{"pageNumber":"615","pageRowStart":"15350","pageSize":"25","recordCount":46679,"records":[{"id":70040089,"text":"sir20125163 - 2012 - Description of 2005-10 domestic water use for selected U.S. cities and guidance for estimating domestic water use","interactions":[],"lastModifiedDate":"2012-09-28T17:16:19","indexId":"sir20125163","displayToPublicDate":"2012-09-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5163","title":"Description of 2005-10 domestic water use for selected U.S. cities and guidance for estimating domestic water use","docAbstract":"Domestic water-use and related socioeconomic and climatic data for 2005-10 were used in an analysis of 21 selected U.S. cities to describe recent domestic per capita water use, investigate variables that potentially affect domestic water use, and provide guidance for estimating domestic water use. Domestic water use may be affected by a combination of several factors. Domestic per capita water use for the selected cities ranged from a median annual average of 43 to 177 gallons per capita per day (gpcd). In terms of year-to-year variability in domestic per capita water use for the selected cities, the difference from the median ranged from ± 7 to ± 26 percent with an overall median variability of ± 14 percent. As a percentage of total annual water use, median annual domestic water use for the selected cities ranged from 33 to 71 percent with an overall median of 57 percent. Monthly production and water sales data were used to calculate daily per capita water use rates for the lowest 3 consecutive months (low-3) and the highest 3 consecutive months (high-3) of usage. Median low-3 domestic per capita water use for 16 selected cities ranged from 40 to 100 gpcd. Median high-3 domestic per capita water use for 16 selected cities ranged from 53 to 316 gpcd. In general, the median domestic water use as a percentage of the median total water use for 16 selected cities was similar for the low-3 and high-3 periods. Statistical analyses of combined data for the selected cities indicated that none of the socioeconomic variables, including cost of water, were potentially useful as determinants of domestic water use at the national level. However, specific socioeconomic variables may be useful for the estimation of domestic water use at the State or local level. Different socioeconomic variables may be useful in different States. Statistical analyses indicated that specific climatic variables may be useful for the estimation of domestic water use for some, but not all, of the selected cities. National average public supply per capita water use declined from 185 gpcd in 1990 to 171 gpcd in 2005. National average domestic delivery per capita water use declined from 105 gpcd in 1990 to 99 gpcd in 2005. Average State domestic delivery per capita water use ranged from 51 to 189 gpcd in 2005. The average annual total per capita water use in 19 selected cities that provided data for each year declined from 167 gpcd in 2006 to 145 gpcd in 2010. During this time period, average per capita water use measured during the low-3 period each year declined from 115 to 102 gpcd, and average per capita use measured during the high-3 period declined from 250 to 211 gpcd. Continued collection of data on water deliveries to domestic populations, as well as updated estimates of the population served by these deliveries, is recommended for determination of regional and temporal trends in domestic per capita water use. Declines in various measures of per capita water use have been observed in recent years for several States with municipal water use data-collection programs. Domestic self-supplied water use historically has not been metered. Estimates of self-supplied domestic water use are made using estimates of the population that is not served by public water suppliers and per capita coefficients. For 2005, the average State domestic self-supplied per capita use in the United States ranged from 50 to 206 gpcd. The median domestic self-supplied per capita use was 76 gpcd for States in which standard coefficients were used, and 98 gpcd for States in which coefficients were based on domestic deliveries from public supply. In specific areas with scarce resources or increasing numbers of households with private wells, an assessment of domestic water use may require metering of households or development of more specific per capita coefficients to estimate water demand.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125163","usgsCitation":"Kenny, J., and Juracek, K.E., 2012, Description of 2005-10 domestic water use for selected U.S. cities and guidance for estimating domestic water use: U.S. Geological Survey Scientific Investigations Report 2012-5163, v, 31 p., https://doi.org/10.3133/sir20125163.","productDescription":"v, 31 p.","numberOfPages":"42","onlineOnly":"Y","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":262134,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5163/","linkFileType":{"id":5,"text":"html"}},{"id":262135,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5163/sir12_5163.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262141,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5163.gif"}],"country":"United States","state":"California;Kansas;Mississippi;Montana;Texas;Wisconsin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4,25.833333333333332 ], [ -124.4,49 ], [ -86.81666666666666,49 ], [ -86.81666666666666,25.833333333333332 ], [ -124.4,25.833333333333332 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5066250fe4b053bff18e1bec","contributors":{"authors":[{"text":"Kenny, Joan F.","contributorId":69132,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan F.","affiliations":[],"preferred":false,"id":467702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Juracek, Kyle E. 0000-0002-2102-8980 kjuracek@usgs.gov","orcid":"https://orcid.org/0000-0002-2102-8980","contributorId":2022,"corporation":false,"usgs":true,"family":"Juracek","given":"Kyle","email":"kjuracek@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":467701,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040105,"text":"ofr20121213 - 2012 - Toxicity, sublethal effects, and potential modes of action of select fungicides on freshwater fish and invertebrates","interactions":[],"lastModifiedDate":"2024-03-04T18:34:47.127959","indexId":"ofr20121213","displayToPublicDate":"2012-09-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1213","title":"Toxicity, sublethal