{"pageNumber":"595","pageRowStart":"14850","pageSize":"25","recordCount":46865,"records":[{"id":70043341,"text":"sir20125288 - 2013 - Aquatic assessment of the Pike Hill Copper Mine Superfund site, Corinth, Vermont","interactions":[],"lastModifiedDate":"2013-02-12T11:35:21","indexId":"sir20125288","displayToPublicDate":"2013-02-12T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5288","title":"Aquatic assessment of the Pike Hill Copper Mine Superfund site, Corinth, Vermont","docAbstract":"The Pike Hill Copper Mine Superfund site in Corinth, Orange County, Vermont, includes the Eureka, Union, and Smith mines along with areas of downstream aquatic ecosystem impairment. The site was placed on the U.S. Environmental Protection Agency (USEPA) National Priorities List in 2004. The mines, which operated from about 1847 to 1919, contain underground workings, foundations from historical structures, several waste-rock piles, and some flotation tailings. The mine site is drained to the northeast by Pike Hill Brook, which includes several wetland areas, and to the southeast by an unnamed tributary that flows to the south and enters Cookville Brook. Both brooks eventually drain into the Waits River, which flows into the Connecticut River. The aquatic ecosystem at the site was assessed using a variety of approaches that investigated surface-water quality, sediment quality, and various ecological indicators of stream-ecosystem health. The degradation of surface-water quality is caused by elevated concentrations of copper, and to a lesser extent cadmium, with localized effects caused by aluminum, iron, and zinc. Copper concentrations in surface waters reached or exceeded the USEPA national recommended chronic water-quality criteria for the protection of aquatic life in all of the Pike Hill Brook sampling locations except for the location farthest downstream, in half of the locations sampled in the tributary to Cookville Brook, and in about half of the locations in one wetland area located in Pike Hill Brook. Most of these same locations also contained concentrations of cadmium that exceeded the chronic water-quality criteria. In contrast, surface waters at background sampling locations were below these criteria for copper and cadmium. Comparison of hardness-based and Biotic Ligand Model (BLM)-based criteria for copper yields similar results with respect to the extent or number of stations impaired for surface waters in the affected area. However, the BLM-based criteria are commonly lower values than the hardness-based criteria and thus suggest a greater degree or magnitude of impairment at the sampling locations. The riffle-habitat benthic invertebrate richness and abundance data correlate strongly with the extent of impact based on water quality for both brooks. Similarly, the fish community assessments document degraded conditions throughout most of Pike Hill Brook, whereas the data for the tributary to Cookville Brook suggest less degradation to this brook. The sediment environment shows similar extents of impairment to the surface-water environment, with most sampling locations in Pike Hill Brook, including the wetland areas, and the tributary to Cookville Brook affected. Sediment impairment is caused by elevated copper concentrations, although localized degradation due to elevated cadmium and zinc concentrations was documented on the basis of exceedances of probable effects concentrations (PECs). In contrast to impairment determined by exceedances of PECs, equilibrium-partitioning sediment benchmarks (based on simultaneously extracted metals, acid volatile sulfides, and total organic carbon) predict no toxic effects in sediments at the background locations and uncertain toxic effects throughout Pike Hill Brook and the tributary to Cookville Brook, with the exception of the most downstream Cookville Brook location, which indicated no toxic effects. Acute laboratory toxicity testing using the amphipod <i>Hyalella azteca</i> and the midge <i>Chironomus dilutus</i> on pore waters extracted from sediment in situ indicate impairment (based on tests with <i>H. azteca</i>) at only one location in Pike Hill Brook and no impairment in the tributary to Cookville Brook. Chronic laboratory sediment toxicity testing using <i>H. azteca</i> and <i>C. dilutus</i> indicated toxicity in Pike Hill Brook at several locations in the lower reach and two locations in the tributary to Cookville Brook. Toxicity was not indicated for either species in sediment from the most acidic metal-rich location, likely due to the low lability of copper in that sediment, as indicated by a low proportion of extractable copper (simultaneously extracted metal (SEM) copper only 5 percent of total copper) and due to the flushing of acidic metal-rich pore water from experimental chambers as overlying test water was introduced before and replaced periodically during the toxicity tests. Depositional habitat invertebrate richness and abundance data generally agreed with the results of toxicity tests and with the extent of impact in the watersheds on the basis of sediment and pore waters. The information was used to develop an overall assessment of the impact of mine drainage on the aquatic system downstream from the Pike Hill copper mines. Most of Pike Hill Brook, including several wetland areas that are all downstream from the Eureka and Union mines, was found to be impaired on the basis of water-quality data and biological assessments of fish or benthic invertebrate communities. In contrast, only one location in the tributary to Cookville Brook, downstream from the Smith mine, is definitively impaired. The biological community begins to recover at the most downstream locations in both brooks due to natural attenuation from mixing with unimpaired streams. On the basis of water quality and biological assessment, the reference locations were of good quality. The sediment toxicity, chemistry, and aquatic community survey data suggest that the sediments could be a source of toxicity in Pike Hill Brook and the tributary to Cookville Brook. On the basis of water quality, sediment quality, and biologic communities, the impacts of mine drainage on the aquatic ecosystem health of the watersheds in the study area are generally consistent with the toxicity suggested from laboratory toxicity testing on pore water and sediments.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125288","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Piatak, N., Argue, D.M., Seal, R., Kiah, R.G., Besser, J.M., Coles, J.F., Hammarstrom, J.M., Levitan, D.M., Deacon, J.R., and Ingersoll, C.G., 2013, Aquatic assessment of the Pike Hill Copper Mine Superfund site, Corinth, Vermont: U.S. Geological Survey Scientific Investigations Report 2012-5288, x, 109 p.; 14 Appendixes; 17 Tables, https://doi.org/10.3133/sir20125288.","productDescription":"x, 109 p.; 14 Appendixes; 17 Tables","startPage":"i","endPage":"109","numberOfPages":"124","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":267279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5288.gif"},{"id":267274,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5288/"},{"id":267275,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5288/pdf/sir2012-5288.pdf"},{"id":267276,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5288/SIR2012_5288_Appendix1.zip"},{"id":267277,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5288/pdf/appendixes2-14.pdf"},{"id":267278,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2012/5288/text_and_appendix_tables.xlsx"}],"country":"United States","state":"Vermont","city":"Corinth","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -72.382768,43.978778 ], [ -72.382768,44.096112 ], [ -72.19157,44.096112 ], [ -72.19157,43.978778 ], [ -72.382768,43.978778 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511b6462e4b0e3ef7b6f1df1","contributors":{"authors":[{"text":"Piatak, Nadine M.","contributorId":23621,"corporation":false,"usgs":true,"family":"Piatak","given":"Nadine M.","affiliations":[],"preferred":false,"id":473437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Argue, Denise M. 0000-0002-1096-5362 dmargue@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-5362","contributorId":2636,"corporation":false,"usgs":true,"family":"Argue","given":"Denise","email":"dmargue@usgs.gov","middleInitial":"M.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":473434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":473429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":473435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":473432,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coles, James F. 0000-0002-1953-012X jcoles@usgs.gov","orcid":"https://orcid.org/0000-0002-1953-012X","contributorId":2239,"corporation":false,"usgs":true,"family":"Coles","given":"James","email":"jcoles@usgs.gov","middleInitial":"F.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473433,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":473430,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Levitan, Denise M.","contributorId":77798,"corporation":false,"usgs":true,"family":"Levitan","given":"Denise","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":473438,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Deacon, Jeffrey R. 0000-0001-5793-6940 jrdeacon@usgs.gov","orcid":"https://orcid.org/0000-0001-5793-6940","contributorId":2786,"corporation":false,"usgs":true,"family":"Deacon","given":"Jeffrey","email":"jrdeacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473436,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":473431,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70038462,"text":"70038462 - 2013 - Velocity Mapping Toolbox (VMT): a processing and visualization suite for moving-vessel ADCP measurements","interactions":[],"lastModifiedDate":"2014-01-15T12:51:57","indexId":"70038462","displayToPublicDate":"2013-02-11T12:47:45","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Velocity Mapping Toolbox (VMT): a processing and visualization suite for moving-vessel ADCP measurements","docAbstract":"The use of acoustic Doppler current profilers (ADCP) for discharge measurements and three-dimensional flow mapping has increased rapidly in recent years and has been primarily driven by advances in acoustic technology and signal processing. Recent research has developed a variety of methods for processing data obtained from a range of ADCP deployments and this paper builds on this progress by describing new software for processing and visualizing ADCP data collected along transects in rivers or other bodies of water. The new utility, the Velocity Mapping Toolbox (VMT), allows rapid processing (vector rotation, projection, averaging and smoothing), visualization (planform and cross-section vector and contouring), and analysis of a range of ADCP-derived datasets. The paper documents the data processing routines in the toolbox and presents a set of diverse examples that demonstrate its capabilities. The toolbox is applicable to the analysis of ADCP data collected in a wide range of aquatic environments and is made available as open-source code along with this publication.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth Surface Processes and Landforms","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"John Wiley & Sons","publisherLocation":"Chichester, Sussex; New York","doi":"10.1002/esp.3367","usgsCitation":"Parsons, D., Jackson, P., Czuba, J.A., Engel, F., Rhoads, B., Oberg, K.A., Best, J., Mueller, D.S., Johnson, K., and Riley, J., 2013, Velocity Mapping Toolbox (VMT): a processing and visualization suite for moving-vessel ADCP measurements: Earth Surface Processes and Landforms, v. 38, no. 11, p. 1244-1260, https://doi.org/10.1002/esp.3367.","productDescription":"17 p.","startPage":"1244","endPage":"1260","numberOfPages":"17","ipdsId":"IP-031729","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":281096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281095,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/esp.3367"}],"volume":"38","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-02-11","publicationStatus":"PW","scienceBaseUri":"53cd7b07e4b0b2908510ddf1","contributors":{"authors":[{"text":"Parsons, D.R.","contributorId":84322,"corporation":false,"usgs":true,"family":"Parsons","given":"D.R.","email":"","affiliations":[],"preferred":false,"id":464275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, P.R.","contributorId":68552,"corporation":false,"usgs":true,"family":"Jackson","given":"P.R.","email":"","affiliations":[],"preferred":false,"id":464273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Czuba, J. A.","contributorId":98036,"corporation":false,"usgs":true,"family":"Czuba","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":464277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engel, F.L.","contributorId":7182,"corporation":false,"usgs":true,"family":"Engel","given":"F.L.","email":"","affiliations":[],"preferred":false,"id":464268,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rhoads, B.L.","contributorId":17186,"corporation":false,"usgs":true,"family":"Rhoads","given":"B.L.","email":"","affiliations":[],"preferred":false,"id":464269,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oberg, K. A.","contributorId":67553,"corporation":false,"usgs":true,"family":"Oberg","given":"K.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":464272,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Best, J.L.","contributorId":49635,"corporation":false,"usgs":true,"family":"Best","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":464270,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, D. S.","contributorId":51338,"corporation":false,"usgs":true,"family":"Mueller","given":"D.