-23T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Coastal subsidence and relative sea level rise","docAbstract":"<p><span>Subsurface fluid-pressure declines caused by pumping of groundwater or hydrocarbons can lead to aquifer-system compaction and consequent land subsidence. This subsidence can be rapid, as much as 30 cm per year in some instances, and large, totaling more than 13 m in extreme examples. Thus anthropogenic subsidence may be the dominant contributor to relative sea-level rise in coastal environments where subsurface fluids are heavily exploited. Maximum observed rates of human-induced subsidence greatly exceed the rates of natural subsidence of unconsolidated sediments (~0.1&ndash;1 cm yr</span><span>&minus;1</span><span>) and the estimated rates of ongoing global sea-level rise (~0.3 cm yr</span><span>&minus;1</span><span>).</span></p>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/9/9/091002","usgsCitation":"Ingebritsen, S.E., and Galloway, D.L., 2014, Coastal subsidence and relative sea level rise: Environmental Research Letters, v. 9, no. 9, 4 p., https://doi.org/10.1088/1748-9326/9/9/091002.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059113","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":472752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/9/9/091002","text":"Publisher Index Page"},{"id":306862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-23","publicationStatus":"PW","scienceBaseUri":"55d4572de4b0518e354694af","chorus":{"doi":"10.1088/1748-9326/9/9/091002","url":"http://dx.doi.org/10.1088/1748-9326/9/9/091002","publisher":"IOP Publishing","authors":"Ingebritsen S E, Galloway D L","journalName":"Environmental Research Letters","publicationDate":"9/1/2014","auditedOn":"4/2/2017","publiclyAccessibleDate":"9/23/2014"},"contributors":{"authors":[{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":567316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":567317,"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":70111066,"text":"cir1396 - 2014 - Tribal engagement strategy of the South Central Climate Science Center, 2014","interactions":[],"lastModifiedDate":"2020-02-26T17:52:29","indexId":"cir1396","displayToPublicDate":"2014-09-22T20:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1396","title":"Tribal engagement strategy of the South Central Climate Science Center, 2014","docAbstract":"The South Central Climate Science Center was established by the U.S. Department of the Interior in 2012 to increase understanding of climate change and coordinate an effective response to climate-change effects on Native American tribes and natural and cultural resources that the Department manages. The eight regional Climate Science Centers of the U.S. Department of the Interior work closely with natural-resource management agencies, university researchers, and others such as tribes and private landowners on climate-change issues. The relatively large number of Native Americans in the south central United States and their special knowledge of changing ecosystems make working with tribes and tribal members on climate-change issues particularly important in this part of the Nation. This circular describes priorities of the South Central Climate Science Center and provides information about resources available from Climate Science Centers and partner agencies regarding climate change. The circular also describes how this Climate Science Center, tribes and tribal members, and others can collaborate to minimize potential harmful effects of climate change on human society and our surrounding ecosystems.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1396","collaboration":"Prepared in cooperation with the South Central Climate Science Center","usgsCitation":"Andrews, W.J., Taylor, A., and Winton, K.T., 2014, Tribal engagement strategy of the South Central Climate Science Center, 2014: U.S. Geological Survey Circular 1396, v, 35 p., https://doi.org/10.3133/cir1396.","productDescription":"v, 35 p.","numberOfPages":"45","onlineOnly":"N","ipdsId":"IP-056394","costCenters":[{"id":560,"text":"South Central Climate Science 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,{"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":70132326,"text":"70132326 - 2014 - Biodemography of ectothermic tetrapods provides insights into the evolution and plasticity of mortality patterns","interactions":[],"lastModifiedDate":"2015-03-06T15:16:45","indexId":"70132326","displayToPublicDate":"2014-09-22T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"13","title":"Biodemography of ectothermic tetrapods provides insights into the evolution and plasticity of mortality patterns","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Sociality, hierarchy, health: comparative biodemography: a collection of papers","language":"English","publisher":"National Academies Press","publisherLocation":"Washington, D.C.","usgsCitation":"Miller, D.A., Janzen, F.J., Fellers, G.M., Kleeman, P.M., and Bronikowski, A.M., 2014, Biodemography of ectothermic tetrapods provides insights into the evolution and plasticity of mortality patterns, chap. 13 <i>of</i> Sociality, hierarchy, health: comparative biodemography: a collection of papers, p. 295-314.","productDescription":"20 p.","startPage":"295","endPage":"314","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057420","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":298334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295773,"type":{"id":15,"text":"Index Page"},"url":"https://www.nap.edu/catalog.php?record_id=18822"}],"country":"United States","state":"California, Illinois","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.88967895507812,\n              