The Trinity aquifer is an important source of groundwater in central Texas, including Bexar County, where population growth has resulted in an increased demand for water (Ashworth, 1983; Mace and others, 2000). Numerous springs issue from rock outcrops within and surrounding the Trinity aquifer in northern Bexar County (fig. 1). The effects of increased groundwater withdrawals from the Trinity aquifer on springflow in the area are not well documented, but because the total amount of water entering, leaving, and being stored in a groundwater system must be conserved, increased groundwater withdrawals will result in decreases in springflow (Alley and others, 1999). Documenting the location, discharge, and basic water-quality information of the springs in northern Bexar County can provide a baseline assessment for comparison to future conditions. Accordingly, the U.S. Geological Survey (USGS), in cooperation with the Trinity Glen Rose Groundwater Conservation District, the Edwards Aquifer Authority, and the San Antonio River Authority, developed a geodatabase populated with data associated with springs within and surrounding outcrops of the Trinity aquifer in northern Bexar County during 2010–11. A geodatabase provides a framework for organizing spatial and tabular data (such as the geographic location and water-quality characteristics, respectively) in a relational database environment, making it easier and more intuitive to evaluate changes over time.
\nData for 141 springs within and surrounding the Trinity aquifer outcrops in northern Bexar County were compiled from existing reports and databases. These data were augmented with selected data collected onsite, including the location, discharge, and water-quality characteristics of selected springs, and were entered into the geodatabase. The Trinity aquifer in central Texas is commonly divided into the upper, middle, and lower Trinity aquifers; all of the information that was compiled pertaining to the aquifer is for the upper and middle Trinity aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133044","collaboration":"Prepared in cooperation with Trinity Glen Rose Groundwater Conservation District, Edwards Aquifer Authority, and San Antonio River Authority","usgsCitation":"Clark, A.K., and Pedraza, D.E., 2013, Development of a geodatabase for springs within and surrounding outcrops of the Trinity aquifer in northern Bexar County, Texas, 2010-11: U.S. Geological Survey Fact Sheet 2013-3044, 4 p., https://doi.org/10.3133/fs20133044.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-048945","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":505356,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98656.htm","linkFileType":{"id":5,"text":"html"}},{"id":275105,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3044/FS_2013-3044.pdf"},{"id":275102,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3044/"},{"id":275106,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133044.gif"}],"country":"United States","state":"Texas","county":"Bexar County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.833333,29.5 ], [ -98.833333,29.8 ], [ -98.333333,29.8 ], [ -98.333333,29.5 ], [ -98.833333,29.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e7aed0e4b080b82b09c5fe","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":481025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pedraza, Diane E.","contributorId":67788,"corporation":false,"usgs":true,"family":"Pedraza","given":"Diane","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":481026,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047082,"text":"sir20135030 - 2013 - Software for analysis of chemical mixtures--composition, occurrence, distribution, and possible toxicity","interactions":[],"lastModifiedDate":"2013-07-17T09:37:11","indexId":"sir20135030","displayToPublicDate":"2013-07-17T09:32:00","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":"2013-5030","title":"Software for analysis of chemical mixtures--composition, occurrence, distribution, and possible toxicity","docAbstract":"The composition, occurrence, distribution, and possible toxicity of chemical mixtures in the environment are research concerns of the U.S. Geological Survey and others. The presence of specific chemical mixtures may serve as indicators of natural phenomena or human-caused events. Chemical mixtures may also have ecological, industrial, geochemical, or toxicological effects. Chemical-mixture occurrences vary by analyte composition and concentration. Four related computer programs have been developed by the National Water-Quality Assessment Program of the U.S. Geological Survey for research of chemical-mixture compositions, occurrences, distributions, and possible toxicities. The compositions and occurrences are identified for the user-supplied data, and therefore the resultant counts are constrained by the user’s choices for the selection of chemicals, reporting limits for the analytical methods, spatial coverage, and time span for the data supplied. The distribution of chemical mixtures may be spatial, temporal, and (or) related to some other variable, such as chemical usage. Possible toxicities optionally are estimated from user-supplied benchmark data.\n\nThe software for the analysis of chemical mixtures described in this report is designed to work with chemical-analysis data files retrieved from the U.S. Geological Survey National Water Information System but can also be used with appropriately formatted data from other sources. Installation and usage of the mixture software are documented. This mixture software was designed to function with minimal changes on a variety of computer-operating systems. To obtain the software described herein and other U.S. Geological Survey software, visit http://water.usgs.gov/software/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135030","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Scott, J.C., Skach, K.A., and Toccalino, P., 2013, Software for analysis of chemical mixtures--composition, occurrence, distribution, and possible toxicity: U.S. Geological Survey Scientific Investigations Report 2013-5030, iv, 27 p., https://doi.org/10.3133/sir20135030.","productDescription":"iv, 27 p.","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-041335","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":275104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135030.gif"},{"id":275101,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5030/"},{"id":275103,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5030/sir2013-5030.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e7aed8e4b080b82b09c61a","contributors":{"authors":[{"text":"Scott, Jonathon C. jcscott@usgs.gov","contributorId":5449,"corporation":false,"usgs":true,"family":"Scott","given":"Jonathon","email":"jcscott@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":481023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skach, Kenneth A. kaskach@usgs.gov","contributorId":1894,"corporation":false,"usgs":true,"family":"Skach","given":"Kenneth","email":"kaskach@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":481022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toccalino, Patricia L. 0000-0003-1066-1702","orcid":"https://orcid.org/0000-0003-1066-1702","contributorId":41089,"corporation":false,"usgs":true,"family":"Toccalino","given":"Patricia L.","affiliations":[{"id":5079,"text":"Pacific Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":481024,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046953,"text":"fs20133038 - 2013 - The National Water-Quality Assessment (NAWQA) Program planned monitoring and modeling activities for Texas, 2013–23","interactions":[],"lastModifiedDate":"2016-08-05T13:48:14","indexId":"fs20133038","displayToPublicDate":"2013-07-16T15:50:00","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":"2013-3038","title":"The National Water-Quality Assessment (NAWQA) Program planned monitoring and modeling activities for Texas, 2013–23","docAbstract":"The U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Program was established by Congress in 1992 to answer the following question: What is the status of the Nation’s water quality and is it getting better or worse? Since 1992, NAWQA has been a primary source of nationally consistent data and information on the quality of the Nation’s streams and groundwater. Data and information obtained from objective and nationally consistent water-quality monitoring and modeling activities provide answers to where, when, and why the Nation’s water quality is degraded and what can be done to improve and protect it for human and ecosystem needs. For NAWQA’s third decade (2013–23), a new strategic Science Plan has been developed that describes a strategy for building upon and enhancing the USGS’s ongoing assessment of the Nation’s freshwater quality and aquatic ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133038","usgsCitation":"Ging, P., 2013, The National Water-Quality Assessment (NAWQA) Program planned monitoring and modeling activities for Texas, 2013–23: U.S. Geological Survey Fact Sheet 2013-3038, 2 p., https://doi.org/10.3133/fs20133038.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046123","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":275099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133038.gif"},{"id":275097,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3038/"},{"id":275098,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3038/FS2013-3038.pdf"}],"country":"United States","state":"Texas","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e65d5ae4b017be1ba34744","contributors":{"authors":[{"text":"Ging, Patricia","contributorId":77027,"corporation":false,"usgs":true,"family":"Ging","given":"Patricia","affiliations":[],"preferred":false,"id":480672,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047080,"text":"ofr20131121 - 2013 - Linear extension rates of massive corals from the Dry Tortugas National Park (DRTO), Florida","interactions":[],"lastModifiedDate":"2016-03-30T11:53:34","indexId":"ofr20131121","displayToPublicDate":"2013-07-16T15:38:00","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":"2013-1121","title":"Linear extension rates of massive corals from the Dry Tortugas National Park (DRTO), Florida","docAbstract":"Colonies of three coral species, Montastraea faveolata, Diploria strigosa, and Siderastrea siderea, located in the Dry Tortugas National Park (DRTO), Florida, were sampled and analyzed to evaluate annual linear extension rates. Montastraea faveolata had the highest average linear extension and variability in (DRTO: C2 = 0.67 centimeters/year (cm yr-1) ± 0.04, B3 = 0.85 cm yr-1 ± 0.07), followed by D. strigosa (DRTO: C1 = 0.73 cm yr-1 ± 0.04; MK = 0.59 cm yr-1 ± 0.06) and S. siderea (DRTO: A1 = 0.41 cm yr-1 ± 0.03). Intercolony comparison of M. faveolata from DRTO yielded a significant correlation (r = 0.34, df = 67, P = 0.005) and similar long-term patterns. DRTO S. siderea core A1 showed an overall increasing trend (r = 0.61, df = 119, P < 0.0001) in extension rates that correlated significantly with International Comprehensive Ocean/Atmosphere Data Set annual sea-surface temperature (r = 0.42, df = 115, P < 0.0001) and an air temperature record from Key West (r = 0.37, df = 111, P < 0.0001). In conclusion, annual linear extension rates are species specific and potentially influence by long-term variability in sea-surface temperature.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131121","usgsCitation":"Muslic, A., Flannery, J.A., Reich, C.D., Umberger, D.K., Smoak, J.M., and Poore, R.Z., 2013, Linear extension rates of massive corals from the Dry Tortugas National Park (DRTO), Florida: U.S. Geological Survey Open-File Report 2013-1121, iii, 22 p., https://doi.org/10.3133/ofr20131121.","productDescription":"iii, 22 p.","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":275096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131121.gif"},{"id":275094,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1121/"},{"id":275095,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1121/pdf/ofr2013-1121.pdf","text":"Report"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park (drto)","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.9275,24.6262 ], [ -82.9275,24.6386 ], [ -82.9146,24.6386 ], [ -82.9146,24.6262 ], [ -82.9275,24.6262 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e65d57e4b017be1ba34729","contributors":{"authors":[{"text":"Muslic, Adis","contributorId":80809,"corporation":false,"usgs":true,"family":"Muslic","given":"Adis","email":"","affiliations":[],"preferred":false,"id":481020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flannery, Jennifer A. 0000-0002-1692-2662 jflannery@usgs.gov","orcid":"https://orcid.org/0000-0002-1692-2662","contributorId":4317,"corporation":false,"usgs":true,"family":"Flannery","given":"Jennifer","email":"jflannery@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":481018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reich, Christopher D. 0000-0002-2534-1456 creich@usgs.gov","orcid":"https://orcid.org/0000-0002-2534-1456","contributorId":900,"corporation":false,"usgs":true,"family":"Reich","given":"Christopher","email":"creich@usgs.gov","middleInitial":"D.