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":464271,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, K. K.","contributorId":70871,"corporation":false,"usgs":true,"family":"Johnson","given":"K. K.","affiliations":[],"preferred":false,"id":464274,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Riley, J.D.","contributorId":85092,"corporation":false,"usgs":true,"family":"Riley","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":464276,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70043297,"text":"sir20125094 - 2013 - Status and understanding of groundwater quality in the Madera, Chowchilla Study Unit, 2008: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2013-02-12T11:34:26","indexId":"sir20125094","displayToPublicDate":"2013-02-11T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5094","subseriesTitle":"California Groundwater Ambient Monitoring and Assessment (GAMA) Program","title":"Status and understanding of groundwater quality in the Madera, Chowchilla Study Unit, 2008: California GAMA Priority Basin Project","docAbstract":"Groundwater quality in the approximately 860-square-mile Madera and Chowchilla Subbasins (Madera-Chowchilla study unit) of the San Joaquin Valley Basin was investigated as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in California's Central Valley region in parts of Madera, Merced, and Fresno Counties. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory. The Project was designed to provide statistically robust assessments of untreated groundwater quality within the primary aquifer systems in California. The primary aquifer system within each study unit is defined by the depth of the perforated or open intervals of the wells listed in the California Department of Public Health (CDPH) database of wells used for municipal and community drinking-water supply. The quality of groundwater in shallower or deeper water-bearing zones may differ from that in the primary aquifer system; shallower groundwater may be more vulnerable to contamination from the surface. The assessments for the Madera-Chowchilla study unit were based on water-quality and ancillary data collected by the USGS from 35 wells during April-May 2008 and water-quality data reported in the CDPH database. Two types of assessments were made: (1) <i>status</i>, assessment of the current quality of the groundwater resource, and (2) <i>understanding</i>, identification of natural factors and human activities affecting groundwater quality. The primary aquifer system is represented by the grid wells, of which 90 percent (%) had depths that ranged from about 200 to 800 feet (ft) below land surface and had depths to the top of perforations that ranged from about 140 to 400 ft below land surface. Relative-concentrations (sample concentrations divided by benchmark concentrations) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration (RC) greater than 1.0 indicates a concentration above a benchmark. RCs for organic constituents (volatile organic compounds and pesticides) and special-interest constituents (perchlorate) were classified as \"high\" (RC is greater than 1.0), \"moderate\" (RC is less than or equal to 1.0 and greater than 0.1), or \"low\" (RC is less than or equal to 0.1). For inorganic constituents (major and minor ions, trace elements, nutrients, and radioactive constituents), the boundary between low and moderate RCs was set at 0.5. The assessments characterize untreated groundwater quality, not the quality of treated drinking water delivered to consumers by water purveyors; drinking-water benchmarks, and thus relative-concentrations, are used to provide context for the concentrations of constituents measured in groundwater. Aquifer-scale proportion was used in the status assessment as the primary metric for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifer system with RCs greater than 1.0 for a particular constituent or class of constituents; moderate and low aquifer-scale proportions are defined as the percentages of the area of the primary aquifer system with moderate and low RCs, respectively. Percentages are based on an areal, rather than a volumetric basis. Two statistical approaches--grid-based, which used one value per grid cell, and spatially weighted, which used multiple values per grid cell--were used to calculate aquifer-scale proportions for individual constituents and classes of constituents. The spatially weighted estimates of high aquifer-scale proportions were within the 90% confidence intervals of the grid-based estimates for all constituents except iron. The status <i>assessment</i> showed that inorganic constituents had greater high and moderate aquifer-scale proportions in the Madera-Chowchilla study unit than did organic constituents. RCs for inorganic constituents with health-based benchmarks were high in 37% of the primary aquifer system, moderate in 30%, and low in 33%. The inorganic constituents contributing most to the high aquifer-scale proportion were arsenic (13%), uranium (17%), gross alpha particle activity (20%), nitrate (6.7%), and vanadium (3.3%). RCs for inorganic constituents with non-health-based benchmarks were high in 6.7% of the primary aquifer system, and the constituent contributing most to the high aquifer-scale proportion was total dissolved solids (TDS). RCs for organic constituents with health-based benchmarks were high in 10% of the primary aquifer system, moderate in 3.3%, and low in 40%; organic constituents were not detected in 47% of the primary aquifer system. The fumigant 1,2-dibromo-3-chloropropane (DBCP) was the only organic constituent detected at high RCs. Seven organic constituents were detected in 10% or more of the primary aquifer system: DBCP; the fumigant additive 1,2,3-trichloropropane; the herbicides simazine, atrazine, and diuron; the trihalomethane chloroform; and the solvent tetrachloroethene (PCE). RCs for the special-interest constituent perchlorate were moderate in 20% of the primary aquifer system. The second component of this study, the <i>understanding assessment</i>, identified the natural and human factors that may affect groundwater quality by evaluating statistical correlations between water-quality constituents and potential explanatory factors, such as land use, position relative to important geologic features, groundwater age, well depth, and geochemical conditions in the aquifer. Results of the statistical evaluations were used to explain the distribution of constituents in the study unit. Depth to the top of perforations in the well and groundwater age were the most important explanatory factors for many constituents. High and moderate RCs of nitrate, uranium, and TDS and the presence of herbicides, trihalomethanes, and solvents were all associated with depths to the top of perforations less than 235 ft and modern- and mixed-age groundwater. Positive correlations between uranium, bicarbonate, TDS, and the proportion of calcium and magnesium in the total cations suggest that downward movement of recharge from irrigation water contributed to the elevated concentrations of these constituents in the primary aquifer system. High and moderate RCs of arsenic were associated with depths to the top of perforations greater than 235 ft, mixed- and pre-modern-age groundwater, and location in sediments from the Chowchilla River alluvial fan, suggesting that increased residence time and appropriate aquifer materials were needed for arsenic to accumulate in the groundwater. High and moderate RCs of fumigants were associated with depths to the top of perforations of less than 235 ft and location south of the city of Madera; low RCs of fumigants were detected in wells dispersed across the study unit with a range of depths to top of perforations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125094","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Shelton, J.L., Fram, M.S., Belitz, K., and Jurgens, B., 2013, Status and understanding of groundwater quality in the Madera, Chowchilla Study Unit, 2008: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2012-5094, x, 86 p., https://doi.org/10.3133/sir20125094.","productDescription":"x, 86 p.","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":267175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5094.jpg"},{"id":267173,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5094/pdf/sir20125094.pdf"},{"id":267174,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5094/"}],"projection":"Albers Equal Area Conic","datum":"North American Datum of 1983","country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.133,32.5000 ], [ -114.133,42.0000 ], [ -124.400,42.0000 ], [ -124.400,32.5000 ], [ -114.133,32.5000 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511a12f3e4b084e2824d68ec","contributors":{"authors":[{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":473318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":22454,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","affiliations":[],"preferred":false,"id":473321,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043299,"text":"sir20125102 - 2013 - Prediction of suspended-sediment concentrations at selected sites in the Fountain Creek watershed, Colorado, 2008-09","interactions":[],"lastModifiedDate":"2013-02-12T11:38:08","indexId":"sir20125102","displayToPublicDate":"2013-02-11T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5102","title":"Prediction of suspended-sediment concentrations at selected sites in the Fountain Creek watershed, Colorado, 2008-09","docAbstract":"In 2008, the U.S. Geological Survey (USGS), in cooperation with Pikes Peak Area Council of Governments, Colorado Water Conservation Board, Colorado Springs City Engineering, and the Lower Arkansas Valley Water Conservancy District, began a small-scale pilot study to evaluate the effectiveness of the use of a computational model of streamflow and suspended-sediment transport for predicting suspended-sediment concentrations and loads in the Fountain Creek watershed in Colorado. Increased erosion and sedimentation damage have been identified by the Fountain Creek Watershed Plan as key problems within the watershed. A recommendation in the Fountain Creek Watershed plan for management of the basin is to establish measurable criteria to determine if progress in reducing erosion and sedimentation damage is being made. The major objective of this study was to test a computational method to predict local suspended-sediment loads at two sites with different geomorphic characteristics in order to evaluate the feasibility of using such an approach to predict local suspended-sediment loads throughout the entire watershed. Detailed topographic surveys, particle-size data, and suspended-sediment samples were collected at two gaged sites: Monument Creek above Woodmen Road at Colorado Springs, Colorado (USGS gage 07103970), and Sand Creek above mouth at Colorado Springs, Colorado (USGS gage 07105600). These data were used to construct three-dimensional computational models of relatively short channel reaches at each site. The streamflow component of these models predicted a spatially distributed field of water-surface elevation, water velocity, and bed shear stress for a range of stream discharges. Using the model predictions, along with measured particle sizes, the sediment-transport component of the model predicted the suspended-sediment concentration throughout the reach of interest. These computed concentrations were used with predicted flow patterns and channel morphology to determine fluxes of suspended sediment for the median particle size and for the measured range of particle sizes in the channel. Three different techniques were investigated for making the suspended-sediment predictions; these techniques have varying degrees of reliance on measured data and also have greatly differing degrees of complexity. Based on these data, the calibrated Rouse method provided the best balance between accuracy and both computational and data collection costs; the presence of substantial washload was the primary factor in eliminating the simpler and the more complex techniques. Based on this work, using the selected technique at additional sites in the watershed to determine relative loads and source areas appears plausible. However, to ensure that the methodology presented in this report yields reasonable results at other selected sites in the basin, it is necessary to collect additional verification data sets at those locations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125102","collaboration":"Prepared in cooperation with Pikes Peak Area Council of Governments, Colorado Water Conservation Board, Colorado Springs City Engineering, and Lower Arkansas Valley Water Conservancy District","usgsCitation":"Stogner, Nelson, J.M., McDonald, R.R., Kinzel, P.J., and Mau, D.P., 2013, Prediction of suspended-sediment concentrations at selected sites in the Fountain Creek watershed, Colorado, 2008-09: U.S. Geological Survey Scientific Investigations Report 2012-5102, vii, 36 p., https://doi.org/10.3133/sir20125102.","productDescription":"vii, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2008-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":267178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5102.gif"},{"id":267176,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5102/SIR12-5102.pdf"},{"id":267177,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5102/"}],"projection":"Albers Equal Area","country":"United States","state":"Colorado","otherGeospatial":"Fountain Creek Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.0753,38.2387 ], [ -105.0753,39.1359 ], [ -104.2369,39.1359 ], [ -104.2369,38.2387 ], [ -105.0753,38.2387 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511a12ede4b084e2824d68e0","contributors":{"authors":[{"text":"Stogner 0000-0002-3185-1452 rstogner@usgs.gov","orcid":"https://orcid.org/0000-0002-3185-1452","contributorId":938,"corporation":false,"usgs":true,"family":"Stogner","email":"rstogner@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":473326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":473328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":473327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":473325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mau, David P. dpmau@usgs.gov","contributorId":457,"corporation":false,"usgs":true,"family":"Mau","given":"David","email":"dpmau@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":473324,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70043314,"text":"fs20123099 - 2013 - Groundwater quality in the Madera and Chowchilla subbasins of the San Joaquin Valley, California","interactions":[],"lastModifiedDate":"2026-06-04T16:13:22.179574","indexId":"fs20123099","displayToPublicDate":"2013-02-11T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3099","title":"Groundwater