37.49011473195046\n            ],\n            [\n              -119.88967895507812,\n              38.18422791820727\n            ],\n            [\n              -119.19479370117186,\n              38.18422791820727\n            ],\n            [\n              -119.19479370117186,\n              37.49011473195046\n            ],\n            [\n              -119.88967895507812,\n              37.49011473195046\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.85853576660156,\n              40.538851525354666\n            ],\n            [\n              -120.85853576660156,\n              40.733730386116875\n            ],\n            [\n              -120.64842224121092,\n              40.733730386116875\n            ],\n            [\n              -120.64842224121092,\n              40.538851525354666\n            ],\n            [\n              -120.85853576660156,\n              40.538851525354666\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.24307250976562,\n              41.580525125613846\n            ],\n            [\n              -90.24307250976562,\n              41.949277245116576\n            ],\n            [\n              -89.615478515625,\n              41.949277245116576\n            ],\n            [\n              -89.615478515625,\n              41.580525125613846\n            ],\n            [\n              -90.24307250976562,\n              41.580525125613846\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54faddb9e4b02419550db6d0","contributors":{"authors":[{"text":"Miller, David A. 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,{"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":70126209,"text":"70126209 - 2014 - Coral communities as indicators of ecosystem-level impacts of the <i>Deepwater Horizon</i> spill","interactions":[],"lastModifiedDate":"2014-09-19T17:53:04","indexId":"70126209","displayToPublicDate":"2014-09-19T17:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Coral communities as indicators of ecosystem-level impacts of the <i>Deepwater Horizon</i> spill","docAbstract":"The Macondo oil spill released massive quantities of oil and gas from a depth of 1500 meters. Although a buoyant plume carried released hydrocarbons to the sea surface, as much as half stayed in the water column and much of that in the deep sea. After the hydrocarbons reached the surface, weathering processes, burning, and the use of a dispersant caused hydrocarbon-rich marine snow to sink into the deep sea. As a result, this spill had a greater potential to affect deep-sea communities than had any previous spill. Here, we review the literature on impacts on deep-sea communities from the Macondo blowout and provide additional data on sediment hydrocarbon loads and the impacts on sediment infauna in areas with coral communities around the Macondo well. We review the literature on the genetic connectivity of deep-sea species in the Gulf of Mexico and discuss the potential for wider effects on deep Gulf coral communities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"BioScience","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Institute of Biological Sciences","doi":"10.1093/biosci/biu129","usgsCitation":"Fisher, C., Demopoulos, A., Cordes, E.E., Baums, I.B., White, H.K., and Bourque, J.R., 2014, Coral communities as indicators of ecosystem-level impacts of the <i>Deepwater Horizon</i> spill: BioScience, v. 64, no. 9, p. 796-807, https://doi.org/10.1093/biosci/biu129.","productDescription":"12 p.","startPage":"796","endPage":"807","numberOfPages":"12","ipdsId":"IP-055458","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472755,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biu129","text":"Publisher Index Page"},{"id":294253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294252,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/biosci/biu129"}],"otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.0,24.0 ], [ -95.0,31.0 ], [ -85.0,31.0 ], [ -85.0,24.0 ], [ -95.0,24.0 ] ] ] } } ] }","volume":"64","issue":"9","noUsgsAuthors":false,"publicationDate":"2014-08-29","publicationStatus":"PW","scienceBaseUri":"541d378be4b0f68901ebd997","contributors":{"authors":[{"text":"Fisher, Charles R.","contributorId":97407,"corporation":false,"usgs":true,"family":"Fisher","given":"Charles R.","affiliations":[],"preferred":false,"id":501931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":28938,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda W.J.","affiliations":[],"preferred":false,"id":501928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":501930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baums, Iliana B.","contributorId":13554,"corporation":false,"usgs":true,"family":"Baums","given":"Iliana","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":501927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Helen K.","contributorId":31288,"corporation":false,"usgs":true,"family":"White","given":"Helen","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":501929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bourque, Jill R. 0000-0003-3809-2601 jbourque@usgs.gov","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":5452,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","email":"jbourque@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":501926,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70126191,"text":"70126191 - 2014 - Chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures","interactions":[],"lastModifiedDate":"2018-09-18T16:45:11","indexId":"70126191","displayToPublicDate":"2014-09-19T17:36:00","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}},"displayTitle":"Chronic sensitivity of white sturgeon (<i>Acipenser