{"pageNumber":"156","pageRowStart":"3875","pageSize":"25","recordCount":16502,"records":[{"id":70045360,"text":"sir20135052 - 2013 - Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10","interactions":[],"lastModifiedDate":"2013-04-10T21:52:21","indexId":"sir20135052","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5052","title":"Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10","docAbstract":"Elevated levels of fluvial sediment can reduce the biological productivity of aquatic systems, impair freshwater quality, decrease reservoir storage capacity, and decrease the capacity of hydraulic structures. The need to measure fluvial sediment has led to the development of sediment surrogate technologies, particularly in locations where streamflow alone is not a good estimator of sediment load because of regulated flow, load hysteresis, episodic sediment sources, and non-equilibrium sediment transport. An effective surrogate technology is low maintenance and sturdy over a range of hydrologic conditions, and measured variables can be modeled to estimate suspended-sediment concentration (SSC), load, and duration of elevated levels on a real-time basis. Among the most promising techniques is the measurement of acoustic backscatter strength using acoustic Doppler velocity meters (ADVMs) deployed in rivers. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, Walla Walla District, evaluated the use of acoustic backscatter, turbidity, laser diffraction, and streamflow as surrogates for estimating real-time SSC and loads in the Clearwater and Snake Rivers, which adjoin in Lewiston, Idaho, and flow into Lower Granite Reservoir. The study was conducted from May 2008 to September 2010 and is part of the U.S. Army Corps of Engineers Lower Snake River Programmatic Sediment Management Plan to identify and manage sediment sources in basins draining into lower Snake River reservoirs.\n\nCommercially available acoustic instruments have shown great promise in sediment surrogate studies because they require little maintenance and measure profiles of the surrogate parameter across a sampling volume rather than at a single point. The strength of acoustic backscatter theoretically increases as more particles are suspended in the water to reflect the acoustic pulse emitted by the ADVM. ADVMs of different frequencies (0.5, 1.5, and 3 Megahertz) were tested to target various sediment grain sizes. Laser diffraction and turbidity also were tested as surrogate technologies. Models between SSC and surrogate variables were developed using ordinary least-squares regression. Acoustic backscatter using the high frequency ADVM at each site was the best predictor of sediment, explaining 93 and 92 percent of the variability in SSC and matching sediment sample data within +8.6 and +10 percent, on average, at the Clearwater River and Snake River study sites, respectively. Additional surrogate models were developed to estimate sand and fines fractions of suspended sediment based on acoustic backscatter. Acoustic backscatter generally appears to be a better estimator of suspended sediment concentration and load over short (storm event and monthly) and long (annual) time scales than transport curves derived solely from the regression of conventional sediment measurements and streamflow. Changing grain sizes, the presence of organic matter, and aggregation of sediments in the river likely introduce some variability in the model between acoustic backscatter and SSC.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135052","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Wood, M.S., and Teasdale, G.N., 2013, Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10: U.S. Geological Survey Scientific Investigations Report 2013-5052, vi, 30 p., https://doi.org/10.3133/sir20135052.","productDescription":"vi, 30 p.","numberOfPages":"40","additionalOnlineFiles":"N","temporalStart":"2008-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":270796,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5052/"},{"id":270797,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5052/pdf/sir20135052.pdf"},{"id":270798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135052.jpg"}],"country":"United States","state":"Idaho;Washington","otherGeospatial":"Clearwater River;Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,42.0 ], [ -124.8,49.0 ], [ -111.0,49.0 ], [ -111.0,42.0 ], [ -124.8,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51667bdae4b0bba30b388bae","contributors":{"authors":[{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teasdale, Gregg N.","contributorId":77440,"corporation":false,"usgs":true,"family":"Teasdale","given":"Gregg","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":477286,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045353,"text":"sir20135031 - 2013 - Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011","interactions":[],"lastModifiedDate":"2018-01-08T12:22:23","indexId":"sir20135031","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5031","title":"Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011","docAbstract":"The lower Platte River corridor provides important habitats for two State- and federally listed bird species: the interior least tern (terns; Sternula antillarum athallassos) and the piping plover (plovers; Charadrius melodus). However, many of the natural morphological and hydrological characteristics of the Platte River have been altered substantially by water development, channelization, hydropower operations, and invasive vegetation encroachment, which have decreased the abundance of high-quality nesting and foraging habitat for terns and plovers. The lower Platte River (LPR), defined as 103 miles (mi) of the Platte River between its confluence with the Loup River and its confluence with the Missouri River, has narrowed since the late-19th and early-20th centuries, yet it partially retains many geomorphologic and hydrologic characteristics important to terns and plovers. These birds nest on the sandbars in the river and along shorelines at sand- and gravel-pit lakes in the adjacent valley. The need to balance continued economic, infrastructure, and resource development with the conservation of important physical and aquatic habitat resources requires increased understanding of the physical and biological dynamics of the lower Platte River. Spatially and temporally rich datasets for emergent sandbar habitats are necessary to quantify emergent sandbar dynamics relative to hypothesized controls and stressors. In cooperation with the Lower Platte South Natural Resources District, the U.S. Geological Survey initiated a pilot study of emergent sandbar dynamics along a 22-mi segment of the LPR downstream from its confluence with Salt Creek, near Ashland, Nebraska. The purposes of the study were to: (1) develop methods to rapidly assess sandbar geometries and locations in a wide, sand-bed river, and (2) apply and validate the method to assess emergent sandbar dynamics over three seasons in 2011. An examination of the height of sandbars relative to the local stage of the formative discharge event, and how subsequent river discharges, of both high and low magnitude, alter sandbar geometries and abundance within the LPR was of particular interest. A “rapid-assessment” method was developed with the goal of characterizing the spatial distribution and habitat-relevant geometries of the complete population of sandbars along the study segment. Three primary measures were used to assess emergent sandbar dynamics in the study segment: sandbar area, sandbar height, and sandbar location. Data to derive these measures were collected during three, week-long survey periods in 2011, herein named “spring survey period,” “summer survey period,” and “fall survey period.” Emergent sandbars were grouped into one of three generalized types: (1) bank-attached, (2) island-attached, and (3) mid-channel.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135031","collaboration":"Prepared in cooperation with the Lower Platte South Natural Resources District","usgsCitation":"Alexander, J.S., Schultze, D.M., and Zelt, R.B., 2013, Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011: U.S. Geological Survey Scientific Investigations Report 2013-5031, vi, 42 p., https://doi.org/10.3133/sir20135031.","productDescription":"vi, 42 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-043639","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":270773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135031.gif"},{"id":270771,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5031/"},{"id":270772,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5031/sir13_5031.pdf"}],"scale":"100000","projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Nebraska","county":"Cass;Sarpy;Saunders","otherGeospatial":"Platte River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.416667,40.966667 ], [ -96.416667,41.166667 ], [ -95.916667,41.166667 ], [ -95.916667,40.966667 ], [ -96.416667,40.966667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51667bd9e4b0bba30b388baa","contributors":{"authors":[{"text":"Alexander, Jason S. 0000-0002-1602-482X jalexand@usgs.gov","orcid":"https://orcid.org/0000-0002-1602-482X","contributorId":2802,"corporation":false,"usgs":true,"family":"Alexander","given":"Jason","email":"jalexand@usgs.gov","middleInitial":"S.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultze, Devin M.","contributorId":90191,"corporation":false,"usgs":true,"family":"Schultze","given":"Devin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zelt, Ronald B. 0000-0001-9024-855X rbzelt@usgs.gov","orcid":"https://orcid.org/0000-0001-9024-855X","contributorId":300,"corporation":false,"usgs":true,"family":"Zelt","given":"Ronald","email":"rbzelt@usgs.gov","middleInitial":"B.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477276,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048497,"text":"70048497 - 2013 - Adaptive management of flows from dams: a win-win framework for water users","interactions":[],"lastModifiedDate":"2014-03-19T10:01:04","indexId":"70048497","displayToPublicDate":"2013-04-09T08:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Adaptive management of flows from dams: a win-win framework for water users","docAbstract":"Alabama is blessed with more than 77,000 miles of rivers and streams that carve through the terrestrial landscape of the state.  When you think about it, every road you drive on crosses a river and many of our major cities are located on the bank of a river.  In fact, Alabama's capital cities - Cahawba (Dallas County; 1820-1826), Tuscaloosa (Tuscaloosa County; 1826-1846), and Montgomery County; 1846-present) - were all located on major rivers.  It is estimated by the U.S. Geological Survey that 10 percent of the freshwater resources in the continental United States flows through Alabama.  When you look at a map of its hydrology, the state is blue!","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Auburn Speaks: On Water","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Auburn University","usgsCitation":"Irwin, E.R., 2013, Adaptive management of flows from dams: a win-win framework for water users, chap. <i>of</i> Auburn Speaks: On Water, p. 264-271.","productDescription":"8 p.","startPage":"264","endPage":"271","ipdsId":"IP-043022","costCenters":[{"id":104,"text":"Alabama Cooperative Fish & Wildlife Unit","active":false,"usgs":true}],"links":[{"id":284202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284201,"type":{"id":11,"text":"Document"},"url":"https://www.auburnspeaks.org/on-water/"}],"country":"United States","state":"Alabama","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.4732,30.1941 ], [ -88.4732,35.0079 ], [ -84.8882,35.0079 ], [ -84.8882,30.1941 ], [ -88.4732,30.1941 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4b2ce4b0b290850f034e","contributors":{"authors":[{"text":"Irwin, Elise R. 0000-0002-6866-4976 eirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-6866-4976","contributorId":2588,"corporation":false,"usgs":true,"family":"Irwin","given":"Elise","email":"eirwin@usgs.gov","middleInitial":"R.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":484838,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045326,"text":"fs20133016 - 2013 - Effects of past and future groundwater development on the hydrologic system of Verde Valley, Arizona","interactions":[],"lastModifiedDate":"2026-06-05T16:27:58.933555","indexId":"fs20133016","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","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":"2013-3016","title":"Effects of past and future groundwater development on the hydrologic system of Verde Valley, Arizona","docAbstract":"Communities in central Arizona’s Verde Valley must manage limited water supplies in the face of rapidly growing populations. Developing groundwater resources to meet human needs has raised questions about the effects of groundwater withdrawals by pumping on the area’s rivers and streams, particularly the Verde River. U.S. Geological Survey hydrologists used a regional groundwater flow model to simulate the effects of groundwater pumping on streamflow in the Verde River. The study found that streamflow in the Verde River between 1910 and 2005 had been reduced as the result of streamflow depletion by groundwater pumping, also known as capture. Additionally, using three hypothetical scenarios for a period from 2005 to 2110, the study’s findings suggest that streamflow reductions will continue and may increase in the future.