quality in the Madera and Chowchilla subbasins of the San Joaquin Valley, California","docAbstract":"Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The Priority Basin Project of the GAMA Program provides a comprehensive assessment of the State’s untreated groundwater quality and increases public access to groundwater-quality information. The Madera and Chowchilla subbasins of the San Joaquin Valley constitute one of the study units being evaluated. The Madera-Chowchilla study unit is about 860 square miles and consists of the Madera and Chowchilla groundwater subbasins of the San Joaquin Valley Basin (California Department of Water Resources, 2003; Shelton and others, 2009). The study unit has hot, dry summers and cool, moist winters. Average annual rainfall ranges from 11 to 15 inches, most of which occurs between November and February. The main surface-water features in the study unit are the San Joaquin, Fresno, and Chowchilla Rivers, and the Madera and Chowchilla canals. Land use in the study unit is about 69 percent (%) agricultural, 28% natural (mainly grasslands), and 3% urban. The primary crops are orchards and vineyards. The largest urban area is the city of Madera. The primary aquifer system is defined as those parts of the aquifer corresponding to the perforated intervals of wells listed in the California Department of Public Health (CDPH) database. In the Madera-Chowchilla study unit, these wells typically are drilled to depths between 200 and 800 feet, consist of a solid casing from land surface to a depth of about 140 to 400 feet, and are perforated below the solid casing. Water quality in the primary aquifer system may differ from that in the shallower and deeper parts of the aquifer system. The primary aquifer system in the study unit consists of Quaternary-age alluvial-fan and fluvial deposits that were formed by the rivers draining the Sierra Nevada. Sediments consist of gravels, sands, silts, and clays and generally are coarser closest to the Sierra Nevada and become finer towards the center of the basin. The structure and composition of the deposits in the Madera-Chowchilla study unit are different from those in other parts of the eastern San Joaquin Valley because the Fresno and Chowchilla Rivers primarily drain the Sierra Nevada foothills, whereas the larger rivers drain higher elevations with greater sediment supply. These differences in the sources of sediments are important because they may affect the groundwater chemistry and the physical structure of the sedimentary deposits. Some of the clay layers are lacustrine deposits, the most extensive of which, the Corcoran Clay, underlies the western part of the study unit and divides the primary aquifer system into an unconfined to semi-confined upper system and a largely confined lower system. Regional lateral flow of groundwater is southwest towards the valley trough. Irrigation return flows are the major source of groundwater recharge, and groundwater pumping is the major source of discharge. Groundwater on a lateral flow path may be repeatedly extracted by pumping wells and reapplied at the surface multiple times before reaching the valley trough, resulting in a substantial component of downward vertical flow (Burow and others, 2004; Phillips and others, 2007; Faunt, 2009). This flow pattern enhances movement of water from shallow depths to the primary aquifer system.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123099","collaboration":"U.S. Geological Survey and the California State Water Resources Control Board","usgsCitation":"Shelton, J.L., Fram, M.S., and Belitz, K., 2013, Groundwater quality in the Madera and Chowchilla subbasins of the San Joaquin Valley, California: U.S. Geological Survey Fact Sheet 2012-3099, 4 p., https://doi.org/10.3133/fs20123099.","productDescription":"4 p.","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":505002,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98151.htm","linkFileType":{"id":5,"text":"html"}},{"id":267245,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3099.gif"},{"id":267244,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sir/2012/5094"},{"id":267243,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3099/pdf/fs20123099.pdf"},{"id":267242,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3099/"}],"country":"United States","state":"California","city":"Chowchilla, Madera","otherGeospatial":"San Joaquin Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.675,36.75 ], [ -120.675,37.2 ], [ -119.597,37.2 ], [ -119.597,36.75 ], [ -120.675,36.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511a12dfe4b084e2824d68dc","contributors":{"authors":[{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473374,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043313,"text":"sir20135001 - 2013 - Sources and characteristics of organic matter in the Clackamas River, Oregon, related to the formation of disinfection by-products in treated drinking water","interactions":[],"lastModifiedDate":"2017-01-17T11:43:26","indexId":"sir20135001","displayToPublicDate":"2013-02-11T00:00:00","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":"2013-5001","title":"Sources and characteristics of organic matter in the Clackamas River, Oregon, related to the formation of disinfection by-products in treated drinking water","docAbstract":"This study characterized the amount and quality of organic matter in the Clackamas River, Oregon, to gain an understanding of sources that contribute to the formation of chlorinated and brominated disinfection by-products (DBPs), focusing on regulated DBPs in treated drinking water from two direct-filtration treatment plants that together serve approximately 100,000 customers. The central hypothesis guiding this study was that natural organic matter leaching out of the forested watershed, in-stream growth of benthic algae, and phytoplankton blooms in the reservoirs contribute different and varying proportions of organic carbon to the river. Differences in the amount and composition of carbon derived from each source affects the types and concentrations of DBP precursors entering the treatment plants and, as a result, yield varying DBP concentrations and species in finished water. The two classes of DBPs analyzed in this study-trihalomethanes (THMs) and haloacetic acids (HAAs)-form from precursors within the dissolved and particulate pools of organic matter present in source water. The five principal objectives of the study were to (1) describe the seasonal quantity and character of organic matter in the Clackamas River; (2) relate the amount and composition of organic matter to the formation of DBPs; (3) evaluate sources of DBP precursors in the watershed; (4) assess the use of optical measurements, including in-situ fluorescence, for estimating dissolved organic carbon (DOC) concentrations and DBP formation; and (5) assess the removal of DBP precursors during treatment by conducting treatability \"jar-test\" experiments at one of the treatment plants. Data collection consisted of (1) monthly sampling of source and finished water at two drinking-water treatment plants; (2) event-based sampling in the mainstem, tributaries, and North Fork Reservoir; and (3) in-situ continuous monitoring of fluorescent dissolved organic matter (FDOM), turbidity, chlorophyll-<i>a</i>, and other constituents to continuously track source-water conditions in near real-time. Treatability tests were conducted during the four event-based surveys to determine the effectiveness of coagulant and powdered activated carbon (PAC) on the removal of DBP precursors. Sample analyses included DOC, total particulate carbon (TPC), total and dissolved nutrients, absorbance and fluorescence spectroscopy, and, for regulated DBPs, concentrations of THMs and HAAs in finished water and laboratory-based THM and HAA formation potentials (THMFP and HAAFP, respectively) for source water and selected locations throughout the watershed. The results of this study may not be typical given the record and near record amounts of precipitation that occurred during spring that produced streamflow much higher than average in 2010-11. Although there were algal blooms, lower concentrations of chlorophyll-<i>a</i> were observed in the water column during the study period compared to historical data. Concentrations of DBPs in finished (treated) water averaged 0.024 milligrams per liter (mg/L) for THMs and 0.022 mg/L for HAAs; maximum values were about 0.040 mg/L for both classes of DBPs. Although DBP concentrations were somewhat higher within the distribution system, none of the samples collected for this study or for the quarterly compliance monitoring by the water utilities exceeded levels permissible under existing U.S. Environmental Protection Agency (USEPA) regulations: 0.080 mg/L for THMs and 0.060 mg/L for HAAs. DOC concentrations were generally low in the Clackamas River, typically about 1.0-1.5 mg/L. Concentrations in the mainstem occasionally increased to nearly 2.5 mg/L during storms; DOC concentrations in tributaries were sometimes much higher (up to 7.8 mg/L). The continuous in-situ FDOM measurements indicated sharp rises in DOC concentrations in the mainstem following rainfall events; concentrations were relatively stable during summer base flow. Even though the first autumn storm mobilized appreciable quantities of carbon, higher concentrations of DBPs in finished water were observed 3-weeks later, after the ground was saturated from additional rainfall. The majority of the DOC in the lower Clackamas River appears to originate from the upper basin, suggesting terrestrial carbon was commonly the dominant source. Lower-basin tributaries typically contained the highest concentrations of DOC and DBP precursors and contributed substantially to the overall loads in the mainstem during storms. During low-flow periods, tributaries were not major sources of DOC or DBP precursors to the Clackamas River. Although the dissolved fraction of organic carbon contributed the majority of DBP precursors, at times the particulate fraction (inorganic sediment and organic particles including detritus and algal material) contributed a substantial fraction of DBP precursors. Considering just the main-stem sites, on average, 10 percent of THMFP and 32 percent of HAAFP were attributed to particulate carbon. This finding suggests water-treatment methods that remove particles prior to chlorination would reduce finished-water DBP concentrations to some degree. Overall, concentrations of THM and HAA precursors were closely linked to DOC concentrations; laboratory DBP formation potentials (DBPFPs) clearly showed that THMFP and HAAFP were greatest in the downstream tributaries that contained elevated carbon concentrations. However, carbon-normalized \"specific\" formation potentials for THMs and HAAs (STHMFP and SHAAFP, respectively) revealed changes in carbon character over time that affected the two types of DBP classes differently. HAA precursors were elevated in waters containing aromatic-rich soil-derived material arising from forested areas. In contrast, THM precursors were associated with carbon having a lower aromatic content; highest STHMFP occurred in autumn 2011 in the mainstem from North Fork Reservoir downstream to LO DWTP. This pattern suggests the potential for a link between THM precursors and algal-derived carbon. The highest STHMFP value was measured within North Fork Reservoir, indicating reservoir derived carbon may be important for this class of DBPs. Weak correlations between STHMFP and SHAAFP emphasize that precursor sources for these types of DBPs may be different. This highlights not only that different locations within the watershed produce carbon with different reactivity (specific DBPFP), but also that different management approaches for each class of DBP precursors could be required for control. Treatability tests conducted on source water during four basin-wide surveys demonstrated that an average of about 40 percent of DOC can be removed by coagulation. While the decrease in THMFP following coagulation was similar to DOC, the decrease in HAAFP was much greater (approximately 70 percent), indicating coagulation is particularly effective at removing HAA precursors'likely because of the aromatic nature of the carbon associated with HAA precursors. Several findings from this study have direct implications for managing drinking-water resources and for providing useful information that may help improve treatment-plant operations. For example, the use of in-situ fluorometers that measure FDOM provided an excellent proxy for DOC concentration in this system and revealed short-term, rapid changes in DOC concentration during storm events. In addition, the strong correlation between FDOM values measured in-situ and HAA5 concentrations in finished water may permit estimation of continuous HAA concentrations, as was done here. As part of this study, multiple in-situ FDOM sensors were deployed continuously and in real-time to characterize the composition of dissolved organic matter. Although the initial results were promising, additional research and engineering developments will be needed to demonstrate the full utility of these sensors for this purpose. In conclusion, although DBPFPs were strongly correlated to DOC concentration, some DBPs formed from particulate carbon, including terrestrial leaf material and algal material such as planktonic species of blue-green algae and sloughed filaments, stalks, and cells of benthic algae. Different precursor sources in the watershed were evident from the data, suggesting specific actions may be available to address some of these sources. In-situ measurements of FDOM proved to be an excellent proxy for DOC concentration as well as HAA formation during treatment, which suggests further development and refinement of these sensors have the potential to provide real-time information about complex watershed processes to operators at the drinking-water treatment plants. Follow-up studies could examine the relative roles that terrestrial and algal sources have on the DBP precursor pool to better understand how watershed-management activities may be