Understanding storm-induced coastal change and forecasting these changes require knowledge of the physical processes associated with a storm and the geomorphology of the impacted coastline. The primary physical processes of interest are the wind field, storm surge, currents, and wave field. Not only does wind cause direct damage to structures along the coast, but it is ultimately responsible for much of the energy that is transferred to the ocean and expressed as storm surge, mean currents, and surface waves. Waves and currents are the processes most responsible for moving sediments in the coastal zone during extreme storm events. Storm surge, which is the rise in water level due to the wind, barometric pressure, and other factors, allows both waves and currents to attack parts of the coast not normally exposed to these processes.
Coastal geomorphology, including shapes of the shoreline, beaches, and dunes, is also a significant aspect of the coastal change observed during extreme storms. Relevant geomorphic variables include sand dune elevation, beach width, shoreline position, sediment grain size, and foreshore beach slope. These variables, in addition to hydrodynamic processes, can be used to predict coastal vulnerability to storms.
The U.S. Geological Survey (USGS) National Assessment of Coastal Change Hazards project (http://coastal.er.usgs.gov/hurricanes) strives to provide hazard information to those concerned about the Nation’s coastlines, including residents of coastal areas, government agencies responsible for coastal management, and coastal researchers. As part of the National Assessment, observations were collected to measure morphological changes associated with Hurricane Gustav, which made landfall near Cocodrie, Louisiana, on September 1, 2008. Methods of observation included oblique aerial photography, airborne topographic surveys, and ground-based topographic surveys. This report documents these data-collection efforts and presents qualitative and quantitative descriptions of hurricane-induced changes to the shoreline, beaches, dunes, and infrastructure in the region that was heavily impacted by Hurricane Gustav.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091279","usgsCitation":"Doran, K., Stockdon, H.F., Plant, N.G., Sallenger, A., Guy, K.K., and Serafin, K.A., 2009, Hurricane Gustav: Observations and analysis of coastal change: U.S. Geological Survey Open-File Report 2009-1279, vii, 28 p., https://doi.org/10.3133/ofr20091279.","productDescription":"vii, 28 p.","onlineOnly":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":13339,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1279/","linkFileType":{"id":5,"text":"html"}},{"id":403717,"rank":2,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_90304.htm","linkFileType":{"id":5,"text":"html"}},{"id":125626,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1279.jpg"}],"country":"United States","state":"Alabama, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91,\n 28.9167\n ],\n [\n -88,\n 28.9167\n ],\n [\n -88,\n 30.5\n ],\n [\n -91,\n 30.5\n ],\n [\n -91,\n 28.9167\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4affe4b07f02db697bfd","contributors":{"authors":[{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":33010,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[],"preferred":false,"id":304173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sallenger, Asbury H. Jr.","contributorId":27458,"corporation":false,"usgs":true,"family":"Sallenger","given":"Asbury H.","suffix":"Jr.","affiliations":[],"preferred":false,"id":304172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":45010,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":304174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Serafin, Katherine A.","contributorId":84466,"corporation":false,"usgs":true,"family":"Serafin","given":"Katherine","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304175,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":98101,"text":"ofr20091225 - 2009 - Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory","interactions":[],"lastModifiedDate":"2022-06-09T20:25:10.852413","indexId":"ofr20091225","displayToPublicDate":"2010-01-14T00:00:00","publicationYear":"2009","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":"2009-1225","title":"Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory","docAbstract":"Oil spillage from natural sources is very common in the waters of southern California. Active oil extraction and shipping is occurring concurrently within the region and it is of great interest to resource managers to be able to distinguish between natural seepage and anthropogenic oil spillage.
The major goal of this study was to establish the geologic setting, sources, and ultimate dispersal of natural oil seeps in the offshore southern Santa Maria Basin and Santa Barbara Basins. Our surveys focused on likely areas of hydrocarbon seepage that are known to occur between Point Arguello and Ventura, California.
Our approach was to 1) document the locations and geochemically fingerprint natural seep oils or tar; 2) geochemically fingerprint coastal tar residues and potential tar sources in this region, both onshore and offshore; 3) establish chemical correlations between offshore active seeps and coastal residues thus linking seep sources to oil residues; 4) measure the rate of natural seepage of individual seeps and attempt to assess regional natural oil and gas seepage rates; and 5) interpret the petroleum system history for the natural seeps.
To document the location of sub-sea oil seeps, we first looked into previous studies within and near our survey area. We measured the concentration of methane gas in the water column in areas of reported seepage and found numerous gas plumes and measured high concentrations of methane in the water column. The result of this work showed that the seeps were widely distributed between Point Conception east to the vicinity of Coal Oil Point, and that they by in large occur within the 3-mile limit of California State waters. Subsequent cruises used sidescan and high resolution seismic to map the seafloor, from just south of Point Arguello, east to near Gaviota, California. The results of the methane survey guided the exploration of the area west of Point Conception east to Gaviota using a combination of seismic instruments. The seafloor was mapped by sidescan sonar, and numerous lines of high -resolution seismic surveys were conducted over areas of interest.
Biomarker and stable carbon isotope ratios were used to infer the age, lithology, organic matter input, and depositional environment of the source rocks for 388 samples of produced crude oil, seep oil, and tarballs mainly from coastal California. These samples were used to construct a chemometric fingerprint (multivariate statistics) decision tree to classify 288 additional samples, including tarballs of unknown origin collected from Monterey and San Mateo County beaches after a storm in early 2007. A subset of 9 of 23 active offshore platform oils and one inactive platform oil representing a few oil reservoirs from the western Santa Barbara Channel were used in this analysis, and thus this model is not comprehensive and the findings are not conclusive. The platform oils included in this study are from west to east: Irene, Hildago, Harvest, Hermosa, Heritage, Harmony, Hondo, Holly, Platform A, and Hilda (now removed).
The results identify three “tribes” of 13C-rich oil samples inferred to originate from thermally mature equivalents of the clayey-siliceous, carbonaceous marl, and lower calcareous-siliceous members of the Monterey Formation. Tribe 1 contains four oil families having geochemical traits of clay-rich marine shale source rock deposited under suboxic conditions with substantial higher-plant input. Tribe 2 contains four oil families with intermediate traits, except for abundant 28,30-bisnorhopane, indicating suboxic to anoxic marine marl source rock with hemipelagic input. Tribe 3 contains five oil families with traits of distal marine carbonate source rock deposited under anoxic conditions with pelagic but little or no higher-plant input. Tribes 1 and 2 occur mainly south of Point Conception in paleogeographic settings where deep burial of the Monterey Formation source rock favored generation from all three members or their equivalents. In this area, oil from the clayey-siliceous and carbonaceous marl members (Tribes 1 and 2) may overwhelm that from the lower calcareous-siliceous member (Tribe 3) because the latter is thinner and less oil-prone than the overlying members. Tribe 3 occurs mainly north of Point Conception, where shallow burial caused preferential generation from the underlying lower calcareous-siliceous member or another unit with similar characteristics.
It is very desirable to be able to clearly distinguish the naturally occurring seep oils from the anthropogenically derived platform oils. Within the “training set” of oils and tars (388 samples), the biomarker parameters are sometimes sufficient to allow unique discrimination of individual platform oils. More often however, platform samples and seep samples with sources geographically close to each other are too similar to each other, with respect to the biomarker parameters, to definitively differentiate them on that basis alone. In some cases other parameters can be helpful. These other parameters are related to the degree of biogeochemical degradation or weathering that the oils or tars have experienced. These components include the typical oil distribution of n-alkane hydrocarbons and isoprenoids pristane and phytane. All of the platform oils in our sample set contain these components. On the other hand, the seep oils or tars have been exposed to significant biodegradation while in the near subsurface. The majority, but not all of seep oils or tars have been biodegraded up to or beyond the loss of n-alkanes and isoprenoids. Seep oils found in the vicinity of Coal Oil Point or Arroyo Burro are apparently the least weathered and are particularly likely to retain significant n-alkanes and isoprenoids. Therefore the combination of chemometric fingerprinting and the presence or absence of n-alkanes and isoprenoids help to differentiate anthropogenic production oils versus natural seeps oils and tars. The differentiation is not always definitive because of the close chemical similarity of some samples and the variability in the biodegradation progression. This is the case near Coal Oil Point, and near Platform A (Dos Cuadros Field) where seep oils and Platform Holly and Platform A oils are genetically very similar and cannot be definitively distinguished after a period of a few days of weathering. In contrast, oils from the Point Conception platforms can be distinguished on the basis of chemometric fingerprinting alone. In the middle of this spectrum are oils from Platforms Harmony, Heritage, and Hondo, where it is expected that oil weathering would take on the order of two weeks to a month to produce tarballs similar to those seen near Point Conception. In this case there is a much greater degree of weathering needed to proceed from produced oil to the biodegraded tar characteristic of tarball stranded on the beach.