transmontanus</i>) and rainbow trout (<i>Oncorhynchus mykiss</i>) to cadmium, copper, lead, or zinc in laboratory water-only exposures","title":"Chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures","docAbstract":"Chronic toxicity of cadmium, copper, lead, or zinc to white sturgeon (<i>Acipenser transmontanus</i>) and rainbow trout (<i>Oncorhynchus mykiss</i>) was evaluated in water-only exposures started with newly hatched larvae or approximately 1-mo-old juveniles. The 20% effect concentration (EC20) for cadmium from the sturgeon tests was higher than the EC20 from the trout tests, whereas the EC20 for copper, lead, or zinc for the sturgeon were lower than those EC20s for the trout. When the EC20s from the present study were included in compiled toxicity databases for all freshwater species, species mean chronic value for white sturgeon was in a relatively low percentile of the species sensitivity distribution for copper (9th percentile) and in the middle percentile for cadmium (55th percentile), zinc (40th percentile), or lead (50th percentile). However, the species mean chronic value for rainbow trout was in a high percentile for copper, lead, and zinc (∼68th–82nd percentile), but in a low percentile for cadmium (23rd percentile). The trout EC20s for each of the 4 metals and the sturgeon EC20s for cadmium or lead were above US Environmental Protection Agency chronic ambient water quality criteria (AWQC) or Washington State chronic water quality standards (WQS), whereas the sturgeon EC20s for copper or zinc were approximately equal to or below the chronic AWQC and WQS. In addition, acute 50% effect concentrations (EC50s) for copper obtained in the first 4 d of the chronic sturgeon test were below the final acute value used to derive acute AWQC and below acute WQS for copper.","language":"English","publisher":"Wiley","doi":"10.1002/etc.2641","usgsCitation":"Wang, N., Ingersoll, C.G., Dorman, R.A., Brumbaugh, W.G., Mebane, C.A., Kunz, J.L., and Hardesty, D., 2014, Chronic sensitivity of white sturgeon (Acipenser transmontanus) and rainbow trout (Oncorhynchus mykiss) to cadmium, copper, lead, or zinc in laboratory water-only exposures: Environmental Toxicology and Chemistry, v. 33, no. 10, p. 2246-2258, https://doi.org/10.1002/etc.2641.","productDescription":"13 p.","startPage":"2246","endPage":"2258","numberOfPages":"13","ipdsId":"IP-055389","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":294251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294250,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/etc.2641"}],"volume":"33","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-05-26","publicationStatus":"PW","scienceBaseUri":"541d378be4b0f68901ebd991","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":501890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":501889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorman, Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":501893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":501888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":501887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":501892,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hardesty, Douglas K. dhardesty@usgs.gov","contributorId":3281,"corporation":false,"usgs":true,"family":"Hardesty","given":"Douglas K.","email":"dhardesty@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":501891,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70121895,"text":"sir20145165 - 2014 - Methods for estimating annual exceedance-probability discharges and largest recorded floods for unregulated streams in rural Missouri","interactions":[],"lastModifiedDate":"2014-09-19T15:30:16","indexId":"sir20145165","displayToPublicDate":"2014-09-19T15:24:00","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":"2014-5165","title":"Methods for estimating annual exceedance-probability discharges and largest recorded floods for unregulated streams in rural Missouri","docAbstract":"<p>Regression analysis techniques were used to develop a set of equations for rural ungaged stream sites for estimating discharges with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. Basin and climatic characteristics were computed using geographic information software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses. Annual exceedance-probability discharge estimates were computed for 278 streamgages by using the expected moments algorithm to fit a log-Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data from water year 1844 to 2012. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized multiple Grubbs-Beck test was used to detect potentially influential low floods. Annual peak flows less than a minimum recordable discharge at a streamgage were incorporated into the at-site station analyses.</p>\n<br>\n<p>An updated regional skew coefficient was determined for the State of Missouri using Bayesian weighted least-squares/generalized least squares regression analyses. At-site skew estimates for 108 long-term streamgages with 30 or more years of record and the 35 basin characteristics defined for this study were used to estimate the regional variability in skew. However, a constant generalized-skew value of -0.30 and a mean square error of 0.14 were determined in this study.