effects, and potential modes of action of select fungicides on freshwater fish and invertebrates","docAbstract":"<p><span>Despite decades of agricultural and urban use of fungicides and widespread detection of these pesticides in surface waters, relatively few data are available on the effects of fungicides on fish and invertebrates in the aquatic environment. Nine fungicides are reviewed in this report: azoxystrobin, boscalid, chlorothalonil, fludioxonil, myclobutanil, fenarimol, pyraclostrobin, pyrimethanil, and zoxamide. These fungicides were identified as emerging chemicals of concern because of their high or increasing global use rates, detection frequency in surface waters, or likely persistence in the environment. A review of the literature revealed significant sublethal effects of fungicides on fish, aquatic invertebrates, and ecosystems, including zooplankton and fish reproduction, fish immune function, zooplankton community composition, metabolic enzymes, and ecosystem processes, such as leaf decomposition in streams, among other biological effects. Some of these effects can occur at fungicide concentrations well below single-species acute lethality values (48- or 96-hour concentration that effects a response in 50 percent of the organisms, that is, effective concentration killing 50 percent of the organisms in 48 or 96 hours) and chronic sublethal values (for example, 21-day no observed adverse effects concentration), indicating that single-species toxicity values may dramatically underestimate the toxic potency of some fungicides. Fungicide modes of toxic action in fungi can sometimes reflect the biochemical and (or) physiological effects of fungicides observed in vertebrates and invertebrates; however, far more studies are needed to explore the potential to predict effects in nontarget organisms based on specific fungicide modes of toxic action. Fungicides can also have additive and (or) synergistic effects when used with other fungicides and insecticides, highlighting the need to study pesticide mixtures that occur in surface waters. For fungicides that partition to organic matter in sediment and soils, it is particularly important to determine their effects on freshwater mussels and other freshwater benthic invertebrates in contact with sediments, as available toxicity studies with pelagic species, mainly&nbsp;</span><i>Daphnia magna</i><span>, may not be representative of these benthic organisms. Finally, there is a critical need for studies of the chronic effects of fungicides on reproduction, immunocompetence, and ecosystem function; sublethal endpoints with population and community-level relevance.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121213","usgsCitation":"Elskus, A.A., 2012, Toxicity, sublethal effects, and potential modes of action of select fungicides on freshwater fish and invertebrates (Version 1.0: September 27, 2012; Version 1,1: November 25, 2014): U.S. Geological Survey Open-File Report 2012-1213, vii, 42 p., https://doi.org/10.3133/ofr20121213.","productDescription":"vii, 42 p.","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040603","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":262163,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1213/","linkFileType":{"id":5,"text":"html"}},{"id":262162,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1213/pdf/ofr2012-1213.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262167,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121213.jpg"}],"edition":"Version 1.0: September 27, 2012; Version 1,1: November 25, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50662516e4b053bff18e1c16","contributors":{"authors":[{"text":"Elskus, Adria A.","contributorId":14521,"corporation":false,"usgs":true,"family":"Elskus","given":"Adria","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":467725,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040093,"text":"sir20125202 - 2012 - Estimation of evaporation from open water - A review of selected studies, summary of U.S. Army Corps of Engineers data collection and methods, and evaluation of two methods for estimation of evaporation from five reservoirs in Texas","interactions":[],"lastModifiedDate":"2016-08-08T08:24:42","indexId":"sir20125202","displayToPublicDate":"2012-09-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5202","title":"Estimation of evaporation from open water - A review of selected studies, summary of U.S. Army Corps of Engineers data collection and methods, and evaluation of two methods for estimation of evaporation from five reservoirs in Texas","docAbstract":"<p>Organizations responsible for the management of water resources, such as the U.S. Army Corps of Engineers (USACE), are tasked with estimation of evaporation for water-budgeting and planning purposes. The USACE has historically used Class A pan evaporation data (pan data) to estimate evaporation from reservoirs but many USACE Districts have been experimenting with other techniques for an alternative to collecting pan data. The energy-budget method generally is considered the preferred method for accurate estimation of open-water evaporation from lakes and reservoirs. Complex equations to estimate evaporation, such as the Penman, DeBruin-Keijman, and Priestley-Taylor, perform well when compared with energy-budget method estimates when all of the important energy terms are included in the equations and ideal data are collected. However, sometimes nonideal data are collected and energy terms, such as the change in the amount of stored energy and advected energy, are not included in the equations. When this is done, the corresponding errors in evaporation estimates are not quantifiable. Much simpler methods, such as the Hamon method and a method developed by the U.S. Weather Bureau (USWB) (renamed the National Weather Service in 1970), have been shown to provide reasonable estimates of evaporation when compared to energy-budget method estimates. Data requirements for the Hamon and USWB methods are minimal and sometimes perform well with remotely collected data. The Hamon method requires average daily air temperature, and the USWB method requires daily averages of air temperature, relative humidity, wind speed, and solar radiation. Estimates of annual lake evaporation from pan data are frequently within 20 percent of energy-budget method estimates. Results of evaporation estimates from the Hamon method