Tar deposition on beaches was monitored as part of cooperative with the County of Santa Barbara Energy Division and the U.S. Geological Survey during 2001-2003. We found tar deposition varies on a seasonal basis. In general, tarballs accumulate at a faster rate or remain longer on all beaches during the summer and fall months. The reasons for this are unclear based on our limited observations, however we speculate that factors such as prevailing winds and currents combined with more quiescent wave conditions favors the accumulation and preservation of tarballs on the beach during the summer and fall months. In contrast, winter storms, with much greater wave action remove beach sand and other materials, and stormy seas tend to break up oil that might weather into tarballs. Natural seepage is affected by the spring/neap tidal cycle; however, the link to tar deposition is unclear. Longer periods of monitoring are needed to address the variability in the data and provide a more robust statistical analysis.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091225","collaboration":"A study in cooperation with the Minerals Management Service and the Energy Division, County of Santa Barbara, California; Also released as MMS report 2009-030; This study was funded in part by the U. S. Department of the Interior, Minerals Management Service (MMS), through an Interagency Agreement No. 18985 with the U.S. Geological Survey, Western Coastal and Marine Geology Team, as part of the MMS Environmental Studies Program.","usgsCitation":"Lorenson, T., Hostettler, F.D., Rosenbauer, R.J., Peters, K., Dougherty, J.A., Kvenvolden, K.A., Gutmacher, C.E., Wong, F.L., and Normark, W.R., 2009, Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory: U.S. Geological Survey Open-File Report 2009-1225, Report: iii, 116 p.; Appendixes, https://doi.org/10.3133/ofr20091225.","productDescription":"Report: iii, 116 p.; Appendixes","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":125640,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1225.jpg"},{"id":402029,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_90302.htm"},{"id":13337,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1225/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Channel, Santa Maria Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.014404296875,\n 34.134541681937364\n ],\n [\n -119.32250976562499,\n 34.134541681937364\n ],\n [\n -119.32250976562499,\n 35.146862906756304\n ],\n [\n -121.014404296875,\n 35.146862906756304\n ],\n [\n -121.014404296875,\n 34.134541681937364\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b00e4b07f02db6982ee","contributors":{"authors":[{"text":"Lorenson, T.D. tlorenson@usgs.gov","contributorId":2622,"corporation":false,"usgs":true,"family":"Lorenson","given":"T.D.","email":"tlorenson@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":304163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostettler, Frances D. fdhostet@usgs.gov","contributorId":3383,"corporation":false,"usgs":true,"family":"Hostettler","given":"Frances","email":"fdhostet@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":304164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenbauer, Robert J. brosenbauer@usgs.gov","contributorId":204,"corporation":false,"usgs":true,"family":"Rosenbauer","given":"Robert","email":"brosenbauer@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304161,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Kenneth E.","contributorId":10897,"corporation":false,"usgs":true,"family":"Peters","given":"Kenneth E.","affiliations":[],"preferred":false,"id":304167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dougherty, Jennifer A.","contributorId":6114,"corporation":false,"usgs":true,"family":"Dougherty","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304166,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kvenvolden, Keith A. kkvenvolden@usgs.gov","contributorId":3384,"corporation":false,"usgs":true,"family":"Kvenvolden","given":"Keith","email":"kkvenvolden@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gutmacher, Christina E.","contributorId":28272,"corporation":false,"usgs":true,"family":"Gutmacher","given":"Christina","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":304168,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wong, Florence L. 0000-0002-3918-5896 fwong@usgs.gov","orcid":"https://orcid.org/0000-0002-3918-5896","contributorId":1990,"corporation":false,"usgs":true,"family":"Wong","given":"Florence","email":"fwong@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304162,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Normark, William R.","contributorId":69570,"corporation":false,"usgs":true,"family":"Normark","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":304169,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":98095,"text":"ofr20091232 - 2009 - Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2001 Through June 2003","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"ofr20091232","displayToPublicDate":"2010-01-07T00:00:00","publicationYear":"2009","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":"2009-1232","title":"Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2001 Through June 2003","docAbstract":"The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2001 through June 2003.\r\n\r\nResults for the quality-control samples for 19 analytical procedures were evaluated for bias and precision. Control charts indicate that data for six of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, chloride, magnesium, nitrate (ion chromatography), potassium, and sodium. The calcium procedure was biased throughout the analysis period for the high-concentration sample, but was within control limits. The total monomeric aluminum and fluoride procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The total aluminum, pH, specific conductance, and sulfate procedures were biased for the high-concentration and low-concentration samples, but were within control limits.\r\n\r\nResults from the filter-blank and analytical-blank analyses indicate that the procedures for 16 of 18 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for the dissolved organic carbon or specific conductance procedures.\r\nSampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 21 analytes. At least 90 percent of the samples met data-quality objectives for all procedures except total monomeric aluminum (83 percent of samples met objectives), total aluminum (76 percent of samples met objectives), ammonium (73 percent of samples met objectives), dissolved organic carbon (86 percent of samples met objectives), and nitrate (81 percent of samples met objectives). The data-quality objective was not met for the nitrite procedure.\r\n\r\nResults of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated satisfactory or above data quality over the time period, with most performance ratings for each sample in the good-to-excellent range. The N-sample (nutrient constituents) analysis had one unsatisfactory rating for the ammonium procedure in one study. The T-sample (trace constituents) analysis had one unsatisfactory rating for the magnesium procedure and one marginal rating for the potassium procedure in one study and one unsatisfactory rating for the sodium procedure in another.\r\n\r\nResults of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 90 percent of the samples met data-quality objectives for 10 of the 14 analytes; the exceptions were acid-neutralizing capacity, ammonium, dissolved organic carbon, and sodium. Data-quality objectives were not met in 37 percent of samples analyzed for acid-neutralizing capacity, 28 percent of samples analyzed for dissolved organic carbon, and 30 percent of samples analyzed for sodium. Results indicate a positive bias for the ammonium procedure in one study and a negative bias in another.\r\nResults from blind reference-sample analyses indicated that data-quality objectives were met by at least 90 percent of the samples analyzed for calcium, chloride, magnesium, pH, potassium, and sodium. Data-quality objectives were met by 78 percent of ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091232","usgsCitation":"Lincoln, T.A., Horan-Ross, D.A., McHale, M.R., and Lawrence, G.B., 2009, Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2001 Through June 2003: U.S. Geological Survey Open-File Report 2009-1232, iv, 33 p., https://doi.org/10.3133/ofr20091232.","productDescription":"iv, 33 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2001-07-01","temporalEnd":"2003-06-30","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":125861,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1232.jpg"},{"id":13331,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1232/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a69e4b07f02db63bfd2","contributors":{"authors":[{"text":"Lincoln, Tricia A. tarenga@usgs.gov","contributorId":3803,"corporation":false,"usgs":true,"family":"Lincoln","given":"Tricia","email":"tarenga@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":304134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horan-Ross, Debra A. dhross@usgs.gov","contributorId":3809,"corporation":false,"usgs":true,"family":"Horan-Ross","given":"Debra","email":"dhross@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":304135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHale, Michael R. 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":1735,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304133,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98092,"text":"sir20095216 - 2009 - Analysis of Water-Quality Trends for Selected Streams in the Water Chemistry Monitoring Program, Michigan, 1998-2005 ","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095216","displayToPublicDate":"2010-01-06T00:00:00","publicationYear":"2009","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":"2009-5216","title":"Analysis of Water-Quality Trends for Selected Streams in the Water Chemistry Monitoring Program, Michigan, 1998-2005 ","docAbstract":"In 1998, the Michigan Department of Environmental Quality and the U.S. Geological Survey began a long-term monitoring program to evaluate the water quality of most watersheds in Michigan. Major goals of this Water-Chemistry Monitoring Program were to identify streams exceeding or not meeting State or Federal water-quality standards and to assess if constituent concentrations reflecting water quality in these streams were increasing or decreasing over time. As part of this program, water-quality data collected from 1998 to 2005 were analyzed to identify potential trends. Sixteen water-quality constituents were analyzed at 31 sites across Michigan, 28 of which had sufficient data to analyze for trends. Trend analysis on the various water-quality data was done using the uncensored Seasonal Kendall test within the computer program ESTREND. The most prevalent trend detected throughout the state was for chloride. Chloride trends were detected at 8 of the 28 sites; trends at 7 sites were increasing and the trend at 1 site was decreasing. Although no trends were detected for various nitrogen species or phosphorus, these constituents were detected at levels greater than the U.S. Environmental Protection Agency recommendations for nutrients in water. The results of the trend analysis will help to establish a baseline to evaluate future changes in water quality in Michigan streams.