</p>\n<br>\n<p>Previous flood studies indicated that the distinct physical features of the three physiographic provinces have a pronounced effect on the magnitude of flood peaks. Trends in the magnitudes of the residuals from preliminary statewide regression analyses from previous studies confirmed that regional analyses in this study were similar and related to three primary physiographic provinces. The final regional regression analyses resulted in three sets of equations. For Regions 1 and 2, the basin characteristics of drainage area and basin shape factor were statistically significant. For Region 3, because of the small amount of data from streamgages, only drainage area was statistically significant. Average standard errors of prediction ranged from 28.7 to 38.4 percent for flood region 1, 24.1 to 43.5 percent for flood region 2, and 25.8 to 30.5 percent for region 3. The regional regression equations are only applicable to stream sites in Missouri with flows not significantly affected by regulation, channelization, backwater, diversion, or urbanization. Basins with about 5 percent or less impervious area were considered to be rural. Applicability of the equations are limited to the basin characteristic values that range from 0.11 to 8,212.38 square miles (mi<sup>2</sup>) and basin shape from 2.25 to 26.59 for Region 1, 0.17 to 4,008.92 mi<sup>2</sup> and basin shape 2.04 to 26.89 for Region 2, and 2.12 to 2,177.58 mi<sup>2</sup> for Region 3.</p>\n<br>\n<p>Annual peak data from streamgages were used to qualitatively assess the largest floods recorded at streamgages in Missouri since the 1915 water year. Based on existing streamgage data, the 1983 flood event was the largest flood event on record since 1915. The next five largest flood events, in descending order, took place in 1993, 1973, 2008, 1994 and 1915. Since 1915, five of six of the largest floods on record occurred from 1973 to 2012.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145165","collaboration":"Prepared in cooperation with the Missouri Department of Transportation and Federal Emergency Management Agency","usgsCitation":"Southard, R.E., and Veilleux, A.G., 2014, Methods for estimating annual exceedance-probability discharges and largest recorded floods for unregulated streams in rural Missouri: U.S. Geological Survey Scientific Investigations Report 2014-5165, Report: viii, 39 p.; Downloads Directory, https://doi.org/10.3133/sir20145165.","productDescription":"Report: viii, 39 p.; Downloads Directory","numberOfPages":"52","onlineOnly":"N","ipdsId":"IP-055972","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":294248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145165.jpg"},{"id":294246,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5165/pdf/sir2014-5165.pdf"},{"id":294243,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5165/"},{"id":294247,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5165/Downloads/"}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Missouri","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.0,36.0 ], [ -96.0,41.0 ], [ -89.0,41.0 ], [ -89.0,36.0 ], [ -96.0,36.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d378ee4b0f68901ebd9b8","contributors":{"authors":[{"text":"Southard, Rodney E. 0000-0001-8024-9698 southard@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-9698","contributorId":3880,"corporation":false,"usgs":true,"family":"Southard","given":"Rodney","email":"southard@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":499289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":499290,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70125962,"text":"ds858 - 2014 - Post-Hurricane Sandy coastal oblique aerial photographs collected from Cape Lookout, North Carolina, to Montauk, New York, November 4-6, 2012","interactions":[],"lastModifiedDate":"2016-12-02T12:19:29","indexId":"ds858","displayToPublicDate":"2014-09-19T15:16:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"858","title":"Post-Hurricane Sandy coastal oblique aerial photographs collected from Cape Lookout, North Carolina, to Montauk, New York, November 4-6, 2012","docAbstract":"<p>The U.S. Geological Survey (USGS) conducts baseline and storm response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms. On November 4-6, 2012, approximately one week after the landfall of Hurricane Sandy, the USGS conducted an oblique aerial photographic survey from Cape Lookout, N.C., to Montauk, N.Y., aboard a Piper Navajo Chieftain (aircraft) at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. This mission was flown to collect post-Hurricane Sandy data for assessing incremental changes in the beach and nearshore area since the last survey in 2009. The data can be used in the assessment of future coastal change.</p>\n<br>\n<p>The photographs provided here are Joint Photographic Experts Group (JPEG) images. The photograph locations are an estimate of the position of the aircraft and do not indicate the location of the feature in the images. These photos document the configuration of the barrier islands and other coastal features at the time of the survey. Exiftool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet.</p>\n<br>\n<p>Table 1 provides detailed information about the GPS location, image name, date, and time each of the 9,481 photographs were taken, along with links to each photograph. The photographs are organized in segments, also referred to as contact sheets, and represent approximately 5 minutes of flight time.</p>\n<br>\n<p>In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds858","usgsCitation":"Morgan, K., and Krohn, M.D., 2014, Post-Hurricane Sandy coastal oblique aerial photographs collected from Cape Lookout, North Carolina, to Montauk, New York, November 4-6, 2012: U.S. Geological Survey Data Series 858, HTML Document, https://doi.org/10.3133/ds858.","productDescription":"HTML Document","onlineOnly":"Y","temporalStart":"2012-11-04","temporalEnd":"2012-11-06","ipdsId":"IP-054522","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":294245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds858.PNG"},{"id":294233,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0858/"},{"id":294244,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0858/ds858_title.html"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, North Carolina, Virginia","otherGeospatial":"Cape Lookout;Montauk","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.5,34.0 ], [ -76.5,42.0 ], [ -72.0,42.0 ], [ -72.0,34.0 ], [ -76.5,34.