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133016","usgsCitation":"Garner, B.D., and Pool, D.R., 2013, Effects of past and future groundwater development on the hydrologic system of Verde Valley, Arizona: U.S. Geological Survey Fact Sheet 2013-3016, 2 p., https://doi.org/10.3133/fs20133016.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":270714,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3016/fs2013-3016.pdf"},{"id":270713,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3016/"},{"id":270715,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133016.gif"},{"id":505100,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98375.htm","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","projection":"Universal transverse mercator, Zone 12","country":"United States","state":"Arizona","otherGeospatial":"Dry Creek, Oak Creek, Verde River, Verde Valley, West Clear Creek, Wet Beaver Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.081146,34.565383 ], [ -112.081146,35.145740 ], [ -111.277771,35.145740 ], [ -111.277771,34.565383 ], [ -112.081146,34.565383 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51652a5ee4b077fa94dadf47","contributors":{"authors":[{"text":"Garner, Bradley D. 0000-0002-6912-5093 bdgarner@usgs.gov","orcid":"https://orcid.org/0000-0002-6912-5093","contributorId":2133,"corporation":false,"usgs":true,"family":"Garner","given":"Bradley","email":"bdgarner@usgs.gov","middleInitial":"D.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":477224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pool, D. R.","contributorId":75581,"corporation":false,"usgs":true,"family":"Pool","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":477225,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045327,"text":"sir20135029 - 2013 - Human effects on the hydrologic system of the Verde Valley, central Arizona, 1910–2005 and 2005–2110, using a regional groundwater flow model","interactions":[],"lastModifiedDate":"2018-03-23T14:28:22","indexId":"sir20135029","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5029","title":"Human effects on the hydrologic system of the Verde Valley, central Arizona, 1910–2005 and 2005–2110, using a regional groundwater flow model","docAbstract":"Water budgets were developed for the Verde Valley of central Arizona in order to evaluate the degree to which human stresses have affected the hydrologic system and might affect it in the future. The Verde Valley is a portion of central Arizona wherein concerns have been raised about water availability, particularly perennial base flow of the Verde River. The Northern Arizona Regional Groundwater Flow Model (NARGFM) was used to generate the water budgets and was run in several configurations for the 1910–2005 and 2005–2110 time periods. The resultant water budgets were subtracted from one another in order to quantify the relative changes that were attributable solely to human stresses; human stresses included groundwater withdrawals and incidental and artificial recharge but did not include, for example, human effects on the global climate. Three hypothetical and varied conditions of human stresses were developed and applied to the model for the 2005–2110 period. On the basis of this analysis, human stresses during 1910–2005 were found to have already affected the hydrologic system of the Verde Valley, and human stresses will continue to affect the hydrologic system during 2005–2110. Riparian evapotranspiration decreased and underflow into the Verde Valley increased because of human stresses, and net groundwater discharge to the Verde River in the Verde Valley decreased for the 1910–2005 model runs. The model also showed that base flow at the upstream end of the study area, as of 2005, was about 4,900 acre-feet per year less than it would have been in the absence of human stresses. At the downstream end of the Verde Valley, base flow had been reduced by about 10,000 acre-feet per year by the year 2005 because of human stresses. For the 2005–2110 period, the model showed that base flow at the downstream end of the Verde Valley may decrease by an additional 5,400 to 8,600 acre-feet per year because of past, ongoing, and hypothetical future human stresses. The process known as capture (or streamflow depletion caused by the pumping of groundwater) was the reason for these human-stress-induced changes in water-budget components.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135029","collaboration":"Prepared in cooperation with the Verde River Basin Partnership and the Town of Clarkdale","usgsCitation":"Garner, B.D., Pool, D.R., Tillman, F., and Forbes, B., 2013, Human effects on the hydrologic system of the Verde Valley, central Arizona, 1910–2005 and 2005–2110, using a regional groundwater flow model: U.S. Geological Survey Scientific Investigations Report 2013-5029, vi, 47 p., https://doi.org/10.3133/sir20135029.","productDescription":"vi, 47 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":270718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135029.gif"},{"id":270716,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5029/"},{"id":270717,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5029/sir2013-5029.pdf"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.82,31.33 ], [ -114.82,37.0 ], [ -109.0,37.0 ], [ -109.0,31.33 ], [ -114.82,31.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f314e4b0bc0bec0a077b","contributors":{"authors":[{"text":"Garner, Bradley D. 0000-0002-6912-5093 bdgarner@usgs.gov","orcid":"https://orcid.org/0000-0002-6912-5093","contributorId":2133,"corporation":false,"usgs":true,"family":"Garner","given":"Bradley","email":"bdgarner@usgs.gov","middleInitial":"D.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":477227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pool, D. R.","contributorId":75581,"corporation":false,"usgs":true,"family":"Pool","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":477229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":1629,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred D.","email":"ftillman@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forbes, Brandon T. bforbes@usgs.gov","contributorId":4625,"corporation":false,"usgs":true,"family":"Forbes","given":"Brandon T.","email":"bforbes@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477228,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042906,"text":"70042906 - 2013 - An isotope-dilution standard GC/MS/MS method for steroid hormones in water","interactions":[],"lastModifiedDate":"2021-05-27T16:01:28.036606","indexId":"70042906","displayToPublicDate":"2013-04-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"An isotope-dilution standard GC/MS/MS method for steroid hormones in water","docAbstract":"An isotope-dilution quantification method was developed for 20 natural and synthetic steroid hormones and additional compounds in filtered and unfiltered water. Deuterium- or carbon-13-labeled isotope-dilution standards (IDSs) are added to the water sample, which is passed through an octadecylsilyl solid-phase extraction (SPE) disk. Following extract cleanup using Florisil SPE, method compounds are converted to trimethylsilyl derivatives and analyzed by gas chromatography with tandem mass spectrometry. Validation matrices included reagent water, wastewater-affected surface water, and primary (no biological treatment) and secondary wastewater effluent. Overall method recovery for all analytes in these matrices averaged 100%; with overall relative standard deviation of 28%. Mean recoveries of the 20 individual analytes for spiked reagent-water samples prepared along with field samples analyzed in 2009–2010 ranged from 84–104%, with relative standard deviations of 6–36%. Detection levels estimated using ASTM International’s D6091–07 procedure range from 0.4 to 4 ng/L for 17 analytes. Higher censoring levels of 100 ng/L for bisphenol A and 200 ng/L for cholesterol and 3-beta-coprostanol are used to prevent bias and false positives associated with the presence of these analytes in blanks. Absolute method recoveries of the IDSs provide sample-specific performance information and guide data reporting. Careful selection of labeled compounds for use as IDSs is important because both inexact IDS-analyte matches and deuterium label loss affect an IDS’s ability to emulate analyte performance. Six IDS compounds initially tested and applied in this method exhibited deuterium loss and are not used in the final method.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Evaluating Veterinary Pharmaceutical Behavior in the Environment: ACS Symposium Series","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/bk-2013-1126.ch004","usgsCitation":"Foreman, W., Gray, J.L., ReVello, R., Lindley, C.E., and Losche, S.A., 2013, An isotope-dilution standard GC/MS/MS method for steroid hormones in water, chap. <i>of</i> Evaluating Veterinary Pharmaceutical Behavior in the Environment: ACS Symposium Series, v. 1126, p. 57-136, https://doi.org/10.1021/bk-2013-1126.ch004.","productDescription":"80 p.","startPage":"57","endPage":"136","ipdsId":"IP-038162","costCenters":[{"id":140,"text":"Branch of Analytical Serv (National Water Quality Laboratory)","active":false,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":270671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270670,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/bk-2013-1126.ch004"}],"volume":"1126","noUsgsAuthors":false,"publicationDate":"2013-03-14","publicationStatus":"PW","scienceBaseUri":"5163d8dae4b0b7010f820135","contributors":{"authors":[{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":472561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":472560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindley, Chris E. clindley@usgs.gov","contributorId":2337,"corporation":false,"usgs":true,"family":"Lindley","given":"Chris","email":"clindley@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":472562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Losche, Scott A. salosche@usgs.gov","contributorId":4694,"corporation":false,"usgs":true,"family":"Losche","given":"Scott","email":"salosche@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":472564,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70045266,"text":"sir20125229 - 2013 - The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model","interactions":[],"lastModifiedDate":"2013-04-05T10:25:18","indexId":"sir20125229","displayToPublicDate":"2013-04-05T00:00:00","publicationYear":"2013","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":"2012-5229","title":"The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model","docAbstract":"This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125229","usgsCitation":"Forney, W.M., Oldham, I.B., and Crescenti, N., 2013, The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model: U.S. Geological Survey Scientific Investigations Report 2012-5229, vi, 54 p., https://doi.org/10.3133/sir20125229.","productDescription":"vi, 54 p.","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":270599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125229.gif"},{"id":270597,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5229/"},{"id":270598,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5229/sir2012-5229.pdf"}],"country":"United States","state":"Nevada","otherGeospatial":"Lake Tahoe Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.25,38.66 ], [ -120.25,39.33 ], [ -119.83,39.33 ], [ -119.83,38.66 ], [ -120.25,38.66 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515fe728e4b03707eea09d01","contributors":{"authors":[{"text":"Forney, William M.","contributorId":43490,"corporation":false,"usgs":true,"family":"Forney","given":"William","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oldham, I. Benson","contributorId":101377,"corporation":false,"usgs":true,"family":"Oldham","given":"I.","email":"","middleInitial":"Benson","affiliations":[],"preferred":false,"id":477165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crescenti, Neil","contributorId":86239,"corporation":false,"usgs":true,"family":"Crescenti","given":"Neil","email":"","affiliations":[],"preferred":false,"id":477164,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045265,"text":"ds756 - 2013 - A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010","interactions":[],"lastModifiedDate":"2026-05-18T16:56:18.160356","indexId":"ds756","displayToPublicDate":"2013-04-05T00:00:00","publicationYear":"2013","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":"756","title":"A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010","docAbstract":"<p>Beginning around 2000, abundance indices of four pelagic fishes (delta smelt, striped bass, longfin smelt, and threadfin shad) within the San Francisco Bay and Sacramento&ndash;San Joaquin Delta began to decline sharply (Sommer and others, 2007). These declines collectively became known as the pelagic organism decline (POD). No single cause has been linked to this decline, and current theories suggest that combinations of multiple stressors are likely to blame. Contaminants (including current-use pesticides) are one potential stressor being investigated for its role in the POD (Anderson, 2007). Pesticide concentration data collected by the U.S. Geological Survey (USGS) at multiple sites in the delta region over the past two decades are critical to understanding the potential effects of current-use pesticides on species of concern as well as the overall health of the delta ecosystem. In April 2010, a compilation of contaminant data for the delta region was published by the State Water Resources Control Board (Johnson and others, 2010). Pesticide occurrence was the major focus of this report, which concluded that &ldquo;there was insufficient high quality data available to make conclusions about the potential role of specific contaminants in the POD.