and the USWB method were compared against historical pan data at five selected reservoirs in Texas (Benbrook Lake, Canyon Lake, Granger Lake, Hords Creek Lake, and Sam Rayburn Lake) to evaluate their performance and to develop coefficients to minimize bias for the purpose of estimating reservoir evaporation with accuracies similar to estimates of evaporation obtained from pan data. The modified Hamon method estimates of reservoir evaporation were similar to estimates of reservoir evaporation from pan data for daily, monthly, and annual time periods. The modified Hamon method estimates of annual reservoir evaporation were always within 20 percent of annual reservoir evaporation from pan data. Unmodified and modified USWB method estimates of annual reservoir evaporation were within 20 percent of annual reservoir evaporation from pan data for about 91 percent of the years compared. Average daily differences between modified USWB method estimates and estimates from pan data as a percentage of the average amount of daily evaporation from pan data were within 20 percent for 98 percent of the months. Without any modification to the USWB method, average daily differences as a percentage of the average amount of daily evaporation from pan data were within 20 percent for 73 percent of the months. Use of the unmodified USWB method is appealing because it means estimates of average daily reservoir evaporation can be made from air temperature, relative humidity, wind speed, and solar radiation data collected from remote weather stations without the need to develop site-specific coefficients from historical pan data. Site-specific coefficients would need to be developed for the modified version of the Hamon method.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125202","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District","usgsCitation":"Harwell, G.R., 2012, Estimation of evaporation from open water - A review of selected studies, summary of U.S. Army Corps of Engineers data collection and methods, and evaluation of two methods for estimation of evaporation from five reservoirs in Texas: U.S. Geological Survey Scientific Investigations Report 2012-5202, vii, 96 p., https://doi.org/10.3133/sir20125202.","productDescription":"vii, 96 p.","numberOfPages":"107","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":262142,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5202.gif"},{"id":262140,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5202/pdf/sir2012-5202.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262139,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5202/","linkFileType":{"id":5,"text":"html"}}],"projection":"Albers Equal Area","datum":"North American Datum of 1983","country":"United States","state":"Texas","city":"Austin, Dallas, Fort Worth, Houston, San Angelo, San Antonio, Waco","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.83333333333333,29 ], [ -100.83333333333333,34.333333333333336 ], [ -93.33333333333333,34.333333333333336 ], [ -93.33333333333333,29 ], [ -100.83333333333333,29 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50662510e4b053bff18e1bf5","contributors":{"authors":[{"text":"Harwell, Glenn R. gharwell@usgs.gov","contributorId":3789,"corporation":false,"usgs":true,"family":"Harwell","given":"Glenn","email":"gharwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467703,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040101,"text":"70040101 - 2012 - Clutch and egg allometry of the turtle Mauremys leprosa (Chelonia: Geoemydidae) from a polluted peri-urban river in west-central Morocco","interactions":[],"lastModifiedDate":"2013-02-24T12:48:53","indexId":"70040101","displayToPublicDate":"2012-09-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1895,"text":"Herpetological Journal","active":true,"publicationSubtype":{"id":10}},"title":"Clutch and egg allometry of the turtle Mauremys leprosa (Chelonia: Geoemydidae) from a polluted peri-urban river in west-central Morocco","docAbstract":"We examined the relationships of clutch size (CS) and egg size to female body size (straight-line carapace length, CL) in a population of the turtle Mauremys leprosa from a polluted segment of oued (river) Tensift in arid west-central Morocco. Twenty-eight adult females were collected in May&ndash;July, 2009 and all were gravid. Each was weighed, measured, humanely euthanized and then dissected. Oviductal shelled eggs were removed, weighed (egg mass, EM) and measured for length (EL) and width (EW). Clutch mass (CM) was the sum of EM for a clutch. Pelvic aperture width (PAW) was measured at the widest point between the ilia bones through which eggs must pass at oviposition. The smallest gravid female had a CL of 124.0 mm. Mean CS was relatively large (9.7&plusmn;2.0 eggs, range: 3&ndash;13) and may reflect high productivity associated with polluted (eutrophic) waters. Regression analyses were conducted using log-transformed data. CM increased isometrically with maternal body size. CS, EW and EM were all significantly hypoallometric in their relationship with CL. EL did not change significantly with increases in CL. EW increased at a hypoallometric rate with increasing CL but was unconstrained by PAW since the widest egg was smaller than the narrowest PAW measurement when excluding the three smallest females. Smaller females may have EW constrained by PAW. As females increase in size they increase both clutch size and egg width in contradiction to predictions of optimal egg size theory.