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d378fe4b0f68901ebd9c6","contributors":{"authors":[{"text":"Morgan, Karen L.M. 0000-0002-2994-5572","orcid":"https://orcid.org/0000-0002-2994-5572","contributorId":95553,"corporation":false,"usgs":true,"family":"Morgan","given":"Karen L.M.","affiliations":[],"preferred":false,"id":501787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krohn, M. Dennis dkrohn@usgs.gov","contributorId":3378,"corporation":false,"usgs":true,"family":"Krohn","given":"M.","email":"dkrohn@usgs.gov","middleInitial":"Dennis","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":501786,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70116855,"text":"sir20145137 - 2014 - Provisional maps of thermal areas in Yellowstone National Park, based on satellite thermal infrared imaging and field observations","interactions":[],"lastModifiedDate":"2019-03-14T08:22:24","indexId":"sir20145137","displayToPublicDate":"2014-09-19T14:38:00","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":"2014-5137","title":"Provisional maps of thermal areas in Yellowstone National Park, based on satellite thermal infrared imaging and field observations","docAbstract":"<p>Maps that define the current distribution of geothermally heated ground are useful toward setting a baseline for thermal activity to better detect and understand future anomalous hydrothermal and (or) volcanic activity. Monitoring changes in the dynamic thermal areas also supports decisions regarding the development of Yellowstone National Park infrastructure, preservation and protection of park resources, and ensuring visitor safety. Because of the challenges associated with field-based monitoring of a large, complex geothermal system that is spread out over a large and remote area, satellite-based thermal infrared images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to map the location and spatial extent of active thermal areas, to generate thermal anomaly maps, and to quantify the radiative component of the total geothermal heat flux. ASTER thermal infrared data acquired during winter nights were used to minimize the contribution of solar heating of the surface. The ASTER thermal infrared mapping results were compared to maps of thermal areas based on field investigations and high-resolution aerial photos. Field validation of the ASTER thermal mapping is an ongoing task. The purpose of this report is to make available ASTER-based maps of Yellowstone&rsquo;s thermal areas. We include an appendix containing the names and characteristics of Yellowstone&rsquo;s thermal areas, georeferenced TIFF files containing ASTER thermal imagery, and several spatial data sets in Esri shapefile format.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145137","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Vaughan, R.G., Heasler, H., Jaworowski, C., Lowenstern, J.B., and Keszthelyi, L., 2014, Provisional maps of thermal areas in Yellowstone National Park, based on satellite thermal infrared imaging and field observations: U.S. Geological Survey Scientific Investigations Report 2014-5137, Report: v, 22 p.; Datasets, https://doi.org/10.3133/sir20145137.","productDescription":"Report: v, 22 p.; Datasets","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049510","costCenters":[{"id":131,"text":"Astrogeology Science 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,{"id":70126205,"text":"ds824 - 2014 - Benthos and plankton community data for selected rivers and harbors along Wisconsin's Lake Michigan shoreline, 2012","interactions":[],"lastModifiedDate":"2014-09-19T14:32:14","indexId":"ds824","displayToPublicDate":"2014-09-19T14:25:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"824","title":"Benthos and plankton community data for selected rivers and harbors along Wisconsin's Lake Michigan shoreline, 2012","docAbstract":"Four river systems on the Wisconsin shoreline of Lake Michigan are designated Areas of Concern (AOCs) because of severe environmental degradation: the Lower Menominee River, Lower Green Bay and Fox River, Sheboygan River, and Milwaukee Estuary. Each AOC has one or more Beneficial Use Impairments (BUIs) that form the basis of the AOC designation and that must be remediated or otherwise addressed before the AOC designation can be removed. All four of these AOCs have BUIs for benthos (bottom-dwelling or benthic invertebrates), and all but the Menominee River have a BUI for plankton (free-floating algae and invertebrates, or phytoplankton and zooplankton, respectively). The U.S. Geological Survey collected samples in 2012 at these four AOCs and at six non-AOCs to support the evaluation of the status of aquatic communities in the benthos and plankton at the AOCs. Samples were collected during three periods representing spring, summer, and fall. Benthos samples were collected using a dredge grab sampler and artificial substrates; plankton samples were collected using a tow net for zooplankton and a vertical water sampler for phytoplankton. Benthos and plankton were identified to the lowest possible taxonomic category and counted; samples for documenting water temperature, pH, and specific conductance, as well as sediment particle size and organic carbon were also collected during biological sampling.