affecting the transport of these compounds to Clackamas River drinking-water intakes. Given the low concentrations of algae in the water column during this study, additional surveys during more typical river conditions could provide a more complete understanding of how algae contribute DBP precursors. Further development of FDOM-sensor technology can improve our understanding of carbon dynamics in the river and how concentrations may be trending over time. This study was conducted in collaboration with Clackamas River Water and the City of Lake Oswego water utilities. Other research partners included Oregon Health and Science University in Hillsboro, Oregon, Alexin Laboratory in Tigard, Oregon, U.S. Geological Survey National Research Program Laboratory in Denver, Colorado, and the U.S. Geological Survey Water Science Centers in Portland, Oregon, and Sacramento, California. This project was supported with funding from Clackamas River Water, City of Lake Oswego, the U.S. Geological Survey, and the Water Research Foundation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135001","collaboration":"Prepared in cooperation with Clackamas River Water and the City of Lake Oswego","usgsCitation":"Carpenter, K., Kraus, T., Goldman, J.H., Saraceno, J., Downing, B.D., Bergamaschi, B., McGhee, G., and Triplett, T., 2013, Sources and characteristics of organic matter in the Clackamas River, Oregon, related to the formation of disinfection by-products in treated drinking water: U.S. Geological Survey Scientific Investigations Report 2013-5001, Report: x, 78 p.; Appendixes: .XLSX file, https://doi.org/10.3133/sir20135001.","productDescription":"Report: x, 78 p.; Appendixes: .XLSX file","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":267249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2013_5001.jpg"},{"id":267247,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5001/"},{"id":267248,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5001/sir20135001_Appendixes.xlsx"},{"id":267246,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5001/pdf/sir20135001.pdf"}],"projection":"State Plane, Zone 5076","datum":"North American Datum of 1983","country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.611542,44.895769 ], [ -122.611542,45.388806 ], [ -121.738815,45.388806 ], [ -121.738815,44.895769 ], [ -122.611542,44.895769 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511a12f1e4b084e2824d68e4","contributors":{"authors":[{"text":"Carpenter, Kurt D. kdcar@usgs.gov","contributorId":1372,"corporation":false,"usgs":true,"family":"Carpenter","given":"Kurt D.","email":"kdcar@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":473366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Tamara E.C. 0000-0002-5187-8644","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":92410,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara E.C.","affiliations":[],"preferred":false,"id":473373,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldman, Jami H. 0000-0001-5466-912X jgoldman@usgs.gov","orcid":"https://orcid.org/0000-0001-5466-912X","contributorId":4848,"corporation":false,"usgs":true,"family":"Goldman","given":"Jami","email":"jgoldman@usgs.gov","middleInitial":"H.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saraceno, John Franco 0000-0003-0064-1820","orcid":"https://orcid.org/0000-0003-0064-1820","contributorId":71686,"corporation":false,"usgs":true,"family":"Saraceno","given":"John Franco","affiliations":[],"preferred":false,"id":473370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473367,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":73241,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian A.","affiliations":[],"preferred":false,"id":473371,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGhee, Gordon","contributorId":80380,"corporation":false,"usgs":true,"family":"McGhee","given":"Gordon","email":"","affiliations":[],"preferred":false,"id":473372,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Triplett, Tracy","contributorId":48844,"corporation":false,"usgs":true,"family":"Triplett","given":"Tracy","email":"","affiliations":[],"preferred":false,"id":473369,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70058575,"text":"70058575 - 2013 - Integrating stations from the North America Gravity Database into a local GPS-based land gravity survey","interactions":[],"lastModifiedDate":"2013-12-10T09:38:02","indexId":"70058575","displayToPublicDate":"2013-02-10T09:29:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2165,"text":"Journal of Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Integrating stations from the North America Gravity Database into a local GPS-based land gravity survey","docAbstract":"The ability to augment local gravity surveys with additional gravity stations from easily accessible national databases can greatly increase the areal coverage and spatial resolution of a survey. It is, however, necessary to integrate such data seamlessly with the local survey. One challenge to overcome in integrating data from national databases is that these data are typically of unknown quality. This study presents a procedure for the evaluation and seamless integration of gravity data of unknown quality from a national database with data from a local Global Positioning System (GPS)-based survey. The starting components include the latitude, longitude, elevation and observed gravity at each station location. Interpolated surfaces of the complete Bouguer anomaly are used as a means of quality control and comparison. The result is an integrated dataset of varying quality with many stations having GPS accuracy and other reliable stations of unknown origin, yielding a wider coverage and greater spatial resolution than either survey alone.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Geophysics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jappgeo.2012.11.011","usgsCitation":"Shoberg, T.G., and Stoddard, P.R., 2013, Integrating stations from the North America Gravity Database into a local GPS-based land gravity survey: Journal of Applied Geophysics, v. 89, p. 76-83, https://doi.org/10.1016/j.jappgeo.2012.11.011.","productDescription":"8 p.","startPage":"76","endPage":"83","numberOfPages":"8","ipdsId":"IP-027895","costCenters":[{"id":161,"text":"Center of Excellence for Geospatial Information Science (CEGIS)","active":false,"usgs":true}],"links":[{"id":280239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280238,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jappgeo.2012.11.011"}],"country":"United States","state":"Missouri","otherGeospatial":"Crooked Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.7741,35.9957 ], [ -95.7741,40.6136 ], [ -89.0988,40.6136 ], [ -89.0988,35.9957 ], [ -95.7741,35.9957 ] ] ] } } ] }","volume":"89","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd62bce4b0b290850fe5db","contributors":{"authors":[{"text":"Shoberg, Thomas G. 0000-0003-0173-1246 tshoberg@usgs.gov","orcid":"https://orcid.org/0000-0003-0173-1246","contributorId":3764,"corporation":false,"usgs":true,"family":"Shoberg","given":"Thomas","email":"tshoberg@usgs.gov","middleInitial":"G.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":487177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoddard, Paul R.","contributorId":7606,"corporation":false,"usgs":true,"family":"Stoddard","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":487178,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043284,"text":"70043284 - 2013 - Effect of heterogeneous atmospheric CO2 on simulated global carbon budget","interactions":[],"lastModifiedDate":"2023-08-18T16:32:34.435679","indexId":"70043284","displayToPublicDate":"2013-02-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1844,"text":"Global and Planetary Change","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effect of heterogeneous atmospheric CO<sub>2</sub> on simulated global carbon budget","title":"Effect of heterogeneous atmospheric CO2 on simulated global carbon budget","docAbstract":"The effects of rising atmospheric carbon dioxide (CO<sub>2</sub>) on terrestrial carbon (C) sequestration have been a key focus in global change studies. As anthropological CO2 emissions substantially increase, the spatial variability of atmospheric CO<sub>2</sub> should be considered to reduce the potential bias on C source and sink estimations. In this study, the global spatial–temporal patterns of near surface CO<sub>2</sub> concentrations for the period 2003-2009 were established using the SCIAMACHY satellite observations and the GLOBALVIEW-CO<sub>2</sub> field observations. With this CO<sub>2</sub> data and the Integrated Biosphere Simulator (IBIS), our estimation of the global mean annual NPP and NEP was 0.5% and 7% respectively which differs from the traditional C sequestration assessments. The Amazon, Southeast Asia, and Tropical Africa showed higher C sequestration than the traditional assessment, and the rest of the areas around the world showed slightly lower C sequestration than the traditional assessment. We find that the variability of NEP is less intense under heterogeneous CO<sub>2</sub> pattern on a global scale. Further studies of the cause of CO<sub>2</sub> variation and the interactions between natural and anthropogenic processes of C sequestration are needed.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.gloplacha.2012.12.002","usgsCitation":"Zhang, Z., Jiang, H., Liu, J., Ju, W., and Zhang, X., 2013, Effect of heterogeneous atmospheric CO2 on simulated global carbon budget: Global and Planetary Change, v. 101, p. 33-51, https://doi.org/10.1016/j.gloplacha.2012.12.002.","productDescription":"19 p.","startPage":"33","endPage":"51","ipdsId":"IP-028757","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":267171,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511a210be4b084e2824d6968","contributors":{"authors":[{"text":"Zhang, Zhen","contributorId":94945,"corporation":false,"usgs":true,"family":"Zhang","given":"Zhen","affiliations":[],"preferred":false,"id":473285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jiang, Hong","contributorId":33200,"corporation":false,"usgs":true,"family":"Jiang","given":"Hong","affiliations":[],"preferred":false,"id":473282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":473281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ju, Weimin","contributorId":94185,"corporation":false,"usgs":true,"family":"Ju","given":"Weimin","email":"","affiliations":[],"preferred":false,"id":473284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Xiuying","contributorId":75038,"corporation":false,"usgs":true,"family":"Zhang","given":"Xiuying","affiliations":[],"preferred":false,"id":473283,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70043247,"text":"ds732 - 2013 - Assessment of groundwater quality data for the Turtle Mountain Indian Reservation, Rolette County, North Dakota","interactions":[],"lastModifiedDate":"2017-10-14T11:19:25","indexId":"ds732","displayToPublicDate":"2013-02-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"732","title":"Assessment of groundwater quality data for the Turtle Mountain Indian Reservation, Rolette County, North Dakota","docAbstract":"The Turtle Mountain Indian Reservation relies on groundwater supplies to meet the demands of community and economic needs. The U.S. Geological Survey, in cooperation with the Turtle Mountain Band of Chippewa Indians, examined historical groundwater-level and groundwater-quality data for the Fox Hills, Hell Creek, Rolla, and Shell Valley aquifers. The two main sources of water-quality data for groundwater were the U.S. Geological Survey National Water Information System database and the North Dakota State Water Commission database. Data included major ions, trace elements, nutrients, field properties, and physical properties. The Fox Hills and Hell Creek aquifers had few groundwater water-quality data. The lack of data limits any detailed assessments that can be made about these aquifers. Data for the Rolla aquifer exist from 1978 through 1980 only. The concentrations of some water-quality constituents exceeded the U.S. Environmental Protection Agency secondary maximum contaminant levels. No samples were analyzed for pesticides and hydrocarbons. Numerous water-quality samples have been obtained from the Shell Valley aquifer. About one-half of the water samples from the Shell Valley aquifer had concentrations of iron, manganese, sulfate, and dissolved solids that exceeded the U.S. Environmental Protection Agency secondary maximum contaminant levels. Overall, the data did not indicate obvious patterns in concentrations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds732","collaboration":"Prepared in cooperation with Turtle Mountain Band of Chippewa Indians","usgsCitation":"Lundgren, R.F., and Vining, K.C., 2013, Assessment of groundwater quality data for the Turtle Mountain Indian Reservation, Rolette County, North Dakota: U.S. Geological Survey Data Series 732, Report: iv, 20 p.; Downloads Directory, https://doi.org/10.3133/ds732.","productDescription":"Report: iv, 20 p.; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-041778","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":267150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_732.gif"},{"id":267147,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/732/"},{"id":267149,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/732/downloads/"},{"id":267148,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/732/ds732.pdf"}],"projection":"Universal Transverse Mercator projection, Zone 14 N","country":"United States","state":"North Dakota","county":"Rolette","otherGeospatial":"Turtle Mountain Indian Reservation","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -10.000277777777777,48.5 ], [ -10.000277777777777,0.0011111111111111111 ], [ -99.5,0.0011111111111111111 ], [ -99.5,48.5 ], [ -10.000277777777777,48.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51161e5fe4b0d1e3dcdedffd","contributors":{"authors":[{"text":"Lundgren, Robert F. 0000-0001-7669-0552 rflundgr@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-0552","contributorId":1657,"corporation":false,"usgs":true,"family":"Lundgren","given":"Robert","email":"rflundgr@usgs.gov","middleInitial":"F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vining, Kevin C. 0000-0001-5738-3872 kcvining@usgs.gov","orcid":"https://orcid.org/0000-0001-5738-3872","contributorId":308,"corporation":false,"usgs":true,"family":"Vining","given":"Kevin","email":"kcvining@usgs.gov","middleInitial":"C.