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Herpetological Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"British Herpetological Society","publisherLocation":"Montrose, Angus, U.K.","usgsCitation":"Naimi, M., Znari, M., Lovich, J.E., Feddadi, Y., and Baamrane, M.A., 2012, Clutch and egg allometry of the turtle Mauremys leprosa (Chelonia: Geoemydidae) from a polluted peri-urban river in west-central Morocco: Herpetological Journal, v. 22, no. 1, p. 43-49.","productDescription":"7 p.","startPage":"43","endPage":"49","numberOfPages":"7","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":262154,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262144,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://www.ingentaconnect.com/content/bhs/thj/2012/00000022/00000001/art00007","linkFileType":{"id":5,"text":"html"}}],"country":"Morocco","otherGeospatial":"Tensift River","volume":"22","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5066250de4b053bff18e1be6","contributors":{"authors":[{"text":"Naimi, Mohamed","contributorId":40838,"corporation":false,"usgs":true,"family":"Naimi","given":"Mohamed","email":"","affiliations":[],"preferred":false,"id":467716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Znari, Mohammed","contributorId":42472,"corporation":false,"usgs":true,"family":"Znari","given":"Mohammed","email":"","affiliations":[],"preferred":false,"id":467717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":467715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feddadi, Youssef","contributorId":51590,"corporation":false,"usgs":true,"family":"Feddadi","given":"Youssef","email":"","affiliations":[],"preferred":false,"id":467718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baamrane, Moulay Abdeljalil Ait","contributorId":103516,"corporation":false,"usgs":true,"family":"Baamrane","given":"Moulay","email":"","middleInitial":"Abdeljalil Ait","affiliations":[],"preferred":false,"id":467719,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040079,"text":"70040079 - 2012 - Electrical anisotropy of gas hydrate-bearing sand reservoirs in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2012-10-03T17:16:15","indexId":"70040079","displayToPublicDate":"2012-09-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Electrical anisotropy of gas hydrate-bearing sand reservoirs in the Gulf of Mexico","docAbstract":"We present new results and interpretations of the electricalanisotropy and reservoir architecture in gashydrate-bearingsands using logging data collected during the Gulf of MexicoGasHydrate Joint Industry Project Leg II. We focus specifically on sandreservoirs in Hole Alaminos Canyon 21 A (AC21-A), Hole Green Canyon 955 H (GC955-H) and Hole Walker Ridge 313 H (WR313-H). Using a new logging-while-drilling directional resistivity tool and a one-dimensional inversion developed by Schlumberger, we resolve the resistivity of the current flowing parallel to the bedding, <i>R</i><sub>&#124;</sub> and the resistivity of the current flowing perpendicular to the bedding, <i>R</i><sub><u>&#124;</u></sub>. We find the sandreservoir in Hole AC21-A to be relatively isotropic, with <i>R</i><sub>&#124;</sub> and <i>R</i><sub><u>&#124;</u></sub> values close to 2 &Omega; m. In contrast, the gashydrate-bearingsandreservoirs in Holes GC955-H and WR313-H are highly anisotropic. In these reservoirs, <i>R</i><sub>&#124;</sub> is between 2 and 30 &Omega; m, and <i>R</i><sub><u>&#124;</u></sub> is generally an order of magnitude higher. Using Schlumberger's WebMI models, we were able to replicate multiple resistivity measurements and determine the formation resistivity the gashydrate-bearingsandreservoir in Hole WR313-H. The results showed that gashydrate saturations within a single reservoir unit are highly variable. For example, the sand units in Hole WR313-H contain thin layers (on the order of 10-100 cm) with varying gashydrate saturations between 15 and 95%. Our combined modeling results clearly indicate that the gashydrate-bearingsandreservoirs in Holes GC955-H and WR313-H are highly anisotropic due to varying saturations of gashydrate forming in thin layers within larger sand units.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.marpetgeo.2011.09.003","usgsCitation":"Cook, A.E., Anderson, B.I., Rasmus, J., Sun, K., Li, Q., Collett, T.S., and Goldberg, D.S., 2012, Electrical anisotropy of gas hydrate-bearing sand reservoirs in the Gulf of Mexico: Marine and Petroleum Geology, v. 34, no. 1, p. 72-84, https://doi.org/10.1016/j.marpetgeo.2011.09.003.","productDescription":"13 p.","startPage":"72","endPage":"84","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":474342,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.7916/d8rf64h0","text":"External Repository"},{"id":262157,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262145,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2011.09.003"}],"country":"United States","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.85,18.166666666666668 ], [ -97.85,30.383333333333333 ], [ -81.03333333333333,30.383333333333333 ], [ -81.03333333333333,18.166666666666668 ], [ -97.85,18.166666666666668 ] ] ] } } ] }","volume":"34","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50662510e4b053bff18e1bf2","contributors":{"authors":[{"text":"Cook, Anne E.","contributorId":84612,"corporation":false,"usgs":true,"family":"Cook","given":"Anne","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":467683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Barbara I.","contributorId":69832,"corporation":false,"usgs":true,"family":"Anderson","given":"Barbara","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":467682,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rasmus, John","contributorId":15451,"corporation":false,"usgs":true,"family":"Rasmus","given":"John","email":"","affiliations":[],"preferred":false,"id":467680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sun, Keli","contributorId":88993,"corporation":false,"usgs":true,"family":"Sun","given":"Keli","email":"","affiliations":[],"preferred":false,"id":467684,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Qiming","contributorId":36792,"corporation":false,"usgs":true,"family":"Li","given":"Qiming","email":"","affiliations":[],"preferred":false,"id":467681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":467679,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goldberg, David S.","contributorId":96133,"corporation":false,"usgs":true,"family":"Goldberg","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":467685,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70044219,"text":"70044219 - 2012 - Survey of roadside alien plants in Hawai`i Volcanoes National Park and adjacent residential areas 2001-2005","interactions":[],"lastModifiedDate":"2018-01-05T12:40:28","indexId":"70044219","displayToPublicDate":"2012-09-27T18:30:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-032","title":"Survey of roadside alien plants in Hawai`i Volcanoes National Park and adjacent residential areas 2001-2005","docAbstract":"<p>The sides of all paved roads of Hawai`i Volcanoes National Park (HAVO) were surveyed on foot in 2001 to 2005, and the roadside presence of 240 target invasive and potentially invasive alien plant species was recorded in mile-long increments. Buffer zones 5&ndash;10 miles (8&ndash;16 km) long along Highway 11 on either side of the