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":481017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Umberger, Daniel K.","contributorId":87839,"corporation":false,"usgs":true,"family":"Umberger","given":"Daniel","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":481021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smoak, Joseph M.","contributorId":32392,"corporation":false,"usgs":true,"family":"Smoak","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":481019,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Poore, Richard Z. rpoore@usgs.gov","contributorId":345,"corporation":false,"usgs":true,"family":"Poore","given":"Richard","email":"rpoore@usgs.gov","middleInitial":"Z.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":481016,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046993,"text":"70046993 - 2013 - Phylogeography and population genetic structure of double-crested cormorants (Phalacrocorax auritus)","interactions":[],"lastModifiedDate":"2017-11-22T10:17:48","indexId":"70046993","displayToPublicDate":"2013-07-16T14:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Phylogeography and population genetic structure of double-crested cormorants (Phalacrocorax auritus)","docAbstract":"We examined the genetic structure of doublecrested cormorants (Phalacrocorax auritus) across their range in the United States and Canada. Sequences of the mitochondrial control region were analyzed for 248 cormorants\nfrom 23 breeding sites. Variation was also examined at eight microsatellite loci for 409 cormorants from the same sites. The mitochondrial and microsatellite data provided strong evidence that the Alaskan subspecies (P. a. cincinnatus)\nis genetically divergent from other populations in North America (net sequence divergence = 5.85 %;UST for mitochondrial control region = 0.708; FST for microsatellite loci = 0.052). Historical records, contemporary population estimates, and field observations are consistent with recognition of the Alaskan subspecies as distinct and potentially of conservation interest. Our data also indicated the presence of another divergent lineage, associated with the southwestern portion of the species range, as evidenced by highly unique haplotypes sampled in southern California. In contrast, there was little support for recognition of subspecies within the conterminous U.S. and Canada. Rather than genetically distinct regions corresponding to the putative subspecies [P. a. albociliatus (Pacific), P. a. auritus (Interior and North Atlantic), and P. a. floridanus (Southeast)], we observed a distribution of genetic variation consistent with a pattern of isolation by distance. This pattern implies that genetic differences across the range are due to geographic distance, rather than discrete subspecific breaks. Although three of the four traditional subspecies were not genetically distinct, possible demographic separation, habitat differences, and documented declines at some colonies within the regions, suggests that the Pacific and possibly North Atlantic portions of the breeding range may warrant differential consideration from the Interior and Southeast breeding regions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Conservation Genetics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10592-013-0477-8","usgsCitation":"Mercer, D., Haig, S.M., and Roby, D.D., 2013, Phylogeography and population genetic structure of double-crested cormorants (Phalacrocorax auritus): Conservation Genetics, v. 14, no. 4, p. 823-836, https://doi.org/10.1007/s10592-013-0477-8.","productDescription":"14 p.","startPage":"823","endPage":"836","numberOfPages":"14","ipdsId":"IP-042945","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":275087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275086,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10592-013-0477-8"},{"id":274903,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/content/pdf/10.1007%2Fs10592-013-0477-8.pdf"}],"country":"Canada;Mexico;United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -166.46,24.45 ], [ -166.46,62.47 ], [ -52.29,62.47 ], [ -52.29,24.45 ], [ -166.46,24.45 ] ] ] } } ] }","volume":"14","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-04-02","publicationStatus":"PW","scienceBaseUri":"51e65d58e4b017be1ba34731","contributors":{"authors":[{"text":"Mercer, Dacey","contributorId":89034,"corporation":false,"usgs":true,"family":"Mercer","given":"Dacey","email":"","affiliations":[],"preferred":false,"id":480815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":480813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roby, Daniel D. 0000-0001-9844-0992 droby@usgs.gov","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":3702,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel","email":"droby@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":480814,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046823,"text":"70046823 - 2013 - The role of viscous magma mush spreading in volcanic flank motion at Kīlauea Volcano, Hawai‘i","interactions":[],"lastModifiedDate":"2018-10-30T08:54:50","indexId":"70046823","displayToPublicDate":"2013-07-16T11:51:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The role of viscous magma mush spreading in volcanic flank motion at Kīlauea Volcano, Hawai‘i","docAbstract":"Multiple mechanisms have been suggested to explain seaward motion of the south flank of Kīlauea Volcano, Hawai‘i. The consistency of flank motion during both waxing and waning magmatic activity at Kīlauea suggests that a continuously acting force, like gravity body force, plays a substantial role. Using finite element models, we test whether gravity is the principal driver of long-term motion of Kīlauea's flank. We compare our model results to geodetic data from Global Positioning System and interferometric synthetic aperture radar during a time period with few magmatic and tectonic events (2000-2003), when deformation of Kīlauea was dominated by summit subsidence and seaward motion of the south flank. We find that gravity-only models can reproduce the horizontal surface velocities if we incorporate a regional décollement fault and a deep, low-viscosity magma mush zone. To obtain quasi steady state horizontal surface velocities that explain the long-term seaward motion of the flank, we find that an additional weak zone is needed, which is an extensional rift zone above the magma mush. The spreading rate in our model is mainly controlled by the magma mush viscosity, while its density plays a less significant role. We find that a viscosity of 2.5 × 1017–2.5 × 1019 Pa s for the magma mush provides an acceptable fit to the observed horizontal surface deformation. Using high magma mush viscosities, such as 2.5 × 1019 Pa s, the deformation rates remain more steady state over longer time scales. These models explain a significant amount of the observed subsidence at Kīlauea's summit. Some of the remaining subsidence is probably a result of magma withdrawal from subsurface reservoirs.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jgrb.50194","usgsCitation":"Plattner, C., Amelung, F., Baker, S., Govers, R., and Poland, M.P., 2013, The role of viscous magma mush spreading in volcanic flank motion at Kīlauea Volcano, Hawai‘i: Journal of Geophysical Research B: Solid Earth, v. 118, no. 5, p. 2474-2487, https://doi.org/10.1002/jgrb.50194.","productDescription":"14 p.","startPage":"2474","endPage":"2487","numberOfPages":"14","ipdsId":"IP-042374","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrb.50194","text":"Publisher Index Page"},{"id":275063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275061,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50194"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.7051,18.93750 ], [ -155.7051,19.7111 ], [ -154.8083,19.7111 ], [ -154.8083,18.93750 ], [ -155.7051,18.93750 ] ] ] } } ] }","volume":"118","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-05-16","publicationStatus":"PW","scienceBaseUri":"51e65d5ce4b017be1ba34748","contributors":{"authors":[{"text":"Plattner, C.","contributorId":53275,"corporation":false,"usgs":true,"family":"Plattner","given":"C.","email":"","affiliations":[],"preferred":false,"id":480366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amelung, F.","contributorId":106268,"corporation":false,"usgs":true,"family":"Amelung","given":"F.","affiliations":[],"preferred":false,"id":480367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, S.","contributorId":31290,"corporation":false,"usgs":true,"family":"Baker","given":"S.","affiliations":[],"preferred":false,"id":480364,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Govers, R.","contributorId":107174,"corporation":false,"usgs":true,"family":"Govers","given":"R.","email":"","affiliations":[],"preferred":false,"id":480368,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":480365,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046901,"text":"70046901 - 2013 - Historical and contemporary geographic data reveal complex spatial and temporal responses of vegetation to climate and land stewardship","interactions":[],"lastModifiedDate":"2013-07-16T11:18:16","indexId":"70046901","displayToPublicDate":"2013-07-16T11:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Historical and contemporary geographic data reveal complex spatial and temporal responses of vegetation to climate and land stewardship","docAbstract":"Vegetation and land-cover changes are not always directional but follow complex trajectories over space and time, driven by changing anthropogenic and abiotic conditions. We present a multi-observational approach to land-change analysis that addresses the complex geographic and temporal variability of vegetation changes related to climate and land use. Using land-ownership data as a proxy for land-use practices, multitemporal land-cover maps, and repeat photography dating to the late 19th century, we examine changing spatial and temporal distributions of two vegetation types with high conservation value in the southwestern United States: grasslands and riparian vegetation. In contrast to many reported vegetation changes, notably shrub encroachment in desert grasslands, we found an overall increase in grassland area and decline of xeroriparian and riparian vegetation. These observed change patterns were neither temporally directional nor spatially uniform over the landscape. Historical data suggest that long-term vegetation changes coincide with broad climate fluctuations while fine-scale patterns are determined by land-management practices. In some cases, restoration and active management appear to weaken the effects of climate on vegetation; therefore, if land managers in this region act in accord with on-going directional changes, the current drought and associated ecological reorganization may provide an opportunity to achieve desired restoration endpoints.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Land","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"MDPI AG","doi":"10.3390/land2020194","usgsCitation":"Villarreal, M., Norman, L.M., Webb, R., and Turner, R., 2013, Historical and contemporary geographic data reveal complex spatial and temporal responses of vegetation to climate and land stewardship: Land, v. 2, no. 2, p. 194-224, https://doi.org/10.3390/land2020194.","productDescription":"31 p.","startPage":"194","endPage":"224","ipdsId":"IP-043863","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land2020194","text":"Publisher Index Page"},{"id":275053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274715,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/land2020194"},{"id":274716,"type":{"id":15,"text":"Index Page"},"url":"https://www.mdpi.com/2073-445X/2/2/194"}],"volume":"2","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-05-15","publicationStatus":"PW","scienceBaseUri":"51e65d56e4b017be1ba34725","contributors":{"authors":[{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":480577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":480574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Robert H. rhwebb@usgs.gov","contributorId":1573,"corporation":false,"usgs":false,"family":"Webb","given":"Robert H.","email":"rhwebb@usgs.gov","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":480575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turner, Raymond M.","contributorId":7383,"corporation":false,"usgs":true,"family":"Turner","given":"Raymond M.","affiliations":[],"preferred":false,"id":480576,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70046865,"text":"70046865 - 2013 - Habitat and co-occurrence of native and invasive crayfish in the Pacific Northwest, USA","interactions":[],"lastModifiedDate":"2013-07-16T11:00:14","indexId":"70046865","displayToPublicDate":"2013-07-16T10:54:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Habitat and co-occurrence of native and invasive crayfish in the Pacific Northwest, USA","docAbstract":"Biological invasions can have dramatic effects on freshwater ecosystems and introduced crayfish can be particularly impacting. We document crayfish distribution in three large hydrographic basins (Rogue, Umpqua, Willamette/Columbia) in the Pacific Northwest USA. We used occupancy analyses to investigate habitat relationships and evidence for displacement of native Pacifastacus leniusculus (Dana, 1852) by two invaders. We found invasive Procambarus clarkii (Girard, 1852), in 51 of 283 sites and in all three hydrographic basins. We found invasive Orconectes n. neglectus (Faxon, 1885) at 68% of sites in the Rogue basin and provide first documentation of their broad distribution in the Umpqua basin. We found P. clarkii in both lentic and lotic habitats, and it was positively associated with manmade sites. P. leniusculus was positively associated with lotic habitats and negatively related to manmade sites. In the Rogue and Umpqua basins, O. n. neglectus and P. leniusculus were similar in their habitat associations. We did not find a negative relationship in site occupancy between O. n. neglectus and P. leniusculus. Our data suggest that P. clarkii has potential to locally displace P. leniusculus. There is still time for preventive measures to limit the spread of the invasive crayfish in this region.