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095216","collaboration":"Prepared in cooperation with the Michigan Department of Environmental Quality","usgsCitation":"Hoard, C.J., Fuller, L.M., and Fogarty, L., 2009, Analysis of Water-Quality Trends for Selected Streams in the Water Chemistry Monitoring Program, Michigan, 1998-2005 : U.S. Geological Survey Scientific Investigations Report 2009-5216, viii, 48 p., https://doi.org/10.3133/sir20095216.","productDescription":"viii, 48 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1998-01-01","temporalEnd":"2005-12-31","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":125875,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5216.jpg"},{"id":13328,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5216/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91,41 ], [ -91,48 ], [ -82,48 ], [ -82,41 ], [ -91,41 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad0e4b07f02db680ae5","contributors":{"authors":[{"text":"Hoard, C. J.","contributorId":37436,"corporation":false,"usgs":true,"family":"Hoard","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":304125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":304124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fogarty, Lisa R.","contributorId":74074,"corporation":false,"usgs":true,"family":"Fogarty","given":"Lisa R.","affiliations":[],"preferred":false,"id":304126,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98090,"text":"ofr20091297 - 2009 - Compilation of Mineral Resource Data for Mississippi Valley-Type and Clastic-Dominated Sediment-Hosted Lead-Zinc Deposits","interactions":[],"lastModifiedDate":"2012-02-02T00:14:47","indexId":"ofr20091297","displayToPublicDate":"2010-01-06T00:00:00","publicationYear":"2009","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":"2009-1297","title":"Compilation of Mineral Resource Data for Mississippi Valley-Type and Clastic-Dominated Sediment-Hosted Lead-Zinc Deposits","docAbstract":"This report contains a global compilation of the mineral resource data for sediment-hosted lead-zinc (SH Pb-Zn) deposits. Sediment-hosted lead-zinc deposits are historically the most significant sources of lead and zinc, and are mined throughout the world. The most important SH Pb-Zn deposits are hosted in clastic-dominated sedimentary rock sequences (CD Pb-Zn) that are traditionally called sedimentary exhalative (SEDEX) deposits, and those in carbonate-dominated sequences that are known as Mississippi Valley-type (MVT) Pb-Zn deposits. In this report, we do not include sandstone-Pb, sandstone-hosted Pb, or Pb-Zn vein districts such as those in Freiberg, Germany, or Coeur d'Alene, Idaho, because these deposits probably represent different deposit types (Leach and others, 2005). We do not include fracture-controlled deposits in which fluorite is dominant and barite typically abundant (for example, Central Kentucky; Hansonburg, N. Mex.) or the stratabound fluorite-rich, but also lead- and zinc-bearing deposits, such as those in southern Illinois, which are considered a genetic variant of carbonate-hosted Pb-Zn deposits (Leach and Sangster, 1993).\r\n\r\nThis report updates the Pb, Zn, copper (Cu), and silver (Ag) grade and tonnage data in Leach and others (2005), which itself was based on efforts in the Canadian Geological Survey World Minerals Geoscience Database Project (contributions of D.F. Sangster to Sinclair and others, 1999). New geological or geochronological data, classifications of the tectonic environment in which the deposits formed, and key references to the geology of the deposits are presented in our report. Data for 121 CD deposits, 113 MVT deposits, and 6 unclassified deposits that were previously classified as either SEDEX or MVT in the Leach and others (2005) compilation, are given in appendix table A1. In some cases, mineral resource data were available only for total district resources, but not for individual mines within the district. For these districts, the resource data are presented in appendix table A2. In addition, numerous figures (appendix figures B1-B9) displaying important grade-tonnage and geologic features are included.\r\n\r\nThese mineral deposit resource data are important for exploration targeting and mineral resource assessments. There is significant variability in the resource data for these deposit types, and ore controls vary from one region to another. Therefore, grade-tonnage estimations are best evaluated as subsets of the data in appendix table A1 where local mineralization styles and ore controls characterize the region being evaluated for grade-tonnage relations. Furthermore, consideration should also be given to the tendency for MVT resources to occur in large mineralized regions.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091297","usgsCitation":"Taylor, R.D., Leach, D.L., Bradley, D., and Pisarevsky, S.A., 2009, Compilation of Mineral Resource Data for Mississippi Valley-Type and Clastic-Dominated Sediment-Hosted Lead-Zinc Deposits: U.S. Geological Survey Open-File Report 2009-1297, iii, 42 p., https://doi.org/10.3133/ofr20091297.","productDescription":"iii, 42 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":177,"text":"Central Region Mineral Resources Science Center","active":false,"usgs":true}],"links":[{"id":125938,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1297.jpg"},{"id":13324,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1297/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1ee4b07f02db6aa045","contributors":{"authors":[{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":304117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leach, David L.","contributorId":83902,"corporation":false,"usgs":true,"family":"Leach","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":304119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley, Dwight 0000-0001-9116-5289 bradleyorchard2@gmail.com","orcid":"https://orcid.org/0000-0001-9116-5289","contributorId":2358,"corporation":false,"usgs":true,"family":"Bradley","given":"Dwight","email":"bradleyorchard2@gmail.com","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":304116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pisarevsky, Sergei A.","contributorId":62315,"corporation":false,"usgs":true,"family":"Pisarevsky","given":"Sergei","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304118,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98089,"text":"sir20095224 - 2009 - Riparian and Associated Habitat Characteristics Related to Nutrient Concentrations and Biological Responses of Small Streams in Selected Agricultural Areas, United States, 2003-04","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095224","displayToPublicDate":"2010-01-06T00:00:00","publicationYear":"2009","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":"2009-5224","title":"Riparian and Associated Habitat Characteristics Related to Nutrient Concentrations and Biological Responses of Small Streams in Selected Agricultural Areas, United States, 2003-04","docAbstract":"Physical factors, including both in-stream and riparian habitat characteristics that limit biomass or otherwise regulate aquatic biological condition, have been identified by previous studies. However, linking the ecological significance of nutrient enrichment to habitat or landscape factors that could allow for improved management of streams has proved to be a challenge in many regions, including agricultural landscapes, where many ecological stressors are strong and the variability among watersheds typically is large. Riparian and associated habitat characteristics were sampled once during 2003-04 for an intensive ecological and nutrients study of small perennial streams in five contrasting agricultural landscapes across the United States to determine how biological communities and ecosystem processes respond to varying levels of nutrient enrichment. Nutrient concentrations were determined in stream water at two different sampling times per site and biological samples were collected once per site near the time of habitat characterization. Data for 141 sampling sites were compiled, representing five study areas, located in parts of the Delmarva Peninsula (Delaware and Maryland), Georgia, Indiana, Ohio, Nebraska, and Washington. This report examines the available data for riparian and associated habitat characteristics to address questions related to study-unit contrasts, spatial scale-related differences, multivariate correlation structure, and bivariate relations between selected habitat characteristics and either stream nutrient conditions or biological responses.\r\n\r\nRiparian and associated habitat characteristics were summarized and categorized into 22 groups of habitat variables, with 11 groups representing land-use and land-cover characteristics and 11 groups representing other riparian or in-stream habitat characteristics. Principal components analysis was used to identify a reduced set of habitat variables that describe most of the variability among the sampled sites. The habitat characteristics sampled within the five study units were compared statistically. Bivariate correlations between riparian habitat variables and either nutrient-chemistry or biological-response variables were examined for all sites combined, and for sites within each study area.\r\n\r\nNutrient concentrations were correlated with the extent of riparian cropland. For nitrogen species, these correlations were more frequently at the basin scale, whereas for phosphorus, they were about equally frequent at the segment and basin scales. Basin-level extents of riparian cropland and reach-level bank vegetative cover were correlated strongly with both total nitrogen and dissolved inorganic nitrogen (DIN) among multiple study areas, reflecting the importance of agricultural land-management and conservation practices for reducing nitrogen delivery from near-stream sources. When sites lacking segment-level wetlands were excluded, the negative correlation of riparian wetland extent with DIN among 49 sites was strong at the reach and segment levels. Riparian wetland vegetation thus may be removing dissolved nutrients from soil water and shallow groundwater passing through riparian zones. Other habitat variables that correlated strongly with nitrogen and phosphorus species included suspended sediment, light availability, and antecedent water temperature.\r\n\r\nChlorophyll concentrations in seston were positively correlated with phosphorus concentrations for all sites combined. Benthic chlorophyll was correlated strongly with nutrient concentrations in only the Delmarva study area and only in fine-grained habitats. Current velocity or hydraulic scour could explain correlation patterns for benthic chlorophyll among Georgia sites, whereas chlorophyll in seston was correlated with antecedent water temperature among Washington and Delmarva sites. The lack of any consistent correlation pattern between habitat characteristics and organic material density (ash-free dry mass)","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095224","usgsCitation":"Zelt, R.B., and Munn, M.D., 2009, Riparian and Associated Habitat Characteristics Related to Nutrient Concentrations and Biological Responses of Small Streams in Selected Agricultural Areas, United States, 2003-04: U.S. Geological Survey Scientific Investigations Report 2009-5224, xiv, 79 p., https://doi.org/10.3133/sir20095224.","productDescription":"xiv, 79 p.","temporalStart":"2003-01-01","temporalEnd":"2004-12-31","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":125779,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5224.jpg"},{"id":13323,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5224/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130,20 ], [ -130,50 ], [ -65,50 ], [ -65,20 ], [ -130,20 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a13e4b07f02db6020ef","contributors":{"authors":[{"text":"Zelt, Ronald B. 0000-0001-9024-855X rbzelt@usgs.gov","orcid":"https://orcid.org/0000-0001-9024-855X","contributorId":300,"corporation":false,"usgs":true,"family":"Zelt","given":"Ronald","email":"rbzelt@usgs.gov","middleInitial":"B.