Kīlauea and Kahuku Units of the park, as well as Wright Road that passed by the disjunct `Ōla`a Tract Unit, were included in the survey. Highway 11 is the primary road through the park and a major island thoroughfare. Three residential subdivisions adjacent to the park were similarly surveyed in 0.5&ndash;1 mile (0.8&ndash;1.6 km) intervals in 2003, and data were analyzed separately. Two roads to the east and northeast were also surveyed, but data from these disjunct areas were analyzed separately from park roads. In total, 174 of the target alien species were observed along HAVO roads and buffers, exclusive of residential areas, and the mean number of target aliens per mile surveyed was 20.6. Highway 11 and its buffer zones had the highest mean number of target alien plants per mile (26.7) of all park roads, and the Mauna Loa Strip Road had the lowest mean (11.7). Segments of Highway 11 adjacent to HAVO and Wright Road next to `Ōla`a Tract had mean numbers of target alien per mile (24&ndash;47) higher than those of any internal road. Alien plant frequencies were summarized for each road in HAVO. Fifteen new records of vascular plants for HAVO were observed and collected along park roads. An additional 28 alien plant species not known from HAVO were observed along the buffer segments of Highway 11 adjacent to the park. Within the adjacent residential subdivisions, 65 target alien plant species were sighted along roadsides. At least 15 potentially invasive species not currently found within HAVO were observed along residential roads, and several other species found there have been previously eliminated from the park or controlled to remnant populations. Data collected from this survey can be used by the park and other landowners to help detect and manage invasive plant species that threaten the natural resources of their lands, and survey findings will inform managers of threats from alien species established along corridors beyond park boundaries. Recommendations were made for refining the list of incipient invasive plant species to search for near the park and for the repetition of periodic roadside weed surveys in the park.</p>","publisher":"University of Hawai'i at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Bio, K.F., Pratt, L.W., and Jacobi, J.D., 2012, Survey of roadside alien plants in Hawai`i Volcanoes National Park and adjacent residential areas 2001-2005: Technical Report HCSU-032, iv, 67.","productDescription":"iv, 67","numberOfPages":"73","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037461","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ac50e7e4b0d1835674b32f","contributors":{"authors":[{"text":"Bio, Keali’i F.","contributorId":79371,"corporation":false,"usgs":true,"family":"Bio","given":"Keali’i","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":517241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, Linda W. lpratt@usgs.gov","contributorId":3708,"corporation":false,"usgs":true,"family":"Pratt","given":"Linda","email":"lpratt@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":644951,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":644952,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040070,"text":"sir20125175 - 2012 - Method for estimating potential wetland extent by utilizing streamflow statistics and flood-inundation mapping techniques: Pilot study for land along the Wabash River near Terre Haute, Indiana","interactions":[],"lastModifiedDate":"2012-09-27T17:16:16","indexId":"sir20125175","displayToPublicDate":"2012-09-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5175","title":"Method for estimating potential wetland extent by utilizing streamflow statistics and flood-inundation mapping techniques: Pilot study for land along the Wabash River near Terre Haute, Indiana","docAbstract":"Potential wetland extents were estimated for a 14-mile reach of the Wabash River near Terre Haute, Indiana. This pilot study was completed by the U.S. Geological Survey in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service (NRCS). The study showed that potential wetland extents can be estimated by analyzing streamflow statistics with the available streamgage data, calculating the approximate water-surface elevation along the river, and generating maps by use of flood-inundation mapping techniques. Planning successful restorations for Wetland Reserve Program (WRP) easements requires a determination of areas that show evidence of being in a zone prone to sustained or frequent flooding. Zone determinations of this type are used by WRP planners to define the actively inundated area and make decisions on restoration-practice installation. According to WRP planning guidelines, a site needs to show evidence of being in an \"inundation zone\" that is prone to sustained or frequent flooding for a period of 7 consecutive days at least once every 2 years on average in order to meet the planning criteria for determining a wetland for a restoration in agricultural land. By calculating the annual highest 7-consecutive-day mean discharge with a 2-year recurrence interval (7MQ2) at a streamgage on the basis of available streamflow data, one can determine the water-surface elevation corresponding to the calculated flow that defines the estimated inundation zone along the river. By using the estimated water-surface elevation (\"inundation elevation\") along the river, an approximate extent of potential wetland for a restoration in agricultural land can be mapped. As part of the pilot study, a set of maps representing the estimated potential wetland extents was generated in a geographic information system (GIS) application by combining (1) a digital water-surface plane representing the surface of inundation elevation that sloped in the downstream direction of flow and (2) land-surface elevation data. These map products from the pilot study will aid the NRCS and its partners with the onsite inundation-zone verification in agricultural land for a potential restoration and will assist in determining at what elevation to plant hardwood trees for increased survivability on ground above frequently flooded terraces.