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Aquatic Invasions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"REABIC","doi":"10.3391/ai.2013.8.2.05","usgsCitation":"Pearl, C., Adams, M.J., and McCreary, B., 2013, Habitat and co-occurrence of native and invasive crayfish in the Pacific Northwest, USA: Aquatic Invasions, v. 8, no. 2, p. 171-184, https://doi.org/10.3391/ai.2013.8.2.05.","productDescription":"14 p.","startPage":"171","endPage":"184","ipdsId":"IP-044200","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473683,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2013.8.2.05","text":"Publisher Index Page"},{"id":275048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274700,"type":{"id":15,"text":"Index Page"},"url":"https://www.aquaticinvasions.net/2013/AI_2013_2_Pearl_etal.pdf"},{"id":275046,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3391/ai.2013.8.2.05"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"8","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e65d56e4b017be1ba3471d","contributors":{"authors":[{"text":"Pearl, Christopher A. 0000-0003-2943-7321","orcid":"https://orcid.org/0000-0003-2943-7321","contributorId":84316,"corporation":false,"usgs":true,"family":"Pearl","given":"Christopher A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":480499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, M. J. 0000-0001-8844-042X mjadams@usgs.gov","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":3133,"corporation":false,"usgs":false,"family":"Adams","given":"M.","email":"mjadams@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":480498,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCreary, Brome","contributorId":105005,"corporation":false,"usgs":true,"family":"McCreary","given":"Brome","affiliations":[],"preferred":false,"id":480500,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047060,"text":"fs20133045 - 2013 - Culvert Analysis Program Graphical User Interface 1.0--A preprocessing and postprocessing tool for estimating flow through culvert","interactions":[],"lastModifiedDate":"2013-07-16T10:56:09","indexId":"fs20133045","displayToPublicDate":"2013-07-16T10:45:00","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":"2013-3045","title":"Culvert Analysis Program Graphical User Interface 1.0--A preprocessing and postprocessing tool for estimating flow through culvert","docAbstract":"The peak discharge of a flood can be estimated from the elevation of high-water marks near the inlet and outlet of a culvert after the flood has occurred. This type of discharge estimate is called an “indirect measurement” because it relies on evidence left behind by the flood, such as high-water marks on trees or buildings. When combined with the cross-sectional geometry of the channel upstream from the culvert and the culvert size, shape, roughness, and orientation, the high-water marks define a water-surface profile that can be used to estimate the peak discharge by using the methods described by Bodhaine (1968). This type of measurement is in contrast to a “direct” measurement of discharge made during the flood where cross-sectional area is measured and a current meter or acoustic equipment is used to measure the water velocity. When a direct discharge measurement cannot be made at a streamgage during high flows because of logistics or safety reasons, an indirect measurement of a peak discharge is useful for defining the high-flow section of the stage-discharge relation (rating curve) at the streamgage, resulting in more accurate computation of high flows. The Culvert Analysis Program (CAP) (Fulford, 1998) is a command-line program written in Fortran for computing peak discharges and culvert rating surfaces or curves. CAP reads input data from a formatted text file and prints results to another formatted text file. Preparing and correctly formatting the input file may be time-consuming and prone to errors. This document describes the CAP graphical user interface (GUI)—a modern, cross-platform, menu-driven application that prepares the CAP input file, executes the program, and helps the user interpret the output","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133045","usgsCitation":"Bradley, D.N., 2013, Culvert Analysis Program Graphical User Interface 1.0--A preprocessing and postprocessing tool for estimating flow through culvert: U.S. Geological Survey Fact Sheet 2013-3045, 4 p., https://doi.org/10.3133/fs20133045.","productDescription":"4 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":338,"text":"Hydrologic Analysis Software Support Program","active":false,"usgs":true}],"links":[{"id":275047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133045.gif"},{"id":275044,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3045/"},{"id":275045,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3045/pdf/fs2013-3045.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e65d4fe4b017be1ba34711","contributors":{"authors":[{"text":"Bradley, D. Nathan","contributorId":79776,"corporation":false,"usgs":true,"family":"Bradley","given":"D.","email":"","middleInitial":"Nathan","affiliations":[],"preferred":false,"id":480945,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047014,"text":"70047014 - 2013 - Fire regimes of quaking aspen in the Mountain West","interactions":[],"lastModifiedDate":"2013-07-15T13:34:46","indexId":"70047014","displayToPublicDate":"2013-07-15T13:25:48","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Fire regimes of quaking aspen in the Mountain West","docAbstract":"Quaking aspen (Populus tremuloides Michx.) is the most widespread tree species in North America, and it is found throughout much of the Mountain West (MW) across a broad range of bioclimatic regions. Aspen typically regenerates asexually and prolifically after fire, and due to its seral status in many western conifer forests, aspen is often considered dependent upon disturbance for persistence. In many landscapes, historical evidence for post-fire aspen establishment is clear, and following extended fire-free periods senescing or declining aspen overstories sometimes lack adequate regeneration and are succeeding to conifers. However, aspen also forms relatively stable stands that contain little or no evidence of historical fire. In fact, aspen woodlands range from highly fire-dependent, seral communities to relatively stable, self-replacing, non-seral communities that do not require fire for persistence. Given the broad geographic distribution of aspen, fire regimes in these forests likely co-vary spatially with changing community composition, landscape setting, and climate, and temporally with land use and climate – but relatively few studies have explicitly focused on these important spatiotemporal variations. Here we reviewed the literature to summarize aspen fire regimes in the western US and highlight knowledge gaps. We found that only about one-fourth of the 46 research papers assessed for this review could be considered fire history studies (in which mean fire intervals were calculated), and all but one of these were based primarily on data from fire-scarred conifers. Nearly half of the studies reported at least some evidence of persistent aspen in the absence of fire. We also found that large portions of the MW have had little or no aspen fire history research. As a result of this review, we put forth a classification framework for aspen that is defined by key fire regime parameters (fire severity and probability), and that reflects underlying biophysical settings and correlated aspen functional types. We propose the following aspen fire regime types: (1) fire-independent, stable aspen; (2) fire-influenced, stable aspen; (3) fire-dependent, seral, conifer-aspen mix; (4) fire-dependent, seral, montane aspen-conifer; and (5) fire-dependent, seral, subalpine aspen-conifer. Closing research gaps and validating our proposed aspen fire regime classification will likely require additional site-specific research, enhanced dendrochronology techniques, charcoal and pollen record analysis, spatially-explicit modeling, and other techniques. We hope to encourage development of site-appropriate disturbance ecology characterizations, in order to aid efforts to manage and restore aspen communities and to diagnose key factors contributing to changes in aspen.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Forest Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2012.11.032","usgsCitation":"Shinneman, D., Baker, W.L., Rogers, P., and Kulakowski, D., 2013, Fire regimes of quaking aspen in the Mountain West: Forest Ecology and Management, v. 299, p. 22-34, https://doi.org/10.1016/j.foreco.2012.11.032.","productDescription":"13 p.","startPage":"22","endPage":"34","ipdsId":"IP-042218","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":274988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274950,"type":{"id":15,"text":"Index Page"},"url":"https://ac.els-cdn.com/S0378112712007086/1-s2.0-S0378112712007086-main.pdf?_tid=e51f440c-eb1c-11e2-9774-00000aacb360&acdnat=1373652191_11d3c5c269906eaf67a6f66c6772b081"},{"id":274984,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.foreco.2012.11.032"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.01,31.33 ], [ -120.01,49.0 ], [ -102.0409,49.0 ], [ -102.0409,31.33 ], [ -120.01,31.33 ] ] ] } } ] }","volume":"299","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e50bd9e4b069f8d27cca7b","chorus":{"doi":"10.1016/j.foreco.2012.11.032","url":"http://dx.doi.org/10.1016/j.foreco.2012.11.032","publisher":"Elsevier BV","authors":"Shinneman Douglas J., Baker William L., Rogers Paul C., Kulakowski Dominik","journalName":"Forest Ecology and Management","publicationDate":"7/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Shinneman, Douglas J.","contributorId":70195,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas J.","affiliations":[],"preferred":false,"id":480858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, William L.","contributorId":30101,"corporation":false,"usgs":true,"family":"Baker","given":"William","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":480855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogers, Paul C.","contributorId":38452,"corporation":false,"usgs":true,"family":"Rogers","given":"Paul C.","affiliations":[],"preferred":false,"id":480856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulakowski, Dominik","contributorId":38453,"corporation":false,"usgs":true,"family":"Kulakowski","given":"Dominik","email":"","affiliations":[],"preferred":false,"id":480857,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70047029,"text":"fs20133029 - 2013 - Water resources of Claiborne Parish, Louisiana","interactions":[],"lastModifiedDate":"2026-06-10T20:37:44.330638","indexId":"fs20133029","displayToPublicDate":"2013-07-15T13:08:00","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":"2013-3029","title":"Water resources of Claiborne Parish, Louisiana","docAbstract":"This fact sheet summarizes basic information on the water resources of Claiborne Parish. Information on groundwater and surface-water availability, quality, development, use, and trends is based on previously published reports listed in the Cited References section. In 2010, about 2.60 million gallons per day (Mgal/d) of water were withdrawn in Claiborne Parish, Louisiana, including about 2.42 Mgal/d from groundwater sources and 0.18 Mgal/d from surface-water sources. Public-supply use accounted for about 84 percent of the total water withdrawn. Other categories of use included industrial, rural domestic, livestock, and general irrigation. Water-use data collected at 5-year intervals from 1960 to 2010 indicated that total water withdrawals in the parish have ranged from about 2.6 to 3.9 Mgal/d.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133029","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Fendick, R., Prakken, L., and Griffith, J.M., 2013, Water resources of Claiborne Parish, Louisiana: U.S. Geological Survey Fact Sheet 2013-3029, 6 p., https://doi.org/10.3133/fs20133029.","productDescription":"6 p.","numberOfPages":"6","additionalOnlineFiles":"N","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":505344,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98655.htm","linkFileType":{"id":5,"text":"html"}},{"id":274986,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3029/FS2013-3029_Claiborne.pdf"},{"id":274985,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3029/"},{"id":274987,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133029.gif"}],"projection":"Universal Transverse Mercator, zone 15","datum":"North American Datum of 1983","country":"United States","state":"Louisiana","county":"Claiborne Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.3653,32.2196 ], [ -93.3653,33.4996 ], [ -92.0853,33.4996 ], [ -92.0853,32.2196 ], [ -93.3653,32.2196 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e50bdae4b069f8d27cca7f","contributors":{"authors":[{"text":"Fendick, Robert B. Jr. rfendick@usgs.gov","contributorId":1313,"corporation":false,"usgs":true,"family":"Fendick","given":"Robert B.","suffix":"Jr.","email":"rfendick@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":480898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griffith, Jason M. 0000-0002-8942-0380 jmgriff@usgs.gov","orcid":"https://orcid.org/0000-0002-8942-0380","contributorId":2923,"corporation":false,"usgs":true,"family":"Griffith","given":"Jason","email":"jmgriff@usgs.gov","middleInitial":"M.