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munn, Mark D. 0000-0002-7154-7252 mdmunn@usgs.gov","orcid":"https://orcid.org/0000-0002-7154-7252","contributorId":976,"corporation":false,"usgs":true,"family":"Munn","given":"Mark","email":"mdmunn@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304115,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98087,"text":"sir20095248 - 2009 - The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion","interactions":[],"lastModifiedDate":"2021-12-15T21:02:47.973093","indexId":"sir20095248","displayToPublicDate":"2010-01-05T00:00:00","publicationYear":"2009","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":"2009-5248","title":"The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion","docAbstract":"The Water Availability Tool for Environmental Resources (WATER) was developed in cooperation with the Kentucky Division of Water to provide a consistent and defensible method of estimating streamflow and water availability in ungaged basins. WATER is process oriented; it is based on the TOPMODEL code and incorporates historical water-use data together with physiographic data that quantitatively describe topography and soil-water storage. The result is a user-friendly decision tool that can estimate water availability in non-karst areas of Kentucky without additional data or processing. The model runs on a daily time step, and critical source data include a historical record of daily temperature and precipitation, digital elevation models (DEMs), the Soil Survey Geographic Database (SSURGO), and historical records of water discharges and withdrawals. The model was calibrated and statistically evaluated for 12 basins by comparing the estimated discharge to that observed at U.S. Geological Survey streamflow-gaging stations. When statistically evaluated over a 2,119-day time period, the discharge estimates showed a bias of -0.29 to 0.42, a root mean square error of 1.66 to 5.06, a correlation of 0.54 to 0.85, and a Nash-Sutcliffe Efficiency of 0.26 to 0.72. The parameter and input modifications that most significantly improved the accuracy and precision of streamflow-discharge estimates were the addition of Next Generation radar (NEXRAD) precipitation data, a rooting depth of 30 centimeters, and a TOPMODEL scaling parameter (m) derived directly from SSURGO data that was multiplied by an adjustment factor of 0.10. No site-specific optimization was used.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095248","collaboration":"Prepared in cooperation with the Kentucky Division of Water","usgsCitation":"Williamson, T., Odom, K.R., Newson, J.K., Downs, A.C., Nelson, H.L., Cinotto, P.J., and Ayers, M.A., 2009, The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion: U.S. Geological Survey Scientific Investigations Report 2009-5248, vi, 34 p., https://doi.org/10.3133/sir20095248.","productDescription":"vi, 34 p.","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":125858,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5248.jpg"},{"id":392968,"rank":3,"type":{"id":36,"text":"NGMDB Index 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Center","active":true,"usgs":true}],"preferred":false,"id":304108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downs, Aimee C. acdowns@usgs.gov","contributorId":929,"corporation":false,"usgs":true,"family":"Downs","given":"Aimee","email":"acdowns@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":304106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Hugh L. hlnelson@usgs.gov","contributorId":4158,"corporation":false,"usgs":true,"family":"Nelson","given":"Hugh","email":"hlnelson@usgs.gov","middleInitial":"L.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304107,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cinotto, Peter J. pcinotto@usgs.gov","contributorId":451,"corporation":false,"usgs":true,"family":"Cinotto","given":"Peter","email":"pcinotto@usgs.gov","middleInitial":"J.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304104,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ayers, Mark A.","contributorId":84730,"corporation":false,"usgs":true,"family":"Ayers","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304110,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":98088,"text":"sir20095231 - 2009 - Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07","interactions":[],"lastModifiedDate":"2016-08-15T11:00:28","indexId":"sir20095231","displayToPublicDate":"2010-01-05T00:00:00","publicationYear":"2009","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":"2009-5231","title":"Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07","docAbstract":"In December 2005, the U.S. Geological Survey in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (total coliform and Escherichia coli), atrazine, and suspended sediment at two U.S. Geological Survey streamflow-gaging stations upstream from Lake Houston near Houston (08068500 Spring Creek near Spring, Texas, and 08070200 East Fork San Jacinto River near New Caney, Texas). The data from the discrete water-quality samples collected during 2005-07, in conjunction with monitored real-time data already being collected - physical properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), streamflow, and rainfall - were used to develop regression models for predicting water-quality constituent concentrations for inflows to Lake Houston. Rainfall data were obtained from a rain gage monitored by Harris County Homeland Security and Emergency Management and colocated with the Spring Creek station. The leaps and bounds algorithm was used to find the best subsets of possible regression models (minimum residual sum of squares for a given number of variables). The potential explanatory or predictive variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, rainfall, and time (to account for seasonal variations inherent in some water-quality data). The response variables at each site were nitrite plus nitrate nitrogen, total phosphorus, organic carbon, Escherichia coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities as a means to estimate concentrations of the various constituents under investigation, with accompanying estimates of measurement uncertainty. Each regression equation can be used to estimate concentrations of a given constituent in real time. In conjunction with estimated concentrations, constituent loads were estimated by multiplying the estimated concentration by the corresponding streamflow and applying the appropriate conversion factor. By computing loads from estimated constituent concentrations, a continuous record of estimated loads can be available for comparison to total maximum daily loads. The regression equations presented in this report are site specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the methods that were developed and documented could be applied to other tributaries to Lake Houston for estimating real-time water-quality data for streams entering Lake Houston.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095231","isbn":"9781411326286","collaboration":"Prepared in cooperation with the City of Houston","usgsCitation":"Oden, T., Asquith, W.H., and Milburn, M.S., 2009, Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07: U.S. Geological Survey Scientific Investigations Report 2009-5231, vi, 44 p., https://doi.org/10.3133/sir20095231.","productDescription":"vi, 44 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":125870,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5231.jpg"},{"id":326480,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5231/pdf/sir2009-5231.pdf","text":"Report","size":"8.0 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":13322,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5231/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.25,29.75 ], [ -96.25,31 ], [ -94.75,31 ], [ -94.75,29.75 ], [ -96.25,29.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a60e4b07f02db634da9","contributors":{"authors":[{"text":"Oden, Timothy D. toden@usgs.gov","contributorId":1284,"corporation":false,"usgs":true,"family":"Oden","given":"Timothy D.","email":"toden@usgs.gov","affiliations":[],"preferred":true,"id":304112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milburn, Matthew S.","contributorId":53896,"corporation":false,"usgs":true,"family":"Milburn","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":304113,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046818,"text":"70046818 - 2009 - USGS standard quadrangle maps for emergency response","interactions":[],"lastModifiedDate":"2014-07-02T13:43:40","indexId":"70046818","displayToPublicDate":"2010-01-01T13:32:00","publicationYear":"2009","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"USGS standard quadrangle maps for emergency response","docAbstract":"The 1:24,000-scale topographic quadrangle was the primary product of the U.S. Geological Survey's (USGS) National Mapping Program from 1947-1992. This map series includes about 54,000 map sheets for the conterminous United States, and is the only uniform map series ever produced that covers this area at such a large scale.
\nThis map series partially was revised under several programs, starting as early as 1968, but these programs were not adequate to keep the series current. Through the 1990s the emphasis of the USGS mapping program shifted away from topographic maps and toward more specialized digital data products. Topographic map revision dropped off rapidly after 1999, and stopped completely by 2004.
\nSince 2001, emergency-response and homeland security requirement have revived the question of whether a standard national topographic series is needed. Emergencies such as Hurricane Katrina in 2005 and California wildfires in 2007-08 demonstrated that familiar maps are important to first responders. Maps that have a standard scale, extent, and grids help reduce confusion and save time in emergencies.
\nTraditional maps are designed to allow the human brain to quickly process large amounts of information, and depend on artistic layout and design that cannot be fully automated. In spite of technical advances, creating a traditional, general-purpose topographic map is still expensive.
\nAlthough the content and layout of traditional topographic maps probably is still desirable, the preferred packaging and delivery of maps has changed. Digital image files are now desired by most users, but to be useful to the emergency-response community, these files must be easy to view and easy to print without specialized geographic information system expertise or software.
","largerWorkTitle":"Annual Association of American Geographers Meeting","conferenceTitle":"Association of American Geographers Annual Meeting","conferenceDate":"2009-03-22T00:00:00","conferenceLocation":"Las Vegas, NV","language":"English","publisher":"Annual Association of American Geographers Meeting","publisherLocation":"Washington, D.C.","usgsCitation":"Moore, L.R., 2009, USGS standard quadrangle maps for emergency response, p. 35-39.","productDescription":"p. 35-39","numberOfPages":"5","ipdsId":"IP-009495","costCenters":[],"links":[{"id":289390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b7b277e4b0388651d9196d","contributors":{"authors":[{"text":"Moore, Laurence R. 0000-0001-9678-7183 lmoore@usgs.gov","orcid":"https://orcid.org/0000-0001-9678-7183","contributorId":2057,"corporation":false,"usgs":true,"family":"Moore","given":"Laurence","email":"lmoore@usgs.gov","middleInitial":"R.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":480360,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046864,"text":"70046864 - 2009 - Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin","interactions":[{"subject":{"id":70046864,"text":"70046864 - 2009 - Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin","indexId":"70046864","publicationYear":"2009","noYear":false,"title":"Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin"},"predicate":"IS_PART_OF","object":{"id":97928,"text":"sir20095049 - 2009 - Planning for an uncertain future - Monitoring, integration, and adaptation","indexId":"sir20095049","publicationYear":"2009","noYear":false,"title":"Planning for an uncertain future - Monitoring, integration, and adaptation"},"id":1}],"isPartOf":{"id":97928,"text":"sir20095049 - 2009 - Planning for an uncertain future - Monitoring, integration, and adaptation","indexId":"sir20095049","publicationYear":"2009","noYear":false,"title":"Planning for an uncertain future - Monitoring, integration, and adaptation"},"lastModifiedDate":"2016-08-18T16:10:55","indexId":"70046864","displayToPublicDate":"2010-01-01T11:49:00","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesNumber":"2009-5049","title":"Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin","docAbstract":"A major focus of the U.S. Geological Survey’s Trout Lake Water, Energy, and Biogeochemical Budgets (WEBB) project is the development of a watershed model to allow predictions of hydrologic response to future conditions including land-use and climate change. The coupled groundwater/surface-water model GSFLOW was chosen for this purpose because it could easily incorporate an existing groundwater flow model and it provides for simulation of surface-water processes.