&rdquo; The report cited multiple sources; however, data collected by the USGS were not included in the publication even though these data met all criteria listed for inclusion in the report. What follows is a summary of publicly available USGS data for pesticide concentrations in surface water and sediments within the Sacramento&ndash;San Joaquin Delta region from the years 1990 through 2010. Data were retrieved though the USGS National Water Information System (NWIS) database, a publicly available online-data repository (U.S. Geological Survey, 1998), and from published USGS reports (also available online at http://pubs.er.usgs.gov/). The majority of the data were collected in support of two long term USGS monitoring programs&mdash;National Water Quality Assessment Program (NAWQA; http://water.usgs.gov/ nawqa/) and National Stream Quality Accounting Network (NASQAN; http://water.usgs.gov/nasqan/)&mdash;and through projects associated with the USGS Toxics Substances Hydrology Program (http://toxics.usgs.gov/). In addition, data were collected during multiple research projects that were supported by various federal, state, and local agencies. Although these data have been previously published in some form, it is hoped that by focusing on samples collected within the delta region and presenting these data in a concise format, they will be a valuable resource for scientists, resource managers, and members of the public working to understand the role of pesticides in the POD and their potential effects on the overall health of the delta ecosystem.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds756","usgsCitation":"Orlando, J., 2013, A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010: U.S. Geological Survey Data Series 756, Report: v, 48 p.; Appendixes, https://doi.org/10.3133/ds756.","productDescription":"Report: v, 48 p.; Appendixes","numberOfPages":"55","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":270593,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/756/"},{"id":270594,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/756/pdf/ds756.pdf"},{"id":270595,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/756/ds756_appendixes.xlsx"},{"id":270596,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds756.jpg"},{"id":504496,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98351.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Sacramento-san Joaquin Delta Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.47695922851562,\n              37.80327385185868\n            ],\n            [\n              -122.47695922851562,\n              38.381498197198816\n            ],\n            [\n              -121.48818969726561,\n              38.591113776147445\n            ],\n            [\n              -121.05697631835938,\n              38.052416771864834\n            ],\n            [\n              -121.53762817382814,\n              37.80327385185868\n            ],\n            [\n              -122.47695922851562,\n              37.80327385185868\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515fe720e4b03707eea09cfd","contributors":{"authors":[{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":477162,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045208,"text":"70045208 - 2013 - Using the KINEROS2 modeling framework to evaluate the increase in storm runoff from residential development in a semi-arid environment","interactions":[],"lastModifiedDate":"2013-05-20T13:43:30","indexId":"70045208","displayToPublicDate":"2013-04-02T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Using the KINEROS2 modeling framework to evaluate the increase in storm runoff from residential development in a semi-arid environment","docAbstract":"The increase in runoff from urbanization is well known; one extreme example comes from a 13 hectare residential neighborhood in southeast Arizona where runoff was 27 times greater than an adjacent grassland watershed over a forty‐month period from 2005 to 2008. Rainfall‐runoff modeling using the newly‐described KINEROS2 urban element and tension infiltrometer measurements indicate that 17±14 percent of this increase in runoff is due to a 53 percent decrease in the saturated hydraulic conductivity of constructed pervious areas, as compared to the undeveloped grassland. Directly connected impervious areas, primarily streets and driveways, cause 56 percent of the increase in runoff, and indirectly connected impervious areas, primarily rooftops and sidewalks, and a decrease in canopy interception account for the remaining 27 percent increase. Tension infiltrometer measurements show that saturated hydraulic conductivity (K<sub>s</sub>) is about double in the grassland watershed than in the urban watershed, 6.2 ± 3.5mm/hr and 2.9 ± 1.6mm/hr, respectively. K<sub>s</sub> in the urban watershed identified from calibrating the rainfall‐runoff model to measured runoff is 9.5 ± 2.8 mm/hr—higher than what was measured but much lower than the 26 mm/hr value indicated by a soil‐texture based KINEROS2 parameter look‐up table. A new component of the KINEROS2 modeling framework, the urban element, forms the basis for the model by simulating a contiguous row of houses and the adjoining street as a series of pervious and impervious overland flow planes. Tests using different levels of discretization found that watershed geometry can be represented in a simplified manner, although more detailed discretization led to better model performance.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrologic Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ASCE","doi":"10.1061/(ASCE)HE.1943-5584.0000655","usgsCitation":"Kennedy, J.R., Goodrich, D.C., and Unkrich, C.L., 2013, Using the KINEROS2 modeling framework to evaluate the increase in storm runoff from residential development in a semi-arid environment: Journal of Hydrologic Engineering, v. 18, no. 6, p. 698-706, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000655.","productDescription":"9 p.","startPage":"698","endPage":"706","numberOfPages":"9","additionalOnlineFiles":"N","ipdsId":"IP-032532","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":270497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270494,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000655"}],"country":"United States","state":"Arizona","county":"Cochise","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.46,31.33 ], [ -110.46,32.43 ], [ -109.0,32.43 ], [ -109.0,31.33 ], [ -110.46,31.33 ] ] ] } } ] }","volume":"18","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515befe0e4b075500ee5ca12","contributors":{"authors":[{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodrich, David C.","contributorId":65552,"corporation":false,"usgs":false,"family":"Goodrich","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":477025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Unkrich, Carl L.","contributorId":73479,"corporation":false,"usgs":true,"family":"Unkrich","given":"Carl","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477026,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70148175,"text":"70148175 - 2013 - Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system","interactions":[],"lastModifiedDate":"2015-05-26T11:16:35","indexId":"70148175","displayToPublicDate":"2013-04-01T12:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system","docAbstract":"<p>Hydrologic connectivity and environmental variation can influence nekton assemblages in coastal ecosystems. We evaluated the effects of hydrologic connectivity (permanently connected pond: PCP; temporary connected pond: TCP), salinity, vegetation coverage, water depth and other environmental variables on seasonal nekton assemblages in freshwater, brackish, and saline marshes of the Chenier Plain, Louisiana, USA. We hypothesize that 1) nekton assemblages in PCPs have higher metrics (density, biomass, assemblage similarity) than TCPs within all marsh types and 2) no nekton species would be dominant across all marsh types. In throw traps, freshwater PCPs in Fall (36.0 &plusmn; 1.90) and Winter 2009 (43.2 &plusmn; 22.36) supported greater biomass than freshwater TCPs (Fall 2009: 9.1 &plusmn; 4.65; Winter 2009: 8.3 &plusmn; 3.42). In minnow traps, saline TCPs (5.9 &plusmn; 0.85) in Spring 2009 had higher catch per unit effort than saline PCPs (0.7 &plusmn; 0.67). Our data only partially support our first hypothesis as freshwater marsh PCPs had greater assemblage similarity than TCPs. As predicted by our second hypothesis, no nekton species dominated across all marsh types. Nekton assemblages were structured by individual species responses to the salinity gradient as well as pond habitat attributes (submerged aquatic vegetation coverage, dissolved oxygen, hydrologic connectivity).</p>","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-013-0386-0","collaboration":"Louisiana Department of Wildlife and Fisheries; U.S. Fish and Wildlife Service; International Crane Foundation","usgsCitation":"Kang, S., and King, S.L., 2013, Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system: Wetlands, v. 33, no. 2, p. 321-334, https://doi.org/10.1007/s13157-013-0386-0.","productDescription":"14 p.","startPage":"321","endPage":"334","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036540","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-02-05","publicationStatus":"PW","scienceBaseUri":"5565993ee4b0d9246a9eb61b","contributors":{"authors":[{"text":"Kang, Sung-Ryong","contributorId":140927,"corporation":false,"usgs":false,"family":"Kang","given":"Sung-Ryong","email":"","affiliations":[],"preferred":false,"id":547609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547533,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041624,"text":"70041624 - 2013 - Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon","interactions":[],"lastModifiedDate":"2013-11-14T11:31:44","indexId":"70041624","displayToPublicDate":"2013-04-01T11:27:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon","docAbstract":"We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2013.01.019","usgsCitation":"Waibel, M.S., Gannett, M.W., Chang, H., and Hulbe, C.L., 2013, Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon: Journal of Hydrology, v. 486, p. 187-201, https://doi.org/10.1016/j.jhydrol.2013.01.019.","productDescription":"15 p.","startPage":"187","endPage":"201","numberOfPages":"15","ipdsId":"IP-040209","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":279076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279075,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2013.01.019"}],"country":"United States","state":"Oregon","otherGeospatial":"Deschutes Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5,43.0 ], [ -122.5,45.0 ], [ -120.5,45.0 ], [ -120.5,43.0 ], [ -122.5,43.0 ] ] ] } } ] }","volume":"486","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528607a5e4b00926c21865bf","contributors":{"authors":[{"text":"Waibel, Michael S.","contributorId":19984,"corporation":false,"usgs":true,"family":"Waibel","given":"Michael","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":470001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chang, Heejun","contributorId":14705,"corporation":false,"usgs":true,"family":"Chang","given":"Heejun","email":"","affiliations":[],"preferred":false,"id":470000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hulbe, Christina L.","contributorId":93371,"corporation":false,"usgs":true,"family":"Hulbe","given":"Christina","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":470002,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70129183,"text":"70129183 - 2013 - Symposium 9: Rocky Mountain futures: preserving, utilizing, and sustaining Rocky Mountain ecosystems","interactions":[],"lastModifiedDate":"2014-10-21T10:45:01","indexId":"70129183","displayToPublicDate":"2013-04-01T10:43:55","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1121,"text":"Bulletin of the Ecological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Symposium 9: Rocky Mountain futures: preserving, utilizing, and sustaining Rocky Mountain ecosystems","docAbstract":"In 2002 we published Rocky Mountain Futures, an Ecological Perspective (Island Press) to examine the cumulative ecological effects of human activity in the Rocky Mountains. We concluded  that multiple local activities concerning land use, hydrologic manipulation, and resource extraction have altered ecosystems, although there were examples where the “tyranny of small decisions” worked in a positive way toward more sustainable coupled human/environment interactions. Superimposed on local change was climate change, atmospheric deposition of nitrogen and other pollutants, regional population growth, and some national management policies such as fire suppression.