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480897,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046825,"text":"70046825 - 2013 - Evolution of dike opening during the March 2011 Kamoamoa fissure eruption, Kīlauea Volcano, Hawai`i","interactions":[],"lastModifiedDate":"2018-10-30T09:10:46","indexId":"70046825","displayToPublicDate":"2013-07-15T12:32:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Evolution of dike opening during the March 2011 Kamoamoa fissure eruption, Kīlauea Volcano, Hawai`i","docAbstract":"The 5–9 March 2011 Kamoamoa fissure eruption along the east rift zone of Kīlauea Volcano, Hawai`i, followed months of pronounced inflation at Kīlauea summit. We examine dike opening during and after the eruption using a comprehensive interferometric synthetic aperture radar (InSAR) data set in combination with continuous GPS data. We solve for distributed dike displacements using a whole Kīlauea model with dilating rift zones and possibly a deep décollement. Modeled surface dike opening increased from nearly 1.5 m to over 2.8 m from the first day to the end of the eruption, in agreement with field observations of surface fracturing. Surface dike opening ceased following the eruption, but subsurface opening in the dike continued into May 2011. Dike volumes increased from 15, to 16, to 21 million cubic meters (MCM) after the first day, eruption end, and 2 months following, respectively. Dike shape is distinctive, with a main limb plunging from the surface to 2–3 km depth in the up‐rift direction toward Kīlauea's summit, and a lesser projection extending in the down‐rift direction toward Pu`u `Ō`ō at 2 km depth. Volume losses beneath Kīlauea summit (1.7 MCM) and Pu`u `Ō`ō (5.6 MCM) crater, relative to dike plus erupted volume (18.3 MCM), yield a dike to source volume ratio of 2.5 that is in the range expected for compressible magma without requiring additional sources. Inflation of Kīlauea's summit in the months before the March 2011 eruption suggests that the Kamoamoa eruption resulted from overpressure of the volcano's magmatic system.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","doi":"10.1002/jgrb.50108","usgsCitation":"Lundgren, P., Poland, M.P., Miklius, A., Orr, T., Yun, S., Fielding, E., Liu, Z., Tanaka, A., Szeliga, W., Hensley, S., and Owen, S., 2013, Evolution of dike opening during the March 2011 Kamoamoa fissure eruption, Kīlauea Volcano, Hawai`i: Journal of Geophysical Research B: Solid Earth, v. 118, no. 3, p. 897-914, https://doi.org/10.1002/jgrb.50108.","productDescription":"18 p.","startPage":"897","endPage":"914","ipdsId":"IP-042091","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrb.50108","text":"Publisher Index Page"},{"id":274980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274979,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50108"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kilauea Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.798371,19.05835 ], [ -155.798371,19.54759 ], [ -155.016307,19.54759 ], [ -155.016307,19.05835 ], [ -155.798371,19.05835 ] ] ] } } ] }","volume":"118","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-03-27","publicationStatus":"PW","scienceBaseUri":"51e50bd9e4b069f8d27cca73","contributors":{"authors":[{"text":"Lundgren, Paul","contributorId":34806,"corporation":false,"usgs":true,"family":"Lundgren","given":"Paul","affiliations":[],"preferred":false,"id":480376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":480377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miklius, Asta 0000-0002-2286-1886 asta@usgs.gov","orcid":"https://orcid.org/0000-0002-2286-1886","contributorId":2060,"corporation":false,"usgs":true,"family":"Miklius","given":"Asta","email":"asta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":480372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orr, Tim R. torr@usgs.gov","contributorId":3766,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","email":"torr@usgs.gov","affiliations":[],"preferred":false,"id":480373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yun, Sang-Ho","contributorId":102772,"corporation":false,"usgs":true,"family":"Yun","given":"Sang-Ho","email":"","affiliations":[],"preferred":false,"id":480382,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fielding, Eric","contributorId":50434,"corporation":false,"usgs":true,"family":"Fielding","given":"Eric","affiliations":[],"preferred":false,"id":480379,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Zhen","contributorId":57750,"corporation":false,"usgs":true,"family":"Liu","given":"Zhen","email":"","affiliations":[],"preferred":false,"id":480380,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tanaka, Akiko","contributorId":30121,"corporation":false,"usgs":true,"family":"Tanaka","given":"Akiko","email":"","affiliations":[],"preferred":false,"id":480375,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Szeliga, Walter","contributorId":50021,"corporation":false,"usgs":true,"family":"Szeliga","given":"Walter","email":"","affiliations":[],"preferred":false,"id":480378,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hensley, Scott","contributorId":85313,"corporation":false,"usgs":true,"family":"Hensley","given":"Scott","email":"","affiliations":[],"preferred":false,"id":480381,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Owen, Susan","contributorId":29004,"corporation":false,"usgs":true,"family":"Owen","given":"Susan","affiliations":[],"preferred":false,"id":480374,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70046879,"text":"70046879 - 2013 - Estimating raptor nesting success: old and new approaches","interactions":[],"lastModifiedDate":"2013-07-15T11:21:18","indexId":"70046879","displayToPublicDate":"2013-07-15T11:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating raptor nesting success: old and new approaches","docAbstract":"Studies of nesting success can be valuable in assessing the status of raptor populations, but differing monitoring protocols can present unique challenges when comparing populations of different species across time or geographic areas. We used large datasets from long-term studies of 3 raptor species to compare estimates of apparent nest success (ANS, the ratio of successful to total number of nesting attempts), Mayfield nesting success, and the logistic-exposure model of nest survival. Golden eagles (Aquila chrysaetos), prairie falcons (Falco mexicanus), and American kestrels (F. sparverius) differ in their breeding biology and the methods often used to monitor their reproduction. Mayfield and logistic-exposure models generated similar estimates of nesting success with similar levels of precision. Apparent nest success overestimated nesting success and was particularly sensitive to inclusion of nesting attempts discovered late in the nesting season. Thus, the ANS estimator is inappropriate when exact point estimates are required, especially when most raptor pairs cannot be located before or soon after laying eggs. However, ANS may be sufficient to assess long-term trends of species in which nesting attempts are highly detectable.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jwmg.566","usgsCitation":"Brown, J.L., Steenhof, K., Kochert, M.N., and Bond, L., 2013, Estimating raptor nesting success: old and new approaches: Journal of Wildlife Management, v. 77, no. 5, p. 1067-1074, https://doi.org/10.1002/jwmg.566.","productDescription":"8 p.","startPage":"1067","endPage":"1074","ipdsId":"IP-016369","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473687,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/jwmg.566","text":"External Repository"},{"id":274974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274710,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.566"}],"volume":"77","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-06-11","publicationStatus":"PW","scienceBaseUri":"51e50bd9e4b069f8d27cca6f","contributors":{"authors":[{"text":"Brown, Jessi L.","contributorId":44817,"corporation":false,"usgs":false,"family":"Brown","given":"Jessi","email":"","middleInitial":"L.","affiliations":[{"id":13184,"text":"Program in Ecology, Evolution and Conservation Biology, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":480552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steenhof, Karen karen_steenhof@usgs.gov","contributorId":30585,"corporation":false,"usgs":true,"family":"Steenhof","given":"Karen","email":"karen_steenhof@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":480551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kochert, Michael N. 0000-0002-4380-3298 mkochert@usgs.gov","orcid":"https://orcid.org/0000-0002-4380-3298","contributorId":3037,"corporation":false,"usgs":true,"family":"Kochert","given":"Michael","email":"mkochert@usgs.gov","middleInitial":"N.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":480550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bond, Laura","contributorId":89103,"corporation":false,"usgs":true,"family":"Bond","given":"Laura","affiliations":[],"preferred":false,"id":480553,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70047489,"text":"70047489 - 2013 - Spatially explicit models for inference about density in unmarked or partially marked populations","interactions":[],"lastModifiedDate":"2013-08-08T08:00:15","indexId":"70047489","displayToPublicDate":"2013-07-15T07:54:57","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":787,"text":"Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit models for inference about density in unmarked or partially marked populations","docAbstract":"Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density—rather, spatial dependence can be informative about individual distribution and density.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Annals of Applied Statistics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Institute of Mathematical Statistics","doi":"10.1214/12-AOAS610","usgsCitation":"Chandler, R.B., and Royle, J., 2013, Spatially explicit models for inference about density in unmarked or partially marked populations: Annals of Applied Statistics, v. 7, no. 2, p. 936-954, https://doi.org/10.1214/12-AOAS610.","productDescription":"19 p.","startPage":"936","endPage":"954","ipdsId":"IP-041849","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473690,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://arxiv.org/abs/1112.3250","text":"Publisher Index Page"},{"id":276189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276184,"type":{"id":15,"text":"Index Page"},"url":"https://projecteuclid.org/euclid.aoas/1372338474"},{"id":276183,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1214/12-AOAS610"}],"volume":"7","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5203a37de4b02bdb1bc63fe4","contributors":{"authors":[{"text":"Chandler, Richard B. rchandler@usgs.gov","contributorId":63524,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":482175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":482176,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046856,"text":"70046856 - 2013 - Integrating resource selection information with spatial capture--recapture","interactions":[],"lastModifiedDate":"2013-07-17T12:46:19","indexId":"70046856","displayToPublicDate":"2013-07-13T12:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Integrating resource selection information with spatial capture--recapture","docAbstract":"1. Understanding space usage and resource selection is a primary focus of many studies of animal populations. Usually, such studies are based on location data obtained from telemetry, and resource selection functions (RSFs) are used for inference. Another important focus of wildlife research is estimation and modeling population size and density. Recently developed spatial capture–recapture (SCR) models accomplish this objective using individual encounter history data with auxiliary spatial information on location of capture. SCR models include encounter probability functions that are intuitively related to RSFs, but to date, no one has extended SCR models to allow for explicit inference about space usage and resource selection.\n2. In this paper we develop the first statistical framework for jointly modeling space usage, resource selection, and population density by integrating SCR data, such as from camera traps, mist-nets, or conventional catch traps, with resource selection data from telemetered individuals. We provide a framework for estimation based on marginal likelihood, wherein we estimate simultaneously the parameters of the SCR and RSF models.