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":473240,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043258,"text":"ofr20131018 - 2013 - Volcano crisis response at Yellowstone volcanic complex - after-action report for exercise held at Salt Lake City, Utah, November 15, 2011","interactions":[],"lastModifiedDate":"2013-02-08T14:11:21","indexId":"ofr20131018","displayToPublicDate":"2013-02-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1018","title":"Volcano crisis response at Yellowstone volcanic complex - after-action report for exercise held at Salt Lake City, Utah, November 15, 2011","docAbstract":"A functional tabletop exercise was run on November 14-15, 2011 in Salt Lake City, Utah, to test crisis response capabilities, communication protocols, and decision-making by the staff of the multi-agency Yellowstone Volcano Observatory (YVO) as they reacted to a hypothetical exercise scenario of accelerating volcanic unrest at the Yellowstone caldera. The exercise simulated a rapid build-up of seismic activity, ground deformation, and hot-spring water-chemistry and temperature anomalies that culminated in a small- to moderate-size phreatomagmatic eruption within Yellowstone National Park. The YVO scientific team's responses to the unfolding events in the scenario and to simulated requests for information by stakeholders and the media were assessed by (a) the exercise organizers; (b) several non-YVO scientists, who observed and queried participants, and took notes throughout the exercise; and (c) the participants themselves, who kept logs of their actions during the exercise and later participated in a group debriefing session and filled out detailed questionnaires. These evaluations were tabulated, interpreted, and summarized for this report, and on the basis of this information, recommendations have been made. Overall, the YVO teams performed their jobs very well. The exercise revealed that YVO scientists were able to successfully provide critical hazards information, issue information statements, and appropriately raise alert levels during a fast-moving crisis. Based on the exercise, it is recommended that several measures be taken to increase YVO effectiveness during a crisis: \n1. Improve role clarification within and between YVO science teams. \n2. Improve communications tools and protocols for data-sharing and consensus-building among YVO scientists, who are geographically and administratively dispersed among various institutions across the United States. \n3. Familiarize YVO staff with Incident Command System (ICS) procedures and protocols, and provide more in-depth training to appropriate staff members, as needed. \n4. Train all science team members in the use of all analytical and computational tools available to them, in order to maximize effectiveness of teams in tracking and interpreting possible accelerating unrest at Yellowstone. \nDesirable pre-crisis preparations include: (a) updating a catalog of existing map and information products (and identifying additional products) that would be helpful during a crisis; (b) creating \"to do\" lists of early-crisis tasks for each scientific team; (c) coordinating radio frequencies among partner agencies; and (d) brief training on and promotion of the internal YVO Web log as a repository for scientific observations, data, photographs, and other material to be shared among YVO scientific teams during a crisis. This exercise was designed as an opportunity to practice response to a fast-developing volcano crisis and to test for organizational and procedural weaknesses that could emerge during a real crisis. This report is based upon the observations of the exercise organizers during the one-day exercise and upon written evaluations by the participants. It does not attempt to evaluate any other aspect of YVO or the scientific expertise of any of the highly competent YVO staff. Participants unanimously found the exercise to be helpful for improving their response capabilities, and it is our hope that the report will be a starting point for internal discussions that will make YVO even better-prepared for some future volcano crisis.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131018","usgsCitation":"Pierson, T.C., Driedger, C.L., and Tilling, R.I., 2013, Volcano crisis response at Yellowstone volcanic complex - after-action report for exercise held at Salt Lake City, Utah, November 15, 2011: U.S. Geological Survey Open-File Report 2013-1018, iv, 31 p., https://doi.org/10.3133/ofr20131018.","productDescription":"iv, 31 p.","numberOfPages":"35","onlineOnly":"Y","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":686,"text":"Yellowstone Volcano Observatory","active":false,"usgs":true}],"links":[{"id":267153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1018.gif"},{"id":267151,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1018/"},{"id":267152,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1018/of2013-1018.pdf"}],"country":"United States","state":"Utah","city":"Salt Lake City","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.10,40.70 ], [ -112.10,40.85 ], [ -111.74,40.85 ], [ -111.74,40.70 ], [ -112.10,40.70 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51161e72e4b0d1e3dcdee005","contributors":{"authors":[{"text":"Pierson, Thomas C. 0000-0001-9002-4273 tpierson@usgs.gov","orcid":"https://orcid.org/0000-0001-9002-4273","contributorId":2498,"corporation":false,"usgs":true,"family":"Pierson","given":"Thomas","email":"tpierson@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":473248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driedger, Carolyn L. 0000-0002-4011-4112 driedger@usgs.gov","orcid":"https://orcid.org/0000-0002-4011-4112","contributorId":537,"corporation":false,"usgs":true,"family":"Driedger","given":"Carolyn","email":"driedger@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":473247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tilling, Robert I. 0000-0003-4263-7221 rtilling@usgs.gov","orcid":"https://orcid.org/0000-0003-4263-7221","contributorId":2567,"corporation":false,"usgs":true,"family":"Tilling","given":"Robert","email":"rtilling@usgs.gov","middleInitial":"I.","affiliations":[],"preferred":true,"id":473249,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043210,"text":"ds709Q - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-02-07T13:45:33","indexId":"ds709Q","displayToPublicDate":"2013-02-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"Q","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Takhar) and the WGS84 datum. The final image mosaics for the Takhar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709Q","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=&quot;http://tfbso.defense.gov/www/&quot; target=&quot;_blank&quot;>Task Force for Business and Stability Operations</a> and the <a href=&quot;http://www.bgs.ac.uk/AfghanMinerals/&quot; target=&quot;_blank&quot;>Afghanistan Geological Survey</a>.  This report is Chapter Q in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>. For more information, see: <a href=&quot;http://pubs.er.usgs.gov/publication/ds709&quot; target=&quot;_blank&quot;>Data Series 709</a>","usgsCitation":"Davis, P.A., and Cagney, L.E., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>: U.S. Geological Survey Data Series 709, HTML Document; Readme; 2 Maps; 2 Image files; 2 Metadata; 1 Shapefile, https://doi.org/10.3133/ds709Q.","productDescription":"HTML Document; Readme; 2 Maps; 2 Image files; 2 Metadata; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":267126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_q.png"},{"id":267119,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/q/"},{"id":267120,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/q/1_readme.txt"},{"id":267121,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/q/index_maps/Takhar_Area-of-Interest_Index_Map.pdf"},{"id":267122,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/q/index_maps/Takhar_Image_Index_Map.pdf"},{"id":267123,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/q/image_files/image_files.html"},{"id":267124,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/q/metadata/metadata.html"},{"id":267125,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/q/shapefiles/shapefiles.html"}],"country":"Afghanistan","otherGeospatial":"Takhar Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.52,29.38 ], [ 60.52,38.49 ], [ 74.89,38.49 ], [ 74.89,29.38 ], [ 60.52,29.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5114cd06e4b0ca7af0743ae3","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":473177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":473178,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043200,"text":"ds709P - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-02-07T13:47:41","indexId":"ds709P","displayToPublicDate":"2013-02-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"P","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Baghlan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Baghlan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709P","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=&quot;http://tfbso.defense.gov/www/&quot; target=&quot;_blank&quot;>Task Force for Business and Stability Operations</a> and the <a href=&quot;http://www.bgs.ac.uk/AfghanMinerals/&quot; target=&quot;_blank&quot;>Afghanistan Geological Survey</a>.  This report is Chapter P in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>. For more information, see: <a href=&quot;http://pubs.er.usgs.gov/publication/ds709&quot; target=&quot;_blank&quot;>Data Series 709</a>","usgsCitation":"Davis, P.A., and Cagney, L.E., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>: U.S. Geological Survey Data Series 709, HTML Document; Readme; 2 Maps; 4 Image Files; 4 Metadata; 1 Shapefile, https://doi.org/10.3133/ds709P.","productDescription":"HTML Document; Readme; 2 Maps; 4 Image Files; 4 Metadata; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":267118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_p.png"},{"id":267113,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/p/index_maps/Baghlan_Area-of-Interest_Index_Map.pdf"},{"id":267111,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/p/"},{"id":267112,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/p/1_readme.txt"},{"id":267114,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/p/index_maps/Baghlan_Image_Index_Map.pdf"},{"id":267115,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/p/image_files/image_files.html"},{"id":267116,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/p/metadata/metadata.html"},{"id":267117,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/p/shapefiles/shapefiles.html"}],"country":"Afghanistan","otherGeospatial":"Baghlan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.52,29.38 ], [ 60.52,38.49 ], [ 74.89,38.49 ], [ 74.89,29.38 ], [ 60.52,29.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5114cd05e4b0ca7af0743adf","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":473151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":473152,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043135,"text":"70043135 - 2013 - Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography","interactions":[],"lastModifiedDate":"2017-05-26T12:58:01","indexId":"70043135","displayToPublicDate":"2013-02-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography","docAbstract":"The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.","language":"English","publisher":"American Water Resources Association","publisherLocation":"Middleburg, VA","doi":"10.1111/jawr.12027","usgsCitation":"Poppenga, S.K., Gesch, D.B., and Worstell, B.B., 2013, Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography: Journal of the American Water Resources Association, v. 49, no. 2, p. 371-389, https://doi.org/10.1111/jawr.12027.","productDescription":"19 p.","startPage":"371","endPage":"389","ipdsId":"IP-035009","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473953,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jawr.12027","text":"Publisher Index Page"},{"id":267066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267042,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jawr.12027"}],"volume":"49","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-01-28","publicationStatus":"PW","scienceBaseUri":"51137b6ae4b0a9ee4115ba00","contributors":{"authors":[{"text":"Poppenga, Sandra K. 0000-0002-2846-6836","orcid":"https://orcid.org/0000-0002-2846-6836","contributorId":84465,"corporation":false,"usgs":true,"family":"Poppenga","given":"Sandra","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":473029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":473028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Worstell, Bruce B. 0000-0001-8927-3336 worstell@usgs.gov","orcid":"https://orcid.org/0000-0001-8927-3336","contributorId":1815,"corporation":false,"usgs":true,"family":"Worstell","given":"Bruce","email":"worstell@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473027,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043179,"text":"ofr20131005 - 2013 - Defining a data management strategy for USGS Chesapeake Bay studies","interactions":[],"lastModifiedDate":"2021-07-06T23:04:57.195617","indexId":"ofr20131005","displayToPublicDate":"2013-02-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1005","title":"Defining a data management strategy for USGS Chesapeake Bay studies","docAbstract":"The mission of U.S. Geological Survey’s (USGS) Chesapeake Bay studies is to provide integrated science for improved understanding and management of the Chesapeake Bay ecosystem. Collective USGS efforts in the Chesapeake Bay watershed began in the 1980s, and by the mid-1990s the USGS adopted the watershed as one of its national place-based study areas. Great focus and effort by the USGS have been directed toward Chesapeake Bay studies for almost three decades. The USGS plays a key role in using “ecosystem-based adaptive management, which will provide science to improve the efficiency and accountability of Chesapeake Bay Program activities” (Phillips, 2011). Each year USGS Chesapeake Bay studies produce published research, monitoring data, and models addressing aspects of bay restoration such as, but not limited to, fish health, water quality, land-cover change, and habitat loss. The USGS is responsible for collaborating and sharing this information with other Federal agencies and partners as described under the President’s Executive Order 13508—Strategy for Protecting and Restoring the Chesapeake Bay Watershed signed by President Obama in 2009. Historically, the USGS Chesapeake Bay studies have relied on national USGS databases to store only major nationally available sources of data such as streamflow and water-quality data collected through local monitoring programs and projects, leaving a multitude of other important project data out of the data management process. This practice has led to inefficient methods of finding Chesapeake Bay studies data and underutilization of data resources. Data management by definition is “the business functions that develop and execute plans, policies, practices and projects that acquire, control, protect, deliver and enhance the value of data and information.” (Mosley, 2008a). In other words, data management is a way to preserve, integrate, and share data to address the needs of the Chesapeake Bay studies to better manage data resources, work more efficiently with partners, and facilitate holistic watershed science. It is now the goal of the USGS Chesapeake Bay studies to implement an enhanced and all-encompassing approach to data management. This report discusses preliminary efforts to implement a physical data management system for program data that is not replicated nationally through other USGS databases.