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Ecological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/0012-9623-94.2.195","usgsCitation":"Baron, J., Seastedt, T., Fagre, D.B., Hicke, J.A., Tomback, D., Garcia, E., Bowen, Z.H., and Logan, J.A., 2013, Symposium 9: Rocky Mountain futures: preserving, utilizing, and sustaining Rocky Mountain ecosystems: Bulletin of the Ecological Society of America, v. 94, no. 2, p. 195-199, https://doi.org/10.1890/0012-9623-94.2.195.","productDescription":"5 p.","startPage":"195","endPage":"199","numberOfPages":"5","ipdsId":"IP-043738","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":473890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/0012-9623-94.2.195","text":"Publisher Index Page"},{"id":295537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295467,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/0012-9623-94.2.195"},{"id":295468,"type":{"id":15,"text":"Index Page"},"url":"https://www.esajournals.org/doi/abs/10.1890/0012-9623-94.2.195"}],"volume":"94","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"544775c1e4b0f888a81b834c","contributors":{"authors":[{"text":"Baron, Jill S. 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":822,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seastedt, Timothy","contributorId":11972,"corporation":false,"usgs":true,"family":"Seastedt","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":503529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":503528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hicke, Jeffrey A.","contributorId":36475,"corporation":false,"usgs":true,"family":"Hicke","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":503531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tomback, Diana","contributorId":32850,"corporation":false,"usgs":true,"family":"Tomback","given":"Diana","affiliations":[],"preferred":false,"id":503530,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garcia, Elizabeth","contributorId":91426,"corporation":false,"usgs":true,"family":"Garcia","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":503533,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503526,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Logan, Jesse A.","contributorId":66617,"corporation":false,"usgs":true,"family":"Logan","given":"Jesse","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":503532,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70046394,"text":"70046394 - 2013 - Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes","interactions":[],"lastModifiedDate":"2013-07-25T10:25:57","indexId":"70046394","displayToPublicDate":"2013-04-01T10:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes","docAbstract":"The Water Availability Tool for Environmental Resources (WATER) is a TOPMODEL-based hydrologic model that depends on spatially accurate soils data to function in diverse terranes. In Kentucky, this includes mountainous regions, karstic plateau, and alluvial plains. Soils data are critical because they quantify the space to store water, as well as how water moves through the soil to the stream during storm events. We compared how the model performs using two different sources of soils data--Soil Survey Geographic Database (SSURGO) and State Soil Geographic Database laboratory data (STATSGO)--for 21 basins ranging in size from 17 to 1564 km<sup>2</sup>. Model results were consistently better when SSURGO data were used, likely due to the higher field capacity, porosity, and available-water holding capacity, which cause the model to store more soil-water in the landscape and improve streamflow estimates for both low- and high-flow conditions. In addition, there were significant differences in the conductivity multiplier and scaling parameter values that describe how water moves vertically and laterally, respectively, as quantified by TOPMODEL. We also evaluated whether partitioning areas that drain to streams via sinkholes in karstic basins as separate hydrologic modeling units (HMUs) improved model performance. There were significant differences between HMUs in properties that control soil-water storage in the model, although the effect of partitioning these HMUs on streamflow simulation was inconclusive.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Soil Science Society of America Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2012.0069","usgsCitation":"Williamson, T., Taylor, C.J., and Newson, J.K., 2013, Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes: Soil Science Society of America Journal, v. 77, no. 3, p. 877-889, https://doi.org/10.2136/sssaj2012.0069.","productDescription":"13 p.","startPage":"877","endPage":"889","numberOfPages":"13","ipdsId":"IP-036109","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":275377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275376,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2136/sssaj2012.0069"}],"country":"United States","state":"Kentucky","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.5715,36.4972 ], [ -89.5715,39.1475 ], [ -81.965,39.1475 ], [ -81.965,36.4972 ], [ -89.5715,36.4972 ] ] ] } } ] }","volume":"77","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-04-19","publicationStatus":"PW","scienceBaseUri":"51f25422e4b0279fe2e1c026","contributors":{"authors":[{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":479605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Charles J.","contributorId":93100,"corporation":false,"usgs":true,"family":"Taylor","given":"Charles","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":479607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newson, Jeremy K. jknewson@usgs.gov","contributorId":4159,"corporation":false,"usgs":true,"family":"Newson","given":"Jeremy","email":"jknewson@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":479606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189267,"text":"70189267 - 2013 - A refined index of model performance: a rejoinder","interactions":[],"lastModifiedDate":"2017-07-07T10:23:43","indexId":"70189267","displayToPublicDate":"2013-04-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"A refined index of model performance: a rejoinder","docAbstract":"<p>Willmott<span>&nbsp;</span><i>et al.</i><span>&nbsp;</span>[Willmott CJ, Robeson SM, Matsuura K. 2012. A refined index of model performance.<span>&nbsp;</span><i>International Journal of Climatology</i>, forthcoming. DOI:10.1002/joc.2419.] recently suggest a refined index of model performance (<i>d</i><sub><i>r</i></sub>) that they purport to be superior to other methods. Their refined index ranges from − 1.0 to 1.0 to resemble a correlation coefficient, but it is merely a linear rescaling of our modified coefficient of efficiency (<i>E</i><sub>1</sub>) over the positive portion of the domain of<span>&nbsp;</span><i>d</i><sub><i>r</i></sub>. We disagree with Willmott<span>&nbsp;</span><i>et al.</i><span>&nbsp;</span>(<a class=\"link__reference js-link__reference\" title=\"Link to bibliographic citation\" rel=\"references:#bib8\" href=\"http://onlinelibrary.wiley.com/doi/10.1002/joc.3487/abstract#bib8\" data-mce-href=\"http://onlinelibrary.wiley.com/doi/10.1002/joc.3487/abstract#bib8\">2012</a>) that<span>&nbsp;</span><i>d</i><sub><i>r</i></sub><span>&nbsp;</span>provides a better interpretation; rather,<span>&nbsp;</span><i>E</i><sub>1</sub><span>&nbsp;</span>is more easily interpreted such that a value of<span>&nbsp;</span><i>E</i><sub>1</sub><span>&nbsp;</span>= 1.0 indicates a perfect model (no errors) while<span>&nbsp;</span><i>E</i><sub>1</sub><span>&nbsp;</span>= 0.0 indicates a model that is no better than the baseline comparison (usually the observed mean). Negative values of<span>&nbsp;</span><i>E</i><sub>1</sub><span>&nbsp;</span>(and, for that matter,<span>&nbsp;</span><i>d</i><sub><i>r</i></sub><span>&nbsp;</span>&lt; 0.5) indicate a substantially flawed model as they simply describe a ‘level of inefficacy’ for a model that is worse than the comparison baseline. Moreover, while<span>&nbsp;</span><i>d</i><sub><i>r</i></sub><span>&nbsp;</span>is piecewise continuous, it is not continuous through the second and higher derivatives. We explain why the coefficient of efficiency (<i>E</i><span>&nbsp;</span>or<span>&nbsp;</span><i>E</i><sub>2</sub>) and its modified form (<i>E</i><sub>1</sub>) are superior and preferable to many other statistics, including<span>&nbsp;</span><i>d</i><sub><i>r</i></sub>, because of intuitive interpretability and because these indices have a fundamental meaning at zero.</p><p>We also expand on the discussion begun by Garrick<span>&nbsp;</span><i>et al.</i><span>&nbsp;</span>[Garrick M, Cunnane C, Nash JE. 1978. A criterion of efficiency for rainfall-runoff models.<span>&nbsp;</span><i>Journal of Hydrology</i><span>&nbsp;</span><strong>36</strong>: 375-381.] and continued by Legates and McCabe [Legates DR, McCabe GJ. 1999. Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation.<span>&nbsp;</span><i>Water Resources Research</i><span>&nbsp;</span><strong>35</strong>(1): 233-241.] and Schaefli and Gupta [Schaefli B, Gupta HV. 2007. Do Nash values have value?<span>&nbsp;</span><i>Hydrological Processes</i><span>&nbsp;</span><strong>21</strong>: 2075-2080. DOI: 10.1002/hyp.6825.]. This important discussion focuses on the appropriate baseline comparison to use, and why the observed mean often may be an inadequate choice for model evaluation and development.<span>&nbsp;</span></p>","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.3487","usgsCitation":"Legates, D.R., and McCabe, G., 2013, A refined index of model performance: a rejoinder: International Journal of Climatology, v. 33, no. 4, p. 1053-1056, https://doi.org/10.1002/joc.3487.","productDescription":"4 p.","startPage":"1053","endPage":"1056","ipdsId":"IP-034043","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-04-18","publicationStatus":"PW","scienceBaseUri":"59609db9e4b0d1f9f0594c46","contributors":{"authors":[{"text":"Legates, David R.","contributorId":194273,"corporation":false,"usgs":false,"family":"Legates","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":703819,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045073,"text":"sir20135049 - 2013 - Shallow groundwater in the Matanuska-Susitna Valley, Alaska—Conceptualization and simulation of flow","interactions":[],"lastModifiedDate":"2018-07-18T13:50:39","indexId":"sir20135049","displayToPublicDate":"2013-03-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5049","title":"Shallow groundwater in the Matanuska-Susitna Valley, Alaska—Conceptualization and simulation of flow","docAbstract":"The Matanuska-Susitna Valley is in the Upper Cook Inlet Basin and is currently undergoing rapid population growth outside of municipal water and sewer service areas. In response to concerns about the effects of increasing water use on future groundwater availability, a study was initiated between the Alaska Department of Natural Resources and the U.S. Geological Survey. The goals of the study were (1) to compile existing data and collect new data to support hydrogeologic conceptualization of the study area, and (2) to develop a groundwater flow model to simulate flow dynamics important at the regional scale. The purpose of the groundwater flow model is to provide a scientific framework for analysis of regional-scale groundwater availability.  To address the first study goal, subsurface lithologic data were compiled into a database and were used to construct a regional hydrogeologic framework model describing the extent and thickness of hydrogeologic units in the Matanuska-Susitna Valley. The hydrogeologic framework model synthesizes existing maps of surficial geology and conceptual geochronologies developed in the study area with the distribution of lithologies encountered in hundreds of boreholes. The geologic modeling package Geological Surveying and Investigation in Three Dimensions (GSI3D) was used to construct the hydrogeologic framework model. In addition to characterizing the hydrogeologic framework, major groundwater-budget components were quantified using several different techniques. A land-surface model known as the Deep Percolation Model was used to estimate in-place groundwater recharge across the study area. This model incorporates data on topography, soils, vegetation, and climate. Model-simulated surface runoff was consistent with observed streamflow at U.S. Geological Survey streamgages. Groundwater withdrawals were estimated on the basis of records from major water suppliers during 2004-2010. Fluxes between groundwater and surface water were estimated during field investigations on several small streams.  Regional groundwater flow patterns were characterized by synthesizing previous water-table maps with a synoptic water-level measurement conducted during 2009. Time-series water-level data were collected at groundwater and lake monitoring stations over the study period (2009–present). Comparison of historical groundwater-level records with time-series groundwater-level data collected during this study showed similar patterns in groundwater-level fluctuation in response to precipitation. Groundwater-age data collected during previous studies show that water moves quickly through the groundwater system, suggesting that the system responds quickly to changes in climate forcing. Similarly, the groundwater system quickly returns to long-term average conditions following variability due to seasonal or interannual changes in precipitation. These analyses indicate that the groundwater system is in a state of dynamic equilibrium, characterized by water-level fluctuation about a constant average state, with no long-term trends in aquifer-system storage.  