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125175","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service","usgsCitation":"Kim, M.H., Ritz, C.T., and Arvin, D.V., 2012, Method for estimating potential wetland extent by utilizing streamflow statistics and flood-inundation mapping techniques: Pilot study for land along the Wabash River near Terre Haute, Indiana: U.S. Geological Survey Scientific Investigations Report 2012-5175, Report: vi, 15 p.; Figures A1-1, A1-2, A2-1, A2-2, A3-1, A3-2: 17 x 12 inches, https://doi.org/10.3133/sir20125175.","productDescription":"Report: vi, 15 p.; Figures A1-1, A1-2, A2-1, A2-2, A3-1, A3-2: 17 x 12 inches","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":262120,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5175.bmp"},{"id":262110,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5175/","linkFileType":{"id":5,"text":"html"}},{"id":262111,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5175/pdf/sir2012-5175_092012.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262112,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5175/pdf/figA1-1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262117,"rank":405,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5175/pdf/figA3-2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262113,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5175/pdf/figA1-2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262114,"rank":402,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5175/pdf/figA2-1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262115,"rank":403,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5175/pdf/figA2-2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262116,"rank":404,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5175/pdf/figA3-1.pdf","linkFileType":{"id":1,"text":"pdf"}}],"projection":"Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Indiana","city":"Terre Haute","otherGeospatial":"Wabash River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.5175,39.38333333333333 ], [ -87.5175,39.50083333333333 ], [ -87.36749999999999,39.50083333333333 ], [ -87.36749999999999,39.38333333333333 ], [ -87.5175,39.38333333333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50662512e4b053bff18e1bfe","contributors":{"authors":[{"text":"Kim, Moon H. 0000-0002-4328-8409 mkim@usgs.gov","orcid":"https://orcid.org/0000-0002-4328-8409","contributorId":3211,"corporation":false,"usgs":true,"family":"Kim","given":"Moon","email":"mkim@usgs.gov","middleInitial":"H.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ritz, Christian T.","contributorId":46352,"corporation":false,"usgs":true,"family":"Ritz","given":"Christian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":467674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arvin, Donald V. dvarvin@usgs.gov","contributorId":3210,"corporation":false,"usgs":true,"family":"Arvin","given":"Donald","email":"dvarvin@usgs.gov","middleInitial":"V.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467672,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040071,"text":"sim3218 - 2012 - Storage capacity and sedimentation trends of Lago Garzas, Puerto Rico, 1996-2007","interactions":[],"lastModifiedDate":"2012-09-28T17:16:18","indexId":"sim3218","displayToPublicDate":"2012-09-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3218","title":"Storage capacity and sedimentation trends of Lago Garzas, Puerto Rico, 1996-2007","docAbstract":"Lago Garzas is located in west-central Puerto Rico, about 3.5 kilometers southwest of the town of Adjuntas, in the confluence of the R&iacute;o Vacas and three other unnamed tributaries (fig. 1). The dam is owned and operated by the Puerto Rico Electric Power Authority (PREPA), and was constructed in 1943 for hydroelectric power generation and municipal water use along the southern coast. The dam is a semi-hydraulic earthfill embankment lined with boulders, and has a height of 61.57 meters, a top width of 9.14 meters, a base width of 365.76 meters, and a crest length of 227.37 meters; State Road PR-518 crosses the top of the dam. A morning-glory-type spillway is located near the west abutment of the dam at an elevation of 736.12 meters above mean sea level (Puerto Rico Water Resources Authority, 1969). Figure 2 shows an aerial photograph of the Lago Garzas earthfill dam and the morning-glory spillway section. Additional information and operational procedures are provided in Soler-L&oacute;pez and others (1999). During July 17-18, 2007, the U.S. Geological Survey (USGS) Caribbean Water Science Center, in cooperation with the Puerto Rico Aqueduct and Sewer Authority, conducted a bathymetric survey of Lago Garzas to update the reservoir storage capacity and update the reservoir sedimentation rate by comparing the 2007 data with the previous 1996 bathymetric survey results. The purpose of this report is to describe and document the USGS sedimentation survey conducted at Lago Garzas during July 2007, including the methods used to update the reservoir storage capacity, sedimentation rates, and areas of substantial sediment accumulation since 1996.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3218","collaboration":"Prepared in cooperation with the Puerto Rico Aqueduct and Sewer Authority","usgsCitation":"Soler-Lopez, L., 2012, Storage capacity and sedimentation trends of Lago Garzas, Puerto Rico, 1996-2007: U.S. Geological Survey Scientific Investigations Map 3218, Map; 29 x 29 inches, https://doi.org/10.3133/sim3218.","productDescription":"Map; 29 x 29 inches","numberOfPages":"1","onlineOnly":"Y","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":262123,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3218/pdf/SIM3218.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262122,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3218/","linkFileType":{"id":5,"text":"html"}},{"id":262126,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3218.jpg"}],"country":"Puerto Rico","otherGeospatial":"Lago Garzas Basin Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -66.83333333333333,18 ], [ -66.83333333333333,18.5 ], [ -66.5,18.5 ], [ -66.5,18 ], [ -66.83333333333333,18 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50662514e4b053bff18e1c0a","contributors":{"authors":[{"text":"Soler-Lopez, L.R.","contributorId":66306,"corporation":false,"usgs":true,"family":"Soler-Lopez","given":"L.R.","affiliations":[],"preferred":false,"id":467675,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040072,"text":"sir20125204 - 2012 - Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River in and into Missouri during summer flooding, July-August 