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds824","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources and the U.S. Environmental Protection Agency-Great Lakes National Program Office","usgsCitation":"Scudder Eikenberry, B.C., Bell, A.H., Burns, D., and Olds, H., 2014, Benthos and plankton community data for selected rivers and harbors along Wisconsin's Lake Michigan shoreline, 2012: U.S. Geological Survey Data Series 824, Report: vii, 30 p.; 8 Appendixes, https://doi.org/10.3133/ds824.","productDescription":"Report: vii, 30 p.; 8 Appendixes","numberOfPages":"44","onlineOnly":"Y","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-052401","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":294236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds824.jpg"},{"id":294235,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0824/appendix"},{"id":294234,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0824/pdf/ds824.pdf"},{"id":294226,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0824/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lake Michigan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.0,43.0 ], [ -90.0,46.0 ], [ -86.0,46.0 ], [ -86.0,43.0 ], [ -90.0,43.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d3788e4b0f68901ebd98a","contributors":{"authors":[{"text":"Scudder Eikenberry, Barbara C.","contributorId":63771,"corporation":false,"usgs":true,"family":"Scudder Eikenberry","given":"Barbara","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":501925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Daniel J. 0000-0002-2305-6117 dburns@usgs.gov","orcid":"https://orcid.org/0000-0002-2305-6117","contributorId":5001,"corporation":false,"usgs":true,"family":"Burns","given":"Daniel J.","email":"dburns@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olds, Hayley T. 0000-0002-6701-6459 htemplar@usgs.gov","orcid":"https://orcid.org/0000-0002-6701-6459","contributorId":5002,"corporation":false,"usgs":true,"family":"Olds","given":"Hayley T.","email":"htemplar@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":false,"id":501924,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70123760,"text":"ofr20141138 - 2014 - Magnetic resonance sounding survey data collected in the North Platte, Twin Platte, and South Platte Natural Resource Districts, Western Nebraska, Fall 2012","interactions":[],"lastModifiedDate":"2014-09-19T12:14:52","indexId":"ofr20141138","displayToPublicDate":"2014-09-19T12:11:00","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":"2014-1138","title":"Magnetic resonance sounding survey data collected in the North Platte, Twin Platte, and South Platte Natural Resource Districts, Western Nebraska, Fall 2012","docAbstract":"This report is a release of digital data and associated survey descriptions from a series of magnetic resonance soundings (MRS, also known as surface nuclear magnetic resonance) that was conducted during October and November of 2012 in areas of western Nebraska as part of a cooperative hydrologic study by the North Platte Natural Resource District (NRD), South Platte NRD, Twin Platte NRD, the Nebraska Environmental Trust, and the U.S. Geological Survey (USGS).  The objective of the study was to delineate the base-of-aquifer and refine the understanding of the hydrologic properties in the aquifer system.  The MRS technique non-invasively measures water content in the subsurface, which makes it a useful tool for hydrologic investigations in the near surface (up to depths of approximately 150 meters).  In total, 14 MRS production-level soundings were acquired by the USGS over an area of approximately 10,600 square kilometers.  The data are presented here in digital format, along with acquisition information, survey and site descriptions, and metadata.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141138","collaboration":"Prepared in cooperation with the North Platte Natural Resources District, the South Platte Natural Resources District, the Twin Platte Natural Resources District, the Nebraska Environmental Trust, and the University of Nebraska Conservation and Survey Division","usgsCitation":"Kass, M.A., Bloss, B., Irons, T.P., Cannia, J.C., and Abraham, J., 2014, Magnetic resonance sounding survey data collected in the North Platte, Twin Platte, and South Platte Natural Resource Districts, Western Nebraska, Fall 2012: U.S. Geological Survey Open-File Report 2014-1138, Report: viii, 18 p.; Downloads Directory, https://doi.org/10.3133/ofr20141138.","productDescription":"Report: viii, 18 p.; Downloads Directory","numberOfPages":"29","ipdsId":"IP-050655","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":294224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141138.jpg"},{"id":294223,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1138/pdf/ofr2014-1138.pdf"},{"id":294221,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1138/"},{"id":294222,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1138/GIS_data"}],"country":"United States","state":"Nebraska","otherGeospatial":"North Platte;Twin Platte;South Platte Natural Resource Districts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.14,40.74 ], [ -104.14,41.96 ], [ -99.44,41.96 ], [ -99.44,40.74 ], [ -104.14,40.74 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d378de4b0f68901ebd9ac","contributors":{"authors":[{"text":"Kass, Mason A. 0000-0001-6119-2593 mkass@usgs.gov","orcid":"https://orcid.org/0000-0001-6119-2593","contributorId":613,"corporation":false,"usgs":true,"family":"Kass","given":"Mason","email":"mkass@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":500224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bloss, Benjamin R.","contributorId":19446,"corporation":false,"usgs":true,"family":"Bloss","given":"Benjamin