\n\n
The Trout Lake watershed in northern Wisconsin is underlain by a highly conductive outwash sand aquifer. In this area, streamflow is dominated by groudwater contributions, however, surface runoff occurs during intense rainfall periods and spring snowmelt. Surface runoff also occurs locally near stream/lake areas where the unsaturated zone is thin. A diverse data set, collected from 1992 to 2007 for the Trout Lake WEBB project and the co-located and NSF-funded North Temperate Lake LTER project, includes snowpack, solar radiation, potential evapotranspiration, lake levels, groundwater levels, and streamflow. The time-series processing software TSPROC (Doherty 2001)was used to distill the large time series data set to a smaller set of observations and summary statistics that captured the salient hydrologic information. The time-series processing reduced hundreds of thousands of observations to less than 5,000. Model calibration included specific predictions for several lakes in the study area using the PEST parameter estimation suit of software (Doherty 2007). The calibrated model was used to simulate the hydrologic response in the study lakes to a variety of climate change scenarios culled from the IPCC Fourth Assessment Report of the Intergovernmental Panel of Climate Change (Solomon et al. 2007). Results from the simulations indicate climate change could result in substantial changes to the lake levels and components of the hydrologic budget of a seepage lake in the flow system. For a drainage lake lower in the flow system, the impacts of climate change are diminished.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Planning for an uncertain future - monitoring, integration, and adaptation (SIR 2009-5049)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"conferenceTitle":"3rd interagency conference on research in the watersheds: planning for an uncertain future: monitoring, integration, and adaptation","conferenceDate":"8-11 September, 2008","conferenceLocation":"Estes Park, CO","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Hunt, R., Walker, J.F., Markstrom, S., Hay, L.E., and Doherty, J., 2009, Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin, in Planning for an uncertain future - monitoring, integration, and adaptation (SIR 2009-5049), Estes Park, CO, 8-11 September, 2008, p. 155-161.","productDescription":"7 p.","startPage":"155","endPage":"161","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-009788","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":289370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":326855,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5049/pdf/SIR09-5049.pdf"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Trout Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.703926,46.012934 ], [ -89.703926,46.079112 ], [ -89.646771,46.079112 ], [ -89.646771,46.012934 ], [ -89.703926,46.012934 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b7b27ee4b0388651d9198c","contributors":{"editors":[{"text":"Webb, Richard M. T. 0000-0001-9531-2207","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":35772,"corporation":false,"usgs":true,"family":"Webb","given":"Richard M. T.","affiliations":[],"preferred":false,"id":646256,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":646257,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, John F. jfwalker@usgs.gov","contributorId":1081,"corporation":false,"usgs":true,"family":"Walker","given":"John","email":"jfwalker@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":1986,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven L.","email":"markstro@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":480495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":480494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, John","contributorId":43843,"corporation":false,"usgs":true,"family":"Doherty","given":"John","affiliations":[],"preferred":false,"id":480497,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70104212,"text":"70104212 - 2009 - Hindcasting of decadal‐timescale estuarine bathymetric change with a tidal‐timescale model","interactions":[],"lastModifiedDate":"2014-05-13T09:07:41","indexId":"70104212","displayToPublicDate":"2010-01-01T09:00:28","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Hindcasting of decadal‐timescale estuarine bathymetric change with a tidal‐timescale model","docAbstract":"Hindcasting decadal-timescale bathymetric change in estuaries is prone to error due to limited data for initial conditions, boundary forcing, and calibration; computational limitations further hinder efforts. We developed and calibrated a tidal-timescale model to bathymetric change in Suisun Bay, California, over the 1867–1887 period. A general, multiple-timescale calibration ensured robustness over all timescales; two input reduction methods, the morphological hydrograph and the morphological acceleration factor, were applied at the decadal timescale. The model was calibrated to net bathymetric change in the entire basin; average error for bathymetric change over individual depth ranges was 37%. On a model cell-by-cell basis, performance for spatial amplitude correlation was poor over the majority of the domain, though spatial phase correlation was better, with 61% of the domain correctly indicated as erosional or depositional. Poor agreement was likely caused by the specification of initial bed composition, which was unknown during the 1867–1887 period. Cross-sectional bathymetric change between channels and flats, driven primarily by wind wave resuspension, was modeled with higher skill than longitudinal change, which is driven in part by gravitational circulation. The accelerated response of depth may have prevented gravitational circulation from being represented properly. As performance criteria became more stringent in a spatial sense, the error of the model increased. While these methods are useful for estimating basin-scale sedimentation changes, they may not be suitable for predicting specific locations of erosion or deposition. They do, however, provide a foundation for realistic estuarine geomorphic modeling applications.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research F: Earth Surface","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Amercan Geophysical Union","doi":"10.1029/2008JF001191","usgsCitation":"Ganju, N., Schoellhamer, D., and Jaffe, B.E., 2009, Hindcasting of decadal‐timescale estuarine bathymetric change with a tidal‐timescale model: Journal of Geophysical Research F: Earth Surface, v. 114, no. F4, 15 p., https://doi.org/10.1029/2008JF001191.","productDescription":"15 p.","numberOfPages":"15","temporalStart":"1866-12-31","temporalEnd":"1887-12-31","ipdsId":"IP-003086","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":476012,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/3105","text":"External Repository"},{"id":287069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287063,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2008JF001191"}],"country":"United States","state":"California","otherGeospatial":"Suisun Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.75,37.75 ], [ -122.75,38.25 ], [ -121.75,38.25 ], [ -121.75,37.75 ], [ -122.75,37.75 ] ] ] } } ] }","volume":"114","issue":"F4","noUsgsAuthors":false,"publicationDate":"2009-12-02","publicationStatus":"PW","scienceBaseUri":"53733efae4b0497061278906","contributors":{"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":93543,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[],"preferred":false,"id":493638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493637,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042388,"text":"70042388 - 2009 - Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA","interactions":[],"lastModifiedDate":"2018-10-05T09:50:25","indexId":"70042388","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA","docAbstract":"Denitrification is an important net sink for NO3− in streams, but direct measurements are limited and in situ controlling factors are not well known. We measured denitrification at multiple scales over a range of flow conditions and NO3− concentrations in streams draining agricultural land in the upper Mississippi River basin. Comparisons of reach-scale measurements (in-stream mass transport and tracer tests) with local-scale in situ measurements (pore-water profiles, benthic chambers) and laboratory data (sediment core microcosms) gave evidence for heterogeneity in factors affecting benthic denitrification both temporally (e.g., seasonal variation in NO3− concentrations and loads, flood-related disruption and re-growth of benthic communities and organic deposits) and spatially (e.g., local stream morphology and sediment characteristics). When expressed as vertical denitrification flux per unit area of streambed (Udenit, in μmol N m−2 h−1), results of different methods for a given set of conditions commonly were in agreement within a factor of 2–3. At approximately constant temperature (~20 ± 4°C) and with minimal benthic disturbance, our aggregated data indicated an overall positive relation between Udenit (~0–4,000 μmol N m−2 h−1) and stream NO3−concentration (~20–1,100 μmol L−1) representing seasonal variation from spring high flow (high NO3−) to late summer low flow (low NO3−). The temporal dependence of Udenit on NO3−was less than first-order and could be described about equally well with power-law or saturation equations (e.g., for the unweighted dataset, Udenit ≈26 * [NO3−]0.44 or Udenit≈640 * [NO3−]/[180 + NO3−]; for a partially weighted dataset, Udenit ≈14 * [NO3−]0.54 or Udenit ≈700 * [NO3−]/[320 + NO3−]). Similar parameters were derived from a recent spatial comparison of stream denitrification extending to lower NO3− concentrations (LINX2), and from the combined dataset from both studies over 3 orders of magnitude in NO3−concentration. Hypothetical models based on our results illustrate: (1) Udenit was inversely related to denitrification rate constant (k1denit, in day−1) and vertical transfer velocity (vf,denit, in m day−1) at seasonal and possibly event time scales; (2) although k1denit was relatively large at low flow (low NO3−), its impact on annual loads was relatively small because higher concentrations and loads at high flow were not fully compensated by increases in Udenit; and (3) although NO3− assimilation and denitrification were linked through production of organic reactants, rates of NO3− loss by these processes may have been partially decoupled by changes in flow and sediment transport. Whereas k1denit and vf,denit are linked implicitly with stream depth, NO3− concentration, and(or) NO3− load, estimates of Udenit may be related more directly to field factors (including NO3− concentration) affecting denitrification rates in benthic sediments. Regional regressions and simulations of benthic denitrification in stream networks might be improved by including a non-linear relation between Udenit and stream NO3−concentration and accounting for temporal variation.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-008-9282-8","usgsCitation":"Bohlke, J., Antweiler, R.C., Harvey, J.W., Laursen, A.E., Smith, L.K., Smith, R.L., and Voytek, M.A., 2009, Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA: Biogeochemistry, v. 93, no. 1, p. 117-141, https://doi.org/10.1007/s10533-008-9282-8.","productDescription":"24 p.","startPage":"117","endPage":"141","ipdsId":"IP-008428","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":476016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10533-008-9282-8","text":"Publisher Index Page"},{"id":270742,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10533-008-9282-8"},{"id":270743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"1","noUsgsAuthors":false,"publicationDate":"2009-01-13","publicationStatus":"PW","scienceBaseUri":"5165386ce4b077fa94dadfc3","contributors":{"authors":[{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - 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Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":471446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laursen, Andrew E.","contributorId":99783,"corporation":false,"usgs":true,"family":"Laursen","given":"Andrew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":471450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Lesley K.","contributorId":82657,"corporation":false,"usgs":true,"family":"Smith","given":"Lesley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":471447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Richard L. 0000-0002-3829-0125 rlsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-3829-0125","contributorId":1592,"corporation":false,"usgs":true,"family":"Smith","given":"Richard","email":"rlsmith@usgs.gov","middleInitial":"L.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - 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At one location in southeastern Lake Ontario, we measured the vertical distribution of mysids, mysid predators (i.e. planktivorous fishes) and mysid prey (i.e. zooplankton), in addition to light and temperature, on 8 occasions from May to September, 2004 and 2005. We use these data to test 3 different predictive models of mysid habitat selection, based on: (1) laboratory-derived responses of mysids to different light and temperature gradients in the absence of predator or prey cues; (2) growth rate of mysids, as estimated with a mysid bioenergetics model, given known prey densities and temperatures at different depths in the water column; (3) ratio of growth rates (g) and mortality risk (μ) associated with the distribution of predatory fishes. The model based on light and temperature preferences was a better predictor of mysid vertical distribution than the models based on growth rate and g:μ on all 8 occasions. Although mysid temperature and light preferences probably evolved as mechanisms to reduce predation while increasing foraging intake, the response to temperature and light alone predicts mysid vertical distribution across seasons in Lake Ontario.
