The total nitrogen load to Long Island Sound from Connecticut and contributing areas to the north was estimated for October 1998 to September 2009. Discrete measurements of total nitrogen concentrations and continuous flow data from 37 water-quality monitoring stations in the Long Island Sound watershed were used to compute total annual nitrogen yields and loads. Total annual computed yields and basin characteristics were used to develop a generalized-least squares regression model for use in estimating the total nitrogen yields from unmonitored areas in coastal and central Connecticut. Significant variables in the regression included the percentage of developed land, percentage of row crops, point-source nitrogen yields from wastewater-treatment facilities, and annual mean streamflow. Computed annual median total nitrogen yields at individual monitoring stations ranged from less than 2,000 pounds per square mile in mostly forested basins (typically less than 10 percent developed land) to more than 13,000 pounds per square mile in urban basins (greater than 40 percent developed) with wastewater-treatment facilities and in one agricultural basin. Medians of computed total annual nitrogen yields for water years 1999–2009 at most stations were similar to those previously computed for water years 1988–98. However, computed medians of annual yields at several stations, including the Naugatuck River, Quinnipiac River, and Hockanum River, were lower than during 1988–98. Nitrogen yields estimated for 26 unmonitored areas downstream from monitoring stations ranged from less than 2,000 pounds per square mile to 34,000 pounds per square mile. Computed annual total nitrogen loads at the farthest downstream monitoring stations were combined with the corresponding estimates for the downstream unmonitored areas for a combined estimate of the total nitrogen load from the entire study area. Resulting combined total nitrogen loads ranged from 38 to 68 million pounds per year during water years 1999–2009. Total annual loads from the monitored basins represent 63 to 74 percent of the total load. Computed annual nitrogen loads from four stations near the Massachusetts border with Connecticut represent 52 to 54 percent of the total nitrogen load during water years 2008–9, the only years with data for all the border sites. During the latter part of the 1999–2009 study period, total nitrogen loads to Long Island Sound from the study area appeared to increase slightly. The apparent increase in loads may be due to higher than normal streamflows, which consequently increased nonpoint nitrogen loads during the study, offsetting major reductions of nitrogen from wastewater-treatment facilities. Nitrogen loads from wastewater treatment facilities declined as much as 2.3 million pounds per year in areas of Connecticut upstream from the monitoring stations and as much as 5.8 million pounds per year in unmonitored areas downstream in coastal and central Connecticut.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135171","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Mullaney, J.R., and Schwarz, G., 2013, Estimated nitrogen loads from selected tributaries in Connecticut draining to Long Island Sound, 1999–2009: U.S. Geological Survey Scientific Investigations Report 2013-5171, vii, 65 p., https://doi.org/10.3133/sir20135171.","productDescription":"vii, 65 p.","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-050762","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":279610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135171.jpg"},{"id":279608,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5171/"},{"id":279609,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5171/pdf/sir2013-5171.pdf"}],"country":"United States","state":"Connecticut;Massachusetts;New Hampshire;Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.62487792968749,\n 40.925964939514294\n ],\n [\n -73.7896728515625,\n 41.11660732012896\n ],\n [\n -73.6138916015625,\n 41.24890252240322\n ],\n [\n -73.5809326171875,\n 41.53325414281322\n ],\n [\n -73.729248046875,\n 41.64418347939748\n ],\n [\n -73.6962890625,\n 42.00032514831621\n ],\n [\n -73.4820556640625,\n 42.15118709351198\n ],\n [\n -73.487548828125,\n 42.39912215986002\n ],\n [\n -73.070068359375,\n 42.75911283724358\n ],\n [\n -72.75146484374999,\n 43.48481212891603\n ],\n [\n -72.9327392578125,\n 43.739352079154706\n ],\n [\n -72.6361083984375,\n 44.629573191951046\n ],\n [\n -71.9219970703125,\n 44.90646871709883\n ],\n [\n -71.4166259765625,\n 45.29034662473615\n ],\n [\n -71.2353515625,\n 45.336701909968106\n ],\n [\n -71.026611328125,\n 45.24008561090264\n ],\n [\n -71.2628173828125,\n 44.09153051045218\n ],\n [\n -71.83959960937499,\n 43.76712702120528\n ],\n [\n -71.7352294921875,\n 42.69454866207692\n ],\n [\n -71.707763671875,\n 42.00848901572399\n ],\n [\n -71.510009765625,\n 41.69752591075902\n ],\n [\n -71.3177490234375,\n 41.40565583808169\n ],\n [\n -71.861572265625,\n 41.261291493919856\n ],\n [\n -72.9217529296875,\n 41.10832999732833\n ],\n [\n -73.62487792968749,\n 40.925964939514294\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52907ce1e4b0bbdcf23ed2b1","contributors":{"authors":[{"text":"Mullaney, John R. 0000-0003-4936-5046 jmullane@usgs.gov","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":1957,"corporation":false,"usgs":true,"family":"Mullaney","given":"John","email":"jmullane@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":486334,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70160619,"text":"70160619 - 2013 - Broad-scale patterns of Brook Trout responses to introduced Brown Trout in New York","interactions":[],"lastModifiedDate":"2019-12-13T06:39:07","indexId":"70160619","displayToPublicDate":"2013-11-22T12:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Broad-scale patterns of Brook Trout responses to introduced Brown Trout in New York","docAbstract":"Brook Trout Salvelinus fontinalis and Brown Trout Salmo trutta are valuable sport fish that coexist in many parts of the world due to stocking introductions. Causes for the decline of Brook Trout within their native range are not clear but include competition with Brown Trout, habitat alteration, and repetitive stocking practices. New York State contains a large portion of the Brook Trout's native range, where both species are maintained by stocking and other management actions. We used artificial neural network models, regression, principal components analysis, and simulation to evaluate the effects of Brown Trout, environmental conditions, and stocking on the distribution of Brook Trout in the center of their native range. We found evidence for the decline of Brook Trout in the presence of Brown Trout across many watersheds; 22% of sampled reaches where both species were expected to occur contained only Brown Trout. However, a model of the direct relationship between Brook Trout and Brown Trout abundance explained less than 1% of data variation. Ordination showed extensive overlap of Brook Trout and Brown Trout habitat conditions, with only small components of the hypervolume (multidimensional space) being distinctive. Subsequent analysis indicated higher abundances of Brook Trout in highly forested areas, while Brown Trout were more abundant in areas with relatively high proportions of agriculture. Simulation results indicated that direct interactions and habitat conditions were relatively minor factors compared with the effects of repeated stocking of Brown Trout into Brook Trout habitat. Intensive annual stocking of Brown Trout could eliminate resident Brook Trout in less than a decade. Ecological differences, harvest behavior, and other habitat changes can exacerbate Brook Trout losses. Custom stocking scenarios with Brown Trout introductions at relatively low proportions of resident Brook Trout populations may be able to sustain healthy populations of both species within their present range.
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Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":627,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":583357,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slattery, Michael T. mslattery@usgs.gov","contributorId":5470,"corporation":false,"usgs":true,"family":"Slattery","given":"Michael","email":"mslattery@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583358,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clifford, Kean M.","contributorId":150867,"corporation":false,"usgs":false,"family":"Clifford","given":"Kean","email":"","middleInitial":"M.","affiliations":[{"id":18127,"text":"State University of New York, College of Environmental Science and Foresty","active":true,"usgs":false}],"preferred":false,"id":583359,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70049000,"text":"sir20135188 - 2013 - Methods for estimating water consumption for thermoelectric power plants in the United States","interactions":[],"lastModifiedDate":"2014-11-24T14:26:19","indexId":"sir20135188","displayToPublicDate":"2013-11-22T08:26:00","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":"2013-5188","title":"Methods for estimating water consumption for thermoelectric power plants in the United States","docAbstract":"Water consumption at thermoelectric power plants represents a small but substantial share of total water consumption in the U.S. However, currently available thermoelectric water consumption data are inconsistent and incomplete, and coefficients used to estimate consumption are contradictory. The U.S. Geological Survey (USGS) has resumed the estimation of thermoelectric water consumption, last done in 1995, based on the use of linked heat and water budgets to complement reported water consumption. This report presents the methods used to estimate freshwater consumption at a study set of 1,284 power plants based on 2010 plant characteristics and operations data.
\nPower plants were categorized for estimation of water consumption in two tiers. First, generating units were assigned to categories based on the technology used to generate electricity. These generation-type categories are combustion steam, combined-cycle, nuclear, geothermal, and solar thermal. Second, cooling systems were separately categorized as either wet cooling towers or surface-water cooling systems, and the surface-water cooling systems were subcategorized as cooling ponds, lakes, and rivers.