R.","affiliations":[],"preferred":false,"id":500226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irons, Trevor P. tirons@usgs.gov","contributorId":4851,"corporation":false,"usgs":true,"family":"Irons","given":"Trevor","email":"tirons@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":500225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cannia, James C.","contributorId":94356,"corporation":false,"usgs":true,"family":"Cannia","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":500228,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Abraham, Jared D.","contributorId":42630,"corporation":false,"usgs":true,"family":"Abraham","given":"Jared D.","affiliations":[],"preferred":false,"id":500227,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70123767,"text":"ds881 - 2014 - Evidence of Absence software","interactions":[],"lastModifiedDate":"2018-09-07T16:40:45","indexId":"ds881","displayToPublicDate":"2014-09-19T10:29:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"881","title":"Evidence of Absence software","docAbstract":"<p>Evidence of Absence software (EoA) is a user-friendly application used for estimating bird and bat fatalities at wind farms and designing search protocols. The software is particularly useful in addressing whether the number of fatalities has exceeded a given threshold and what search parameters are needed to give assurance that thresholds were not exceeded. The software is applicable even when zero carcasses have been found in searches. Depending on the effectiveness of the searches, such an absence of evidence of mortality may or may not be strong evidence that few fatalities occurred. Under a search protocol in which carcasses are detected with nearly 100 percent certainty, finding zero carcasses would be convincing evidence that overall mortality rate was near zero. By contrast, with a less effective search protocol with low probability of detecting a carcass, finding zero carcasses does not rule out the possibility that large numbers of animals were killed but not detected in the searches. EoA uses information about the search process and scavenging rates to estimate detection probabilities to determine a maximum credible number of fatalities, even when zero or few carcasses are observed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds881","usgsCitation":"Dalthorp, D., Huso, M.M., Dail, D., and Kenyon, J., 2014, Evidence of Absence software: U.S. Geological Survey Data Series 881, Report: iv, 34 p.; Zip file, https://doi.org/10.3133/ds881.","productDescription":"Report: iv, 34 p.; Zip file","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056182","costCenters":[],"links":[{"id":294211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds881.PNG"},{"id":294210,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0881/downloads/evidence_of_absence_v1.00.zip","text":"Evidence of Absence Software","size":"2 MB","linkFileType":{"id":6,"text":"zip"}},{"id":343468,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1055","text":"Data Series 1055—Evidence of Absence (v2.0) Software"},{"id":294209,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0881/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":294208,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0881/pdf/ds881.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 881 PDF"},{"id":318205,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/media/videos/evidence-absence","text":"Evidence of Absence Video"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d378ce4b0f68901ebd99e","contributors":{"authors":[{"text":"Dalthorp, Daniel 0000-0002-4815-6309 ddalthorp@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-6309","contributorId":4902,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Daniel","email":"ddalthorp@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":500237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huso, Manuela M. P. mhuso@usgs.gov","contributorId":4487,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","middleInitial":"M. P.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":500236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dail, David","contributorId":23464,"corporation":false,"usgs":true,"family":"Dail","given":"David","affiliations":[],"preferred":false,"id":500238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenyon, Jessica","contributorId":62154,"corporation":false,"usgs":true,"family":"Kenyon","given":"Jessica","email":"","affiliations":[],"preferred":false,"id":500239,"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":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water 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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":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":70102567,"text":"70102567 - 2014 - Stochastic ground motion simulation","interactions":[],"lastModifiedDate":"2015-11-12T17:15:10","indexId":"70102567","displayToPublicDate":"2014-09-19T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Stochastic ground motion simulation","docAbstract":"<p><span>Strong earthquake ground motion records are fundamental in engineering applications. Ground motion time series are used in&nbsp;</span><span class=\"ExternalRef\"><a href=\"http://link.springer.com/search?facet-content-type=ReferenceWorkEntry&amp;query=response-history%20dynamic%20analysis\"><span class=\"RefSource\">response-history dynamic analysis</span></a></span><span>&nbsp;of structural or geotechnical systems. In such analysis, the validity of predicted responses depends on the validity of the input excitations. Ground motion records are also used to develop&nbsp;</span><span class=\"ExternalRef\"><a href=\"http://link.springer.com/search?facet-content-type=ReferenceWorkEntry&amp;query=ground%20motion%20prediction%20equations\"><span class=\"RefSource\">ground motion prediction equations</span></a></span><span>(GMPEs) for intensity measures such as spectral accelerations that are used in&nbsp;</span><span class=\"ExternalRef\"><a href=\"http://link.springer.com/search?facet-content-type=ReferenceWorkEntry&amp;query=response-spectrum%20dynamic%20analysis\"><span class=\"RefSource\">response-spectrum dynamic analysis</span></a></span><span>. Despite the thousands of available strong ground motion records, there remains a shortage of records for large-magnitude earthquakes at short distances or in specific regions, as well as records that sample specific combinations of source, path, and site characteristics.