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2009 - Lysimetric Evaluation of Simplified Surface Energy Balance Approach in the Texas High Plains","interactions":[],"lastModifiedDate":"2013-04-07T21:40:33","indexId":"70043493","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":833,"text":"Applied Engineering in Agriculture","active":true,"publicationSubtype":{"id":10}},"title":"Lysimetric Evaluation of Simplified Surface Energy Balance Approach in the Texas High Plains","docAbstract":"Numerous energy balance (EB) algorithms have been developed to make use of remote sensing data to estimate evapotranspiration (ET) regionally. However, most EB models are complex to use and efforts are being made to simplify procedures mainly through the scaling of reference ET. The Simplified Surface Energy Balance (SSEB) is one such method. This approach has never been evaluated using measured ET data. In this study, the SSEB approach was applied to fourteen Landsat TM images covering a major portion of the Southern High Plains that were acquired during 2006 and 2007 cropping seasons. Performance of the SSEB was evaluated by comparing estimated ET with measured daily ET from four large monolithic lysimeters at the USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas. Statistical evaluation of results indicated that the SSEB accounted for 84% of the variability in the measured ET values with a slope and intercept of 0.75 and 1.1 mm d-1, respectively. Considering the minimal amount of ancillary data required and excellent performance in predicting daily ET, the SSEB approach is a promising tool for mapping ET in the semiarid Texas High Plains and in other parts of the world with similar hydro-climatic conditions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Engineering in Agriculture","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisherLocation":"Reston, VA","usgsCitation":"Senay, G.B., Gowda, P., Howell, T., and Marek, T., 2009, Lysimetric Evaluation of Simplified Surface Energy Balance Approach in the Texas High Plains: Applied Engineering in Agriculture, v. 25, no. 5, p. 665-669.","startPage":"665","endPage":"669","ipdsId":"IP-021547","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270643,"type":{"id":11,"text":"Document"},"url":"https://naldc.nal.usda.gov/download/37867/PDF"}],"country":"United States","volume":"25","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5162956ee4b0c25842758cff","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gowda, P.H.","contributorId":63652,"corporation":false,"usgs":true,"family":"Gowda","given":"P.H.","email":"","affiliations":[],"preferred":false,"id":473708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howell, T.A.","contributorId":57694,"corporation":false,"usgs":true,"family":"Howell","given":"T.A.","affiliations":[],"preferred":false,"id":473707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marek, T.H.","contributorId":38815,"corporation":false,"usgs":true,"family":"Marek","given":"T.H.","email":"","affiliations":[],"preferred":false,"id":473706,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70161856,"text":"70161856 - 2009 - 2008 Spawning Cisco Investigations in the Canadian Waters of Lake Superior","interactions":[],"lastModifiedDate":"2016-06-23T14:48:40","indexId":"70161856","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"2008 Spawning Cisco Investigations in the Canadian Waters of Lake Superior","docAbstract":"The Great Lakes Science Center of the United States Geological Survey (USGS) is working cooperatively with the Ontario Ministry of Natural Resources (OMNR) on a threeyear study to develop standard procedures for acoustic and midwater trawl (AC-MT) assessments of spawning cisco Coregonus artedi that the OMNR can carry forward as a management activity. In year two (2008), we conducted an AC-MT survey of the northern shore from Nipigon Bay to Thunder Bay. Spawning-cisco (> 250 mm total length) densities were lowest near Nipigon Bay (<10/ha), moderate in and around Black Bay (15- 30/ha), and highest in Thunder Bay (118/ha). Rainbow smelt Osmerus mordax densities were highest in Nipigon (2,179/ha) and Black (3,219/ha) bays, and lowest in Thunder Bay (961/ha). We combined our AC-MT survey results with commercial catch records to estimate exploitation fractions of female cisco in Thunder Bay during the 2008 fishery at 4% for ages 1-5, 8.7% for ages 6-12, and 4.4% for ages ≥ 13. Lake Superior fishery managers recently recommended that annual exploitation of adult female lake cisco be kept below 10-15%. Recruitment of cisco since 2003 has been low and there is a strong probability the Thunder Bay stock will decline into the future. Using a simple population dynamics approach we estimated that if the current total allowable catch (TAC) quota is held constant, exploitation fractions could exceed 10% by 2010 and 15% by 2011. Our 2008 collections suggested the survey of Black Bay was likely conducted before all spawners had returned there to spawn. Our data also suggested that cisco collected in Black Bay and east of this site in mid-November may be from the same stock. During November 2009 we will attempt to get better definition of the area occupied by cisco around Black Bay and also determine when surveys should be conducted at this location.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70161856","usgsCitation":"Yule, D., Addison, P.A., Evrard, L.M., Cullis, K.I., and Cholwek, G.A., 2009, 2008 Spawning Cisco Investigations in the Canadian Waters of Lake Superior, 47 p., https://doi.org/10.3133/70161856.","productDescription":"47 p.","numberOfPages":"47","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-014726","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":324306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":313995,"type":{"id":11,"text":"Document"},"url":"https://www.glsc.usgs.gov/products/reports/1970178148"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576d082ce4b07657d1a37543","contributors":{"authors":[{"text":"Yule, Daniel L. 0000-0002-0117-5115 dyule@usgs.gov","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":139532,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","email":"dyule@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Addison, Peter A.","contributorId":105987,"corporation":false,"usgs":true,"family":"Addison","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":587947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evrard, Lori M. 0000-0001-8582-5818 levrard@usgs.gov","orcid":"https://orcid.org/0000-0001-8582-5818","contributorId":2720,"corporation":false,"usgs":true,"family":"Evrard","given":"Lori","email":"levrard@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587945,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cullis, Ken I.","contributorId":150786,"corporation":false,"usgs":false,"family":"Cullis","given":"Ken","email":"","middleInitial":"I.","affiliations":[{"id":13173,"text":"Ontario Ministry of Natural Resources, Upper Great Lakes Management Unit","active":true,"usgs":false}],"preferred":false,"id":587948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cholwek, Gary A. gcholwek@usgs.gov","contributorId":2719,"corporation":false,"usgs":true,"family":"Cholwek","given":"Gary","email":"gcholwek@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587944,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70034027,"text":"70034027 - 2009 - Predicting the natural flow regime: Models for assessing hydrological alteration in streams","interactions":[],"lastModifiedDate":"2017-10-25T12:51:49","indexId":"70034027","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the natural flow regime: Models for assessing hydrological alteration in streams","docAbstract":"Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also demonstrate how the models can be applied to predict expected natural flow characteristics at ungaged sites. ?? 2009 John Wiley & Sons, Ltd.","language":"English","publisher":"Wiley","doi":"10.1002/rra.1247","issn":"15351459","usgsCitation":"Carlisle, D., Falcone, J., Wolock, D., Meador, M.R., and Norris, R., 2009, Predicting the natural flow regime: Models for assessing hydrological alteration in streams: River Research and Applications, v. 26, no. 2, p. 118-136, https://doi.org/10.1002/rra.1247.","productDescription":"19 p.","startPage":"118","endPage":"136","ipdsId":"IP-004184","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":244636,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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States\"}}]}","volume":"26","issue":"2","noUsgsAuthors":false,"publicationDate":"2009-03-03","publicationStatus":"PW","scienceBaseUri":"505a81d1e4b0c8380cd7b753","contributors":{"authors":[{"text":"Carlisle, D.M.","contributorId":81059,"corporation":false,"usgs":true,"family":"Carlisle","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":443723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falcone, J.","contributorId":20548,"corporation":false,"usgs":true,"family":"Falcone","given":"J.","email":"","affiliations":[],"preferred":false,"id":443719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolock, D.M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":36601,"corporation":false,"usgs":true,"family":"Wolock","given":"D.M.","affiliations":[],"preferred":false,"id":443721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meador, M. R.","contributorId":74400,"corporation":false,"usgs":true,"family":"Meador","given":"M.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":443722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Norris, R.H.","contributorId":32016,"corporation":false,"usgs":true,"family":"Norris","given":"R.H.","email":"","affiliations":[],"preferred":false,"id":443720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206925,"text":"70206925 - 2009 - Efficacy of automatic vocalization recognition software for anuran monitoring","interactions":[],"lastModifiedDate":"2019-11-27T16:22:42","indexId":"70206925","displayToPublicDate":"2009-12-31T16:13:55","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"title":"Efficacy of automatic vocalization recognition software for anuran monitoring","docAbstract":"Surveys of vocalizations are a widely used method for monitoring anurans, but it can be difficult to coordinate standardized data collection across a large geographic area. Digital automated recording systems (ARS) offer a low-cost method for obtaining samples of anuran vocalizations, but the number of recordings can easily overwhelm human listeners. We tested Song Scope, an automatic vocalization recognition software program for personal computers to determine if this type of machine learning approach is currently a viable solution for anuran monitoring. For three species, Song Scope scanned more than 200 h of recordings in 3-20 h at the settings we chose. The software misidentified true calls (false positive) at rates of 2.7%-15.8% per species and failed to detect calls (false negative) in 45%-51% of recordings. There exists a tradeoff between false positive and false negative errors, which can be adjusted by setting the minimum criteria for the recognition software. Users of this approach should carefully consider their reasons for monitoring and how they intend to use the data before creating a large monitoring network.