To address the second study goal, a steady-state groundwater flow model was developed to simulate regional groundwater flow patterns. The groundwater flow model was bounded by physically meaningful hydrologic features, and appropriate internal model boundaries were specified on the basis of conceptualization of the groundwater system resulting in a three-layer model. Calibration data included 173 water‑level measurements and 18 measurements of streamflow gains and losses along small streams.  Comparison of simulated and observed heads and flows showed that the model accurately simulates important regional characteristics of the groundwater flow system. This model is therefore appropriate for studying regional-scale groundwater availability. Mismatch between model-simulated and observed hydrologic quantities is likely because of the coarse grid size of the model and seasonal transient effects. Next steps towards model refinement include the development of a transient groundwater flow model that is suitable for analysis of seasonal variability in hydraulic heads and flows. In addition, several important groundwater budget components remain poorly quantified—including groundwater outflow to the Matanuska River, Little Susitna River, and Knik Arm.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135049","collaboration":"Prepared in cooperation with the Alaska Department of Natural Resources","usgsCitation":"Kikuchi, C.P., 2013, Shallow groundwater in the Matanuska-Susitna Valley, Alaska—Conceptualization and simulation of flow: U.S. Geological Survey Scientific Investigations Report 2013-5049, Report: viii, 86 p.; 4 Appendices, https://doi.org/10.3133/sir20135049.","productDescription":"Report: viii, 86 p.; 4 Appendices","numberOfPages":"96","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":270376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135049.jpg"},{"id":270372,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5049/sir20135049_appendixA.xlsx"},{"id":270373,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5049/sir20135049_appendixB.xlsx"},{"id":270374,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5049/sir20135049_appendixC.xlsx"},{"id":270375,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5049/sir20135049_appendixD.xlsx"},{"id":270370,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5049/"},{"id":270371,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5049/pdf/sir20135049.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Matanuska-susitna Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5156a9e9e4b06ea905cdbff6","contributors":{"authors":[{"text":"Kikuchi, Colin P.","contributorId":61311,"corporation":false,"usgs":true,"family":"Kikuchi","given":"Colin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":476735,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045083,"text":"sir20135043 - 2013 - Statistical classification of hydrogeologic regions in the fractured rock area of Maryland and parts of the District of Columbia, Virginia, West Virginia, Pennsylvania, and Delaware","interactions":[],"lastModifiedDate":"2023-03-09T20:13:46.600467","indexId":"sir20135043","displayToPublicDate":"2013-03-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5043","title":"Statistical classification of hydrogeologic regions in the fractured rock area of Maryland and parts of the District of Columbia, Virginia, West Virginia, Pennsylvania, and Delaware","docAbstract":"Hydrogeologic regions in the fractured rock area of Maryland were classified using geographic information system tools with principal components and cluster analyses. A study area consisting of the 8-digit Hydrologic Unit Code (HUC) watersheds with rivers that flow through the fractured rock area of Maryland and bounded by the Fall Line was further subdivided into 21,431 catchments from the National Hydrography Dataset Plus. The catchments were then used as a common hydrologic unit to compile relevant climatic, topographic, and geologic variables. A principal components analysis was performed on 10 input variables, and 4 principal components that accounted for 83 percent of the variability in the original data were identified. A subsequent cluster analysis grouped the catchments based on four principal component scores into six hydrogeologic regions. Two crystalline rock hydrogeologic regions, including large parts of the Washington, D.C. and Baltimore metropolitan regions that represent over 50 percent of the fractured rock area of Maryland, are distinguished by differences in recharge, Precipitation minus Potential Evapotranspiration, sand content in soils, and groundwater contributions to streams. This classification system will provide a georeferenced digital hydrogeologic framework for future investigations of groundwater availability in the fractured rock area of Maryland.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135043","collaboration":"Prepared in cooperation with the Maryland Department of the Environment","usgsCitation":"Fleming, B.J., LaMotte, A.E., and Sekellick, A.J., 2013, Statistical classification of hydrogeologic regions in the fractured rock area of Maryland and parts of the District of Columbia, Virginia, West Virginia, Pennsylvania, and Delaware: U.S. Geological Survey Scientific Investigations Report 2013-5043, Report: vi, 16 p.; Additional Information, https://doi.org/10.3133/sir20135043.","productDescription":"Report: vi, 16 p.; Additional Information","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":270388,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135043.gif"},{"id":270387,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sir/2013/5043/frac_rx_HRs.csv"},{"id":270386,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5043/pdf/sir2013-5043.pdf"},{"id":270385,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5043/"}],"scale":"100000","datum":"North American Datum 1983","country":"United States","state":"Delaware;District of Columbia;Maryl;Pennsylvania;Virginia;West Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80,3.118888888888889 ], [ -80,0.0011111111111111111 ], [ -75,0.0011111111111111111 ], [ -75,3.118888888888889 ], [ -80,3.118888888888889 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5156a9eae4b06ea905cdbffe","contributors":{"authors":[{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sekellick, Andrew J. 0000-0002-0440-7655 ajsekell@usgs.gov","orcid":"https://orcid.org/0000-0002-0440-7655","contributorId":4125,"corporation":false,"usgs":true,"family":"Sekellick","given":"Andrew","email":"ajsekell@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476760,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045064,"text":"tm4C3 - 2013 - Stochastic empirical loading and dilution model (SELDM) version 1.0.0","interactions":[],"lastModifiedDate":"2014-06-10T15:49:42","indexId":"tm4C3","displayToPublicDate":"2013-03-29T00:00:00","publicationYear":"2013","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":"4-C3","title":"Stochastic empirical loading and dilution model (SELDM) version 1.0.0","docAbstract":"The Stochastic Empirical Loading and Dilution Model (SELDM) is designed to transform complex scientific data into meaningful information about the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. The U.S. Geological Survey developed SELDM in cooperation with the Federal Highway Administration to help develop planning-level estimates of event mean concentrations, flows, and loads in stormwater from a site of interest and from an upstream basin. Planning-level estimates are defined as the results of analyses used to evaluate alternative management measures; planning-level estimates are recognized to include substantial uncertainties (commonly orders of magnitude). SELDM uses information about a highway site, the associated receiving-water basin, precipitation events, stormflow, water quality, and the performance of mitigation measures to produce a stochastic population of runoff-quality variables. SELDM provides input statistics for precipitation, prestorm flow, runoff coefficients, and concentrations of selected water-quality constituents from National datasets. Input statistics may be selected on the basis of the latitude, longitude, and physical characteristics of the site of interest and the upstream basin. The user also may derive and input statistics for each variable that are specific to a given site of interest or a given area. SELDM is a stochastic model because it uses Monte Carlo methods to produce the random combinations of input variable values needed to generate the stochastic population of values for each component variable. SELDM calculates the dilution of runoff in the receiving waters and the resulting downstream event mean concentrations and annual average lake concentrations. Results are ranked, and plotting positions are calculated, to indicate the level of risk of adverse effects caused by runoff concentrations, flows, and loads on receiving waters by storm and by year. Unlike deterministic hydrologic models, SELDM is not calibrated by changing values of input variables to match a historical record of values. Instead, input values for SELDM are based on site characteristics and representative statistics for each hydrologic variable. Thus, SELDM is an empirical model based on data and statistics rather than theoretical physiochemical equations. SELDM is a lumped parameter model because the highway site, the upstream basin, and the lake basin each are represented as a single homogeneous unit. Each of these source areas is represented by average basin properties, and results from SELDM are calculated as point estimates for the site of interest. Use of the lumped parameter approach facilitates rapid specification of model parameters to develop planning-level estimates with available data. The approach allows for parsimony in the required inputs to and outputs from the model and flexibility in the use of the model. For example, SELDM can be used to model runoff from various land covers or land uses by using the highway-site definition as long as representative water quality and impervious-fraction data are available.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Water Quality in Book 4 <i>Hydrologic Analysis and Interpretation</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4C3","collaboration":"Prepared in cooperation with the  Department of Transportation Federal Highway Administration, Office of Project Development and Environmental Review.  This report is Chapter 3 of Section C: Water Quality in Book 4 <i>Hydrologic Analysis and Interpretation</i>","usgsCitation":"Granato, G., 2013, Stochastic empirical loading and dilution model (SELDM) version 1.0.0: U.S. Geological Survey Techniques and Methods 4-C3, Manual: xii, 112 p.; 5 Appendices; Digital Media Directory, https://doi.org/10.3133/tm4C3.","productDescription":"Manual: xii, 112 p.; 5 Appendices; Digital Media Directory","numberOfPages":"124","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":270337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm4C3.jpg"},{"id":270332,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_apdx1_v030813.pdf"},{"id":270330,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/04/c03/"},{"id":270333,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_apdx2_v030813.pdf"},{"id":270331,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_main_v031913.pdf"},{"id":270334,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_apdx3_pages_v030813.pdf"},{"id":270335,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_apdx4_v030813.pdf"},{"id":270336,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/tm/04/c03/virtual_CD/index.html"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5156a9ece4b06ea905cdc006","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":476716,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045097,"text":"70045097 - 2013 - A new map of standardized terrestrial  ecosystems of Africa","interactions":[],"lastModifiedDate":"2018-03-23T14:25:00","indexId":"70045097","displayToPublicDate":"2013-03-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":669,"text":"African Geographical Review","active":true,"publicationSubtype":{"id":10}},"title":"A new map of standardized terrestrial  ecosystems of Africa","docAbstract":"Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In addition to creating several rich, new continent-wide biophysical datalayers describing African vegetation and ecosystems, our intention was to explore feasible approaches to rapidly moving this type of standardized, continent-wide, ecosystem classification and mapping effort forward.","language":"English","publisher":"Association of American Geographers","publisherLocation":"Washington, D.C.","usgsCitation":"Sayre, R.G., Comer, P., Hak, J., Josse, C., Bow, J., Warner, H., Larwanou, M., Kelbessa, E., Bekele, T., Kehl, H., Amena, R., Andriamasimanana, R., Ba, T., Benson, L., Boucher, T., Brown, M., Cress, J.J., Dassering, O., Friesen, B.A., Gachathi, F., Houcine, S., Keita, M., Khamala, E., Marangu, D., Mokua, F., Morou, B., Mucina, L., Mugisha, S., Mwavu, E., Rutherford, M., Sanou, P., Syampungani, S., Tomor, B., Vall, A.O., Vande Weghe, J.P., Wangui, E., and Waruingi, L., 2013, A new map of standardized terrestrial  ecosystems of Africa: African Geographical Review, 24 p.","productDescription":"24 p.","numberOfPages":"24","costCenters":[],"links":[{"id":270402,"type":{"id":15,"text":"Index Page"},"url":"https://www.aag.org/cs/publications/special/map_african_ecosystems"},{"id":270403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -26.6,-37.5 ], [ -26.6,38.0 ], [ 60.6,38.0 ], [ 60.6,-37.5 ], [ -26.6,-37.