\n3. Our method leads to increases in precision for estimating parameters of ordinary SCR models. Importantly, we also find that SCR models alone can estimate parameters of RSFs and, as such, SCR methods can be used as the sole source for studying space-usage; however, precision will be higher when telemetry data are available.\n4. Finally, we find that SCR models using standard symmetric and stationary encounter probability models may not fully explain variation in encounter probability due to space usage, and therefore produce biased estimates of density when animal space usage is related to resource selection. Consequently, it is important that space usage be taken into consideration, if possible, in studies focused on estimating density using capture–recapture methods.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Methods in Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12039","usgsCitation":"Royle, J., Chandler, R.B., Sun, C.C., and Fuller, A.K., 2013, Integrating resource selection information with spatial capture--recapture: Methods in Ecology and Evolution, v. 4, no. 6, p. 520-530, https://doi.org/10.1111/2041-210X.12039.","productDescription":"11 p.","startPage":"520","endPage":"530","ipdsId":"IP-042739","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473691,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://arxiv.org/abs/1207.3288","text":"Publisher Index Page"},{"id":275116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274698,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12039/abstract"},{"id":275115,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/2041-210X.12039"}],"volume":"4","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-03-07","publicationStatus":"PW","scienceBaseUri":"51e7bce1e4b080b82b09c639","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":480476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, Richard B. rchandler@usgs.gov","contributorId":63524,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":480474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Catherine C.","contributorId":70274,"corporation":false,"usgs":false,"family":"Sun","given":"Catherine","email":"","middleInitial":"C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":480475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":480473,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70046997,"text":"ofr20131145 - 2013 - Total suspended solids concentrations and yields for water-quality monitoring stations in Gwinnett County, Georgia, 1996-2009","interactions":[],"lastModifiedDate":"2016-12-08T16:41:04","indexId":"ofr20131145","displayToPublicDate":"2013-07-12T09:56:00","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":"2013-1145","title":"Total suspended solids concentrations and yields for water-quality monitoring stations in Gwinnett County, Georgia, 1996-2009","docAbstract":"The U.S. Geological Survey, in cooperation with the Gwinnett County Department of Water Resources, established a water-quality monitoring program during late 1996 to collect comprehensive, consistent, high-quality data for use by watershed managers. As of 2009, continuous streamflow and water-quality data as well as discrete water-quality samples were being collected for 14 watershed monitoring stations in Gwinnett County.\n\nThis report provides statistical summaries of total suspended solids (TSS) concentrations for 730 stormflow and 710 base-flow water-quality samples collected between 1996 and 2009 for 14 watershed monitoring stations in Gwinnett County. Annual yields of TSS were estimated for each of the 14 watersheds using methods described in previous studies. TSS yield was estimated using linear, ordinary least-squares regression of TSS and explanatory variables of discharge, turbidity, season, date, and flow condition. The error of prediction for estimated yields ranged from 1 to 42 percent for the stations in this report; however, the actual overall uncertainty of the estimated yields cannot be less than that of the observed yields (± 15 to 20 percent). These watershed yields provide a basis for evaluation of how watershed characteristics, climate, and watershed management practices affect suspended sediment yield.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131145","collaboration":"Prepared in cooperation with the Gwinnett County Department of Water Resources","usgsCitation":"Landers, M.N., 2013, Total suspended solids concentrations and yields for water-quality monitoring stations in Gwinnett County, Georgia, 1996-2009: U.S. Geological Survey Open-File Report 2013-1145, iv, 10 p., https://doi.org/10.3133/ofr20131145.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1996-01-01","temporalEnd":"2009-12-13","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":274911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131145.gif"},{"id":274909,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1145/"},{"id":274910,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1145/pdf/ofr2013-1145.pdf"}],"country":"United States","state":"Georgia","county":"Gwinnett County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.276822,33.747276 ], [ -84.276822,34.168231 ], [ -83.799059,34.168231 ], [ -83.799059,33.747276 ], [ -84.276822,33.747276 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e1176ae4b02f5cae2b7354","contributors":{"authors":[{"text":"Landers, Mark N. 0000-0002-3014-0480 landers@usgs.gov","orcid":"https://orcid.org/0000-0002-3014-0480","contributorId":1103,"corporation":false,"usgs":true,"family":"Landers","given":"Mark","email":"landers@usgs.gov","middleInitial":"N.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":480827,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046883,"text":"70046883 - 2013 - Consideration of vertical uncertainty in elevation-based sea-level rise assessments: Mobile Bay, Alabama case study","interactions":[],"lastModifiedDate":"2013-07-11T12:42:41","indexId":"70046883","displayToPublicDate":"2013-07-11T12:38:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Consideration of vertical uncertainty in elevation-based sea-level rise assessments: Mobile Bay, Alabama case study","docAbstract":"The accuracy with which coastal topography has been mapped directly affects the reliability and usefulness of elevationbased sea-level rise vulnerability assessments. Recent research has shown that the qualities of the elevation data must be well understood to properly model potential impacts. The cumulative vertical uncertainty has contributions from elevation data error, water level data uncertainties, and vertical datum and transformation uncertainties. The concepts of minimum sealevel rise increment and minimum planning timeline, important parameters for an elevation-based sea-level rise assessment, are used in recognition of the inherent vertical uncertainty of the underlying data. These concepts were applied to conduct a sea-level rise vulnerability assessment of the Mobile Bay, Alabama, region based on high-quality lidar-derived elevation data. The results that detail the area and associated resources (land cover, population, and infrastructure) vulnerable to a 1.18-m sea-level rise by the year 2100 are reported as a range of values (at the 95% confidence level) to account for the vertical uncertainty in the base data. Examination of the tabulated statistics about land cover, population, and infrastructure in the minimum and maximum vulnerable areas shows that these resources are not uniformly distributed throughout the overall vulnerable zone. The methods demonstrated in the Mobile Bay analysis provide an example of how to consider and properly account for vertical uncertainty in elevation-based sea-level rise vulnerability assessments, and the advantages of doing so.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Coastal Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI63-016.1","usgsCitation":"Gesch, D.B., 2013, Consideration of vertical uncertainty in elevation-based sea-level rise assessments: Mobile Bay, Alabama case study: Journal of Coastal Research, v. 63, p. 197-210, https://doi.org/10.2112/SI63-016.1.","productDescription":"14 p.","startPage":"197","endPage":"210","ipdsId":"IP-034553","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":274874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274712,"type":{"id":15,"text":"Index Page"},"url":"https://www.bioone.org/doi/abs/10.2112/SI63-016.1"},{"id":274873,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2112/SI63-016.1"}],"country":"United States","state":"Alabama","otherGeospatial":"Mobile Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.1643,30.2646 ], [ -88.1643,30.6972 ], [ -87.7397,30.6972 ], [ -87.7397,30.2646 ], [ -88.1643,30.2646 ] ] ] } } ] }","volume":"63","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dfc5dae4b0d332bf22f335","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":480561,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70147933,"text":"70147933 - 2013 - The predicted influence of climate change on lesser prairie-chicken reproductive parameters","interactions":[],"lastModifiedDate":"2017-02-23T14:05:44","indexId":"70147933","displayToPublicDate":"2013-07-11T12:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The predicted influence of climate change on lesser prairie-chicken reproductive parameters","docAbstract":"The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0068225","usgsCitation":"Grisham, B.A., Boal, C.W., Haukos, D.A., Davis, D., Boydston, K.K., Dixon, C., and Heck, W.R., 2013, The predicted influence of climate change on lesser prairie-chicken reproductive parameters: PLoS ONE, v. 8, no. 7, p. 1-10, https://doi.org/10.1371/journal.pone.0068225.","productDescription":"10 p.","startPage":"1","endPage":"10","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043440","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":582,"text":"Texas Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473694,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0068225","text":"Publisher Index Page"},{"id":300284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-07-11","publicationStatus":"PW","scienceBaseUri":"5551d2bde4b0a92fa7e93c19","contributors":{"authors":[{"text":"Grisham, Blake A.","contributorId":75419,"corporation":false,"usgs":true,"family":"Grisham","given":"Blake","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":546638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":546432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":546639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, D.","contributorId":85747,"corporation":false,"usgs":true,"family":"Davis","given":"D.","affiliations":[],"preferred":false,"id":546640,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boydston, Kathy K.","contributorId":15501,"corporation":false,"usgs":true,"family":"Boydston","given":"Kathy","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":546641,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dixon, Charles","contributorId":68203,"corporation":false,"usgs":true,"family":"Dixon","given":"Charles","email":"","affiliations":[],"preferred":false,"id":546642,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heck, Willard R.","contributorId":61732,"corporation":false,"usgs":true,"family":"Heck","given":"Willard","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":546643,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70046719,"text":"sir20135127 - 2013 - Construction of 3-D geologic framework and textural models for Cuyama Valley groundwater basin, California","interactions":[],"lastModifiedDate":"2013-07-11T11:57:26","indexId":"sir20135127","displayToPublicDate":"2013-07-11T12:00:00","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":"2013-5127","title":"Construction of 3-D geologic framework and textural models for Cuyama Valley groundwater basin, California","docAbstract":"Groundwater is the sole source of water supply in Cuyama Valley, a rural agricultural area in Santa Barbara County, California, in the southeasternmost part of the Coast Ranges of California. Continued groundwater withdrawals and associated water-resource management concerns have prompted an evaluation of the hydrogeology and water availability for the Cuyama Valley groundwater basin by the U.S. Geological Survey, in cooperation with the Water Agency Division of the Santa Barbara County Department of Public Works. As a part of the overall groundwater evaluation, this report documents the construction of a digital three-dimensional geologic framework model of the groundwater basin suitable for use within a numerical hydrologic-flow model. The report also includes an analysis of the spatial variability of lithology and grain size, which forms the geologic basis for estimating aquifer hydraulic properties.\n\nThe geologic framework was constructed as a digital representation of the interpreted geometry and thickness of the principal stratigraphic units within the Cuyama Valley groundwater basin, which include younger alluvium, older alluvium, and the Morales Formation, and underlying consolidated bedrock. The framework model was constructed by creating gridded surfaces representing the altitude of the top of each stratigraphic unit from various input data, including lithologic and electric logs from oil and gas wells and water wells, cross sections, and geologic maps.