\nHeat budgets were constructed for the first four generation-type categories; data at solar thermal plants were insufficient for heat budgets. These heat budgets yielded estimates of the amount of heat transferred to the condenser. The ratio of evaporation to the heat discharged through the condenser was estimated using existing heat balance models that are sensitive to environmental data; this feature allows estimation of consumption under different climatic conditions. These two estimates were multiplied to yield an estimate of consumption at each power plant.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135188","collaboration":"USGS National Water Census and National Streamflow Information Program","usgsCitation":"Diehl, T.H., Harris, M., Murphy, J.C., Hutson, S.S., and Ladd, D.E., 2013, Methods for estimating water consumption for thermoelectric power plants in the United States: U.S. Geological Survey Scientific Investigations Report 2013-5188, Report: vii, 78 p.; Appendix 4, https://doi.org/10.3133/sir20135188.","productDescription":"Report: vii, 78 p.; Appendix 4","numberOfPages":"90","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-045152","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":279513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135188.jpg"},{"id":279511,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5188/pdf/sir2013-5188.pdf"},{"id":279512,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5188/appendix/sir2013-5188_appendix4_fews_version_3.104_edit_20141106.xlsx","description":"Appendix 4"},{"id":279502,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5188/"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173,16.916667 ], [ 173,71.833333 ], [ -66.95,71.833333 ], [ -66.95,16.916667 ], [ 173,16.916667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52907d0ee4b0bbdcf23ed313","contributors":{"authors":[{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Melissa","contributorId":17519,"corporation":false,"usgs":true,"family":"Harris","given":"Melissa","affiliations":[],"preferred":false,"id":485972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hutson, Susan S. sshutson@usgs.gov","contributorId":2040,"corporation":false,"usgs":true,"family":"Hutson","given":"Susan","email":"sshutson@usgs.gov","middleInitial":"S.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ladd, David E. 0000-0002-9247-7839 deladd@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7839","contributorId":1646,"corporation":false,"usgs":true,"family":"Ladd","given":"David","email":"deladd@usgs.gov","middleInitial":"E.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485969,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70055684,"text":"sir20135142 - 2013 - Land subsidence along the Delta-Mendota Canal in the northern part of the San Joaquin Valley, California, 2003-10","interactions":[],"lastModifiedDate":"2013-11-21T12:47:43","indexId":"sir20135142","displayToPublicDate":"2013-11-21T12:40:00","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":"2013-5142","title":"Land subsidence along the Delta-Mendota Canal in the northern part of the San Joaquin Valley, California, 2003-10","docAbstract":"Extensive groundwater withdrawal from the unconsolidated deposits in the San Joaquin Valley caused widespread aquifer-system compaction and resultant land subsidence from 1926 to 1970—locally exceeding 8.5 meters. The importation of surface water beginning in the early 1950s through the Delta-Mendota Canal and in the early 1970s through the California Aqueduct resulted in decreased pumping, initiation of water-level recovery, and a reduced rate of compaction in some areas of the San Joaquin Valley. However, drought conditions during 1976–77 and 1987–92, and drought conditions and regulatory reductions in surface-water deliveries during 2007–10, decreased surface-water availability, causing pumping to increase, water levels to decline, and renewed compaction. Land subsidence from this compaction has reduced freeboard and flow capacity of the Delta-Mendota Canal, the California Aqueduct, and other canals that deliver irrigation water and transport floodwater.\n\nThe U.S. Geological Survey, in cooperation with the U.S. Bureau of Reclamation and the San Luis and Delta-Mendota Water Authority, assessed land subsidence in the vicinity of the Delta-Mendota Canal as part of an effort to minimize future subsidence-related damages to the canal. The location, magnitude, and stress regime of land-surface deformation during 2003–10 were determined by using extensometer, Global Positioning System (GPS), Interferometric Synthetic Aperture Radar (InSAR), spirit leveling, and groundwater-level data. Comparison of continuous GPS, shallow extensometer, and groundwater-level data, combined with results from a one-dimensional model, indicated the vast majority of the compaction took place beneath the Corcoran Clay, the primary regional confining unit.\n\nLand-surface deformation measurements indicated that much of the northern portion of the Delta-Mendota Canal (Clifton Court Forebay to Check 14) was fairly stable or minimally subsiding on an annual basis; some areas showed seasonal periods of subsidence and of uplift that resulted in little or no longer-term elevation loss. Many groundwater levels in this northern area did not reach historical lows during 2003–10, indicating that deformation in this region was primarily elastic.\n\nAlthough the northern portion of the Delta-Mendota Canal was relatively stable, land-surface deformation measurements indicated the southern portion of the Delta-Mendota Canal (Checks 15–21) subsided as part of a large subsidence feature centered about 15 kilometers northeast of the Delta-Mendota Canal, south of the town of El Nido. Results of InSAR analysis indicated at least 540 millimeters of subsidence near the San Joaquin River and the Eastside Bypass during 2008–10, which is part of a 3,200 square-kilometer area—including the southern part of the Delta-Mendota Canal—affected by 20 millimeters or more of subsidence during the same period. Calculations indicated that the subsidence rate doubled in 2008 in some areas. The GPS surveys done in 2008 and 2010 confirmed the high subsidence rate measured by using InSAR for the same period. Water levels in many shallow and deep wells in this area declined during 2007–10; water levels in many deep wells reached historical lows, indicating that subsidence measured during this period was largely inelastic. InSAR-derived subsidence maps for various periods during 2003–10 showed that the area of maximum active subsidence (that is, the largest rates of subsidence) shifted from its historical (1926–70) location southwest of Mendota to south of El Nido.\n\nContinued groundwater-level and land-subsidence monitoring in the San Joaquin Valley is important because (1) regulatory- and drought-related reductions in surface-water deliveries since 1976 have resulted in increased groundwater pumping and associated land subsidence, and (2) land use and associated groundwater pumping continue to change throughout the valley. The availability of surface water remains uncertain; even during record-setting precipitation years, such as 2010–11, water deliveries have fallen short of requests and groundwater pumping was required to meet the irrigation demand. Due to the expected continued demand for irrigation supply water and the limitations and uncertainty of surface-water supplies, groundwater pumping and associated land subsidence is likely to continue in the future. Spatially detailed information on land subsidence is needed to facilitate minimization of future subsidence-related damages to the Delta-Mendota Canal and other infrastructure in the San Joaquin Valley. The integration of subsidence, deformation, and water-level measurements—particularly continuous measurements—enables the analysis of aquifer-system response to increased groundwater pumping, which in turn, enables identification of the preconsolidation head and calculation of aquifer-system storage properties. This information can be used to improve numerical model simulations of groundwater flow and aquifer-system compaction and allow for consideration of land subsidence in the evaluation of water-resource management alternatives.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135142","issn":"2328-0328","collaboration":"Prepared in cooperation with U.S. Bureau of Reclamation and the San Luis and Delta-Mendota Water Authority","usgsCitation":"Sneed, M., Brandt, J.T., and Solt, M., 2013, Land subsidence along the Delta-Mendota Canal in the northern part of the San Joaquin Valley, California, 2003-10: U.S. Geological Survey Scientific Investigations Report 2013-5142, Report: x, 86 p.; 2 Appendices, https://doi.org/10.3133/sir20135142.","productDescription":"Report: x, 86 p.; 2 Appendices","numberOfPages":"100","onlineOnly":"Y","temporalStart":"2003-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-037140","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":279412,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135142.jpg"},{"id":279407,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5142/pdf/sir2013-5142_appendixE.pdf"},{"id":279408,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5142/sir2013-5142_appendixE_tables.xlsx"},{"id":279405,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5142/"},{"id":279406,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5142/pdf/sir2013-5142.pdf"}],"country":"United States","state":"California","otherGeospatial":"Delta-mendota Canal;San Joaquin Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5,35.5 ], [ -122.5,38.0 ], [ -119.5,38.0 ], [ -119.5,35.5 ], [ -122.5,35.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528f53c9e4b0660d392bed6f","contributors":{"authors":[{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solt, Mike","contributorId":88258,"corporation":false,"usgs":true,"family":"Solt","given":"Mike","email":"","affiliations":[],"preferred":false,"id":486202,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048958,"text":"sir20135166 - 2013 - Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches","interactions":[],"lastModifiedDate":"2013-11-21T12:41:47","indexId":"sir20135166","displayToPublicDate":"2013-11-21T11:40:00","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":"2013-5166","title":"Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches","docAbstract":"Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report.\n\nLocal agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development.