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5156b7dfe4b06ea905cdc00e","contributors":{"authors":[{"text":"Sayre, Roger G. rsayre@usgs.gov","contributorId":2882,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","email":"rsayre@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":false,"id":476783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Comer, Patrick","contributorId":85683,"corporation":false,"usgs":true,"family":"Comer","given":"Patrick","affiliations":[],"preferred":false,"id":476787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hak, Jon","contributorId":28138,"corporation":false,"usgs":true,"family":"Hak","given":"Jon","affiliations":[],"preferred":false,"id":476785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Josse, Carmen","contributorId":107164,"corporation":false,"usgs":true,"family":"Josse","given":"Carmen","affiliations":[],"preferred":false,"id":476788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bow, Jacquie","contributorId":69860,"corporation":false,"usgs":true,"family":"Bow","given":"Jacquie","email":"","affiliations":[],"preferred":false,"id":476786,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Warner, Harumi hwarner@usgs.gov","contributorId":2881,"corporation":false,"usgs":true,"family":"Warner","given":"Harumi","email":"hwarner@usgs.gov","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":649854,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Larwanou, Mahamane","contributorId":174997,"corporation":false,"usgs":false,"family":"Larwanou","given":"Mahamane","email":"","affiliations":[],"preferred":false,"id":649855,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kelbessa, Ensermu","contributorId":174998,"corporation":false,"usgs":false,"family":"Kelbessa","given":"Ensermu","email":"","affiliations":[],"preferred":false,"id":649856,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bekele, Tamrat","contributorId":174999,"corporation":false,"usgs":false,"family":"Bekele","given":"Tamrat","email":"","affiliations":[],"preferred":false,"id":649857,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kehl, Harald","contributorId":175000,"corporation":false,"usgs":false,"family":"Kehl","given":"Harald","email":"","affiliations":[],"preferred":false,"id":649858,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Amena, Ruba","contributorId":175001,"corporation":false,"usgs":false,"family":"Amena","given":"Ruba","email":"","affiliations":[],"preferred":false,"id":649859,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Andriamasimanana, Rado","contributorId":175002,"corporation":false,"usgs":false,"family":"Andriamasimanana","given":"Rado","email":"","affiliations":[],"preferred":false,"id":649860,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ba, Taibou","contributorId":175003,"corporation":false,"usgs":false,"family":"Ba","given":"Taibou","email":"","affiliations":[],"preferred":false,"id":649861,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Benson, Laurence","contributorId":175004,"corporation":false,"usgs":false,"family":"Benson","given":"Laurence","email":"","affiliations":[],"preferred":false,"id":649862,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Boucher, Timothy","contributorId":175005,"corporation":false,"usgs":false,"family":"Boucher","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":649863,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Brown, Matthew","contributorId":175006,"corporation":false,"usgs":false,"family":"Brown","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":649864,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Cress, Jill J. jjcress@usgs.gov","contributorId":1600,"corporation":false,"usgs":true,"family":"Cress","given":"Jill","email":"jjcress@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":649865,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Dassering, Oueddo","contributorId":175007,"corporation":false,"usgs":false,"family":"Dassering","given":"Oueddo","email":"","affiliations":[],"preferred":false,"id":649866,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Friesen, Beverly A. bafriesen@usgs.gov","contributorId":3216,"corporation":false,"usgs":true,"family":"Friesen","given":"Beverly","email":"bafriesen@usgs.gov","middleInitial":"A.","affiliations":[{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"preferred":true,"id":649867,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Gachathi, Francis","contributorId":175008,"corporation":false,"usgs":false,"family":"Gachathi","given":"Francis","email":"","affiliations":[],"preferred":false,"id":649868,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Houcine, Sebei","contributorId":175009,"corporation":false,"usgs":false,"family":"Houcine","given":"Sebei","email":"","affiliations":[],"preferred":false,"id":649869,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Keita, Mahamadou","contributorId":175010,"corporation":false,"usgs":false,"family":"Keita","given":"Mahamadou","email":"","affiliations":[],"preferred":false,"id":649870,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Khamala, Erick","contributorId":175011,"corporation":false,"usgs":false,"family":"Khamala","given":"Erick","email":"","affiliations":[],"preferred":false,"id":649871,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Marangu, Dan","contributorId":175012,"corporation":false,"usgs":false,"family":"Marangu","given":"Dan","email":"","affiliations":[],"preferred":false,"id":649872,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Mokua, Fredrick","contributorId":175013,"corporation":false,"usgs":false,"family":"Mokua","given":"Fredrick","email":"","affiliations":[],"preferred":false,"id":649873,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Morou, Boube","contributorId":175014,"corporation":false,"usgs":false,"family":"Morou","given":"Boube","email":"","affiliations":[],"preferred":false,"id":649874,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Mucina, Ladislav","contributorId":166896,"corporation":false,"usgs":false,"family":"Mucina","given":"Ladislav","email":"","affiliations":[{"id":24570,"text":"School of Plant Biology, Stellenbosch University, South Africa","active":true,"usgs":false}],"preferred":false,"id":649875,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Mugisha, Samuel","contributorId":175015,"corporation":false,"usgs":false,"family":"Mugisha","given":"Samuel","email":"","affiliations":[],"preferred":false,"id":649876,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Mwavu, Edward","contributorId":175016,"corporation":false,"usgs":false,"family":"Mwavu","given":"Edward","email":"","affiliations":[],"preferred":false,"id":649877,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Rutherford, Michael","contributorId":175017,"corporation":false,"usgs":false,"family":"Rutherford","given":"Michael","email":"","affiliations":[],"preferred":false,"id":649878,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Sanou, Patrice","contributorId":175018,"corporation":false,"usgs":false,"family":"Sanou","given":"Patrice","email":"","affiliations":[],"preferred":false,"id":649879,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Syampungani, Stephen","contributorId":175019,"corporation":false,"usgs":false,"family":"Syampungani","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":649880,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Tomor, Bojoi","contributorId":175020,"corporation":false,"usgs":false,"family":"Tomor","given":"Bojoi","email":"","affiliations":[],"preferred":false,"id":649881,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Vall, Abdallahi Ould Mohamed","contributorId":175021,"corporation":false,"usgs":false,"family":"Vall","given":"Abdallahi","email":"","middleInitial":"Ould Mohamed","affiliations":[],"preferred":false,"id":649882,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Vande Weghe, Jean Pierre","contributorId":175022,"corporation":false,"usgs":false,"family":"Vande Weghe","given":"Jean","email":"","middleInitial":"Pierre","affiliations":[],"preferred":false,"id":649883,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Wangui, Eunice","contributorId":175023,"corporation":false,"usgs":false,"family":"Wangui","given":"Eunice","email":"","affiliations":[],"preferred":false,"id":649884,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Waruingi, Lucy","contributorId":175024,"corporation":false,"usgs":false,"family":"Waruingi","given":"Lucy","email":"","affiliations":[],"preferred":false,"id":649885,"contributorType":{"id":1,"text":"Authors"},"rank":37}]}}
,{"id":70045021,"text":"ofr20121225 - 2013 - Web-based flood database for Colorado, water years 1867 through 2011","interactions":[],"lastModifiedDate":"2013-03-27T09:10:10","indexId":"ofr20121225","displayToPublicDate":"2013-03-27T00:00:00","publicationYear":"2013","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":"2012-1225","title":"Web-based flood database for Colorado, water years 1867 through 2011","docAbstract":"In order to provide a centralized repository of flood information for the State of Colorado, the U.S. Geological Survey, in cooperation with the Colorado Department of Transportation, created a Web-based geodatabase for flood information from water years 1867 through 2011 and data for paleofloods occurring in the past 5,000 to 10,000 years. The geodatabase was created using the Environmental Systems Research Institute ArcGIS JavaScript Application Programing Interface 3.2. The database can be accessed at http://cwscpublic2.cr.usgs.gov/projects/coflood/COFloodMap.html.\n\nData on 6,767 flood events at 1,597 individual sites throughout Colorado were compiled to generate the flood database. The data sources of flood information are indirect discharge measurements that were stored in U.S. Geological Survey offices (water years 1867–2011), flood data from indirect discharge measurements referenced in U.S. Geological Survey reports (water years 1884–2011), paleoflood studies from six peer-reviewed journal articles (data on events occurring in the past 5,000 to 10,000 years), and the U.S. Geological Survey National Water Information System peak-discharge database (water years 1883–2010). A number of tests were performed on the flood database to ensure the quality of the data. The Web interface was programmed using the Environmental Systems Research Institute ArcGIS JavaScript Application Programing Interface 3.2, which allows for display, query, georeference, and export of the data in the flood database. The data fields in the flood database used to search and filter the database include hydrologic unit code, U.S. Geological Survey station number, site name, county, drainage area, elevation, data source, date of flood, peak discharge, and field method used to determine discharge. Additional data fields can be viewed and exported, but the data fields described above are the only ones that can be used for queries.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121225","collaboration":"Prepared in cooperation with the Colorado Department of Transportation","usgsCitation":"Kohn, M.S., Jarrett, R.D., Krammes, G.S., and Mommandi, A., 2013, Web-based flood database for Colorado, water years 1867 through 2011: U.S. Geological Survey Open-File Report 2012-1225, vi, 26 p., https://doi.org/10.3133/ofr20121225.","productDescription":"vi, 26 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1867-09-30","temporalEnd":"2011-09-30","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":270312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121225.gif"},{"id":270310,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1225/"},{"id":270311,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1225/OF12-1225-508.pdf"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515406e1e4b030c71ee06717","contributors":{"authors":[{"text":"Kohn, Michael S. 0000-0002-5989-7700 mkohn@usgs.gov","orcid":"https://orcid.org/0000-0002-5989-7700","contributorId":4549,"corporation":false,"usgs":true,"family":"Kohn","given":"Michael","email":"mkohn@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarrett, Robert D. rjarrett@usgs.gov","contributorId":2260,"corporation":false,"usgs":true,"family":"Jarrett","given":"Robert","email":"rjarrett@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":476633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krammes, Gary S. gkrammes@usgs.gov","contributorId":5102,"corporation":false,"usgs":true,"family":"Krammes","given":"Gary","email":"gkrammes@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":476635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mommandi, Amanullah","contributorId":40874,"corporation":false,"usgs":true,"family":"Mommandi","given":"Amanullah","email":"","affiliations":[],"preferred":false,"id":476636,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70044975,"text":"tm6D2 - 2013 - CRT--Cascade Routing Tool to define and visualize flow paths for grid-based watershed models","interactions":[],"lastModifiedDate":"2013-03-25T16:12:26","indexId":"tm6D2","displayToPublicDate":"2013-03-25T00:00:00","publicationYear":"2013","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-D2","title":"CRT--Cascade Routing Tool to define and visualize flow paths for grid-based watershed models","docAbstract":"The U.S. Geological Survey Cascade Routing Tool (CRT) is a computer application for watershed models that include the coupled Groundwater and Surface-water FLOW model, GSFLOW, and the Precipitation-Runoff Modeling System (PRMS). CRT generates output to define cascading surface and shallow subsurface flow paths for grid-based model domains. CRT requires a land-surface elevation for each hydrologic response unit (HRU) of the model grid; these elevations can be derived from a Digital Elevation Model raster data set of the area containing the model domain. Additionally, a list is required of the HRUs containing streams, swales, lakes, and other cascade termination features along with indices that uniquely define these features. Cascade flow paths are determined from the altitudes of each HRU. Cascade paths can cross any of the four faces of an HRU to a stream or to a lake within or adjacent to an HRU. Cascades can terminate at a stream, lake, or HRU that has been designated as a watershed outflow location.