\n\nSediment grain-size data were analyzed in both two and three dimensions to help define textural variations in the Cuyama Valley groundwater basin and identify areas with similar geologic materials that potentially have fairly uniform hydraulic properties. Sediment grain size was used to construct three-dimensional textural models that employed simple interpolation between drill holes and two-dimensional textural models for each stratigraphic unit that incorporated spatial structure of the textural data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135127","usgsCitation":"Sweetkind, D., Faunt, C., and Hanson, R.T., 2013, Construction of 3-D geologic framework and textural models for Cuyama Valley groundwater basin, California: U.S. Geological Survey Scientific Investigations Report 2013-5127, vii, 46 p., https://doi.org/10.3133/sir20135127.","productDescription":"vii, 46 p.","numberOfPages":"58","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":274299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135127.jpg"},{"id":274297,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5127/"},{"id":274298,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5127/pdf/sir2013-5127.pdf"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cea254e4b044272b8e88fa","contributors":{"authors":[{"text":"Sweetkind, Donald S.","contributorId":18732,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[],"preferred":false,"id":480088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":1491,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":480087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480086,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046724,"text":"sir20135108 - 2013 - Geology, water-quality, hydrology, and geomechanics of the Cuyama Valley groundwater basin, California, 2008--12","interactions":[],"lastModifiedDate":"2013-07-11T11:56:45","indexId":"sir20135108","displayToPublicDate":"2013-07-11T12:00:00","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":"2013-5108","title":"Geology, water-quality, hydrology, and geomechanics of the Cuyama Valley groundwater basin, California, 2008--12","docAbstract":"To assess the water resources of the Cuyama Valley groundwater basin in Santa Barbara County, California, a series of cooperative studies were undertaken by the U.S. Geological Survey and the Santa Barbara County Water Agency. Between 2008 and 2012, geologic, water-quality, hydrologic and geomechanical data were collected from selected sites throughout the Cuyama Valley groundwater basin.\n\nGeologic data were collected from three multiple-well groundwater monitoring sites and included lithologic descriptions of the drill cuttings, borehole geophysical logs, temperature logs, as well as bulk density and sonic velocity measurements of whole-core samples.\n\nGeneralized lithologic characterization from the monitoring sites indicated the water-bearing units in the subsurface consist of unconsolidated to partly consolidated sand, gravel, silt, clay, and occasional cobbles within alluvial fan and stream deposits. Analysis of geophysical logs indicated alternating layers of finer- and coarser-grained material that range from less than 1 foot to more than 20 feet thick. On the basis of the geologic data collected, the principal water-bearing units beneath the monitoring-well sites were found to be composed of younger alluvium of Holocene age, older alluvium of Pleistocene age, and the Tertiary-Quaternary Morales Formation. At all three sites, the contact between the recent fill and younger alluvium is approximately 20 feet below land surface.\n\nWater-quality samples were collected from 12 monitoring wells, 27 domestic and supply wells, 2 springs, and 4 surface-water sites and were analyzed for a variety of constituents that differed by site, but, in general, included trace elements; nutrients; dissolved organic carbon; major and minor ions; silica; total dissolved solids; alkalinity; total arsenic and iron; arsenic, chromium, and iron species; and isotopic tracers, including the stable isotopes of hydrogen and oxygen, activities of tritium, and carbon-14 abundance.\n\nOf the 39 wells sampled, concentrations of total dissolved solids and sulfate from 38 and 37 well samples, respectively, were greater than the U.S. Environmental Protection Agency’s secondary maximum contaminant levels. Concentrations greater than the maximum contaminant levels for nitrate were observed in five wells and were observed for arsenic in four wells.\n\nDifferences in the stable-isotopic values of hydrogen and oxygen among groundwater samples indicated that water does not move freely between different formations or between different zones within the Cuyama Valley. Variations in isotopic composition indicated that recharge is derived from several different sources. The age of the groundwater, expressed as time since recharge, was between 600 and 38,000 years before present. Detectable concentrations of tritium indicated that younger water, recharged since the early 1950s, is present in parts of the groundwater basin.\n\nHydrologic data were collected from 12 monitoring wells, 56 domestic and supply wells, 3 surface-water sites, and 4 rainfall-gaging stations. Rainfall in the valley averaged about 8 inches annually, whereas the mountains to the south received between 12 and 19 inches. Stream discharge records showed seasonal variability in surface-water flows ranging from no-flow to over 1,500 cubic feet per second. During periods when inflow to the valley exceeds outflow, there is potential recharge from stream losses to the groundwater system\n\nWater-level records included manual quarterly depth-to-water measurements collected from 68 wells, time-series data collected from 20 of those wells, and historic water levels from 16 wells. Hydrographs of the manual measurements showed declining water levels in 16 wells, mostly in the South-Main zone, and rising water levels in 14 wells, mostly in the Southern Ventucopa Uplands. Time-series hydrographs showed daily, seasonal, and longer-term effects associated with local pumping. Water-level data from the multiple-well monitoring sites indicated seasonal fluctuations as great as 80 feet and water-level differences between aquifers as great as 40 feet during peak pumping season. Hydrographs from the multiple-well groundwater monitoring sites showed vertical hydraulic gradients were upward during the winter months and downward during the irrigation season. Historic hydrographs showed water-level declines in the Southern-Main, Western Basin, Caliente Northern-Main, and Southern Sierra Madre zone ranging from 1 to 7 feet per year. Hydrographs of wells in the Southern Ventucopa Uplands zone showed several years with marked increases in water levels that corresponded to increased precipitation in the Cuyama Valley.\n\nInvestigation of hydraulic properties included hydraulic conductivity and transmissivity estimated from aquifer tests performed on 63 wells. Estimates of horizontal hydraulic conductivity ranged from about 1.5 to 28 feet per day and decreased with depth. The median estimated hydraulic conductivity for the older alluvium was about five times that estimated for the Morales Formation. Estimates of transmissivity ranged from 560 to 163,400 gallons per day per foot and decreased with depth. The median estimated transmissivity for the younger alluvium was about three times that estimated for the older alluvium.\n\nGeomechanical analysis included land-surface elevation changes at five continuously operating global positioning systems (GPS) and land-subsidence detection at five interferometric synthetic aperture radar (InSAR) reference points. Analysis of data collected from continuously operating GPS stations showed the mountains to the south and west moved upward about 1 millimeter (mm) annually, whereas the station in the center of the Southern-Main zone moved downward more than 7 mm annually, indicating subsidence. It is likely that this subsidence is inelastic (permanent) deformation and indicates reduced storage capacity in the aquifer sediments. Analysis of InSAR data showed local and regional changes that appeared to be dependent, in part, on the time span of the interferogram, seasonal variations in pumping, and tectonic uplift. Long-term InSAR time series showed a total maximum detected subsidence rate of approximately 12 mm per year at one location and approximately 8 mm per year at a second location, while short-term InSAR time series showed maximum subsidence of about 15 mm at one location and localized maximum uplift of about 10 mm at another location.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135108","collaboration":"Prepared in cooperation with the County of Santa Barbara","usgsCitation":"Everett, R., Gibbs, D.R., Hanson, R.T., Sweetkind, D., Brandt, J.T., Falk, S.E., and Harich, C.R., 2013, Geology, water-quality, hydrology, and geomechanics of the Cuyama Valley groundwater basin, California, 2008--12: U.S. Geological Survey Scientific Investigations Report 2013-5108, x, 62 p.; Tables, https://doi.org/10.3133/sir20135108.","productDescription":"x, 62 p.; Tables","numberOfPages":"76","additionalOnlineFiles":"Y","temporalStart":"2008-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":274317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135108.jpg"},{"id":274316,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5108/pdf/sir20135108_tables.xlsx"},{"id":274314,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5108/"},{"id":274315,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5108/pdf/sir2013-5108.pdf"}],"country":"United States","state":"California","otherGeospatial":"Cuyama Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.833333,34.666667 ], [ -119.833333,35.1 ], [ -119.166667,35.1 ], [ -119.166667,34.666667 ], [ -119.833333,34.666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d296d6e4b0ca184833899f","contributors":{"authors":[{"text":"Everett, Rhett R. 0000-0001-7983-6270 reverett@usgs.gov","orcid":"https://orcid.org/0000-0001-7983-6270","contributorId":843,"corporation":false,"usgs":true,"family":"Everett","given":"Rhett R.","email":"reverett@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbs, Dennis R.","contributorId":21050,"corporation":false,"usgs":true,"family":"Gibbs","given":"Dennis","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":480108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sweetkind, Donald S.","contributorId":18732,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[],"preferred":false,"id":480107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandt, Justin T. 0000-0002-9397-6824","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":28326,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":480109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Falk, Sarah E. sefalk@usgs.gov","contributorId":1056,"corporation":false,"usgs":true,"family":"Falk","given":"Sarah","email":"sefalk@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":480105,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harich, Christopher R. charich@usgs.gov","contributorId":3917,"corporation":false,"usgs":true,"family":"Harich","given":"Christopher","email":"charich@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":480106,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70046971,"text":"ofr20131141 - 2013 - Preliminary stratigraphic and hydrogeologic cross sections and seismic profile of the Floridan aquifer system of Broward County, Florida","interactions":[],"lastModifiedDate":"2013-07-11T09:48:25","indexId":"ofr20131141","displayToPublicDate":"2013-07-11T09:37:00","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":"2013-1141","title":"Preliminary stratigraphic and hydrogeologic cross sections and seismic profile of the Floridan aquifer system of Broward County, Florida","docAbstract":"To help water-resource managers evaluate the Floridan aquifer system (FAS) as an alternative water supply, the U.S. Geological Survey initiated a study, in cooperation with the Broward County Environmental Protection and Growth Management Department, to refine the hydrogeologic framework of the FAS in the eastern part of Broward County. This report presents three preliminary cross sections illustrating stratigraphy and hydrogeology in eastern Broward County as well as an interpreted seismic profile along one of the cross sections. Marker horizons were identified using borehole geophysical data and were initially used to perform well-to-well correlation. Core sample data were integrated with the borehole geophysical data to support stratigraphic and hydrogeologic interpretations of marker horizons. Stratigraphic and hydrogeologic units were correlated across the county using borehole geophysical data from multiple wells. Seismic-reflection data were collected along the Hillsboro Canal. Borehole geophysical data were used to identify and correlate hydrogeologic units in the seismic-reflection profile. Faults and collapse structures that intersect hydrogeologic units were also identified in the seismic profile. The information provided in the cross sections and the seismic profile is preliminary and subject to revision.