\n\nPredictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135166","collaboration":"Coastal and Marine Geology Program Prepared in cooperation with the U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Francy, D.S., Brady, A., Carvin, R.B., Corsi, S., Fuller, L.M., Harrison, J.H., Hayhurst, B.A., Lant, J., Nevers, M.B., Terrio, P.J., and Zimmerman, T.M., 2013, Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches: U.S. Geological Survey Scientific Investigations Report 2013-5166, Report: vii, 68 p.; 3 Appendices, Downloads Directory, https://doi.org/10.3133/sir20135166.","productDescription":"Report: vii, 68 p.; 3 Appendices, Downloads Directory","ipdsId":"IP-037603","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":279395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135166.jpg"},{"id":279349,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5166/"},{"id":279400,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5166/pdf/sir2013-5166_appendix2.pdf"},{"id":279401,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5166/table/sir2013-5166_appendix3.xlsx"},{"id":279398,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5166/pdf/sir2013-5166.pdf"},{"id":279399,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5166/table/sir2013-5166_appendix1.xls"},{"id":279402,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5166/Downloads"}],"country":"Canada;United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.33,41.25 ], [ -92.33,49.12 ], [ -75.73,49.12 ], [ -75.73,41.25 ], [ -92.33,41.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528f53c8e4b0660d392bed69","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Amie M. G.","contributorId":29774,"corporation":false,"usgs":true,"family":"Brady","given":"Amie M. G.","affiliations":[],"preferred":false,"id":485876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carvin, Rebecca B. 0000-0001-7778-4841 rbcarvin@usgs.gov","orcid":"https://orcid.org/0000-0001-7778-4841","contributorId":4456,"corporation":false,"usgs":true,"family":"Carvin","given":"Rebecca","email":"rbcarvin@usgs.gov","middleInitial":"B.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":511,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485869,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Lori M. lmfuller@usgs.gov","contributorId":2100,"corporation":false,"usgs":true,"family":"Fuller","given":"Lori","email":"lmfuller@usgs.gov","middleInitial":"M.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485871,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harrison, John H.","contributorId":34011,"corporation":false,"usgs":true,"family":"Harrison","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":485878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hayhurst, Brett A. 0000-0002-1717-2015 bhayhurs@usgs.gov","orcid":"https://orcid.org/0000-0002-1717-2015","contributorId":3398,"corporation":false,"usgs":true,"family":"Hayhurst","given":"Brett","email":"bhayhurs@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485874,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lant, Jeremiah","contributorId":30904,"corporation":false,"usgs":true,"family":"Lant","given":"Jeremiah","affiliations":[],"preferred":false,"id":485877,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nevers, Meredith B.","contributorId":91803,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":485879,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485873,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zimmerman, Tammy M. 0000-0003-0842-6981 tmzimmer@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-6981","contributorId":2359,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Tammy","email":"tmzimmer@usgs.gov","middleInitial":"M.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485872,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70048949,"text":"ds802 - 2013 - Water quality, sediment characteristics, aquatic habitat, geomorphology, and mussel population status of the Clinch River, Virginia and Tennessee, 2009-2011","interactions":[],"lastModifiedDate":"2016-07-08T12:21:37","indexId":"ds802","displayToPublicDate":"2013-11-21T10:40:00","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":"802","title":"Water quality, sediment characteristics, aquatic habitat, geomorphology, and mussel population status of the Clinch River, Virginia and Tennessee, 2009-2011","docAbstract":"Chemical, physical, and biological data were collected during 2009-2011 as part of a study of the Clinch River in Virginia and Tennessee. The data from this study, data-collection methods, and laboratory analytical methods used in the study are documented in this report. The study was conducted to describe the conditions of the Clinch River and to determine if there are measurable differences in chemical, physical, or biological characteristics in a segment of the river where freshwater mussel populations are in decline, have low density, richness, little to no recruitment, and lack endangered species (low-quality reach) compared to a segment of the river where mussel assemblages have relatively high density, richness, evidence of recruitment, and support endangered species (high-quality reach). Five continuous water-quality monitors were installed and operated on the mainstem of the Clinch River and two tributaries. Discrete water-quality sample sets were collected during base-flow and stormflow conditions two sites on the Clinch River and on the Guest River, a tributary to the Clinch River predominantly in the Appalachian Plateaus Physiographic Province. Base-flow water-quality samples were collected in July and August 2011 at 15 sites along the mainstem of the Clinch River. Other analyses included longitudinal sampling along the mainstem of the Clinch River at 10 sites to evaluate bed-sediment chemistry, habitat condition, and mollusk community status. In situ freshwater mussel growth and mortality experiments were conducted with hatchery propogated Villosa iris (rainbow mussels). Tissue from the V. iris as well as tissue from 16 Actinonaias pectorosa mussels were analyzed for trace metals, and V. iris mussel tissue was analyzed for organic compounds. Data collected during this investigation were analyzed by various U.S. Geological Survey or U.S. Fish and Wildlife Service laboratories.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds802","collaboration":"Prepared in cooperation with the Tennessee Wildlife Resources Agency and the Tennessee Department of Environment and Conservation","usgsCitation":"Krstolic, J.L., Johnson, G.C., and Ostby, B.J., 2013, Water quality, sediment characteristics, aquatic habitat, geomorphology, and mussel population status of the Clinch River, Virginia and Tennessee, 2009-2011: U.S. Geological Survey Data Series 802, Report: vi, 14 p.; 2 Appendices; 1 Figure: 17 inches x 11 inches, https://doi.org/10.3133/ds802.","productDescription":"Report: vi, 14 p.; 2 Appendices; 1 Figure: 17 inches x 11 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-034903","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":279326,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0802/pdf/ds802.pdf","text":"Report","size":"753.47 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":279327,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0802/table/ds802_appendix_tables_1-2_4-25.xlsx","text":"Tables 1-2, 4-25","size":"542 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Tables 1-2, 4-25"},{"id":279328,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0802/table/ds802_appendix_table3.xlsx","text":"Table 3","size":"11.4 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 3"},{"id":279329,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/ds/0802/pdf/ds802_figure1_clinch_river_11x17.pdf","text":"Figure 1","size":"984.67 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 1"},{"id":279330,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds802.gif"},{"id":279318,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0802/"}],"country":"United States","state":"Tennessee, Virginia","otherGeospatial":"Clinch River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.980224609375,\n 37.405073750176946\n ],\n [\n -81.23291015625,\n 37.405073750176946\n ],\n [\n -81.683349609375,\n 37.26530995561875\n ],\n [\n -82.628173828125,\n 37.01132594307015\n ],\n [\n -82.96875,\n 36.84446074079564\n ],\n [\n -83.199462890625,\n 36.721273880045004\n ],\n [\n -83.726806640625,\n 36.633162095586556\n ],\n [\n -83.990478515625,\n 36.53612263184686\n ],\n [\n -84.00146484374999,\n 36.33282808737919\n ],\n [\n -84.012451171875,\n 36.1733569352216\n ],\n [\n -83.94653320312499,\n 36.04021586880111\n ],\n [\n -83.8037109375,\n 35.99578538642032\n ],\n [\n -83.51806640624999,\n 35.98689628443791\n ],\n [\n -83.3203125,\n 35.98689628443791\n ],\n [\n -83.1005859375,\n 35.969115075774845\n ],\n [\n -82.85888671875,\n 36.02244668175846\n ],\n [\n -82.694091796875,\n 36.05798104702501\n ],\n [\n -82.254638671875,\n 36.27085020723905\n ],\n [\n -81.88110351562499,\n 36.46547188679816\n ],\n [\n -81.683349609375,\n 36.50963615733049\n ],\n [\n -81.474609375,\n 36.58906837139909\n ],\n [\n -80.947265625,\n 36.70365959719453\n ],\n [\n -80.870361328125,\n 36.84446074079564\n ],\n [\n -80.870361328125,\n 37.046408899699564\n ],\n [\n -80.980224609375,\n 37.405073750176946\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528f53cce4b0660d392bed81","contributors":{"authors":[{"text":"Krstolic, Jennifer L. 0000-0003-2253-9886 jkrstoli@usgs.gov","orcid":"https://orcid.org/0000-0003-2253-9886","contributorId":3677,"corporation":false,"usgs":true,"family":"Krstolic","given":"Jennifer","email":"jkrstoli@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Gregory C. 0000-0003-3683-5010 gcjohnso@usgs.gov","orcid":"https://orcid.org/0000-0003-3683-5010","contributorId":1420,"corporation":false,"usgs":true,"family":"Johnson","given":"Gregory","email":"gcjohnso@usgs.gov","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostby, Brett J.K.","contributorId":42863,"corporation":false,"usgs":true,"family":"Ostby","given":"Brett","email":"","middleInitial":"J.K.","affiliations":[],"preferred":false,"id":485842,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70056139,"text":"sir20125208 - 2013 - Evaluation of intake efficiencies and associated sediment-concentration errors in US D-77 bag-type and US D-96-type depth-integrating suspended-sediment samplers","interactions":[],"lastModifiedDate":"2018-03-21T15:48:11","indexId":"sir20125208","displayToPublicDate":"2013-11-21T09:29:00","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":"2012-5208","title":"Evaluation of intake efficiencies and associated sediment-concentration errors in US D-77 bag-type and US D-96-type depth-integrating suspended-sediment samplers","docAbstract":"Accurate measurements of suspended-sediment concentration require suspended-sediment samplers to operate isokinetically, within an intake-efficiency range of 1.0 ± 0.10, where intake efficiency is defined as the ratio of the velocity of the water through the sampler intake to the local ambient stream velocity. Local ambient stream velocity is defined as the velocity of the water in the river at the location of the nozzle, unaffected by the presence of the sampler. Results from Federal Interagency Sedimentation Project (FISP) laboratory experiments published in the early 1940s show that when the intake efficiency is less than 1.0, suspended-sediment samplers tend to oversample sediment relative to water, leading to potentially large positive biases in suspended-sediment concentration that are positively correlated with grain size. Conversely, these experiments show that, when the intake efficiency is greater than 1.0, suspended‑sediment samplers tend to undersample sediment relative to water, leading to smaller negative biases in suspended-sediment concentration that become slightly more negative as grain size increases.\n\nThe majority of FISP sampler development and testing since the early 1990s has been conducted under highly uniform flow conditions via flume and slack-water tow tests, with relatively little work conducted under the greater levels of turbulence that exist in actual rivers. Additionally, all of this recent work has been focused on the hydraulic characteristics and intake efficiencies of these samplers, with no field investigations conducted on the accuracy of the suspended-sediment data collected with these samplers. When depth-integrating suspended-sediment samplers are deployed under the more nonuniform and turbulent conditions that exist in rivers, multiple factors may contribute to departures from isokinetic sampling, thus introducing errors into the suspended-sediment data collected by these samplers that may not be predictable on the basis of flume and tow tests alone.