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131005","usgsCitation":"Ladino, C., 2013, Defining a data management strategy for USGS Chesapeake Bay studies: U.S. Geological Survey Open-File Report 2013-1005, iii, 7 p., https://doi.org/10.3133/ofr20131005.","productDescription":"iii, 7 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":267086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1005.gif"},{"id":267084,"type":{"id":15,"text":"Index 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ccladino@usgs.gov","contributorId":3514,"corporation":false,"usgs":true,"family":"Ladino","given":"Cassandra","email":"ccladino@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":473114,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70043174,"text":"sir20125286 - 2013 - Analysis of changes in water-level dynamics at selected sites in the Florida Everglades","interactions":[],"lastModifiedDate":"2013-02-06T17:37:55","indexId":"sir20125286","displayToPublicDate":"2013-02-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5286","title":"Analysis of changes in water-level dynamics at selected sites in the Florida Everglades","docAbstract":"The historical modification and regulation of the hydrologic patterns in the Florida Everglades have resulted in changes in the ecosystem of South Florida and the Florida Everglades. Since the 1970s, substantial focus has been given to the restoration of the Everglades ecosystem. The U.S. Geological Survey through its Greater Everglades Priority Ecosystem Science and National Water-Quality Assessment Programs has been providing scientific information to resource managers to assist in the Everglades restoration efforts. The current investigation included development of a simple method to identify and quantify changes in historical hydrologic behavior within the Everglades that could be used by researchers to identify responses of ecological communities to those changes. Such information then could be used by resource managers to develop appropriate water-management practices within the Everglades to promote restoration. The identification of changes in historical hydrologic behavior within the Everglades was accomplished by analyzing historical time-series water-level data from selected gages in the Everglades using (1) break-point analysis of cumulative Z-scores to identify hydrologic changes and (2) cumulative water-level frequency distribution curves to evaluate the magnitude of those changes. This analytical technique was applied to six long-term water-level gages in the Florida Everglades. The break-point analysis for the concurrent period of record (1978–2011) identified 10 common periods of changes in hydrologic behavior at the selected gages. The water-level responses at each gage for the 10 periods displayed similarity in fluctuation patterns, highlighting the interconnectedness of the Florida Everglades hydrologic system. While the patterns were similar, the analysis also showed that larger fluctuations in water levels between periods occurred in Water Conservation Areas 2 and 3 in contrast to those in Water Conservation Area 1 and the Everglades National Park. Results from the analysis indicate that the cumulative Z-score curve, in conjunction with cumulative water-level frequency distribution curves, can be a useful tool in identifying and quantifying changes in historical hydrologic behavior within the Everglades. In addition to the analysis, a spreadsheet application was developed to assist in applying these techniques to time-series water-level data at gages within the Everglades and is included with this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125286","collaboration":"Prepared as part of the U.S. Geological Survey Greater Everglades Priority Ecosystem Science","usgsCitation":"Conrads, P., and Benedict, S., 2013, Analysis of changes in water-level dynamics at selected sites in the Florida Everglades: U.S. Geological Survey Scientific Investigations Report 2012-5286, v, 36 p.; ZEBRA Spreadsheet, https://doi.org/10.3133/sir20125286.","productDescription":"v, 36 p.; ZEBRA Spreadsheet","startPage":"i","endPage":"36","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":267083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5286.gif"},{"id":267082,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2012/5286/ZEBRA_(Beta-Version).xlsx"},{"id":267080,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5286/"},{"id":267081,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5286/pdf/sir2012-5286.pdf"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.63,24.52 ], [ -87.63,31.0 ], [ -80.03,31.0 ], [ -80.03,24.52 ], [ -87.63,24.52 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51137b5fe4b0a9ee4115b9f8","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":473103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benedict, Stephen T. benedict@usgs.gov","contributorId":3198,"corporation":false,"usgs":true,"family":"Benedict","given":"Stephen T.","email":"benedict@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":473104,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043164,"text":"ds709O - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-02-06T14:05:56","indexId":"ds709O","displayToPublicDate":"2013-02-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"O","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Helmand mineral district, which has travertine deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (41 for South Helmand) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the South Helmand area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709O","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\"http://tfbso.defense.gov/www/\" target=\"_blank\">Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>.  This report is Chapter O in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>. For more information, see: <a href=\"http://pubs.er.usgs.gov/publication/ds709\" target=\"_blank\">Data Series 709</a>.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 80.06 x 34.65 inches; 16 Image Files; 16 Metadata Files; 1 Shapefile; DS 709, https://doi.org/10.3133/ds709O.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 80.06 x 34.65 inches; 16 Image Files; 16 Metadata Files; 1 Shapefile; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":267079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_O.jpg"},{"id":267071,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/o/1_readme.txt"},{"id":267072,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/o/index_maps/index_maps.html"},{"id":267073,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/o/index_maps/South_Helmand_Area-of-Interest_Index_Map.pdf"},{"id":267070,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/o/"},{"id":267074,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/o/index_maps/South_Helmand_Image_Index_Map.pdf"},{"id":267075,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/o/image_files/image_files.html"},{"id":267076,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/o/metadata/metadata.html"},{"id":267077,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/o/shapefiles/shapefiles.html"},{"id":267078,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","otherGeospatial":"South Helmand Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 63.25,29.25 ], [ 63.25,30.0 ], [ 65.0,30.0 ], [ 65.0,29.25 ], [ 63.25,29.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51138978e4b0a9ee4115ba28","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":473093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":473094,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043143,"text":"tm7C10 - 2013 - Computing ordinary least-squares parameter estimates for the National Descriptive Model of Mercury in Fish","interactions":[],"lastModifiedDate":"2013-02-05T16:04:45","indexId":"tm7C10","displayToPublicDate":"2013-02-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C10","title":"Computing ordinary least-squares parameter estimates for the National Descriptive Model of Mercury in Fish","docAbstract":"A specialized technique is used to compute weighted ordinary least-squares (OLS) estimates of the parameters of the National Descriptive Model of Mercury in Fish (NDMMF) in less time using less computer memory than general methods. The characteristics of the NDMMF allow the two products <i><b>X'X</i></b> and <i><b>X'y</i></b> in the normal equations to be filled out in a second or two of computer time during a single pass through the N data observations. As a result, the matrix <i><b>X</i></b> does not have to be stored in computer memory and the computationally expensive matrix multiplications generally required to produce <i><b>X'X</i></b> and <i><b>X'y</i></b> do not have to be carried out. The normal equations may then be solved to determine the best-fit parameters in the OLS sense. The computational solution based on this specialized technique requires O(8<i>p</i><sup>2</sup>+16<i>p</i>) bytes of computer memory for <i>p</i> parameters on a machine with 8-byte double-precision numbers. This publication includes a reference implementation of this technique and a Gaussian-elimination solver in preliminary custom software.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer programs in Book 7 <i>Automated Data Processing and Computations</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C10","collaboration":"This report is Chapter 10 of Section C: Computer programs in Book 7 <i>Automated Data Processing and Computations</i>","usgsCitation":"Donato, D.I., 2013, Computing ordinary least-squares parameter estimates for the National Descriptive Model of Mercury in Fish: U.S. Geological Survey Techniques and Methods 7-C10, iii, 9 p.; Appendix, https://doi.org/10.3133/tm7C10.","productDescription":"iii, 9 p.; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":267063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_7_c10.gif"},{"id":267060,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/07/c10/"},{"id":267062,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/07/c10/Ols.zip"},{"id":267061,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c10/pdf/tm7-c10.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511229e3e4b0ebe69d7eb5fc","contributors":{"authors":[{"text":"Donato, David I. 0000-0002-5412-0249 didonato@usgs.gov","orcid":"https://orcid.org/0000-0002-5412-0249","contributorId":2234,"corporation":false,"usgs":true,"family":"Donato","given":"David","email":"didonato@usgs.gov","middleInitial":"I.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":473038,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70043094,"text":"ofr20131002 - 2013 - New vitrinite reflectance data for the Wind River Basin, Wyoming","interactions":[],"lastModifiedDate":"2013-02-12T10:27:15","indexId":"ofr20131002","displayToPublicDate":"2013-02-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1002","title":"New vitrinite reflectance data for the Wind River Basin, Wyoming","docAbstract":"The Wind River Basin is a large Laramide (Late Cretaceous through Eocene) structural and sedimentary basin that encompasses about 7,400 square miles in central Wyoming. The basin is bounded by the Washakie Range and Owl Creek and southern Bighorn Mountains on the north, the Casper arch on the east and northeast, and the Granite Mountains on the south, and Wind River Range on the west. The purpose of this report is to present new vitrinite reflectance data collected mainly from Cretaceous marine shales in the Wind River Basin to better characterize their thermal maturity and hydrocarbon potential.