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131141","collaboration":"Prepared in cooperation with Broward County, Florida","usgsCitation":"Reese, R.S., and Cunningham, K.J., 2013, Preliminary stratigraphic and hydrogeologic cross sections and seismic profile of the Floridan aquifer system of Broward County, Florida: U.S. Geological Survey Open-File Report 2013-1141, iv, 10 p.; 3 Plates: 37 x 38 inches; 4 Tables, https://doi.org/10.3133/ofr20131141.","productDescription":"iv, 10 p.; 3 Plates: 37 x 38 inches; 4 Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":274861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131141.gif"},{"id":274852,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1141/"},{"id":274853,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1141/pdf/ofr2013-1141.pdf"},{"id":274856,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1141/Downloads/Plates/Plate03_Z-Z.pdf"},{"id":274854,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1141/Downloads/Plates/Plate01_A-A.pdf"},{"id":274857,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1141/Downloads/Tables/Table01.xlsx"},{"id":274858,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1141/Downloads/Tables/Table02.xlsx"},{"id":274855,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1141/Downloads/Plates/Plate02_C-C.pdf"},{"id":274859,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1141/Downloads/Tables/Table03.xlsx"},{"id":274860,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1141/Downloads/Tables/Table04.xlsx"}],"country":"United States","state":"Florida","county":"Broward County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.8814,25.9567 ], [ -80.8814,26.3347 ], [ -80.0153,26.3347 ], [ -80.0153,25.9567 ], [ -80.8814,25.9567 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dfc5dce4b0d332bf22f34b","contributors":{"authors":[{"text":"Reese, Ronald S. rsreese@usgs.gov","contributorId":1090,"corporation":false,"usgs":true,"family":"Reese","given":"Ronald","email":"rsreese@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":480744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cunningham, Kevin J. 0000-0002-2179-8686 kcunning@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-8686","contributorId":1689,"corporation":false,"usgs":true,"family":"Cunningham","given":"Kevin","email":"kcunning@usgs.gov","middleInitial":"J.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":480745,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046968,"text":"ofr20131135 - 2013 - Hydrologic conditions in New Hampshire and Vermont, water year 2011","interactions":[],"lastModifiedDate":"2013-07-11T06:55:38","indexId":"ofr20131135","displayToPublicDate":"2013-07-11T06:45:07","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":"2013-1135","title":"Hydrologic conditions in New Hampshire and Vermont, water year 2011","docAbstract":"Record-high hydrologic conditions in New Hampshire and Vermont occurred during water year 2011, according to data from 125 streamgages and lake gaging stations, 27 creststage gages, and 41 groundwater wells. Annual runoff for the 2011 water year was the sixth highest on record for New Hampshire and the highest on record for Vermont on the basis of a 111-year reference period (water years 1901–2011). Groundwater levels for the 2011 water year were generally normal in New Hampshire and normal to above normal in Vermont. Record flooding occurred in April, May, and August of water year 2011. Peak-of-record streamflows were recorded at 38 streamgages, 25 of which had more than 10 years of record. Flooding in April 2011 was widespread in parts of northern New Hampshire and Vermont; peak-of-record streamflows were recorded at nine streamgages. Flash flooding in May 2011 was isolated to central and northeastern Vermont; peakof- record streamflows were recorded at five streamgages. Devastating flooding in August 2011 occurred throughout most of Vermont and in parts of New Hampshire as a result of the heavy rains associated with Tropical Storm Irene. Peak-ofrecord streamflows were recorded at 24 streamgages.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131135","collaboration":"Prepared in cooperation with the States of New Hampshire and Vermont and with other agencies","usgsCitation":"Kiah, R.G., Jarvis, J.D., Hegemann, R.F., Hilgendorf, G.S., and Ward, S.L., 2013, Hydrologic conditions in New Hampshire and Vermont, water year 2011: U.S. Geological Survey Open-File Report 2013-1135, vi, 38 p., https://doi.org/10.3133/ofr20131135.","productDescription":"vi, 38 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":274842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131135.gif"},{"id":274840,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1135/"},{"id":274841,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1135/pdf/ofr2013-1135_report_508.pdf"}],"country":"United States","state":"New Hampshire;Vermont","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.4305,42.7268 ], [ -73.4305,45.3055 ], [ -70.6014,45.3055 ], [ -70.6014,42.7268 ], [ -73.4305,42.7268 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dfc5dce4b0d332bf22f347","contributors":{"authors":[{"text":"Kiah, Richard G. 0000-0001-6236-2507 rkiah@usgs.gov","orcid":"https://orcid.org/0000-0001-6236-2507","contributorId":2637,"corporation":false,"usgs":true,"family":"Kiah","given":"Richard","email":"rkiah@usgs.gov","middleInitial":"G.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarvis, Jason D. jdjarvis@usgs.gov","contributorId":5146,"corporation":false,"usgs":true,"family":"Jarvis","given":"Jason","email":"jdjarvis@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":480731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hegemann, Robert F. hegemann@usgs.gov","contributorId":5145,"corporation":false,"usgs":true,"family":"Hegemann","given":"Robert","email":"hegemann@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":480730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hilgendorf, Gregory S. gshilgen@usgs.gov","contributorId":5144,"corporation":false,"usgs":true,"family":"Hilgendorf","given":"Gregory","email":"gshilgen@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":480729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ward, Sanborn L. sward@usgs.gov","contributorId":5147,"corporation":false,"usgs":true,"family":"Ward","given":"Sanborn","email":"sward@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":480732,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043959,"text":"70043959 - 2013 - Snake River fall Chinook salmon life history investigations: Annual report 2011 (April 2011 - March 2012)","interactions":[],"lastModifiedDate":"2016-05-04T12:28:01","indexId":"70043959","displayToPublicDate":"2013-07-11T06:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Snake River fall Chinook salmon life history investigations: Annual report 2011 (April 2011 - March 2012)","docAbstract":"Chapter One – This chapter was published in the Transactions of the American Fisheries Society in 2012. We conducted a three-year radiotelemetry study in the lower Snake River to answer the questions: do fall Chinook salmon juveniles pass dams during winter when bypass systems and structures designed to prevent mortality are not operated; does downstream movement rate vary annually, seasonally, and from reservoir to reservoir; and, what are some of the factors that contribute to annual, seasonal, and spatial variation in downstream movement rate? Fall Chinook salmon juveniles moved downstream up to 169 km and fast enough (7.5 km/d) such that large percentages (up to 93%) of the fish passed one or more dams during winter. Mean downstream movement rate varied annually (9.2-11.3 km/d), increased from winter (7.5 km/d) to spring (16.4 km/d), and increased (6.9-16.8 km/d) as fish moved downstream from reservoir to reservoir. Fish condition factor at tagging explained some of the annual variation (P≤ 0.01) in downstream movement rate, whereas water particle velocity (P≤0.0001) and temperature (P≤0.0001) explained portions of the seasonal variation. An increase in migrational disposition as fish moved downstream helped explain the spatial variation (P=0.05-0.07). The potential cost of winter movement might be reduced survival due to turbine passage when the bypass systems and spillway passage structures are not operated. Efforts to understand and increase passage survival of winter migrants in large impoundments might help to rehabilitate some imperiled anadromous salmonid populations.
\nChapter Two – Natural juvenile fall Chinook salmon in the Snake and Clearwater rivers exhibit two life history strategies. “Ocean-type” fish migrate out to the ocean in their first summer of life as subyearlings, but “reservoir-type” fish delay seaward migration during the summer, and some overwinter in reservoirs before continuing their migration the following spring as yearlings. Earlier emerging fish produced in the Snake River tend to adopt the ocean-type life history whereas many of the later emerging fish from the Clearwater River tend to adopt the reservoirtype life history. The underlying cause of the reservoir-type life history is poorly understood, but we believe there may be link to physiological development. We used traditional markers of the parr-smolt transformation (smoltification), including gill Na+/K+-ATPase activity and thyroid hormone levels, along with gene expression microarrays to assess the development of ocean-type juvenile fall Chinook salmon and then compared it to that of juvenile fall Chinook salmon from the Clearwater River. We showed that parr in the Snake River are physiologically distinct from actively-migrating smolts but smolts migrating early and late in the summer and fall are physiologically similar. Juvenile fall Chinook salmon collected from the Clearwater River were similar in size to early-migrating smolts in the Snake River but were most physiologically similar to Snake River parr. Genes differentially expressed between Snake River parr and smolts and between fish from the Clearwater River and smolts from the Snake River were involved in the cell cycle, steroid metabolism and other metabolic pathways, and DNA repair and packaging. Many of the genes differentially expressed in these comparisons had expression patterns that correlated with gill Na+/K+-ATPase activity, suggesting that they were related to smoltification and migration status.
\nChapter Three – Natural subyearlings produced in the Clearwater River are exposed to cool (~10-12°C) temperatures when water is released from Dworshak Reservoir for summer flow augmentation. Total dissolved gas (TDG) levels range from 100-110% in the lower Clearwater iv River. When fish move into the Snake River, they encounter temperatures up to 24°C at the surface which have the potential to incur gas bubble disease (GBD) in fish as dissolved gases in their bodies expand under warmer temperatures. This may result in both direct and indirect mortality, but this situation has been little studied. We conducted laboratory experiments to examine subyearling mortality rates and incidence and severity of GBD in fish that were moved between waters that varied in TDG and temperature. Fish experienced significant mortality only at temperatures of 25°C, which increased with exposure time. However there was no significance difference in mortality between fish acclimated to 100% TDG and 110% TDG. Fish that died did show signs of GBD. Generally, signs of GBD such as bubbles in the lateral line and unpaired fins were higher in fish acclimated at 110% TDG than in fish acclimated at 100% TDG, but there were few trends related to exposure temperature. Field measurements of TDG showed that TDG ranged from about 100% to 122.5% at some locations. Generally, TDG fluctuated daily, up to 8% during August and early September, and was highest late in the afternoon and lowest in the early morning. Laboratory results and field monitoring demonstrated that emigrating juvenile salmon can potentially be at risk from elevated temperatures, TDG, and GBD albeit to an unknown extent, which may increase their vulnerability to predation.
\nChapter Four – We conducted monthly beam trawling in Lower Granite and Little Goose reservoirs to describe the seasonal abundance of benthic epifauna that are potentially important as prey to juvenile fall Chinook salmon. The predominant taxa collected were Siberian prawns, the opossum shrimp Neomysis mercedis, and the amphipod Corophium sp. Prawns were relatively abundant at shallow sites in both reservoirs in June, but were more abundant at deep sites in lower and middle reservoir reaches in autumn. Prawn densities were commonly <0.2/m2. Prawn length-frequency data indicated that there were at least two size classes. Juvenile prawns present in shallow water more often than adult prawns, which were generally only found in deep water by autumn. Ovigerous prawns had an average of 171 eggs, which represented about 11.5% of their body weight. Limited diet analyses suggested that prawns consumed Corophium, Neomysis, and aquatic insects. Neomysis dominated all catches both in terms of abundance and biomass, and they were more abundant in Lower Granite compared to Little Goose reservoir. Neomysis were more abundant at shallow sites than at deep sites. Corophium were present in our collections but were never abundant, probably because our trawl was not effective at capturing them. The caloric content of prawns (4,782 Kcal), Neomysis (4,962 Kcal), and Corophium (4,926 Kcal) indicates that these prey would be energetically profitable for juvenile salmon. Subyearling fall Chinook salmon prey heavily on Neomysis and Corophium at times, but the importance of prawns as prey is uncertain.