Spacecraft continue to send back extraordinary amounts of data from Mars leaving scientists with the considerable task of analyzing an ever-increasing wealth of information. There are abundant uses for coregistered topography and images, but coregistering various datasets can be time-consuming and labor-intensive. We have developed a set of C-shell Unix scripts and Interactive Data Language (IDL) programs that overlay individual Mars Orbiter Laser Altimeter topography footprints on high-resolution Mars images including those from the Mars Orbiter Camera (MOC), the High Resolution Imaging Science Experiment (HiRISE), and the Context Camera (CTX). After all programs are installed, initial file customizations are made, and raw data are obtained, a user enters only three commands to overlay color-coded, scaled, and labeled topographic data on a high-resolution image. The codes have a variety of options including incremental labeling, zooming in on the topography, and shifting large-scale features to align with topography. They can be used as a group or individually. Our codes minimize human interaction in the coregistration process and produce usable, effective products.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2009.04.008","usgsCitation":"Kolb, K.J., and Okubo, C.H., 2009, Coregistration of Mars Orbiter Laser Altimeter (MOLA) topography with high-resolution Mars images: Computers & Geosciences, v. 35, no. 12, p. 2304-2313, https://doi.org/10.1016/j.cageo.2009.04.008.","productDescription":"10 p.","startPage":"2304","endPage":"2313","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":360978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"35","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kolb, Kelly J.","contributorId":210546,"corporation":false,"usgs":false,"family":"Kolb","given":"Kelly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":756438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Okubo, Chris H. 0000-0001-9776-8128 cokubo@usgs.gov","orcid":"https://orcid.org/0000-0001-9776-8128","contributorId":140482,"corporation":false,"usgs":true,"family":"Okubo","given":"Chris","email":"cokubo@usgs.gov","middleInitial":"H.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":false,"id":756439,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042088,"text":"70042088 - 2009 - TerraLook: A GIS-ready time-series of satellite imagery","interactions":[],"lastModifiedDate":"2021-11-08T15:30:34.388972","indexId":"70042088","displayToPublicDate":"2009-12-31T09:28:15","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"TerraLook: A GIS-ready time-series of satellite imagery","docAbstract":"The goal of TerraLook is to provide satellite images that anyone can use to see changes in the Earth's surface over time. Landsat and other satellites have been collecting images of the Earth from Space for more than 35 years. TerraLook allows users to create their own collections of georeferenced simulated natural-color JPEG images from Landsat (circa 1975, 1990, 2005) and ASTER (2000 to present) at no charge. The simulated natural colors in TerraLook images are consistently processed so that images from these time periods can be easily compared. TerraLook images are bundled with stands- compliant metadata, a world file, and an outline of each image's ground footprint, enabling their use in Geographic Information Systems and Web mapping applications. Different ArcGIS solutions were developed to use with TerraLook Collections. For ArcGIS and ArcGIS Explorer users, project files are available to permit TerraLook Collections to be easily integrated into GIS projects of educational curricula for visual analysis. A Pythion Script is available to extract vector data, such as country boundaries, protected areas, hydrography, and populated places, from global datasets to create extended TerraLook collections. Users can add local data, included ground photography, to the TerraLook Collections, These localized collections can be easily shared. An ArcGIS Publisher tool is provided with the ArcMap project file for publishing documents for use with the free ArcReader application.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"GIS—Designing our future","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"ESRI International User Conference","conferenceDate":"Jul 13-17, 2009","conferenceLocation":"San Diego, CA","language":"English","publisher":"ESRI","publisherLocation":"Reston, VA","usgsCitation":"Young, C., Geller, G., and Fosnight, E.A., 2009, TerraLook: A GIS-ready time-series of satellite imagery, in GIS—Designing our future, San Diego, CA, Jul 13-17, 2009, 14 p.","productDescription":"14 p.","ipdsId":"IP-013788","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":391470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391469,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings.esri.com/library/userconf/proc09/uc/abstracts/a1455.html"}],"country":"UNITED STATES","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Young, Claudia 0000-0002-0859-7206 claudia.young.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-0859-7206","contributorId":192363,"corporation":false,"usgs":true,"family":"Young","given":"Claudia","email":"claudia.young.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":826442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geller, Gary","contributorId":81395,"corporation":false,"usgs":true,"family":"Geller","given":"Gary","affiliations":[],"preferred":false,"id":826443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fosnight, Eugene A. 0000-0002-8557-3697 fosnight@usgs.gov","orcid":"https://orcid.org/0000-0002-8557-3697","contributorId":2961,"corporation":false,"usgs":true,"family":"Fosnight","given":"Eugene","email":"fosnight@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":826444,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98084,"text":"ofr20091249 - 2009 - Evansville Area Earthquake Hazards Mapping Project (EAEHMP)— Progress report, 2008","interactions":[],"lastModifiedDate":"2021-09-24T13:50:00.537569","indexId":"ofr20091249","displayToPublicDate":"2009-12-31T00:00:00","publicationYear":"2009","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":"2009-1249","title":"Evansville Area Earthquake Hazards Mapping Project (EAEHMP)— Progress report, 2008","docAbstract":"Maps of surficial geology, deterministic and probabilistic seismic hazard, and liquefaction potential index have been prepared by various members of the Evansville Area Earthquake Hazard Mapping Project for seven quadrangles in the Evansville, Indiana, and Henderson, Kentucky, metropolitan areas. The surficial geologic maps feature 23 types of surficial geologic deposits, artificial fill, and undifferentiated bedrock outcrop and include alluvial and lake deposits of the Ohio River valley. Probabilistic and deterministic seismic hazard and liquefaction hazard mapping is made possible by drawing on a wealth of information including surficial geologic maps, water well logs, and in-situ testing profiles using the cone penetration test, standard penetration test, down-hole shear wave velocity tests, and seismic refraction tests. These data were compiled and collected with contributions from the Indiana Geological Survey, Kentucky Geological Survey, Illinois State Geological Survey, United States Geological Survey, and Purdue University. Hazard map products are in progress and are expected to be completed by the end of 2009, with a public roll out in early 2010. Preliminary results suggest that there is a 2 percent probability that peak ground accelerations of about 0.3 g will be exceeded in much of the study area within 50 years, which is similar to the 2002 USGS National Seismic Hazard Maps for a firm rock site value. Accelerations as high as 0.4-0.5 g may be exceeded along the edge of the Ohio River basin. Most of the region outside of the river basin has a low liquefaction potential index (LPI), where the probability that LPI is greater than 5 (that is, there is a high potential for liquefaction) for a M7.7 New Madrid type event is only 20-30 percent. Within the river basin, most of the region has high LPI, where the probability that LPI is greater than 5 for a New Madrid type event is 80-100 percent.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091249","usgsCitation":"Boyd, O.S., Haase, J.L., and Moore, D., 2009, Evansville Area Earthquake Hazards Mapping Project (EAEHMP)— Progress report, 2008: U.S. Geological Survey Open-File Report 2009-1249, iv, 16 p., https://doi.org/10.3133/ofr20091249.","productDescription":"iv, 16 p.","onlineOnly":"Y","temporalStart":"2008-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":415,"text":"National Earthquake Information Center","active":false,"usgs":true}],"links":[{"id":125867,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1249.jpg"},{"id":389710,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_89351.htm"},{"id":13318,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1249/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Indiana, Kentucky","city":"Evansville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.64137268066406,\n 37.82876846980744\n ],\n [\n -87.44911193847656,\n 37.82876846980744\n ],\n [\n -87.44911193847656,\n 38.07133872299575\n ],\n [\n -87.64137268066406,\n 38.07133872299575\n ],\n [\n -87.64137268066406,\n 37.82876846980744\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a08e4b07f02db5f9d2b","contributors":{"authors":[{"text":"Boyd, Oliver S. olboyd@usgs.gov","contributorId":956,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":304096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haase, Jennifer L.","contributorId":50992,"corporation":false,"usgs":true,"family":"Haase","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":304097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, David W.","contributorId":63835,"corporation":false,"usgs":true,"family":"Moore","given":"David W.","affiliations":[],"preferred":false,"id":304098,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98083,"text":"sir20095246 - 2009 - Water-Quality Characterization of Surface Water in the Onondaga Lake Basin, Onondaga County, New York, 2005-08","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095246","displayToPublicDate":"2009-12-31T00:00:00","publicationYear":"2009","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":"2009-5246","title":"Water-Quality Characterization of Surface Water in the Onondaga Lake Basin, Onondaga County, New York, 2005-08","docAbstract":"Water-resources managers in Onondaga County, N.Y., have been faced with the challenge of improving the water-quality of Onondaga Lake. To assist in this endeavor, the U.S. Geological Survey undertook a 3-year basinwide study to assess the water quality of surface water in the Onondaga Lake Basin. The study quantified the relative contributions of nonpoint sources associated with the major land uses in the basin and also focused on known sources (streams with large sediment loads) and presumed sinks (Onondaga Reservoir and Otisco Lake) of sediment and nutrient loads, which previously had not been evaluated.\r\n\r\nWater samples were collected and analyzed for nutrients and suspended sediment at 26 surface-water sites and 4 springs in the 285-square-mile Onondaga Lake Basin from October 2005 through December 2008. More than 1,060 base-flow, stormflow, snowmelt, spring-water, and quality-assurance samples collected during the study were analyzed for ammonia, nitrite, nitrate-plus-nitrite, ammonia-plus-organic nitrogen, orthophosphate, phosphorus, and suspended sediment. The concentration of total suspended solids was measured in selected samples. Ninety-one additional samples were collected, including 80 samples from 4 county-operated sites, which were analyzed for suspended sediment or total suspended solids, and 8 precipitation and 3 snowpack samples, which were analyzed for nutrients. Specific conductance, salinity, dissolved oxygen, and water temperature were periodically measured in the field.\r\n\r\nThe mean concentrations of selected constituents in base-flow, stormflow, and snowmelt samples were related to the land use or land cover that either dominated the basin or had a substantial effect on the water quality of the basin. Almost 40 percent of the Onondaga Lake Basin is forested, 30 percent is in agricultural uses, and almost 21 percent, including the city of Syracuse, is in developed uses. The data indicated expected relative differences among the land types for concentrations of nitrate, ammonia-plus-organic nitrogen, and orthophosphate. The data departed from the expected relations for concentrations of phosphorus and suspended sediment, and plausible explanations for these departures were posited. Snowmelt concentrations of dissolved constituents generally were greater and those of particulate constituents were less than concentrations of these constituents in storm runoff. Presumably, the snowpack acted as a short-term sink for dissolved constituents that had accumulated from atmospheric deposition, and streambed erosion and resuspension of previously deposited material, rather than land-surface erosion, were the primary sources of particulate constituents in snowmelt flows.