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131002","usgsCitation":"Pawlewicz, M.J., and Finn, T.M., 2013, New vitrinite reflectance data for the Wind River Basin, Wyoming: U.S. Geological Survey Open-File Report 2013-1002, iii, 11 p., https://doi.org/10.3133/ofr20131002.","productDescription":"iii, 11 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040666","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":266975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1002.gif"},{"id":266973,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1002/"},{"id":266974,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1002/OF13-1002.pdf"}],"country":"United States","state":"Arizona;Colorado;Idaho;Montana;Nebraska;New Mexico;North Dakota;South Dakota;Wyoming","otherGeospatial":"Wind River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.37,35.87 ], [ -112.37,46.07 ], [ -102.46,46.07 ], [ -102.46,35.87 ], [ -112.37,35.87 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511229fee4b0ebe69d7eb604","contributors":{"authors":[{"text":"Pawlewicz, Mark J. pawlewicz@usgs.gov","contributorId":752,"corporation":false,"usgs":true,"family":"Pawlewicz","given":"Mark","email":"pawlewicz@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":472943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Thomas M. 0000-0001-6396-9351 finn@usgs.gov","orcid":"https://orcid.org/0000-0001-6396-9351","contributorId":778,"corporation":false,"usgs":true,"family":"Finn","given":"Thomas","email":"finn@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":472944,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043097,"text":"ds735 - 2013 - Seafloor video footage and still-frame grabs from U.S. Geological Survey cruises in Hawaiian nearshore waters","interactions":[],"lastModifiedDate":"2026-05-12T17:38:58.095147","indexId":"ds735","displayToPublicDate":"2013-02-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"735","title":"Seafloor video footage and still-frame grabs from U.S. Geological Survey cruises in Hawaiian nearshore waters","docAbstract":"Underwater video footage was collected in nearshore waters (<60-meter depth) off the Hawaiian Islands from 2002 to 2011 as part of the U.S. Geological Survey (USGS) Coastal and Marine Geology Program's Pacific Coral Reef Project, to improve seafloor characterization and for the development and ground-truthing of benthic-habitat maps. This report includes nearly 53 hours of digital underwater video footage collected during four USGS cruises and more than 10,200 still images extracted from the videos, including still frames from every 10 seconds along transect lines, and still frames showing both an overview and a near-bottom view from fixed stations. Environmental Systems Research Institute (ESRI) shapefiles of individual video and still-image locations, and Google Earth kml files with explanatory text and links to the video and still images, are included. This report documents the various camera systems and methods used to collect the videos, and the techniques and software used to convert the analog video tapes into digital data in order to process the images for optimum viewing and to extract the still images, along with a brief summary of each survey cruise.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds735","usgsCitation":"Gibbs, A.E., Cochran, S., and Tierney, P.W., 2013, Seafloor video footage and still-frame grabs from U.S. Geological Survey cruises in Hawaiian nearshore waters: U.S. Geological Survey Data Series 735, Report: iv, 11 p.; Videos; Stills; Shapefiles; Google Earth kml files, https://doi.org/10.3133/ds735.","productDescription":"Report: iv, 11 p.; Videos; Stills; Shapefiles; Google Earth kml files","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":504284,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98130.htm","linkFileType":{"id":5,"text":"html"}},{"id":266972,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_735.gif"},{"id":266970,"rank":6,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/735/"},{"id":267266,"rank":5,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/735/VideoStills"},{"id":266971,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/735/ds735_text.pdf"},{"id":267265,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/735/Video"},{"id":267268,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/735/kml"},{"id":267267,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/735/shapefiles"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -157.8186,20.4836 ], [ -157.8186,21.4224 ], [ -156.3629,21.4224 ], [ -156.3629,20.4836 ], [ -157.8186,20.4836 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51122a00e4b0ebe69d7eb608","contributors":{"authors":[{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Susan A.","contributorId":27533,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","affiliations":[],"preferred":false,"id":472946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tierney, Peter W.","contributorId":68187,"corporation":false,"usgs":true,"family":"Tierney","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":472947,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047357,"text":"70047357 - 2013 - Deep subsurface drip irrigation using coal-bed sodic water: part I. water and solute movement","interactions":[],"lastModifiedDate":"2013-08-01T15:34:53","indexId":"70047357","displayToPublicDate":"2013-02-01T15:26:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Deep subsurface drip irrigation using coal-bed sodic water: part I. water and solute movement","docAbstract":"Water co-produced with coal-bed methane (CBM) in the semi-arid Powder River Basin of Wyoming and Montana commonly has relatively low salinity and high sodium adsorption ratios that can degrade soil permeability where used for irrigation. Nevertheless, a desire to derive beneficial use from the water and a need to dispose of large volumes of it have motivated the design of a deep subsurface drip irrigation (SDI) system capable of utilizing that water. Drip tubing is buried 92 cm deep and irrigates at a relatively constant rate year-round, while evapotranspiration by the alfalfa and grass crops grown is seasonal. We use field data from two sites and computer simulations of unsaturated flow to understand water and solute movements in the SDI fields. Combined irrigation and precipitation exceed potential evapotranspiration by 300-480 mm annually. Initially, excess water contributes to increased storage in the unsaturated zone, and then drainage causes cyclical rises in the water table beneath the fields. Native chloride and nitrate below 200 cm depth are leached by the drainage. Some CBM water moves upward from the drip tubing, drawn by drier conditions above. Chloride from CBM water accumulates there as root uptake removes the water. Year over year accumulations indicated by computer simulations illustrate that infiltration of precipitation water from the surface only partially leaches such accumulations away. Field data show that 7% and 27% of added chloride has accumulated above the drip tubing in an alfalfa and grass field, respectively, following 6 years of irrigation. Maximum chloride concentrations in the alfalfa field are around 45 cm depth but reach the surface in parts of the grass field, illustrating differences driven by crop physiology. Deep SDI offers a means of utilizing marginal quality irrigation waters and managing the accumulation of their associated solutes in the crop rooting zone.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Agricultural Water Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2012.11.014","usgsCitation":"Bern, C., Breit, G.N., Healy, R.W., Zupancic, J.W., and Hammack, R., 2013, Deep subsurface drip irrigation using coal-bed sodic water: part I. water and solute movement: Agricultural Water Management, v. 118, p. 122-134, https://doi.org/10.1016/j.agwat.2012.11.014.","productDescription":"13 p.","startPage":"122","endPage":"134","numberOfPages":"13","ipdsId":"IP-036926","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"links":[{"id":275891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275800,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.agwat.2012.11.014"},{"id":275801,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0378377412003071"}],"country":"United States","state":"Wyoming","otherGeospatial":"Powder River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.858878,44.690745 ], [ -106.858878,44.955734 ], [ -106.269986,44.955734 ], [ -106.269986,44.690745 ], [ -106.858878,44.690745 ] ] ] } } ] }","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51fbca70e4b04b00e3d88fa0","chorus":{"doi":"10.1016/j.agwat.2012.11.014","url":"http://dx.doi.org/10.1016/j.agwat.2012.11.014","publisher":"Elsevier BV","authors":"Bern Carleton R., Breit George N., Healy Richard W., Zupancic John W., Hammack Richard","journalName":"Agricultural Water Management","publicationDate":"2/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Bern, Carleton R.","contributorId":59325,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton R.","affiliations":[],"preferred":false,"id":481812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":481810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":481809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zupancic, John W.","contributorId":73885,"corporation":false,"usgs":true,"family":"Zupancic","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":481813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hammack, Richard","contributorId":44449,"corporation":false,"usgs":true,"family":"Hammack","given":"Richard","affiliations":[],"preferred":false,"id":481811,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70199859,"text":"70199859 - 2013 - Modeling plant species distributions under future climates: how fine scale do climate projections need to be?","interactions":[],"lastModifiedDate":"2018-10-01T14:47:22","indexId":"70199859","displayToPublicDate":"2013-02-01T14:46:36","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling plant species distributions under future climates: how fine scale do climate projections need to be?","docAbstract":"<p><span>Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16&nbsp;km</span><sup>2</sup><span>). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90&nbsp;m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800&nbsp;m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4&nbsp;km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.12051","usgsCitation":"Franklin, J., Davis, F.W., Ikegami, M., Syphard, A.D., Flint, L.E., Flint, A.L., and Hannah, L., 2013, Modeling plant species distributions under future climates: how fine scale do climate projections need to be?: Global Change Biology, v. 19, no. 2, p. 473-483, https://doi.org/10.1111/gcb.12051.","productDescription":"11 p.","startPage":"473","endPage":"483","ipdsId":"IP-041557","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":473956,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/75k42636","text":"External 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aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746936,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hannah, Lee","contributorId":208392,"corporation":false,"usgs":false,"family":"Hannah","given":"Lee","email":"","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":746941,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70048507,"text":"70048507 - 2013 - Dynamics of seabird colonies vulnerable to sea-level rise at French Frigate Shoals, Hawai`i","interactions":[],"lastModifiedDate":"2016-10-19T13:57:41","indexId":"70048507","displayToPublicDate":"2013-02-01T14:21:10","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":257,"text":"Hawai‘i Cooperative Studies Unit Technical Report","active":false,"publicationSubtype":{"id":3}},"seriesNumber":"HCSU-037","title":"Dynamics of seabird colonies vulnerable to sea-level rise at French Frigate Shoals, Hawai`i","docAbstract":"Globally, seabirds are vulnerable to anthropogenic threats both at sea and on land. Seabirds \ntypically nest colonially and show strong site fidelity; therefore, conservation strategies could \nbenefit from an understanding of the population dynamics and vulnerability of breeding colonies \nto climate change. More than 350 atolls exist across the Pacific Ocean; while they provide \nnesting habitat for many seabirds, they are also vulnerable to sea-level rise. We used French \nFrigate Shoals, the largest atoll in the Hawaiian Archipelago, as a case study to explore seabird \ncolony dynamics and the potential consequences of sea-level rise. We compiled a unique \ncombination of data sets: historical observations of islands and seabirds, a 30-year time series \nof population abundance, LiDAR- (light detection and ranging) derived elevations, and satellite\nimagery. To model population dynamics for ten species at Tern Island from 1980 to 2009, we \nused the Gompertz model with parameters for the population growth rate, density dependence, \nprocess variation, and observation error. We used a Bayesian approach to estimate the \nparameters. All species increased in a pattern that provided evidence of density dependence. \nDensity dependence may exacerbate the consequences of sea-level rise on seabirds because \nspecies that are already near the carrying capacity of the nesting habitat will be limited more \nthan species that still have space for population growth. Laysan Albatross (<i>Phoebastria \nimmutabilis</i>), Great Frigatebird (<i>Fregata minor</i>), Red-tailed Tropicbird (<i>Phaethon rubricauda</i>),\nMasked Booby (<i>Sula dactylatra</i>), Gray-backed Tern (<i>Onychoprion lunatus</i>), and White Tern\n(<i>Gygis alba</i>) are likely already at carrying capacity at Tern Island and therefore are most likely \nto be negatively impacted by sea-level rise. We project 12% of French Frigate Shoals (excluding \nLa Perouse Pinnacle) will be inundated with +1.0 m sea-level rise or 32% with +2.0 m. Gray-backed Terns that nest along the coastal perimeters of islands and shrub-nesting species that \nare habitat limited are especially vulnerable to sea-level rise. However, at Tern Island, seawalls\nand habitat creation may mitigate projected seabird population declines due to habitat loss. We \npredict substantial losses in seabird nesting habitat across the low-lying Hawaiian Islands by \n2100 and emphasize the need to restore higher elevation seabird colonies.","language":"English","publisher":"University of Hawai‘i at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Reynolds, M.H., Courtot, K., Krause, C.M., Seavy, N., Hartzell, P., and Hatfield, J.S., 2013, Dynamics of seabird colonies vulnerable to sea-level rise at French Frigate Shoals, Hawai`i: Hawai‘i Cooperative Studies Unit Technical Report HCSU-037, iv, 32 p.","productDescription":"iv, 32 p.","numberOfPages":"38","ipdsId":"IP-042488","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":279192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279191,"type":{"id":15,"text":"Index