","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Tiffan, K.F., Connor, W.P., Bellgraph, B., Kock, T.J., Mullins, F., Steinhorst, R., Christiansen, H.E., McCormick, S., Ortega, L.A., Carter, K.M., Arntzen, E.V., Klett, K.J., Deng, Z.D., Abel, T.K., Linley, T.J., Cullinan, V.I., St John, S.J., Erhardt, J.M., Bickford, B.K., Schmidt, A., and Rhodes, T.N., 2013, Snake River fall Chinook salmon life history investigations: Annual report 2011 (April 2011 - March 2012), 134 p.","productDescription":"134 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040902","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":320564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":320968,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/PiscesPublication.mvc/SearchByTextInDocuments/?SearchString=P128358"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Lower Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.7569580078125,\n 45.251688256117646\n ],\n [\n -117.7569580078125,\n 46.76244305208004\n ],\n [\n -116.53198242187499,\n 46.76244305208004\n ],\n [\n -116.53198242187499,\n 45.251688256117646\n ],\n [\n -117.7569580078125,\n 45.251688256117646\n ]\n ]\n ]\n }\n }\n ]\n}","tableOfContents":"Chapter 1: Downstream movement of fall Chinook salmon juveniles in the lower Snake River reservoirs during winter and early spring
\nChapter 2: Gene expression and physiological development of natural subyearling fall Chinook salmon in the Snake and Clearwater rivers
\nChapter 3: Mortality and severity of gas bubble disease of juvenile fall Chinook salmon exposed to supersaturated gas concentrations and sudden changes in temperature
\nChapter 4: Distribution and abundance of potential invertebrate prey for juvenile fall Chinook salmon in the Snake River
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We develop a technique for inverting geodetic, extrusive flux, and other types of data using a physics-based model of an effusive silicic volcanic eruption to estimate the geometry, pressure, depth, and volatile content of a magma chamber, and properties of the conduit linking the chamber to the surface. A Bayesian inverse formulation makes it possible to easily incorporate independent information into the inversion, such as petrologic estimates of melt water content, and yields probabilistic estimates for model parameters and other properties of the volcano. Probability distributions are sampled using a Markov-Chain Monte Carlo algorithm. We apply the technique using GPS and extrusion data from the 2004–2008 eruption of Mount St. Helens. In contrast to more traditional inversions such as those involving geodetic data alone in combination with kinematic forward models, this technique is able to provide constraint on properties of the magma, including its volatile content, and on the absolute volume and pressure of the magma chamber. Results suggest a large chamber of >40 km3 with a centroid depth of 11–18 km and a dissolved water content at the top of the chamber of 2.6–4.9 wt%.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","doi":"10.1002/jgrb.50169","usgsCitation":"Anderson, K., and Segall, P., 2013, Bayesian inversion of data from effusive volcanic eruptions using physics-based models: Application to Mount St. Helens 2004--2008: Journal of Geophysical Research B: Solid Earth, v. 118, no. 5, p. 2017-2037, https://doi.org/10.1002/jgrb.50169.","productDescription":"21 p.","startPage":"2017","endPage":"2037","ipdsId":"IP-042668","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"links":[{"id":473700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrb.50169","text":"Publisher Index Page"},{"id":274824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274708,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50169"},{"id":274709,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/jgrb.50169/abstract"}],"country":"United States","state":"Washington","county":"Skamania County","otherGeospatial":"Mount Saint Helens","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.248734,46.156062 ], [ -122.248734,46.24062 ], [ -122.12654,46.24062 ], [ -122.12654,46.156062 ], [ -122.248734,46.156062 ] ] ] } } ] }","volume":"118","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-05-22","publicationStatus":"PW","scienceBaseUri":"51de7455e4b0d24b0f89c65e","contributors":{"authors":[{"text":"Anderson, Kyle 0000-0001-8041-3996","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":53677,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","affiliations":[{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":480544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Segall, Paul","contributorId":75942,"corporation":false,"usgs":true,"family":"Segall","given":"Paul","affiliations":[],"preferred":false,"id":480545,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046952,"text":"sir20135060 - 2013 - The simulated effects of wastewater-management actions on the hydrologic system and nitrogen-loading rates to wells and ecological receptors, Popponesset Bay Watershed, Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2013-07-10T10:59:31","indexId":"sir20135060","displayToPublicDate":"2013-07-10T10:50:00","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":"2013-5060","title":"The simulated effects of wastewater-management actions on the hydrologic system and nitrogen-loading rates to wells and ecological receptors, Popponesset Bay Watershed, Cape Cod, Massachusetts","docAbstract":"The discharge of excess nitrogen into Popponesset Bay, an estuarine system on western Cape Cod, has resulted in eutrophication and the loss of eel grass habitat within the estuaries. Septic-system return flow in residential areas within the watershed is the primary source of nitrogen. Total Maximum Daily Loads (TMDLs) for nitrogen have been assigned to the six estuaries that compose the system, and local communities are in the process of implementing the TMDLs by the partial sewering, treatment, and disposal of treated wastewater at wastewater-treatment facilities (WTFs). Loads of waste-derived nitrogen from both current (1997–2001) and future sources can be estimated implicitly from parcel-scale water-use data and recharge areas delineated by a groundwater-flow model. These loads are referred to as “instantaneous” loads because it is assumed that the nitrogen from surface sources is delivered to receptors instantaneously and that there is no traveltime through the aquifer. The use of a solute-transport model to explicitly simulate the transport of mass through the aquifer from sources to receptors can improve implementation of TMDLs by (1) accounting for traveltime through the aquifer, (2) avoiding limitations associated with the estimation of loads from static recharge areas, (3) accounting more accurately for the effect of surface waters on nitrogen loads, and (4) determining the response of waste-derived nitrogen loads to potential wastewater-management actions.\n\nThe load of nitrogen to Popponesset Bay on western Cape Cod, which was estimated by using current sources as input to a solute-transport model based on a steady-state flow model, is about 50 percent of the instantaneous load after about 7 years of transport (loads to estuary are equal to loads discharged from sources); this estimate is consistent with simulated advective traveltimes in the aquifer, which have a median of 5 years. Model-calculated loads originating from recharge areas reach 80 percent of the instantaneous load within 30 years; this result indicates that loads estimated from recharge areas likely are reasonable for estimating current instantaneous loads. However, recharge areas are assumed to remain static as stresses and hydrologic conditions change in response to wastewater-management actions.\n\nSewering of the Popponesset Bay watershed would not change hydraulic gradients and recharge areas to receptors substantially; however, disposal of wastewater from treatment facilities can change hydraulic gradients and recharge areas to nearby receptors, particularly if the facilities are near the boundary of the recharge area. In these cases, nitrogen loads implicitly estimated by using current recharge areas that do not accurately represent future hydraulic stresses can differ significantly from loads estimated with recharge areas that do represent those stresses. Nitrogen loads to two estuaries in the Popponesset Bay system estimated by using recharge areas delineated for future hydrologic conditions and nitrogen sources were about 3 and 9 times higher than loads estimated by using current recharge areas; for this reason, reliance on static recharge areas can present limitations for effective TMDL implementation by means of a hypothetical, but realistic, wastewater-management action. A solute-transport model explicitly represents nitrogen transport from surface sources and does not rely on the use of recharge areas; because changes in gradients resulting from wastewater-management actions are accounted for in transport simulations, they provide more reliable predictions of future nitrogen loads.\n\nExplicitly representing the mass transport of nitrogen can better account for the mechanisms by which nitrogen enters the estuary and improve estimates of the attenuation of nitrogen concentrations in fresh surface waters. Water and associated nitrogen can enter an estuary as either direct groundwater discharge or as surface-water inflow. Two estuaries in the Popponesset Bay watershed receive surface-water inflows: Shoestring Bay receives water from the Santuit River, and the tidal reach of the Mashpee River receives water (and associated nitrogen) from the nontidal reach of the Mashpee River. Much of the water discharging into these streams passes through ponds prior to discharge. The additional attenuation of nitrogen in groundwater that has passed through a pond and discharged into a stream prior to entering an estuary is about 3 kilograms per day.\n\nAdvective-transport times in the aquifer generally are small—median traveltimes are about 4.5 years—and nitrogen loads at receptors respond quickly to wastewater-management actions. The simulated decreases in nitrogen loads were 50 and 80 percent of the total decreases within 5 and 15 years, respectively, after full sewering of the watershed and within 3 and 10 years, for sequential phases of partial sewering and disposal at WTFs. The results show that solute-transport models can be used to assess the responses of nitrogen loads to wastewater-management actions, and that loads at ecological receptors (receiving waters—ponds, streams or coastal waters—that support ecosystems) will respond within a few years to those actions.\n\nThe responses vary for individual receptors as functions of hydrologic setting, traveltimes in the aquifer, and the unique set of nitrogen sources representing current and future wastewater-disposal actions within recharge areas. Changes in nitrogen loads from groundwater discharge to individual estuaries range from a decrease of 90 percent to an increase of 80 percent following sequential phases of hypothetical but realistic wastewater-management actions. The ability to explicitly represent the transport of mass through the aquifer allows for the evaluation of complex responses that include the effects of surface waters, traveltimes, and complex changes in sources. Most of the simulated decreases in nitrogen loads to Shoestring Bay and the tidal portion of the Mashpee River, 79 and 69 percent, respectively, were caused by decreases in the nitrogen loads from surface-water inflow.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135060","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Walter, D.A., 2013, The simulated effects of wastewater-management actions on the hydrologic system and nitrogen-loading rates to wells and ecological receptors, Popponesset Bay Watershed, Cape Cod, Massachusetts: U.S. Geological Survey Scientific Investigations Report 2013-5060, vii, 62 p., https://doi.org/10.3133/sir20135060.","productDescription":"vii, 62 p.","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":274823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135060.jpg"},{"id":274821,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5060/"},{"id":274822,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5060/pdf/sir2013-5060_report.pdf"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod;Popponesset Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.75,41.5 ], [ -70.75,42.083333 ], [ -69.833333,42.083333 ], [ -69.833333,41.5 ], [ -70.75,41.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51de7457e4b0d24b0f89c66e","contributors":{"authors":[{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480671,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}