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Ground-Water/Surface-Water 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/tm6D2","collaboration":"Groundwater Resources Program; This report is Chapter 2 of Section D: Ground-Water/Surface-Water in Book 6: <i>Modeling Techniques</i>","usgsCitation":"Henson, W., Medina, R.L., Mayers, C.J., Niswonger, R., and Regan, R., 2013, CRT--Cascade Routing Tool to define and visualize flow paths for grid-based watershed models: U.S. Geological Survey Techniques and Methods 6-D2, Pamphlet: vii, 28 p.; Software, https://doi.org/10.3133/tm6D2.","productDescription":"Pamphlet: vii, 28 p.; Software","additionalOnlineFiles":"Y","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":270035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6D2.jpg"},{"id":270034,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://water.usgs.gov/ogw/CRT/"},{"id":270032,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm6d2/"},{"id":270033,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/tm6d2/pdf/tm6-D2.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515163d2e4b087909f0bbe2b","contributors":{"authors":[{"text":"Henson, Wesley R. 0000-0003-4962-5565","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":96561,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley R.","affiliations":[],"preferred":false,"id":476548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medina, Rose L. 0000-0002-3463-7224 rlmedina@usgs.gov","orcid":"https://orcid.org/0000-0002-3463-7224","contributorId":4378,"corporation":false,"usgs":true,"family":"Medina","given":"Rose","email":"rlmedina@usgs.gov","middleInitial":"L.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mayers, C. Justin cjmayers@usgs.gov","contributorId":94745,"corporation":false,"usgs":true,"family":"Mayers","given":"C.","email":"cjmayers@usgs.gov","middleInitial":"Justin","affiliations":[],"preferred":false,"id":476547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niswonger, Richard G.","contributorId":45402,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","affiliations":[],"preferred":false,"id":476545,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regan, R.S.","contributorId":51794,"corporation":false,"usgs":true,"family":"Regan","given":"R.S.","email":"","affiliations":[],"preferred":false,"id":476546,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70042994,"text":"70042994 - 2013 - Arsenic in groundwater: a summary of sources and the biogeochemical and hydrogeologic factors affecting arsenic occurrence and mobility","interactions":[],"lastModifiedDate":"2013-03-24T20:06:08","indexId":"70042994","displayToPublicDate":"2013-03-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Arsenic in groundwater: a summary of sources and the biogeochemical and hydrogeologic factors affecting arsenic occurrence and mobility","docAbstract":"Arsenic (As) is a metalloid element (atomic number 33) with one naturally occurring isotope of atomic mass 75, and four oxidation states (-3, 0, +3, and +5) (Smedley and Kinniburgh, 2002). In the aqueous environment, the +3 and +5 oxidation states are most prevalent, as the oxyanions arsenite (H<sub>3</sub>AsO<sub>3</sub> or H<sub>2</sub>AsO<sub>3</sub><sup>-</sup> at pH ~9-11) and arsenate (H<sub>2</sub>AsO<sub>4</sub><sup>-</sup> and HAsO<sub>4</sub><sup>2-</sup> at pH ~4-10) (Smedley and Kinniburgh, 2002). In soils, arsine gases (containing As<sup>3-</sup>) may be generated by fungi and other organisms (Woolson, 1977).\n\nThe different forms of As have different toxicities, with arsine gas being the most toxic form. Of the inorganic oxyanions, arsenite is considered more toxic than arsenate, and the organic (methylated) arsenic forms are considered least toxic (for a detailed discussion of toxicity issues, the reader is referred to Mandal and Suzuki (2002)). Arsenic is a global health concern due to its toxicity and the fact that it occurs at unhealthful levels in water supplies, particularly groundwater, in more than 70 countries (Ravenscroft et al., 2009) on six continents.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Current perspectives in contaminant hydrology and water resources sustainability","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"InTech","publisherLocation":"Rijeka, Croatia","doi":"10.5772/55354","collaboration":"This is Chapter 4 in Current perspectives in contaminant hydrology and water resources sustainability","usgsCitation":"Barringer, J., and Reilly, P.A., 2013, Arsenic in groundwater: a summary of sources and the biogeochemical and hydrogeologic factors affecting arsenic occurrence and mobility, chap. <i>of</i> Current perspectives in contaminant hydrology and water resources sustainability, p. 83-116, https://doi.org/10.5772/55354.","productDescription":"34 p.","startPage":"83","endPage":"116","ipdsId":"IP-041793","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":473907,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5772/55354","text":"Publisher Index Page"},{"id":269959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269958,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5772/55354"}],"noUsgsAuthors":false,"publicationDate":"2013-02-27","publicationStatus":"PW","scienceBaseUri":"5150124fe4b08df5cb1312b9","contributors":{"editors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":509186,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Barringer, Julia L.","contributorId":59419,"corporation":false,"usgs":true,"family":"Barringer","given":"Julia L.","affiliations":[],"preferred":false,"id":472767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472766,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70044922,"text":"70044922 - 2013 - Modeling the long-term fate of agricultural nitrate in groundwater in the San Joaquin Valley, California","interactions":[],"lastModifiedDate":"2022-12-27T16:43:54.0106","indexId":"70044922","displayToPublicDate":"2013-03-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"6","title":"Modeling the long-term fate of agricultural nitrate in groundwater in the San Joaquin Valley, California","docAbstract":"Nitrate contamination of groundwater systems used for human water supplies is a major environmental problem in many parts of the world. Fertilizers containing a variety of reduced nitrogen compounds are commonly added to soils to increase agricultural yields. But the amount of nitrogen added during fertilization typically exceeds the amount of nitrogen taken up by crops. Oxidation of reduced nitrogen compounds present in residual fertilizers can produce substantial amounts of nitrate which can be transported to the underlying water table. Because nitrate concentrations exceeding 10 mg/L in drinking water can have a variety of deleterious effects for humans, agriculturally derived nitrate contamination of groundwater can be a serious public health issue.\n\nThe Central Valley aquifer of California accounts for 13 percent of all the groundwater withdrawals in the United States. The Central Valley, which includes the San Joaquin Valley, is one of the most productive agricultural areas in the world and much of this groundwater is used for crop irrigation. However, rapid urbanization has led to increasing groundwater withdrawals for municipal public water supplies. That, in turn, has led to concern about how contaminants associated with agricultural practices will affect the chemical quality of groundwater in the San Joaquin Valley. Crop fertilization with various forms of nitrogen-containing compounds can greatly increase agricultural yields. However, leaching of nitrate from soils due to irrigation has led to substantial nitrate contamination of shallow groundwater. That shallow nitrate-contaminated groundwater has been moving deeper into the Central Valley aquifer since the 1960s. Denitrification can be an important process limiting the mobility of nitrate in groundwater systems. However, substantial denitrification requires adequate sources of electron donors in order to drive the process. In many cases, dissolved organic carbon (DOC) and particulate organic carbon (POC) are the primary electron donors driving active denitrification in groundwater. The purpose of this chapter is to use a numerical mass balance modeling approach to quantitatively compare sources of electron donors (DOC, POC) and electron acceptors (dissolved oxygen, nitrate, and ferric iron) in order to assess the potential for denitrification to attenuate nitrate migration in the Central Valley aquifer.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Current perspectives in contaminant hydrology and water resources sustainability","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"InTech","publisherLocation":"Rijeka, Croatia","doi":"10.5772/53652","usgsCitation":"Chapelle, F.H., Campbell, B.G., Widdowson, M.A., and Landon, M.K., 2013, Modeling the long-term fate of agricultural nitrate in groundwater in the San Joaquin Valley, California, chap. 6 <i>of</i> Current perspectives in contaminant hydrology and water resources sustainability, p. 151-167, https://doi.org/10.5772/53652.","productDescription":"17 p.","startPage":"151","endPage":"167","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":473905,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5772/53652","text":"Publisher Index Page"},{"id":269963,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.39180782283782,\n              37.831343892420776\n            ],\n            [\n              -121.39180782283782,\n              37.37396546986268\n            ],\n            [\n              -120.64955102989776,\n              37.37396546986268\n            ],\n            [\n              -120.64955102989776,\n              37.831343892420776\n            ],\n            [\n              -121.39180782283782,\n              37.831343892420776\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationDate":"2013-02-27","publicationStatus":"PW","scienceBaseUri":"51501262e4b08df5cb1312dd","contributors":{"authors":[{"text":"Chapelle, Francis H. chapelle@usgs.gov","contributorId":1350,"corporation":false,"usgs":true,"family":"Chapelle","given":"Francis","email":"chapelle@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Bruce G. 0000-0003-4800-6674 bcampbel@usgs.gov","orcid":"https://orcid.org/0000-0003-4800-6674","contributorId":995,"corporation":false,"usgs":true,"family":"Campbell","given":"Bruce","email":"bcampbel@usgs.gov","middleInitial":"G.