\n\nThis study has three interrelated goals. First, the intake efficiencies of the older US D-77 bag-type and newer, FISP-approved US D-96-type1 depth-integrating suspended‑sediment samplers are evaluated at multiple cross‑sections under a range of actual-river conditions. The intake efficiencies measured in these actual-river tests are then compared to those previously measured in flume and tow tests. Second, other physical effects, mainly water temperature and the duration of sampling at a vertical, are examined to determine whether these effects can help explain observed differences in intake efficiency both between the two types of samplers and between the laboratory and field tests. Third, the signs and magnitudes of the likely errors in suspendedsand concentration in measurements made with both types of samplers are predicted based the intake efficiencies of these two types of depth-integrating samplers. Using the relative difference in isokinetic sampling observed between the US D-77 bag-type and D-96-type samplers during river tests, measured differences in suspended-sediment concentration in a variety of size classes were evaluated between paired equal-discharge-increment (EDI) and equal-width-increment (EWI) measurements made with these two types of samplers to determine whether these differences in concentration are consistent with the differences in concentrations expected on the basis of the 1940s FISP laboratory experiments. In addition, sequential single-vertical depth-integrated samples were collected (concurrent with velocity measurements) with the US D-96-type bag sampler and two different rigidcontainer samplers to evaluate whether the predicted errors in suspended-sand concentrations measured with the US D-96- type sampler are consistent with those expected on the basis of the 1940s FISP laboratory experiments.\n\nResults from our study indicate that the intake efficiency of the US D-96-type sampler is superior to that of the US D-77 bag-type sampler under actual-river conditions, with overall performance of the US D-96-type sampler being closer to, yet still typically below, the FISP-acceptable range of isokinetic operation. These results are in contrast to the results from FISP-conducted flume tests that showed that both the US D-77 bag-type and US D-96-type samplers sampled isokinetically in the laboratory. Results from our study indicate that the single largest problem with the behavior of both the US D-77 bag-type and the US D-96-type samplers under actual‑river conditions is that both samplers are prone to large time‑dependent decreases in intake efficiency as sampling duration increases. In the case of the US D-96-type sampler, this problem may be at least partially overcome by shortening the duration of sampling (or, instead, perhaps by a simple design improvement); in the case of the US D-77 bag-type sampler, although shortening the sampling duration improves the intake efficiency, it does not bring it into agreement with the FISP‑accepted range of isokinetic operation.\n\nThe predicted errors in suspended-sand concentration in EDI or EWI measurements made with the US-96-type sampler are much smaller than those associated with EDI or EWI measurements made with the US D-77 bag-type sampler, especially when the results are corrected for the effects of water temperature and sampling duration. The bias in the concentration in each size class measured using the US D-77 bag-type relative to the concentration measured using the US D-96-type sampler behaves in a manner consistent with that expected on the basis of the observed differences in intake efficiency between the two samplers in conjunction with the results from the 1940s FISP laboratory experiments. In addition, the bias in the concentration in each size class measured using the US D-96‑type sampler relative to the concentration measured using the truly isokinetic rigid-container samplers is in excellent agreement with that predicted on the basis of the 1940s FISP laboratory experiments. Because suspended-sediment samplers can respond differently between laboratory and field conditions, actual-river tests such as those in this study should be conducted when models of suspended-sediment samplers are changed from one type to another during the course of long-term monitoring programs. Otherwise, potential large differences in the suspended-sediment data collected by different types of samplers would lead to large step changes in sediment loads that may be misinterpreted as real, when, in fact, they are associated with the change in suspended‑sediment sampling equipment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125208","issn":"2328-0328","usgsCitation":"Sabol, T., and Topping, D.J., 2013, Evaluation of intake efficiencies and associated sediment-concentration errors in US D-77 bag-type and US D-96-type depth-integrating suspended-sediment samplers: U.S. Geological Survey Scientific Investigations Report 2012-5208, viii, 88 p., https://doi.org/10.3133/sir20125208.","productDescription":"viii, 88 p.","numberOfPages":"100","ipdsId":"IP-027819","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":279306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125208.jpg"},{"id":279305,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5208/pdf/sir2012-5208.pdf"},{"id":279302,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5208/"}],"projection":"North America Albers Equal Area","datum":"North American Datum of 1983","country":"United States","state":"Arizona;Nevada;Utah","otherGeospatial":"Grand Canyon;Marble Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.5,35.5 ], [ -114.5,37.5 ], [ -111.0,37.5 ], [ -111.0,35.5 ], [ -114.5,35.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528f53c9e4b0660d392bed6c","contributors":{"authors":[{"text":"Sabol, Thomas A.","contributorId":67186,"corporation":false,"usgs":true,"family":"Sabol","given":"Thomas A.","affiliations":[],"preferred":false,"id":486324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":715,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":486323,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048894,"text":"ofr20131261 - 2013 - Landscape consequences of natural gas extraction in Sullivan and Wyoming Counties, Pennsylvania, 2004–2010","interactions":[],"lastModifiedDate":"2016-08-19T18:07:33","indexId":"ofr20131261","displayToPublicDate":"2013-11-21T08:30:00","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":"2013-1261","title":"Landscape consequences of natural gas extraction in Sullivan and Wyoming Counties, Pennsylvania, 2004–2010","docAbstract":"Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Sullivan County and Wyoming County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131261","usgsCitation":"Slonecker, T.E., Milheim, L., Roig-Silva, C.M., and Malizia, A.R., 2013, Landscape consequences of natural gas extraction in Sullivan and Wyoming Counties, Pennsylvania, 2004–2010: U.S. Geological Survey Open-File Report 2013-1261, v, 34 p., https://doi.org/10.3133/ofr20131261.","productDescription":"v, 34 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-042856","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":279303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131261.jpg"},{"id":279298,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1261/pdf/of2013-1261.pdf","text":"Report","size":"4.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":279297,"type":{"id":15,"text":"Index 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croig@usgs.gov","contributorId":4213,"corporation":false,"usgs":true,"family":"Roig-Silva","given":"Coral","email":"croig@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":485791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malizia, Alexander R.","contributorId":83018,"corporation":false,"usgs":true,"family":"Malizia","given":"Alexander","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":485792,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70049027,"text":"ofr20131263 - 2013 - Landscape consequences of natural gas extraction in Armstrong and Indiana Counties, Pennsylvania, 2004–2010","interactions":[],"lastModifiedDate":"2016-08-19T18:05:36","indexId":"ofr20131263","displayToPublicDate":"2013-11-21T08:29:00","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":"2013-1263","title":"Landscape consequences of natural gas extraction in Armstrong and Indiana Counties, Pennsylvania, 2004–2010","docAbstract":"Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Armstrong County and Indiana County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131263","usgsCitation":"Slonecker, T.E., Milheim, L., Roig-Silva, C.M., and Malizia, A.R., 2013, Landscape consequences of natural gas extraction in Armstrong and Indiana Counties, Pennsylvania, 2004–2010: U.S. Geological Survey Open-File Report 2013-1263, v, 35 p., https://doi.org/10.3133/ofr20131263.","productDescription":"v, 35 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049110","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":279304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131263.jpg"},{"id":279299,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1263/"},{"id":279300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1263/pdf/of2013-1263.pdf","text":"Report","size":"5.30 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528f53cae4b0660d392bed72","contributors":{"authors":[{"text":"Slonecker, Terry E. tslonecker@usgs.gov","contributorId":446,"corporation":false,"usgs":true,"family":"Slonecker","given":"Terry","email":"tslonecker@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":486043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milheim, Lesley E. lmilheim@usgs.gov","contributorId":2560,"corporation":false,"usgs":true,"family":"Milheim","given":"Lesley E.","email":"lmilheim@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":486044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roig-Silva, Coral M. croig@usgs.gov","contributorId":4213,"corporation":false,"usgs":true,"family":"Roig-Silva","given":"Coral","email":"croig@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":486045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malizia, Alexander R.","contributorId":83018,"corporation":false,"usgs":true,"family":"Malizia","given":"Alexander","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":486046,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70057382,"text":"70057382 - 2013 - Location-only and use-availability data: analysis methods converge","interactions":[],"lastModifiedDate":"2013-11-22T13:40:17","indexId":"70057382","displayToPublicDate":"2013-11-20T13:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Location-only and use-availability data: analysis methods converge","docAbstract":"This Special Feature arose from a session on a topic of the same name that took place during The Wildlife Society meeting in Kona, Hawaii, from 5 to 10 November, 2011. The purpose of that session and this Special Feature is to compare methods for predictive modelling of species geographical distributions and the modelling of habitat (resource) selection by animals. The predictive modelling of species geographical distributions and the modelling of habitat selection based on the environmental conditions at sites where animals are known to occur are essentially the same problem. Presence-only and used-available data\nboth consist of a sample of locations with known presence of a species or an individual. A separate sample of locations from a study area, with unknown presence (pseudo-absence), is also assumed to exist. The probability or relative probability of presence of a species or individual is modelled and estimated across a certain time implicitly defined by the sampling mechanism, for example, by the time period during which museum specimens or radiotelemetry data were collected. A number of modelling methods have appeared in the literature over the last couple of decades. Many of these methods were made feasible\nby the availability of geographical information systems (GIS), global positioning system (GPS) radiotelemetry and public online data access initiatives (e.g. global biodiversity information facility). The papers in this Special Feature are intended to present the state of the methodological art in their subject area, with particular attention paid to contrasting the advantages and disadvantages of alternative methods of analysis for data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Animal Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"British