2011","interactions":[],"lastModifiedDate":"2012-09-27T17:16:16","indexId":"sir20125204","displayToPublicDate":"2012-09-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5204","title":"Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River in and into Missouri during summer flooding, July-August 2011","docAbstract":"Bathymetric and velocimetric surveys were conducted by the U.S. Geological Survey, in cooperation with the Kansas and Missouri Departments of Transportation, in the vicinity of 36 bridges at 27 highway crossings of the Missouri River between Brownville, Nebraska and St. Louis, Missouri, from July 13 through August 3, 2011, during a summer flood. A multibeam echo sounder mapping system was used to obtain channel-bed elevations for river reaches ranging from 1,350 to 1,860 feet and extending across the active channel of the Missouri River. These bathymetric scans provide a \"snapshot\" of the channel conditions at the time of the surveys and provide characteristics of scour holes that may be useful in the development of predictive guidelines or equations for scour holes. These data also may be used by the Kansas and Missouri Departments of Transportation to assess the bridges for stability and integrity issues with respect to bridge scour during floods. Bathymetric data were collected around every pier that was in water, except those at the edge of water, in extremely shallow water, or surrounded by debris rafts. Scour holes were present at most piers for which bathymetry could be obtained, except at piers on channel banks, those near or embedded in lateral or longitudinal spur dikes, and those on exposed bedrock outcrops. Scour holes observed at the surveyed bridges were examined with respect to depth and shape. Although exposure of parts of foundational support elements was observed at several piers, at most sites the exposure likely can be considered minimal compared to the overall substructure that remains buried in bed material; however, there were several notable exceptions where the bed material thickness between the bottom of the scour hole and bedrock was less than 6 feet. Such substantial exposure of usually buried substructural elements may warrant special observation in future flood events. Previous bathymetric surveys had been done at several of the sites, and comparisons between bathymetric surfaces from the previous surveys and those of this study indicate substantial variability in the response of the channel bed to the 2011 summer flood conditions. At sites in Kansas City, there was no consistent deepening of the channel or increase in the size of scour holes, despite substantially more discharge and a higher water-surface elevation in the 2011 surveys, which implies the high-flow conditions during the 2011 surveys created a similar scour scenario to the previous surveys. At Jefferson City and the St. Louis sites, there was a consistent deepening of the channel, and a slight to substantial increase in the depth of scour holes in the 2011 surveys compared to previous surveys, although the effects of the higher flow appeared to be mitigated by the shape and alignment of the piers at most sites in St. Louis. Construction activities related to a new bridge at the Atchison, Kansas, site likely have contributed to the substantial additional scour observed there in a previous survey during the 2010 flooding, and the subsequent aggradation of the channel bed observed in the 2011 survey. Pier size, nose shape, and alignment to flow also had a profound effect on the size of the scour hole observed for a given pier.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125204","collaboration":"Prepared in cooperation with the Kansas and Missouri Departments of Transportation","usgsCitation":"Huizinga, R.J., 2012, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River in and into Missouri during summer flooding, July-August 2011: U.S. Geological Survey Scientific Investigations Report 2012-5204, xii; 166 p., https://doi.org/10.3133/sir20125204.","productDescription":"xii; 166 p.","numberOfPages":"182","onlineOnly":"Y","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":262127,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5204.gif"},{"id":262124,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5204/","linkFileType":{"id":5,"text":"html"}},{"id":262125,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5204/sir12-5204.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Missouri;Nebraska","otherGeospatial":"Missouri River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96,38.333333333333336 ], [ -96,41 ], [ -90,41 ], [ -90,38.333333333333336 ], [ -96,38.333333333333336 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5066250be4b053bff18e1bdd","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467676,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040080,"text":"ofr20121151 - 2012 - Database of the United States Coal Pellet Collection of the U.S. Geological Survey Organic Petrology Laboratory","interactions":[],"lastModifiedDate":"2012-09-27T17:16:16","indexId":"ofr20121151","displayToPublicDate":"2012-09-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1151","title":"Database of the United States Coal Pellet Collection of the U.S. Geological Survey Organic Petrology Laboratory","docAbstract":"The Organic Petrology Laboratory (OPL) of the U.S. Geological Survey (USGS) Eastern Energy Resources Science Center in Reston, Virginia, contains several thousand processed coal sample materials that were loosely organized in laboratory drawers for the past several decades. The majority of these were prepared as 1-inch-diameter particulate coal pellets (more than 6,000 pellets; one sample usually was prepared as two pellets, although some samples were prepared in as many as four pellets), which were polished and used in reflected light petrographic studies. These samples represent the work of many scientists from the 1970s to the present, most notably Ron Stanton, who managed the OPL until 2001 (see Warwick and Ruppert, 2005, for a comprehensive bibliography of Ron Stanton's work). The purpose of the project described herein was to organize and catalog the U.S. part of the petrographic sample collection into a comprehensive database (available with this report as a Microsoft Excel file) and to compile and list published studies associated with the various sample sets. Through this work, the extent of the collection is publicly documented as a resource and sample library available to other scientists and researchers working in U.S. coal basins previously studied by organic petrologists affiliated with the USGS. Other researchers may obtain samples in the OPL collection on loan at the discretion of the USGS authors listed in this report and its associated Web page.