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Earthquake Engineering","language":"English","publisher":"Springer Berlin Heidelberg","doi":"10.1007/978-3-642-36197-5_239-1","usgsCitation":"Rezaeian, S., and Xiaodan, S., 2014, Stochastic ground motion simulation, chap. <i>of</i> Encyclopedia of Earthquake Engineering, p. 1-15, https://doi.org/10.1007/978-3-642-36197-5_239-1.","productDescription":"15 p.","startPage":"1","endPage":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056302","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":311282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2014-09-19","publicationStatus":"PW","scienceBaseUri":"5645c64fe4b0e2669b30f21c","contributors":{"editors":[{"text":"Beer, Michael","contributorId":149829,"corporation":false,"usgs":false,"family":"Beer","given":"Michael","email":"","affiliations":[],"preferred":false,"id":579709,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Kougioumtzoglou, Ioannis A.","contributorId":149830,"corporation":false,"usgs":false,"family":"Kougioumtzoglou","given":"Ioannis","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":579710,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Patelli, Edoardo","contributorId":149831,"corporation":false,"usgs":false,"family":"Patelli","given":"Edoardo","email":"","affiliations":[],"preferred":false,"id":579711,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Siu-Kui Au, Ivan","contributorId":149832,"corporation":false,"usgs":false,"family":"Siu-Kui Au","given":"Ivan","email":"","affiliations":[],"preferred":false,"id":579712,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":518733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xiaodan, Sun","contributorId":99901,"corporation":false,"usgs":true,"family":"Xiaodan","given":"Sun","email":"","affiliations":[],"preferred":false,"id":518734,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"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":70125286,"text":"70125286 - 2014 - The influence of controlled floods on fine sediment storage in debris fan-affected canyons of the Colorado River basin","interactions":[],"lastModifiedDate":"2018-01-08T12:20:54","indexId":"70125286","displayToPublicDate":"2014-09-18T13:16:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The influence of controlled floods on fine sediment storage in debris fan-affected canyons of the Colorado River basin","docAbstract":"<p>Prior to the construction of large dams on the Green and Colorado Rivers, annual floods aggraded sandbars in lateral flow-recirculation eddies with fine sediment scoured from the bed and delivered from upstream. Flows greater than normal dam operations may be used to mimic this process in an attempt to increase time-averaged sandbar size. These controlled floods may rebuild sandbars, but sediment deficit conditions downstream from the dams restrict the frequency that controlled floods produce beneficial results. Here, we integrate complimentary, long-term monitoring data sets from the Colorado River in Marble and Grand Canyons downstream from Glen Canyon dam and the Green River in the Canyon of Lodore downstream from Flaming Gorge dam. Since the mid-1990s, several controlled floods have occurred in these canyon rivers. These controlled floods scour fine sediment from the bed and build sandbars in eddies, thus increasing channel relief. These changes are short-lived, however, as interflood dam operations erode sandbars within several months to years. Controlled flood response and interflood changes in bed elevation are more variable in Marble Canyon and Grand Canyon, likely reflecting more variable fine sediment supply and stronger transience in channel bed sediment storage. Despite these differences, neither system shows a trend in fine-sediment storage during the period in which controlled floods were monitored. These results demonstrate that controlled floods build eddy sandbars and increase channel relief for short interflood periods, and this response may be typical in other dam-influenced canyon rivers. The degree to which these features persist depends on the frequency of controlled floods, but careful consideration of sediment supply is necessary to avoid increasing the long-term sediment deficit.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2014.07.029","usgsCitation":"Mueller, E.R., Grams, P.E., Schmidt, J.C., Hazel, J., Alexander, J.S., and Kaplinski, M., 2014, The influence of controlled floods on fine sediment storage in debris fan-affected canyons of the Colorado River basin: Geomorphology, v. 226, p. 65-75, https://doi.org/10.1016/j.geomorph.2014.07.029.","productDescription":"11 p.","startPage":"65","endPage":"75","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052795","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":294171,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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