Ecologyical Society","doi":"10.1111/1365-2656.12145","usgsCitation":"McDonald, L., Manly, B., Huettmann, F., and Thogmartin, W., 2013, Location-only and use-availability data: analysis methods converge: Journal of Animal Ecology, v. 82, no. 6, p. 1120-1124, https://doi.org/10.1111/1365-2656.12145.","productDescription":"5 p.","startPage":"1120","endPage":"1124","ipdsId":"IP-051603","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":473439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12145","text":"Publisher Index Page"},{"id":279605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279604,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2656.12145"},{"id":279584,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/1365-2656.12145/abstract"}],"volume":"82","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-10-24","publicationStatus":"PW","scienceBaseUri":"52908b09e4b0bbdcf23f092c","contributors":{"authors":[{"text":"McDonald, Lyman","contributorId":23588,"corporation":false,"usgs":true,"family":"McDonald","given":"Lyman","affiliations":[],"preferred":false,"id":486665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manly, Bryan","contributorId":64292,"corporation":false,"usgs":true,"family":"Manly","given":"Bryan","affiliations":[],"preferred":false,"id":486667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huettmann, Falk","contributorId":15663,"corporation":false,"usgs":false,"family":"Huettmann","given":"Falk","email":"","affiliations":[],"preferred":false,"id":486664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne","contributorId":36974,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","affiliations":[],"preferred":false,"id":486666,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70055549,"text":"fs20133075 - 2013 - Water resources of Lafourche Parish, Louisiana","interactions":[],"lastModifiedDate":"2013-11-20T12:52:03","indexId":"fs20133075","displayToPublicDate":"2013-11-20T12:47:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3075","title":"Water resources of Lafourche Parish, Louisiana","docAbstract":"This fact sheet presents a brief overview of groundwater and surface-water resources in Lafourche Parish, Louisiana. Information on the availability, past and current use trends, and water quality from groundwater and surface-water sources in the parish is discussed. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133075","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and Lovelace, J.K., 2013, Water resources of Lafourche Parish, Louisiana: U.S. Geological Survey Fact Sheet 2013-3075, 4 p., https://doi.org/10.3133/fs20133075.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-050772","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":279254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133075.jpg"},{"id":279252,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3075/pdf/fs2013-3075.pdf"},{"id":279253,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3075/"}],"country":"United States","state":"Louisiana","county":"Lafourche Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.0365,28.942 ], [ -91.0365,30.222 ], [ -89.7565,30.222 ], [ -89.7565,28.942 ], [ -91.0365,28.942 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a64090e4b0a6d6958827b7","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":486141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486140,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70057791,"text":"70057791 - 2013 - Performance of quantitative vegetation sampling methods across gradients of cover in Great Basin plant communities","interactions":[],"lastModifiedDate":"2013-11-27T12:03:15","indexId":"70057791","displayToPublicDate":"2013-11-20T11:56:26","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Performance of quantitative vegetation sampling methods across gradients of cover in Great Basin plant communities","docAbstract":"Resource managers and scientists need efficient, reliable methods for quantifying vegetation to conduct basic research, evaluate land management actions, and monitor trends in habitat conditions. We examined three methods for quantifying vegetation in 1-ha plots among different plant communities in the northern Great Basin: photography-based grid-point intercept (GPI), line-point intercept (LPI), and point-quarter (PQ). We also evaluated each method for within-plot subsampling adequacy and effort requirements relative to information gain. We found that, for most functional groups, percent cover measurements collected with the use of LPI, GPI, and PQ methods were strongly correlated. These correlations were even stronger when we used data from the upper canopy only (i.e., top “hit” of pin flags) in LPI to estimate cover. PQ was best at quantifying cover of sparse plants such as shrubs in early successional habitats. As cover of a given functional group decreased within plots, the variance of the cover estimate increased substantially, which required more subsamples per plot (i.e., transect lines, quadrats) to achieve reliable precision. For GPI, we found that that six–nine quadrats per hectare were sufficient to characterize the vegetation in most of the plant communities sampled. All three methods reasonably characterized the vegetation in our plots, and each has advantages depending on characteristics of the vegetation, such as cover or heterogeneity, study goals, precision of measurements required, and efficiency needed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Rangeland Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Society for Range Management","doi":"10.2111/REM-D-13-00063.1","usgsCitation":"Pilliod, D., and Arkle, R., 2013, Performance of quantitative vegetation sampling methods across gradients of cover in Great Basin plant communities: Rangeland Ecology and Management, v. 66, no. 6, p. 634-647, https://doi.org/10.2111/REM-D-13-00063.1.","productDescription":"14 p.","startPage":"634","endPage":"647","ipdsId":"IP-045275","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473440,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/642750","text":"External Repository"},{"id":279868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279866,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2111/REM-D-13-00063.1"},{"id":279867,"type":{"id":15,"text":"Index Page"},"url":"https://www.bioone.org/doi/full/10.2111/REM-D-13-00063.1"}],"country":"United States","state":"Idaho;Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.61,41.99 ], [ -124.61,49.0 ], [ -111.04,49.0 ], [ -111.04,41.99 ], [ -124.61,41.99 ] ] ] } } ] }","volume":"66","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52972290e4b08e44bf670c47","contributors":{"authors":[{"text":"Pilliod, David S.","contributorId":101760,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[],"preferred":false,"id":486875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arkle, Robert S.","contributorId":55679,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert S.","affiliations":[],"preferred":false,"id":486874,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70055658,"text":"ofr20131172 - 2013 - Borehole-explosion and air-gun data acquired in the 2011 Salton Seismic Imaging Project (SSIP), southern California: description of the survey","interactions":[],"lastModifiedDate":"2013-11-20T11:16:29","indexId":"ofr20131172","displayToPublicDate":"2013-11-20T10:53:00","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":"2013-1172","title":"Borehole-explosion and air-gun data acquired in the 2011 Salton Seismic Imaging Project (SSIP), southern California: description of the survey","docAbstract":"The Imperial and Coachella Valleys are being formed by active plate-tectonic processes. From the Imperial Valley southward into the Gulf of California, plate motions are rifting the continent apart. In the Coachella Valley, the plates are sliding past one another along the San Andreas and related faults (fig. 1). These processes build the stunning landscapes of the region, but also produce damaging earthquakes.
\nRupture of the southern section of the San Andreas Fault (SAF), from the Coachella Valley to the Mojave Desert, is believed to be the greatest natural hazard that California will face in the near future. With an estimated magnitude between 7.2 and 8.1, such an event would result in violent shaking, loss of life, and disruption of infrastructure (freeways, aqueducts, power, petroleum, and communication lines) that might bring much of southern California to a standstill. As part of the nation’s efforts to avert a catastrophe of this magnitude, a number of projects have been undertaken to more fully understand and mitigate the effects of such an event. The Salton Seismic Imaging Project (SSIP), funded jointly by the National Science Foundation (NSF) and the U.S. Geological Survey (USGS), seeks to understand, through seismic imaging, the structure of the Earth surrounding the SAF, including the sedimentary basins on which cities are built.
\nThe principal investigators (PIs) of this collaborative project represent the USGS, Virginia Polytechnic Institute and State University (Virginia Tech), California Institute of Technology (Caltech), Scripps Institution of Oceanography (Scripps), University of Nevada, Reno (UNR), and Stanford University.
\nSSIP will create images of underground structure and sediments in the Imperial and Coachella Valleys and adjacent mountain ranges to investigate the earthquake hazards posed to cities in this area. Importantly, the images will help determine the underground geometry of the SAF, how deep the sediments are, and how fast earthquake energy can travel through the sediments. All of these factors determine how hard the earth will shake during a major earthquake. If we can improve on our understanding of how and where earthquakes will occur, and how strong their resultant shaking will be, then buildings can be designed or retrofitted accordingly in order to resist damage and collapse, and emergency plans can be adequately prepared. In addition, SSIP will investigate the processes of rifting and magmatism in the Salton Trough in order to better understand this important plate-boundary region. The Salton Trough is a unique rift in that subsidence is accompanied by huge influxes of infilling sediment from the Colorado River. Volcanism that accompanies the subsidence here is muted by these influxes of sediment. The Salton Trough, in the central part of the Imperial Valley, is apparently made up of entirely new crust: young sediment in the upper crust and basaltic intrusive rocks in the mid-to-lower crust (Fuis and others, 1984).
\nSimilar to the ultrasound and computed tomography (CT) scans performed by the medical industry, seismic imaging is a collection of techniques that enable scientists to obtain a picture of what is underground. The petroleum industry routinely uses these techniques to search for oil and gas at relatively shallow depths; however, the scope of this project demanded that we image as much as 30 km into the Earth’s crust. This project generated and recorded seismic waves, similar to sound waves, which move downward into the Earth and are bent (refracted) or echoed (reflected) back to the surface.
\nSSIP acquired data in a series of intersecting lines that cover key areas of the Salton Trough. The sources of sound waves were detonations (shots) in deep boreholes, designed to create energy equivalent to magnitude 1–2 earthquakes. The study region routinely experiences earthquakes of these magnitudes, but earthquakes are not located in such a way as to permit us to create the detailed images we need for earthquake hazard assessment. Air gun bursts, generated in the Salton Sea along extensions of our onshore seismic lines, also were utilized as sound-wave sources. Temporary deployments of portable land seismometers, as well as ocean-bottom seismometers (OBSs) on the floor of the Salton Sea, recorded the energy from the land shots and air gun bursts.
\nSSIP is similar to the Los Angeles Regional Seismic Experiments of 1994 and 1999 (LARSE I and II, respectively; Murphy and others, 1996; Fuis and others, 2001). The LARSE surveys demonstrated that the USGS and collaborators can safely and effectively conduct seismic imaging surveys in urban and nonurban areas, on lands owned and/or managed by many different types of agencies and entities. Information was produced that could not have been obtained any other way, and this information was key to changing the leading ideas about earthquake hazards at that time in the Los Angeles region. These surveys produced no significant environmental impact or damage to structures, and they did not trigger earthquakes.