\r\n\r\nLongitudinal assessments documented the changes in the median concentrations of constituents in base flows and event flows (combined stormflow and snowmelt) from upstream to downstream monitoring sites along the two major tributaries to Onondaga Lake - Onondaga Creek and Ninemile Creek. Median base-flow concentrations of ammonia and phosphorus and event concentrations of ammonia increased in the downstream direction in both streams. Whereas median event concentrations of other constituents in Onondaga Creek displayed no consistent trends, concentrations of ammonia-plus-organic nitrogen, orthophosphate, phosphorus, and suspended sediment in Ninemile Creek decreased from upstream to downstream sites. Springs discharging from the Onondaga and Bertie Limestone had measureable effects on water temperatures in the receiving streams and increased salinity and values of specific conductance in base flows.\r\n\r\nLoads of selected nutrients and suspended sediment transported in three tributaries of Otisco Lake were compared with loads from 1981-83. Loads of ammonia-plus-organic nitrogen and orthophosphate decreased from 1981-83 to 2005-08, but those of nitrate-plus-nitrite, phosphorus, and suspended sediment increased. The largest load increase was for suspende","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095246","collaboration":"Prepared in cooperation with the Onondaga Lake Partnership","usgsCitation":"Coon, W.F., Hayhurst, B.A., Kappel, W.M., Eckhardt, D., and Szabo, C.O., 2009, Water-Quality Characterization of Surface Water in the Onondaga Lake Basin, Onondaga County, New York, 2005-08: U.S. Geological Survey Scientific Investigations Report 2009-5246, vi, 68 p., https://doi.org/10.3133/sir20095246.","productDescription":"vi, 68 p.","additionalOnlineFiles":"N","temporalStart":"2005-10-01","temporalEnd":"2008-12-31","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":125943,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5246.jpg"},{"id":13317,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5246/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.4,42.784166666666664 ], [ -76.4,43.1175 ], [ -76.05,43.1175 ], [ -76.05,42.784166666666664 ], [ -76.4,42.784166666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49efe4b07f02db5edd91","contributors":{"authors":[{"text":"Coon, William F. 0000-0002-7007-7797 wcoon@usgs.gov","orcid":"https://orcid.org/0000-0002-7007-7797","contributorId":1765,"corporation":false,"usgs":true,"family":"Coon","given":"William","email":"wcoon@usgs.gov","middleInitial":"F.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":304094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eckhardt, David A.V.","contributorId":80233,"corporation":false,"usgs":true,"family":"Eckhardt","given":"David A.V.","affiliations":[],"preferred":false,"id":304095,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szabo, Carolyn O. cszabo@usgs.gov","contributorId":2840,"corporation":false,"usgs":true,"family":"Szabo","given":"Carolyn","email":"cszabo@usgs.gov","middleInitial":"O.","affiliations":[],"preferred":true,"id":304093,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193855,"text":"70193855 - 2009 - Compositional variation in the chevkinite group: new data from igneous and metamorphic rocks","interactions":[],"lastModifiedDate":"2017-11-07T12:06:49","indexId":"70193855","displayToPublicDate":"2009-12-31T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2748,"text":"Mineralogical Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Compositional variation in the chevkinite group: new data from igneous and metamorphic rocks","docAbstract":"Electron microprobe analyses are presented of chevkinite-group minerals from Canada, USA, Guatemala, Norway, Scotland, Italy and India. The host rocks are metacarbonates, alkaline and subalkaline granitoids, quartz-bearing pegmatites, carbonatite and an inferred K-rich tuff. The analyses extend slightly the range of compositions in the chevkinite group, e.g. the most MgO-rich phases yet recorded, and we report two further examples where La is the dominant cation in the A site. Patchily- zoned crystals from Virginia and Guatemala contain both perrierite and chevkinite compositions. The new and published analyses are used to review compositional variation in minerals of the perrierite subgroup, which can form in a wide range of host rock compositions and over a substantial pressure- temperature range. The dominant substitutions in the various cation sites and a generalized substitution scheme are described.","language":"English","publisher":"The Mineralogical Society","doi":"10.1180/minmag.2009.073.5.777","usgsCitation":"Belkin, H.E., MacDonald, R., Wall, F., and Baginski, B., 2009, Compositional variation in the chevkinite group: new data from igneous and metamorphic rocks: Mineralogical Magazine, v. 73, no. 5, p. 777-796, https://doi.org/10.1180/minmag.2009.073.5.777.","productDescription":"20 p.","startPage":"777","endPage":"796","ipdsId":"IP-011575","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":348366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Guatemala, India, Italy, Norway, United Kingdom, United 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PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5a07f827e4b09af898c8ce07","contributors":{"authors":[{"text":"Belkin, Harvey E. 0000-0001-7879-6529 hbelkin@usgs.gov","orcid":"https://orcid.org/0000-0001-7879-6529","contributorId":581,"corporation":false,"usgs":true,"family":"Belkin","given":"Harvey","email":"hbelkin@usgs.gov","middleInitial":"E.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":720687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacDonald, R.","contributorId":200066,"corporation":false,"usgs":false,"family":"MacDonald","given":"R.","email":"","affiliations":[],"preferred":false,"id":720889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wall, F.","contributorId":91336,"corporation":false,"usgs":true,"family":"Wall","given":"F.","email":"","affiliations":[],"preferred":false,"id":720890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baginski, B.","contributorId":80516,"corporation":false,"usgs":true,"family":"Baginski","given":"B.","email":"","affiliations":[],"preferred":false,"id":720891,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188856,"text":"70188856 - 2009 - Nocturnal movements of desert bighorn sheep in the Muddy Mountains, Nevada","interactions":[],"lastModifiedDate":"2017-06-27T11:06:07","indexId":"70188856","displayToPublicDate":"2009-12-31T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1379,"text":"Desert Bighorn Council Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Nocturnal movements of desert bighorn sheep in the Muddy Mountains, Nevada","docAbstract":"Adequate management of a species requires complete knowledge of its ecology, including both nocturnal and diurnal behavior. Knowledge of the movement behavior of bighorn sheep can provide insight for understanding spatial population processes as the combined result of individual behavior, physiological constraints, and fine-scale environmental influences. However, because of past difficulties in tracking radio-collared animals in the dark, little is known about nocturnal movements of many ungulates, including desert bighorn sheep (Ovis canadensis nelsoni). The use of GPS collars that supply sequential location records over a 24-hour period has provided new opportunities for recording movements of animals. We report findings from a preliminary analysis of data on nocturnal movements of desert bighorn sheep wearing GPS collars in the Muddy Mountains, Nevada. The study is part of a larger research project on movement patterns aimed at assessing the connectivity of bighorn sheep populations that comprise the metapopulation in southern Nevada. We recorded nighttime locations at 2100 and 0400 PST and calculated a total of 8,758 nocturnal movement distances for 12 ewes and 16 rams. Nocturnal movements were characteristic of all individuals. Bighorn sheep varied in the magnitude of movement from night to night and there were significant differences among individuals in the mean distance moved. Females had a greater proportion of short movement distances when compared to males; males had the greatest proportion of long distance movements. Movement distances were affected by sex, season, and percent of the moon’s surface illumination. Mean movement distances of males were greater than those of females. For both males and females, mean movement distances were shortest during the late spring months (April-June) and greatest during summer (July–September). Mean movement distances were greatest when the moon was brightest for all seasons except late spring, when movement distances for both sexes were shortest. We also describe movement distances >1 km (19% ewes, 81% rams) relative to movements within or between 50% core use areas, and nighttime intermountain and intra-mountain travel.","language":"English","publisher":"Desert Bighorn Council","usgsCitation":"Longshore, K.M., Lowrey, C.E., Jeffress, M., and Thompson, D.B., 2009, Nocturnal movements of desert bighorn sheep in the Muddy Mountains, Nevada: Desert Bighorn Council Transactions, v. 50, p. 18-31.","productDescription":"14 p.","startPage":"18","endPage":"31","ipdsId":"IP-017019","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":342906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States ","otherGeospatial":" Black Mountain, Muddy 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\"}}]}","volume":"50","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59521d29e4b062508e3c36e7","contributors":{"authors":[{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":700709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowrey, Chris E. 0000-0001-5084-7275 clowrey@usgs.gov","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":3225,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","email":"clowrey@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":700710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeffress, Matthew","contributorId":193517,"corporation":false,"usgs":false,"family":"Jeffress","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":700711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Daniel B.","contributorId":193518,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":700712,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98078,"text":"ofr20091280 - 2009 - Land-cover change in the Lower Mississippi Valley, 1973-2000","interactions":[],"lastModifiedDate":"2017-03-29T13:28:24","indexId":"ofr20091280","displayToPublicDate":"2009-12-30T00:00:00","publicationYear":"2009","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":"2009-1280","title":"Land-cover change in the Lower Mississippi Valley, 1973-2000","docAbstract":"The Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. The project is coordinated by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in conjunction with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 were processed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into four temporal periods: 1973 to1980, 1980 to 1986, 1986 to 1992, 1992 to 2000 and overall from 1973 to 2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation.
The rates of land-cover change were estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images were used to interpret land-cover change. The sample block data then were incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20091280","usgsCitation":"Karstensen, K.A., and Sayler, K., 2009, Land-cover change in the Lower Mississippi Valley, 1973-2000: U.S. Geological Survey Open-File Report 2009-1280, iv, 13 p., https://doi.org/10.3133/ofr20091280.","productDescription":"iv, 13 p.","temporalStart":"1973-01-01","temporalEnd":"2000-12-31","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":383,"text":"Mid-Continent Geographic Science Center","active":true,"usgs":true}],"links":[{"id":338631,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2009/1280/pdf/of2009-1280.pdf"},{"id":125869,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1280.jpg"},{"id":13312,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1280/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95,29 ], [ -95,38 ], [ -87,38 ], [ -87,29 ], [ -95,29 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6ae344","contributors":{"authors":[{"text":"Karstensen, Krista A. kkarstensen@usgs.gov","contributorId":286,"corporation":false,"usgs":true,"family":"Karstensen","given":"Krista","email":"kkarstensen@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":304081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sayler, Kristi L. 0000-0003-2514-242X sayler@usgs.gov","orcid":"https://orcid.org/0000-0003-2514-242X","contributorId":2988,"corporation":false,"usgs":true,"family":"Sayler","given":"Kristi","email":"sayler@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":304082,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}