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Widdowson, Mark A.","contributorId":90379,"corporation":false,"usgs":true,"family":"Widdowson","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landon, Mathew K. 0000-0002-5766-0494","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":49254,"corporation":false,"usgs":true,"family":"Landon","given":"Mathew","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":476476,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040199,"text":"70040199 - 2013 - Electrical signatures of ethanol-liquid mixtures: implications for monitoring biofuels migration in the subsurface","interactions":[],"lastModifiedDate":"2013-03-24T22:04:10","indexId":"70040199","displayToPublicDate":"2013-03-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Electrical signatures of ethanol-liquid mixtures: implications for monitoring biofuels migration in the subsurface","docAbstract":"Ethanol (EtOH), an emerging contaminant with potential direct and indirect environmental effects, poses threats to water supplies when spilled in large volumes. A series of experiments was directed at understanding the electrical geophysical signatures arising from groundwater contamination by ethanol. Conductivity measurements were performed at the laboratory scale on EtOH–water mixtures (0 to 0.97 v/v EtOH) and EtOH–salt solution mixtures (0 to 0.99 v/v EtOH) with and without a sand matrix using a conductivity probe and a four-electrode electrical measurement over the low frequency range (1–1000 Hz). A Lichtenecker–Rother (L–R) type mixing model was used to simulate electrical conductivity as a function of EtOH concentration in the mixture. For all three experimental treatments increasing EtOH concentration resulted in a decrease in measured conductivity magnitude (|σ|). The applied L–R model fitted the experimental data at concentration ≤ 0.4 v/v EtOH, presumably due to predominant and symmetric intermolecular (EtOH–water) interaction in the mixture. The deviation of the experimental |σ| data from the model prediction at higher EtOH concentrations may be associated with hydrophobic effects of EtOH–EtOH interactions in the mixture. The |σ| data presumably reflected changes in relative strength of the three types of interactions (water–water, EtOH–water, and EtOH–EtOH) occurring simultaneously in EtOH–water mixtures as the ratio of EtOH to water changed. No evidence of measurable polarization effects at the EtOH–water and EtOH–water–mineral interfaces over the investigated frequency range was found. Our results indicate the potential for using electrical measurements to characterize and monitor EtOH spills in the subsurface.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Contaminant Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jconhyd.2012.10.011","usgsCitation":"Personna, Y.R., Slater, L., Ntarlagiannis, D., Werkema, D.D., and Szabo, Z., 2013, Electrical signatures of ethanol-liquid mixtures: implications for monitoring biofuels migration in the subsurface: Journal of Contaminant Hydrology, v. 144, no. 1, p. 99-107, https://doi.org/10.1016/j.jconhyd.2012.10.011.","productDescription":"9 p.","startPage":"99","endPage":"107","ipdsId":"IP-037076","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":269971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269970,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2012.10.011"}],"volume":"144","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5150125fe4b08df5cb1312cd","contributors":{"authors":[{"text":"Personna, Yves Robert","contributorId":77820,"corporation":false,"usgs":false,"family":"Personna","given":"Yves","email":"","middleInitial":"Robert","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":467878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Lee","contributorId":55707,"corporation":false,"usgs":false,"family":"Slater","given":"Lee","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":467877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ntarlagiannis, Dimitrios","contributorId":55303,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":467876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":467875,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":2240,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":467874,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044920,"text":"70044920 - 2013 - Managing the effects of endocrine disrupting chemicals in wastewater-impacted streams","interactions":[],"lastModifiedDate":"2022-12-27T16:40:06.750716","indexId":"70044920","displayToPublicDate":"2013-03-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Managing the effects of endocrine disrupting chemicals in wastewater-impacted streams","docAbstract":"A revolution in analytical instrumentation circa 1920 greatly improved the ability to characterize chemical substances. This analytical foundation resulted in an unprecedented explosion in the design and production of synthetic chemicals during and post-World War II. What is now often referred to as the 2nd Chemical Revolution has provided substantial societal benefits; with modern chemical design and manufacturing supporting dramatic advances in medicine, increased food production, and expanding gross domestic products at the national and global scales as well as improved health, longevity, and lifestyle convenience at the individual scale. Presently, the chemical industry is the largest manufacturing sector in the United States (U.S.) and the second largest in Europe and Japan, representing approximately 5% of the Gross Domestic Product (GDP) in each of these countries. At the turn of the 21st century, the chemical industry was estimated to be worth more than $1.6 trillion and to employ over 10 million people, globally.\n\nDuring the first half of the 20th century, the chemical sector expanded rapidly, the chemical industry enjoyed a generally positive status in society, and chemicals were widely appreciated as fundamental to individual and societal quality of life. Starting in the 1960s, however, the environmental costs associated with the chemical industry increasingly became the focus, due in part to the impact of books like “Silent Spring” and “Our Stolen Future” and to a number of highly publicized environmental disasters. Galvanizing chemical industry disasters included the 1976 dioxin leak north of Milan, Italy, the Love Canal evacuations in Niagara, New York beginning in 1978, and the Union Carbide leak in Bhopal, India in 1984.\n\nUnderstanding the environmental impact of synthetic compounds is essential to any informed assessment of net societal benefit, for the simple reason that any chemical substance that is in commercial production or use will eventually find its way to the environment. Not surprisingly given the direct link to profits, manufacturers intensely investigate and routinely document the potential benefits of new chemicals and chemical products. In contrast, the environmental risks associated with chemical production and uses are often investigated less intensely and are poorly communicated.\n\nAn imbalance in the risk-benefit analysis of any synthetic chemical substance or naturally occurring chemical, which presence and concentration in the environment largely reflects human activities and management, is a particular concern owing to the fundamental link between chemistry and biology. Biological organisms are intrinsically a homeostatic balance of innumerable internal and external chemical interactions and, thus, inherently sensitive to changes in the external chemical environment.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Current perspectives in contaminant hydrology and water resources sustainability","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"InTech","publisherLocation":"Rijeka, Croatia","doi":"10.5772/54337","usgsCitation":"Bradley, P.M., and Kolpin, D.W., 2013, Managing the effects of endocrine disrupting chemicals in wastewater-impacted streams, chap. 1 <i>of</i> Current perspectives in contaminant hydrology and water resources sustainability, p. 3-26, https://doi.org/10.5772/54337.","productDescription":"24 p.","startPage":"3","endPage":"26","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":473901,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5772/54337","text":"Publisher Index Page"},{"id":269957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2013-02-27","publicationStatus":"PW","scienceBaseUri":"51501261e4b08df5cb1312d9","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476470,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70044740,"text":"sir20125247 - 2013 - Geophysical and hydrologic analysis of an earthen dam site in southern Westchester County, New York","interactions":[],"lastModifiedDate":"2013-03-21T14:03:42","indexId":"sir20125247","displayToPublicDate":"2013-03-21T00:00:00","publicationYear":"2013","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":"2012-5247","title":"Geophysical and hydrologic analysis of an earthen dam site in southern Westchester County, New York","docAbstract":"Ninety percent of the drinking water for New York City passes through the Hillview Reservoir facility in the City of Yonkers, Westchester County, New York. In the past, several seeps located downslope from the reservoir have flowed out from the side of the steepest slope at the southern end of the earthen embankment. One seep that has been flowing continuously was discovered during an inspection of the embankment in 1999. Efforts were made in 2001 to locate the potential sources of the continuous flowing seep. In 2005, the U.S. Geological Survey, in cooperation with the New York City Department of Environmental Protection, began a cooperative study to investigate the relevant hydrogeologic framework to characterize the local groundwater-flow system and to determine possible sources of the seeps. The two agencies used hydrologic and surface geophysical techniques to assess the earthen embankment of the Hillview Reservoir. Between April 1, 2005 and March 1, 2008, water levels were measured manually each month at 46 wells surrounding the reservoir, and flow was measured monthly at three of the five seeps on the embankment. Water levels were measured hourly in the East Basin of the reservoir, at 24 of 46 wells, and discharge was measured hourly at two of the five seeps. Slug tests were performed at 16 wells to determine the hydraulic conductivity of the geologic material surrounding the screened zone. Estimated hydraulic conductivities for 25 wells on the southern embankment ranged from 0.0063 to 1.2 feet per day and averaged 0.17 foot per day. The two-dimensional resistivity surveys indicate a subsurface mound of electrically conductive material (low-resistivity zone) beneath the terrace area (top of dam) surrounding the reservoir with a distinct elevation increase closer to the crest. Two-dimensional shear wave velocity surveys indicate a similar structure of the high shear wave velocity materials (high-velocity zone), increasing in elevation toward the crest and decreasing toward the reservoir and toward the northern part of the study area. Water-quality samples collected from 12 wells, downtake chamber 1 of the reservoir, and two seeps detected the presence of arsenic, toluene, and two trihalomethanes. Water-quality samples collected at the two seeps detected fluoride, indicating a connection with reservoir water.\n\nShallow wells on the southern embankment exhibited the largest seasonal water-level fluctuations ranging between 6 feet and 12 feet. The embankment is constructed from reworked low-permeability glacial deposits at the site. Water-level responses in observation wells within the embankment indicate that there is a shallow (approximately the upper 45 feet of the embankment) and a deep water-bearing unit within the embankment with a large downward vertical gradient between the shallow and deep water-bearing units. Precipitation strongly affected water levels in shallow wells, whereas the basin appears to be the main control on water levels in the deep wells. Seeps on the embankment slope appear to be caused by above-average precipitation that increases water levels in the shallow water-bearing unit, but does not easily recharge the deep water-bearing unit. Based on the data that have been analyzed, source water to the seeps appears to be primarily groundwater and, to a lesser extent, water from the East Basin of the reservoir.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125247","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Chu, A., Stumm, F., Joesten, P.K., and Noll, M.L., 2013, Geophysical and hydrologic analysis of an earthen dam site in southern Westchester County, New York: U.S. Geological Survey Scientific Investigations Report 2012-5247, vii, 64 p., https://doi.org/10.3133/sir20125247.","productDescription":"vii, 64 p.","numberOfPages":"76","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":269858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125247.gif"},{"id":269856,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5247/"},{"id":269857,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5247/pdf/sir2012-5247_report_508.pdf"}],"country":"United States","state":"New York","county":"Westchester County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.982887,40.878872 ], [ -73.982887,41.36384 ], [ -73.482709,41.36384 ], [ -73.482709,40.878872 ], [ -73.982887,40.878872 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"514c1ddee4b0cf4196fef2d9","contributors":{"authors":[{"text":"Chu, Anthony 0000-0001-8623-2862 achu@usgs.gov","orcid":"https://orcid.org/0000-0001-8623-2862","contributorId":2517,"corporation":false,"usgs":true,"family":"Chu","given":"Anthony","email":"achu@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stumm, Frederick 0000-0002-5388-8811 fstumm@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-8811","contributorId":1077,"corporation":false,"usgs":true,"family":"Stumm","given":"Frederick","email":"fstumm@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joesten, Peter K. pjoesten@usgs.gov","contributorId":1929,"corporation":false,"usgs":true,"family":"Joesten","given":"Peter","email":"pjoesten@usgs.gov","middleInitial":"K.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noll, Michael L. 0000-0003-2050-3134 mnoll@usgs.gov","orcid":"https://orcid.org/0000-0003-2050-3134","contributorId":4652,"corporation":false,"usgs":true,"family":"Noll","given":"Michael","email":"mnoll@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476268,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}