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a6407be4b0a6d6958826e8","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":486101,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70055716,"text":"sir20135195 - 2013 - Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2010-12","interactions":[],"lastModifiedDate":"2013-11-18T16:26:52","indexId":"sir20135195","displayToPublicDate":"2013-11-18T16:20:00","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":"2013-5195","title":"Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2010-12","docAbstract":"From 1953 to 1988, approximately 0.941 curies of iodine-129 (129I) were contained in wastewater generated at the Idaho National Laboratory (INL) with almost all of this wastewater discharged at or near the Idaho Nuclear Technology and Engineering Center (INTEC). Most of the wastewater containing 129I was discharged directly into the eastern Snake River Plain (ESRP) aquifer through a deep disposal well until 1984; lesser quantities also were discharged into unlined infiltration ponds or leaked from distribution systems below the INTEC.\n\nDuring 2010–12, the U.S. Geological Survey in cooperation with the U.S. Department of Energy collected groundwater samples for 129I from 62 wells in the ESRP aquifer to track concentration trends and changes for the carcinogenic radionuclide that has a 15.7 million-year half-life. Concentrations of 129I in the aquifer ranged from 0.0000013±0.0000005 to 1.02±0.04 picocuries per liter (pCi/L), and generally decreased in wells near the INTEC, relative to previous sampling events. The average concentration of 129I in groundwater from 15 wells sampled during four different sample periods decreased from 1.15 pCi/L in 1990–91 to 0.173 pCi/L in 2011–12. All but two wells within a 3-mile radius of the INTEC showed decreases in concentration, and all but one sample had concentrations less than the U.S. Environmental Protection Agency maximum contaminant level of 1 pCi/L. These decreases are attributed to the discontinuation of disposal of 129I in wastewater and to dilution and dispersion in the aquifer. The decreases in 129I concentrations, in areas around INTEC where concentrations increased between 2003 and 2007, were attributed to less recharge near INTEC either from less flow in the Big Lost River or from less local snowmelt and anthropogenic sources.\n\nAlthough wells near INTEC sampled in 2011–12 showed decreases in 129I concentrations compared with previously collected data, some wells south and east of the Central Facilities Area, near the site boundary, and south of the INL showed small increases. These slight increases are attributed to variable discharge rates of wastewater that eventually moved to these well locations as a pulse of water from a particular disposal period.\n\nWells sampled for the first time around the Naval Reactors Facility had 129I concentrations slightly greater than background concentrations in the ESRP aquifer. These concentrations are attributed to possible leakage from landfills at the Naval Reactors Facility or seepage from air emission deposits from INTEC, or both.\n\nIn 2012, the U.S. Geological Survey collected discrete groundwater samples from 25 zones in 11 wells equipped with multilevel monitoring systems to help define the vertical distribution of 129I in the aquifer. Concentrations ranged from 0.000006±0.000004 to 0.082±0.003 pCi/L. Two new wells completed in 2012 showed variability of up to one order of magnitude of concentrations of 129I among various zones. Two other wells showed similar concentrations of 129I in all three zones sampled. Concentrations were well less than the maximum contaminant level in all zones.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135195","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Bartholomay, R.C., 2013, Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2010-12: U.S. Geological Survey Scientific Investigations Report 2013-5195, vi, 22 p., https://doi.org/10.3133/sir20135195.","productDescription":"vi, 22 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044719","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":279154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135195.jpg"},{"id":279153,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5195/pdf/sir20135195.pdf"},{"id":279152,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5195/"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.4556,42.0085 ], [ -114.4556,44.4397 ], [ -111.6129,44.4397 ], [ -111.6129,42.0085 ], [ -114.4556,42.0085 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528b3709e4b031f8c843946e","contributors":{"authors":[{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486232,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70056175,"text":"70056175 - 2013 - Paleomagnetic contributions to the Klamath Mountains terrane puzzle-a new piece from the Ironside Mountain batholith, northern California","interactions":[],"lastModifiedDate":"2023-05-26T16:13:12.725475","indexId":"70056175","displayToPublicDate":"2013-11-18T15:37:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"Paleomagnetic contributions to the Klamath Mountains terrane puzzle-a new piece from the Ironside Mountain batholith, northern California","docAbstract":"We obtained paleomagnetic samples from six sites within the Middle Jurassic Ironside Mountain batholith (~170 Ma), which constitutes the structurally lowest part of the Western Hayfork terrane, in the Klamath Mountains province of northern California and southern Oregon. Structural attitudes measured in the coeval Hayfork Bally Meta-andesite were used to correct paleomagnetic data from the batholith. Comparing the corrected paleomagnetic pole with a 170-Ma reference pole for North America indicates 73.5° ± 10.6° of clockwise rotation relative to the craton. Nearly one-half of this rotation may have occurred before the terrane accreted to the composite Klamath province at ~168 Ma. No latitudinal displacement of the batholith was detected.","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2013.09.007","usgsCitation":"Mankinen, E.A., Gromme, C.S., and Irwin, W.P., 2013, Paleomagnetic contributions to the Klamath Mountains terrane puzzle-a new piece from the Ironside Mountain batholith, northern California: Tectonophysics, v. 608, p. 401-407, https://doi.org/10.1016/j.tecto.2013.09.007.","productDescription":"6 p.","startPage":"401","endPage":"407","ipdsId":"IP-050598","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":279149,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.0,40.5 ], [ -124.0,43.0 ], [ -122.5,43.0 ], [ -122.5,40.5 ], [ -124.0,40.5 ] ] ] } } ] }","volume":"608","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528b370ae4b031f8c8439474","contributors":{"authors":[{"text":"Mankinen, Edward A. 0000-0001-7496-2681 emank@usgs.gov","orcid":"https://orcid.org/0000-0001-7496-2681","contributorId":1054,"corporation":false,"usgs":true,"family":"Mankinen","given":"Edward","email":"emank@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":486397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gromme, C. Sherman","contributorId":22236,"corporation":false,"usgs":true,"family":"Gromme","given":"C.","email":"","middleInitial":"Sherman","affiliations":[],"preferred":false,"id":486398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, W. Porter","contributorId":84262,"corporation":false,"usgs":true,"family":"Irwin","given":"W.","email":"","middleInitial":"Porter","affiliations":[],"preferred":false,"id":486399,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048946,"text":"sim3270 - 2013 - Water-table and Potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers beneath Long Island, New York, April-May 2010","interactions":[],"lastModifiedDate":"2013-11-18T15:36:06","indexId":"sim3270","displayToPublicDate":"2013-11-18T14:51:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3270","title":"Water-table and Potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers beneath Long Island, New York, April-May 2010","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with State and local agencies, systematically collects groundwater data at varying measurement frequencies to monitor the hydrologic conditions on Long Island, New York. Each year during April and May, the USGS conducts a synoptic survey of water levels to define the spatial distribution of the water table and potentiometric surfaces within the three main water-bearing units underlying Long Island—the upper glacial, Magothy, and Lloyd aquifers (Smolensky and others, 1989)—and the hydraulically connected Jameco (Soren, 1971) and North Shore aquifers (Stumm, 2001). These data and the maps constructed from them are commonly used in studies of Long Island’s hydrology and are used by water managers and suppliers for aquifer management and planning purposes. Water-level measurements made in 503 monitoring wells, a network of observation and supply wells, and 16 streamgage locations across Long Island during April–May 2010 were used to prepare the maps in this report. Measurements were made by the wetted-tape method to the nearest hundredth of a foot. Water-table and potentiometric-surface altitudes in these aquifers were contoured by using these measurements. The water-table contours were interpreted by using water-level data collected from 16 streamgages, 349 observation wells, and 1 supply well screened in the upper glacial aquifer and (or) shallow Magothy aquifer; the Magothy aquifer’s potentiometric-surface contours were interpreted from measurements at 67 observation wells and 27 supply wells screened in the middle to deep Magothy aquifer and (or) the contiguous and hydraulically connected Jameco aquifer. The Lloyd aquifer’s potentiometric-surface contours were interpreted from measurements at 55 observation wells and 4 supply wells screened in the Lloyd aquifer or the contiguous and hydraulically connected North Shore aquifer. Many of the supply wells are in continuous operation and, therefore, were turned off for a minimum of 24 hours before measurements were made so that the water levels in the wells could recover to the level of the potentiometric head in the surrounding aquifer. Full recovery time at some of these supply wells can exceed 24 hours; therefore, water levels measured at these wells are assumed to be less accurate than those measured at observation wells, which are not pumped (Busciolano, 2002). In this report, all water-level altitudes are referenced to the National Geodetic Vertical Datum of 1929 (NGVD 29). Hydrographs are included on these maps for selected wells that are instrumented with recording equipment. These hydrographs are representative of the 2010 water year1 to show the changes that have occurred throughout that period. The synoptic survey water level measured at the well is included on each hydrograph.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3270","collaboration":"Prepared in cooperation with the Nassau County Department of Public Works, New York City Department of Environmental Protection, New York State Department of Environmental Conservation, Suffolk County Department of Health, Services Suffolk County Water Authority, Town of North Hempstead, Town of Shelter Island, and the U.S. Environmental Protection Agency","usgsCitation":"Monti, J., Como, M.D., and Busciolano, R., 2013, Water-table and Potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers beneath Long Island, New York, April-May 2010: U.S. Geological Survey Scientific Investigations Map 3270, Map text content: 5 p.; 5 Sheets: 72 inches x 34 inches, https://doi.org/10.3133/sim3270.","productDescription":"Map text content: 5 p.; 5 Sheets: 72 inches x 34 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-034294","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":438781,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FRG2Z3","text":"USGS data release","linkHelpText":"Geospatial Dataset of Water-Table and Potentiometric-Surface Altitudes in the Upper Glacial, Magothy, and Lloyd Aquifers of Long Island, New York, April-May 2010"},{"id":279144,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_s3p.pdf"},{"id":279145,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_s4p.pdf"},{"id":279146,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_monti_Map_text_content.pdf"},{"id":279147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3270.PNG"},{"id":279142,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_s1p.pdf"},{"id":279143,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_s2p.pdf"},{"id":279140,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3270/"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.0419,40.5418 ], [ -74.0419,41.1408 ], [ -71.8563,41.1408 ], [ -71.8563,40.5418 ], [ -74.0419,40.5418 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528b370be4b031f8c8439485","contributors":{"authors":[{"text":"Monti, Jack Jr. jmonti@usgs.gov","contributorId":1185,"corporation":false,"usgs":true,"family":"Monti","given":"Jack","suffix":"Jr.","email":"jmonti@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Como, Michael D. 0000-0002-7911-5390 mcomo@usgs.gov","orcid":"https://orcid.org/0000-0002-7911-5390","contributorId":4651,"corporation":false,"usgs":true,"family":"Como","given":"Michael","email":"mcomo@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Busciolano, Ronald 0000-0002-9257-8453 rjbuscio@usgs.gov","orcid":"https://orcid.org/0000-0002-9257-8453","contributorId":1059,"corporation":false,"usgs":true,"family":"Busciolano","given":"Ronald","email":"rjbuscio@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485828,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70055736,"text":"ofr20131273 - 2013 - Post-fire debris-flow hazard assessment of the area burned by the 2013 Beaver Creek Fire near Hailey, central Idaho","interactions":[],"lastModifiedDate":"2013-11-18T14:35:05","indexId":"ofr20131273","displayToPublicDate":"2013-11-18T11:57:00","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":"2013-1273","title":"Post-fire debris-flow hazard assessment of the area burned by the 2013 Beaver Creek Fire near Hailey, central Idaho","docAbstract":"A preliminary hazard assessment was developed for debris-flow hazards in the 465 square-kilometer (115,000 acres) area burned by the 2013 Beaver Creek fire near Hailey in central Idaho. The burn area covers all or part of six watersheds and selected basins draining to the Big Wood River and is at risk of substantial post-fire erosion, such as that caused by debris flows. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the Intermountain Region in Western United States were used to estimate the probability of debris-flow occurrence, potential volume of debris flows, and the combined debris-flow hazard ranking along the drainage network within the burn area and to estimate the same for analyzed drainage basins within the burn area. Input data for the empirical models included topographic parameters, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall, referred to as a 2-year storm (13 mm); (2) 10-year-recurrence, 1-hour-duration rainfall, referred to as a 10-year storm (19 mm); and (3) 25-year-recurrence, 1-hour-duration rainfall, referred to as a 25-year storm (22 mm). Estimated debris-flow probabilities for drainage basins upstream of 130 selected basin outlets ranged from less than 1 to 78 percent with the probabilities increasing with each increase in storm magnitude. Probabilities were high in three of the six watersheds. For the 25-year storm, probabilities were greater than 60 percent for 11 basin outlets and ranged from 50 to 60 percent for an additional 12 basin outlets. Probability estimates for stream segments within the drainage network can vary within a basin. For the 25-year storm, probabilities for stream segments within 33 basins were higher than the basin outlet, emphasizing the importance of evaluating the drainage network as well as basin outlets. Estimated debris-flow volumes for the three modeled storms range from a minimal debris flow volume of 10 cubic meters [m3]) to greater than 100,000 m3. Estimated debris-flow volumes increased with basin size and distance downstream. For the 25-year storm, estimated debris-flow volumes were greater than 100,000 m3 for 4 basins and between 50,000 and 100,000 m3 for 10 basins. The debris-flow hazard rankings did not result in the highest hazard ranking of 5, indicating that none of the basins had a high probability of debris-flow occurrence and a high debris-flow volume estimate. The hazard ranking was 4 for one basin using the 10-year-recurrence storm model and for three basins using the 25-year-recurrence storm model. The maps presented herein may be used to prioritize areas where post-wildfire remediation efforts should take place within the 2- to 3-year period of increased erosional vulnerability.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131273","collaboration":"Prepared in cooperation with Blaine County, Idaho","usgsCitation":"Skinner, K.D., 2013, Post-fire debris-flow hazard assessment of the area burned by the 2013 Beaver Creek Fire near Hailey, central Idaho: U.S. Geological Survey Open-File Report 2013-1273, Report: iv, 12 p.; Table: XLSX file; 9 plates: 24 inches x 31 inches, https://doi.org/10.3133/ofr20131273.","productDescription":"Report: iv, 12 p.; Table: XLSX file; 9 plates: 24 inches x 31 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052301","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":279139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131273.PNG"},{"id":279121,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1273/"},{"id":279129,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1273/downloads/ofr2013-1273_table1.xlsx"},{"id":279130,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate1.pdf"},{"id":279131,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate3.pdf"},{"id":279128,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273.pdf"},{"id":279132,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate2.pdf"},{"id":279133,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate4.pdf"},{"id":279134,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate5.pdf"},{"id":279135,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate6.pdf"},{"id":279136,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate7.pdf"},{"id":279137,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate8.pdf"},{"id":279138,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate9.pdf"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.67495,43.499756 ], [ -114.67495,43.699651 ], [ -114.311371,43.699651 ], [ -114.311371,43.499756 ], [ -114.67495,43.499756 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528b370ae4b031f8c843947a","contributors":{"authors":[{"text":"Skinner, Kenneth D. 0000-0003-1774-6565 kskinner@usgs.gov","orcid":"https://orcid.org/0000-0003-1774-6565","contributorId":1836,"corporation":false,"usgs":true,"family":"Skinner","given":"Kenneth","email":"kskinner@usgs.gov","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486256,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047103,"text":"70047103 - 2013 - Temporal changes and sexual differences in spatial distribution of Burbot in Lake Erie","interactions":[],"lastModifiedDate":"2013-11-15T10:18:01","indexId":"70047103","displayToPublicDate":"2013-11-15T11:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Temporal changes and sexual differences in spatial distribution of Burbot in Lake Erie","docAbstract":"We used GIS mapping techniques to examine capture data for Burbot Lota lota from annual gill-net surveys in Canadian waters of Lake Erie during late August and September 1994–2011. Adult males were captured over a larger area (3–17% for ≥20% maximum yearly catch [MYC]) than adult females. More males than females were caught in the gill nets in 14 of the 15 study years. Collectively, these results support a hypothesis of greater activity by adult males during summer, when Burbot are actively feeding. The area of capture contracted by more than 60% (for ≥20% MYC) for both sexes during the time period, which is consistent with the documented decrease of the Burbot population in the lake. The sex ratio (females: males) varied over the time series but declined steadily from 0.97 in 2001 to 0.59 in 2011. The overlap in the capture areas of adult males and females was scale dependent. The depth distribution at which adult Burbot were caught did not change over the time series, and there was no difference in the median depths (about 30 m) at which adult male and female Burbot were caught. The last results are consistent with the Burbot's reliance on coldwater habitats. Additional research is recommended, including telemetry to describe daily and seasonal movements and assessment of gender bias in active and passive capture gear.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2013.795191","usgsCitation":"Stapanian, M.A., Witzel, L.D., and Cook, A., 2013, Temporal changes and sexual differences in spatial distribution of Burbot in Lake Erie: Transactions of the American Fisheries Society, v. 142, no. 6, p. 1724-1732, https://doi.org/10.1080/00028487.2013.795191.","productDescription":"9 p.","startPage":"1724","endPage":"1732","numberOfPages":"9","ipdsId":"IP-045137","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":279105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279104,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/00028487.2013.795191"}],"country":"Canada;United States","otherGeospatial":"Lake Erie","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.6803,41.8693 ], [ -80.6803,42.9038 ], [ -78.8183,42.9038 ], [ -78.8183,41.8693 ], [ -80.6803,41.8693 ] ] ] } } ] }","volume":"142","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-11-07","publicationStatus":"PW","scienceBaseUri":"5287425ee4b03b89f6f15080","contributors":{"authors":[{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":481059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Witzel, Larry D.","contributorId":68642,"corporation":false,"usgs":true,"family":"Witzel","given":"Larry","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":481061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Andy","contributorId":48473,"corporation":false,"usgs":true,"family":"Cook","given":"Andy","email":"","affiliations":[],"preferred":false,"id":481060,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70055619,"text":"sir20135155 - 2013 - Equations for estimating bankfull channel geometry and discharge for streams in Massachusetts","interactions":[],"lastModifiedDate":"2013-11-14T15:49:49","indexId":"sir20135155","displayToPublicDate":"2013-11-14T15:45:00","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":"2013-5155","title":"Equations for estimating bankfull channel geometry and discharge for streams in Massachusetts","docAbstract":"Regression equations were developed for estimating bankfull geometry—width, mean depth, cross-sectional area—and discharge for streams in Massachusetts. The equations provide water-resource and conservation managers with methods for estimating bankfull characteristics at specific stream sites in Massachusetts. This information can be used for the adminstration of the Commonwealth of Massachusetts Rivers Protection Act of 1996, which establishes a protected riverfront area extending from the mean annual high-water line corresponding to the elevation of bankfull discharge along each side of a perennial stream. Additionally, information on bankfull channel geometry and discharge are important to Federal, State, and local government agencies and private organizations involved in stream assessment and restoration projects.\n\nRegression equations are based on data from stream surveys at 33 sites (32 streamgages and 1 crest-stage gage operated by the U.S. Geological Survey) in and near Massachusetts. Drainage areas of the 33 sites ranged from 0.60 to 329 square miles (mi2). At 27 of the 33 sites, field data were collected and analyses were done to determine bankfull channel geometry and discharge as part of the present study. For 6 of the 33 sites, data on bankfull channel geometry and discharge were compiled from other studies done by the U.S. Geological Survey, Natural Resources Conservation Service of the U.S. Department of Agriculture, and the Vermont Department of Environmental Conservation. Similar techniques were used for field data collection and analysis for bankfull channel geometry and discharge at all 33 sites. Recurrence intervals of the bankfull discharge, which represent the frequency with which a stream fills its channel, averaged 1.53 years (median value 1.34 years) at the 33 sites. Simple regression equations were developed for bankfull width, mean depth, cross-sectional area, and discharge using drainage area, which is the most significant explanatory variable in estimating these bankfull characteristics. The use of drainage area as an explanatory variable is also the most commonly published method for estimating these bankfull characteristics. Regional curves (graphic plots) of bankfull channel geometry and discharge by drainage area are presented. The regional curves are based on the simple regression equations and can be used to estimate bankfull characteristics from drainage area. Multiple regression analysis, which includes basin characteristics in addition to drainage area, also was used to develop equations. Variability in bankfull width, mean depth, cross-sectional area, and discharge was more fully explained by the multiple regression equations that include mean-basin slope and drainage area than was explained by equations based on drainage area alone. The Massachusetts regional curves and equations developed in this study are similar, in terms of values of slopes and intercepts, to those developed for other parts of the northeastern United States.\n\nLimitations associated with site selection and development of the equations resulted in some constraints for the application of equations and regional curves presented in this report. The curves and equations are applicable to stream sites that have (1) less than about 25 percent of their drainage basin area occupied by urban land use (commercial, industrial, transportation, and high-density residential), (2) little to no streamflow regulation, especially from flood-control structures, (3) drainage basin areas greater than 0.60 mi2 and less than 329 mi2, and (4) a mean basin slope greater than 2.2 percent and less than 23.9 percent. The equations may not be applicable where streams flow through extensive wetlands. The equations also may not apply in areas of Cape Cod and the Islands and the area of southeastern Massachusetts close to Cape Cod with extensive areas of coarse-grained glacial deposits where none of the study sites are located. Regardless of the setting, the regression equations are not intended for use as the sole method of estimating bankfull characteristics; however, they may supplement field identification of the bankfull channel when used in conjunction with field verified bankfull indicators, flood-frequency analysis, or other supporting evidence.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135155","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection Bureau of Resource Protection Wetlands and Waterways Program and Massachusetts Environmental Trust","usgsCitation":"Bent, G.C., and Waite, A.M., 2013, Equations for estimating bankfull channel geometry and discharge for streams in Massachusetts: U.S. Geological Survey Scientific Investigations Report 2013-5155, vii, 61 p., https://doi.org/10.3133/sir20135155.","productDescription":"vii, 61 p.","numberOfPages":"74","onlineOnly":"N","ipdsId":"IP-009440","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":279091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135155.jpg"},{"id":279090,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5155/pdf/sir2013-5155.pdf"},{"id":279087,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5155/"}],"country":"United States","state":"Massachusetts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.5081,41.2491 ], [ -73.5081,42.8868 ], [ -69.928,42.8868 ], [ -69.928,41.2491 ], [ -73.5081,41.2491 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52860762e4b00926c218653e","contributors":{"authors":[{"text":"Bent, Gardner C. 0000-0002-5085-3146 gbent@usgs.gov","orcid":"https://orcid.org/0000-0002-5085-3146","contributorId":1864,"corporation":false,"usgs":true,"family":"Bent","given":"Gardner","email":"gbent@usgs.gov","middleInitial":"C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waite, Andrew M. awaite@usgs.gov","contributorId":2215,"corporation":false,"usgs":true,"family":"Waite","given":"Andrew","email":"awaite@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":486154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048994,"text":"sir20135133 - 2013 - Hydrogeology and hydrologic conditions of the Northern Atlantic Coastal Plain aquifer System from Long Island, New York, to North Carolina","interactions":[],"lastModifiedDate":"2017-01-17T20:47:58","indexId":"sir20135133","displayToPublicDate":"2013-11-14T15:33:00","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":"2013-5133","title":"Hydrogeology and hydrologic conditions of the Northern Atlantic Coastal Plain aquifer System from Long Island, New York, to North Carolina","docAbstract":"The seaward-dipping sedimentary wedge that underlies the Northern Atlantic Coastal Plain forms a complex groundwater system. This major source of water provides for public and domestic supply and serves as a vital source of freshwater for industrial and agricultural uses throughout the region. Population increases and land-use and climate changes, however, have led to competing demands for water. The regional response of the aquifer system to these stresses poses regional challenges for water-resources management at the State level because hydrologic effects often extend beyond State boundaries. In response to these challenges, the U.S. Geological Survey Groundwater Resources Program began a regional assessment of the groundwater availability of the Northern Atlantic Coastal Plain aquifer system in 2010.