Page"},"url":"https://hilo.hawaii.edu/hcsu/publications.php"}],"country":"United States","state":"Hawai'i","otherGeospatial":"French Frigate Shoals","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -179.89,14.96 ], [ -179.89,35.48 ], [ -151.24,35.48 ], [ -151.24,14.96 ], [ -179.89,14.96 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528c96ace4b0c629af44dda3","contributors":{"authors":[{"text":"Reynolds, Michelle H. 0000-0001-7253-8158 mreynolds@usgs.gov","orcid":"https://orcid.org/0000-0001-7253-8158","contributorId":3871,"corporation":false,"usgs":true,"family":"Reynolds","given":"Michelle","email":"mreynolds@usgs.gov","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":484874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Courtot, Karen N.","contributorId":26909,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen N.","affiliations":[],"preferred":false,"id":484876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krause, Crystal M.","contributorId":101919,"corporation":false,"usgs":true,"family":"Krause","given":"Crystal","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seavy, Nathaniel E.","contributorId":19829,"corporation":false,"usgs":true,"family":"Seavy","given":"Nathaniel E.","affiliations":[],"preferred":false,"id":484875,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartzell, Paula","contributorId":69050,"corporation":false,"usgs":true,"family":"Hartzell","given":"Paula","email":"","affiliations":[],"preferred":false,"id":484877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hatfield, Jeff S.","contributorId":95187,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeff","email":"","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":484878,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70046974,"text":"70046974 - 2013 - Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands","interactions":[],"lastModifiedDate":"2013-07-12T12:47:17","indexId":"70046974","displayToPublicDate":"2013-02-01T12:39:11","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":"Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands","docAbstract":"Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0054988","usgsCitation":"O’Halloran, L., Borer, E.T., Seabloom, E.W., MacDougall, A.S., Cleland, E., McCulley, R.L., Hobbie, S., Harpole, W.S., DeCrappeo, N.M., Chu, C., Bakker, J.D., Davies, K.F., Du, G., Firn, J., Hagenah, N., Hofmockel, K.S., Knops, J.M., Li, W., Melbourne, B.A., Morgan, J.W., Orrock, J., Prober, S.M., and Stevens, C.J., 2013, Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands: PLoS ONE, v. 8, no. 2, e54988, 9 p., https://doi.org/10.1371/journal.pone.0054988.","productDescription":"e54988, 9 p.","ipdsId":"IP-044989","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0054988","text":"Publisher Index Page"},{"id":274924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274869,"type":{"id":15,"text":"Index Page"},"url":"https://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0054988"},{"id":274923,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0054988"}],"otherGeospatial":"Earth","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-02-06","publicationStatus":"PW","scienceBaseUri":"51e1256fe4b02f5cae2b73ce","contributors":{"authors":[{"text":"O’Halloran, Lydia R.","contributorId":72280,"corporation":false,"usgs":true,"family":"O’Halloran","given":"Lydia R.","affiliations":[],"preferred":false,"id":480761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":480755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":480757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacDougall, Andrew S.","contributorId":39509,"corporation":false,"usgs":true,"family":"MacDougall","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":480754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cleland, Elsa E.","contributorId":92790,"corporation":false,"usgs":true,"family":"Cleland","given":"Elsa E.","affiliations":[],"preferred":false,"id":480768,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCulley, Rebecca L.","contributorId":102197,"corporation":false,"usgs":true,"family":"McCulley","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":480770,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hobbie, Sarah","contributorId":64973,"corporation":false,"usgs":true,"family":"Hobbie","given":"Sarah","affiliations":[],"preferred":false,"id":480758,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harpole, W. Stan","contributorId":27340,"corporation":false,"usgs":true,"family":"Harpole","given":"W.","email":"","middleInitial":"Stan","affiliations":[],"preferred":false,"id":480752,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DeCrappeo, Nicole M.","contributorId":92383,"corporation":false,"usgs":true,"family":"DeCrappeo","given":"Nicole","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":480767,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chu, Cheng-Jin","contributorId":45820,"corporation":false,"usgs":true,"family":"Chu","given":"Cheng-Jin","email":"","affiliations":[],"preferred":false,"id":480756,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bakker, Jonathan D.","contributorId":15754,"corporation":false,"usgs":true,"family":"Bakker","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":480749,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Davies, Kendi F.","contributorId":30346,"corporation":false,"usgs":true,"family":"Davies","given":"Kendi","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":480753,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Du, Guozhen","contributorId":89429,"corporation":false,"usgs":true,"family":"Du","given":"Guozhen","email":"","affiliations":[],"preferred":false,"id":480765,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Firn, Jennifer","contributorId":66405,"corporation":false,"usgs":false,"family":"Firn","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":480759,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hagenah, Nicole","contributorId":95998,"corporation":false,"usgs":true,"family":"Hagenah","given":"Nicole","affiliations":[],"preferred":false,"id":480769,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hofmockel, Kirsten S.","contributorId":69038,"corporation":false,"usgs":false,"family":"Hofmockel","given":"Kirsten","email":"","middleInitial":"S.","affiliations":[{"id":12468,"text":"Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":480760,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Knops, Johannes M.H.","contributorId":105843,"corporation":false,"usgs":true,"family":"Knops","given":"Johannes","email":"","middleInitial":"M.H.","affiliations":[],"preferred":false,"id":480771,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Li, Wei","contributorId":22894,"corporation":false,"usgs":true,"family":"Li","given":"Wei","email":"","affiliations":[],"preferred":false,"id":480751,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Melbourne, Brett A.","contributorId":86473,"corporation":false,"usgs":true,"family":"Melbourne","given":"Brett","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":480763,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Morgan, John W.","contributorId":88077,"corporation":false,"usgs":true,"family":"Morgan","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":480764,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Orrock, John L.","contributorId":18101,"corporation":false,"usgs":true,"family":"Orrock","given":"John L.","affiliations":[],"preferred":false,"id":480750,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Prober, Suzanne M.","contributorId":74498,"corporation":false,"usgs":false,"family":"Prober","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":480762,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Stevens, Carly J.","contributorId":89658,"corporation":false,"usgs":true,"family":"Stevens","given":"Carly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":480766,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}}
,{"id":70118057,"text":"70118057 - 2013 - VisTrails SAHM: visualization and workflow management for species habitat modeling","interactions":[],"lastModifiedDate":"2018-09-21T11:22:56","indexId":"70118057","displayToPublicDate":"2013-02-01T11:48:13","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1446,"text":"Ecography: Pattern and Diversity in Ecology","active":true,"publicationSubtype":{"id":10}},"title":"VisTrails SAHM: visualization and workflow management for species habitat modeling","docAbstract":"The Software for Assisted Habitat Modeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model through the established workflow management and visualization VisTrails software. This paper provides an overview of the VisTrails:SAHM software including a link to the open source code, a table detailing the current SAHM modules, and a simple example modeling an invasive weed species in Rocky Mountain National Park, USA.","language":"English","publisher":"Wiley","doi":"10.1111/j.1600-0587.2012.07815.x","usgsCitation":"Morisette, J.T., Jarnevich, C.S., Holcombe, T.R., Talbert, C., Ignizio, D.A., Talbert, M., Silva, C., Koop, D., Swanson, A., and Young, N.E., 2013, VisTrails SAHM: visualization and workflow management for species habitat modeling: Ecography: Pattern and Diversity in Ecology, v. 36, no. 2, p. 129-135, https://doi.org/10.1111/j.1600-0587.2012.07815.x.","productDescription":"7 p.","startPage":"129","endPage":"135","numberOfPages":"7","ipdsId":"IP-037234","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":291001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291000,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1600-0587.2012.07815.x"}],"volume":"36","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-01-25","publicationStatus":"PW","scienceBaseUri":"57f7f357e4b0bc0bec0a090f","contributors":{"authors":[{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":496200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":496201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holcombe, Tracy R. holcombet@usgs.gov","contributorId":3694,"corporation":false,"usgs":true,"family":"Holcombe","given":"Tracy","email":"holcombet@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":496202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbert, Colin B. talbertc@usgs.gov","contributorId":147948,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin B.","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":496209,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ignizio, Drew A. 0000-0001-8054-5139 dignizio@usgs.gov","orcid":"https://orcid.org/0000-0001-8054-5139","contributorId":139842,"corporation":false,"usgs":true,"family":"Ignizio","given":"Drew","email":"dignizio@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":496207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbert, Marian mtalbert@usgs.gov","contributorId":5180,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":false,"id":496203,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Silva, Claudio","contributorId":48486,"corporation":false,"usgs":true,"family":"Silva","given":"Claudio","email":"","affiliations":[],"preferred":false,"id":496204,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koop, David","contributorId":83845,"corporation":false,"usgs":true,"family":"Koop","given":"David","email":"","affiliations":[],"preferred":false,"id":496206,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Swanson, Alan","contributorId":99054,"corporation":false,"usgs":true,"family":"Swanson","given":"Alan","email":"","affiliations":[],"preferred":false,"id":496208,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Young, Nicholas E.","contributorId":58572,"corporation":false,"usgs":true,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":496205,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70118043,"text":"70118043 - 2013 - Valuing morbidity from wildfire smoke exposure: a comparison of revealed and stated preference techniques","interactions":[],"lastModifiedDate":"2014-07-25T10:55:51","indexId":"70118043","displayToPublicDate":"2013-02-01T10:45:49","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2598,"text":"Land Economics","active":true,"publicationSubtype":{"id":10}},"title":"Valuing morbidity from wildfire smoke exposure: a comparison of revealed and stated preference techniques","docAbstract":"<p>Estimating the economic benefits of reduced health damages due to improvements in environmental quality continues to challenge economists. We review welfare measures associated with reduced wildfire smoke exposure, and a unique dataset from California’s Station Fire of 2009 allows for a comparison of cost of illness (COI) estimates with willingness to pay (WTP) measures. The WTP for one less symptom day is estimated to be $87 and $95, using the defensive behavior and contingent valuation methods, respectively. These WTP estimates are not statistically different but do differ from a $3 traditional daily COI estimate and $17 comprehensive daily COI estimate.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Land Economics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"University of Wisconsin Press","publisherLocation":"Madison, WI","usgsCitation":"Richardson, L., Loomis, J., and Champ, P.A., 2013, Valuing morbidity from wildfire smoke exposure: a comparison of revealed and stated preference techniques: Land Economics, v. 89, no. 1, p. 76-100.","productDescription":"25 p.","startPage":"76","endPage":"100","numberOfPages":"25","costCenters":[],"links":[{"id":290986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f357e4b0bc0bec0a0911","contributors":{"authors":[{"text":"Richardson, Leslie","contributorId":35584,"corporation":false,"usgs":true,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":496174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loomis, John B.","contributorId":27560,"corporation":false,"usgs":true,"family":"Loomis","given":"John B.","affiliations":[],"preferred":false,"id":496173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Champ, Patricia A.","contributorId":97011,"corporation":false,"usgs":true,"family":"Champ","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":496175,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}