\nThe initial phase of this investigation included a refinement of the hydrogeologic framework and an updated hydrologic budget of this aquifer system from the last regional aquifer system assessment completed by the U.S. Geological Survey in the 1980s. Refinements to the hydrogeologic framework include revision of the regional aquifer names to be more consistent with local names in New York, New Jersey, Delaware, Maryland, and Virginia, the primary States included in the study area. Other revisions to the framework include characterization of the aquifers of the regional Potomac aquifer system. The regional Potomac aquifer system is subdivided for this report into two regional aquifers. These aquifers include the single Potomac aquifer in Virginia and two aquifers in Maryland, Delaware, and New Jersey, where the Potomac aquifer system thickens within the Salisbury Embayment. The two regional aquifers making up the Potomac aquifer system include the Potomac-Patapsco aquifer and the underlying Potomac-Patuxent aquifer.
\nThe Potomac-Patuxent aquifer includes the Lower Potomac-Raritan-Magothy aquifer in southern New Jersey and the Patuxent aquifers in Delaware and Maryland. In northern New Jersey and on Long Island, New York, the PotomacPatuxent aquifer is absent, but the Late Cretaceous fluvialdeltaic aquifer that is laterally equivalent with the upper part of the Potomac Formation now is considered part of the regional Potomac-Patapsco aquifer. This aquifer includes the Middle Potomac-Raritan-Magothy aquifer in New Jersey and the Lloyd aquifer on Long Island.
\nThe name “Upper Potomac aquifer” has been removed as part of this regional framework revision. The local aquifer previously considered part of the Upper Potomac aquifer now are part of the regional Magothy aquifer. These units include the Upper Potomac-Raritan-Magothy aquifer in New Jersey, the Magothy aquifers on Long Island, Delaware, and Maryland, and the Virginia Beach aquifer in Virginia.
\nUpdates to the regional hydrologic budget include revised estimates of aquifer recharge, water use and streamflow data. Inflow to the aquifer system of about 20,000 million gallons per day (Mgal/d) includes 19,600 Mgal/d from recharge from precipitation, 200 Mgal/d of recharge from wastewater via onsite domestic septic systems, and 200 Mgal/d from the release of water from aquifer storage. Outflow from the aquifer system includes groundwater discharge to streams (11,900 Mgal/d), groundwater withdrawals (1,500 Mgal/d), and groundwater discharge to coastal waters (6,600 Mgal/d). A numerical modeling analysis is required to improve this hydrologic budget calculation and to forecast future changes in water levels and aquifer storage caused by groundwater withdrawals, land-use changes, and the effects of climate variability and change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135133","collaboration":"Groundwater Resources Program","usgsCitation":"Masterson, J.P., Pope, J.P., Monti, Jack, Jr., Nardi, M.R., Finkelstein, J.S., and McCoy, K.J., 2015, Hydrogeology and hydrologic conditions of the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina (ver. 1.1, September 2015): U.S. Geological Survey Scientific Investigations Report 2013–5133, 76 p., https://dx.doi.org/10.3133/sir20135133.","productDescription":"viii, 76 p.","numberOfPages":"88","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044313","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":308391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":279088,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5133/pdf/sir20135133.pdf"},{"id":308378,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5133/"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, North Carolina, Virginia","otherGeospatial":"Northern Atlantic Coastal Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -78.0,34.0 ], [ -78.0,42.0 ], [ -71.0,42.0 ], [ -71.0,34.0 ], [ -78.0,34.0 ] ] ] } } ] }","edition":"Version 1.0 November 14, 2013; Version 1.1 September 22, 2015","contact":"Office Chief
U.S. Geological Survey
New England Water Science Center
Massachusetts-Rhode Island Office
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://ma.water.usgs.gov
Abstract
\nIntroduction
\nHydrogeology
\nHydrologic Conditions
\nSummary and Conclusions
\nReferences Cited
\nThe Gap Analysis Project (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP is managed by the U.S. Geological Survey, Department of the Interior. GAP supports a wide range of national, State, and local agencies as well as nongovernmental organizations and businesses with scientific tools and data. GAP uses a collaborative approach to do research, analysis, and data development, resulting in a history of cooperation with more than 500 agencies and organizations nationally.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70055528","collaboration":"Gap Analysis Project","usgsCitation":"Gergely, K.J., and McKerrow, A., 2013, Tools and data for meeting America's conservation challenges: General Information Product 151, 2 p., https://doi.org/10.3133/70055528.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-035164","costCenters":[{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":279092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":279023,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/151/"},{"id":279070,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/151/pdf/gip151.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.616667,13.233333 ], [ 144.616667,71.833333 ], [ -64.566667,71.833333 ], [ -64.566667,13.233333 ], [ 144.616667,13.233333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52860787e4b00926c2186550","contributors":{"authors":[{"text":"Gergely, Kevin J. 0000-0002-4379-2189 gergely@usgs.gov","orcid":"https://orcid.org/0000-0002-4379-2189","contributorId":2706,"corporation":false,"usgs":true,"family":"Gergely","given":"Kevin","email":"gergely@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":486130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":4542,"corporation":false,"usgs":false,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":486131,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70049018,"text":"ofr20131250 - 2013 - MODIS phenology image service ArcMap toolbox","interactions":[],"lastModifiedDate":"2013-11-13T15:02:31","indexId":"ofr20131250","displayToPublicDate":"2013-11-13T14:59:00","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":"2013-1250","title":"MODIS phenology image service ArcMap toolbox","docAbstract":"Seasonal change is important to consider when managing conservation areas at landscape scales. The study of such patterns throughout the year is referred to as phenology. Recurring life-cycle events that are initiated and driven by environmental factors include animal migration and plant flowering. Phenological events capture public attention, such as fall color change in deciduous forests, the first flowering in spring, and for those with allergies, the start of the pollen season. These events can affect our daily lives, provide clues to help understand and manage ecosystems, and provide evidence of how climate variability can affect the natural cycle of plants and animals. Phenological observations can be gathered at a range of scales, from plots smaller than an acre to landscapes of hundreds to thousands of acres. Linking these observations to diverse disciplines such as evolutionary biology or climate sciences can help further research in species and ecosystem responses to climate change scenarios at appropriate scales.
\nA cooperative study between the National Park Service (NPS), the U.S. Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA) has been exploring how satellite information can be used to summarize phenological patterns observed at the park or landscape scale and how those summaries can be presented to both park managers and visitors. This study specifically addressed seasonal changes in plants, including the onset of growth, photosynthesis in the spring, and the senescence of deciduous vegetation in the fall. The primary objective of the work is to demonstrate that seasonality even in protected areas changes considerably across years. A major challenge is to decouple natural variability from possible trends—directional change that can lead to a permanent and radically different ecosystem state. Trends can be either a gradual degradation of the landscape (often from external influences) or steady improvement (by implementing long-term conservation plans). In either case, it is important to first grasp the magnitude of natural variation so that it is not confused with actual trends.
\nThis work used existing and freely available remote sensing data, specifically the NASA-funded 250-meter (m) spatial resolution land-surface phenology product for North America. This product is calculated from an annual record of vegetation health observed by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The land-surface phenology product is, in essence, a method to summarize all the observations throughout a year into a few key, ecologically relevant “metrics”.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131250","collaboration":"Prepared in cooperation with the National Park Service and the Great Northern Landscape Conservation Cooperative","usgsCitation":"Talbert, C., Kern, T., Morisette, J., Brown, D., and James, K., 2013, MODIS phenology image service ArcMap toolbox: U.S. Geological Survey Open-File Report 2013-1250, iii, 6 p., https://doi.org/10.3133/ofr20131250.","productDescription":"iii, 6 p.","numberOfPages":"9","onlineOnly":"Y","ipdsId":"IP-045950","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":279059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131250.jpg"},{"id":279058,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1250/pdf/of2013-1250.pdf"},{"id":279057,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1250/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52849f61e4b063f258e57461","contributors":{"authors":[{"text":"Talbert, Colin talbertc@usgs.gov","contributorId":4668,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":486033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kern, Tim J. kernt@usgs.gov","contributorId":4454,"corporation":false,"usgs":true,"family":"Kern","given":"Tim J.","email":"kernt@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":486032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morisette, Jeff","contributorId":20640,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeff","email":"","affiliations":[],"preferred":false,"id":486034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Don","contributorId":73490,"corporation":false,"usgs":true,"family":"Brown","given":"Don","email":"","affiliations":[],"preferred":false,"id":486035,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"James, Kevin","contributorId":106787,"corporation":false,"usgs":true,"family":"James","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":486036,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}