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121151","usgsCitation":"Deems, N.J., and Hackley, P.C., 2012, Database of the United States Coal Pellet Collection of the U.S. Geological Survey Organic Petrology Laboratory: U.S. Geological Survey Open-File Report 2012-1151, iii, 18 p.; Coal Pellet Collection Database XLSX, https://doi.org/10.3133/ofr20121151.","productDescription":"iii, 18 p.; Coal Pellet Collection Database XLSX","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":262136,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1151.gif"},{"id":262128,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1151/","linkFileType":{"id":5,"text":"html"}},{"id":262129,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1151/OFR2012-1151.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5066250ee4b053bff18e1be9","contributors":{"authors":[{"text":"Deems, Nikolaus J.","contributorId":77410,"corporation":false,"usgs":true,"family":"Deems","given":"Nikolaus","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":467687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":467686,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040081,"text":"ofr20121099 - 2012 - Summary of oceanographic and water-quality measurements near the Blackwater National Wildlife Refuge, Maryland, 2011","interactions":[],"lastModifiedDate":"2012-10-08T17:16:12","indexId":"ofr20121099","displayToPublicDate":"2012-09-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1099","title":"Summary of oceanographic and water-quality measurements near the Blackwater National Wildlife Refuge, Maryland, 2011","docAbstract":"Suspended-sediment transport is a critical element governing the geomorphology of tidal marshes. Marshes rely on both organic material and inorganic sediment deposition to maintain their elevation relative to sea level. In wetlands near the Blackwater National Wildlife Refuge, Maryland, portions of the salt marsh have been subsiding relative to sea level since the early 20th century. Other portions of the marsh have been successful at maintaining elevation. The U.S. Geological Survey performed observational deployments to measure suspended-sediment concentration in the tidal channels in order to understand the magnitude of suspended-sediment concentrations, the sediment-transport mechanisms, and differences between two marsh areas, one that subsided and one that maintained elevation. We deployed optical turbidity sensors and acoustic velocity meters at multiple sites over two periods in 2011. This report presents the time-series of oceanographic data collected during those field studies, including velocity, depth, turbidity, salinity, water temperature, and pH.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121099","usgsCitation":"Ganju, N., Dickhudt, P., Montgomery, E., Brennand, P., Derby, R.K., Brooks, T.W., Guntenspergen, G.R., Martini, M.A., Borden, J., and Baldwin, S., 2012, Summary of oceanographic and water-quality measurements near the Blackwater National Wildlife Refuge, Maryland, 2011: U.S. Geological Survey Open-File Report 2012-1099, HTML Document, https://doi.org/10.3133/ofr20121099.","productDescription":"HTML Document","onlineOnly":"Y","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":262137,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1099.jpg"},{"id":262130,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1099/","linkFileType":{"id":5,"text":"html"}},{"id":262131,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1099/title_page.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maryl","otherGeospatial":"Blackwater River;Transquaking River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.1,38.3 ], [ -76.1,38.4 ], [ -76,38.4 ], [ -76,38.3 ], [ -76.1,38.3 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50662514e4b053bff18e1c0d","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":467697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickhudt, Patrick J.","contributorId":48302,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","affiliations":[],"preferred":false,"id":467693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Montgomery, Ellyn T.","contributorId":78038,"corporation":false,"usgs":true,"family":"Montgomery","given":"Ellyn T.","affiliations":[],"preferred":false,"id":467696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brennand, Patrick","contributorId":62095,"corporation":false,"usgs":true,"family":"Brennand","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":467694,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Derby, R. Kyle","contributorId":24643,"corporation":false,"usgs":true,"family":"Derby","given":"R.","email":"","middleInitial":"Kyle","affiliations":[],"preferred":false,"id":467692,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooks, Thomas W. 0000-0002-0555-3398 wallybrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-0555-3398","contributorId":5989,"corporation":false,"usgs":true,"family":"Brooks","given":"Thomas","email":"wallybrooks@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":467691,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":467689,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martini, Marinna A. 0000-0002-7757-5158 mmartini@usgs.gov","orcid":"https://orcid.org/0000-0002-7757-5158","contributorId":2456,"corporation":false,"usgs":true,"family":"Martini","given":"Marinna","email":"mmartini@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":467688,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Borden, Jonathan 0000-0001-6844-3340 jborden@usgs.gov","orcid":"https://orcid.org/0000-0001-6844-3340","contributorId":3098,"corporation":false,"usgs":true,"family":"Borden","given":"Jonathan","email":"jborden@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":467690,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Baldwin, Sandra M. sbrosnahan@usgs.gov","contributorId":75620,"corporation":false,"usgs":true,"family":"Baldwin","given":"Sandra M.","email":"sbrosnahan@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":467695,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70040086,"text":"ofr20121049 - 2012 - Test drilling and data collection in the Calaveras County portion of the Eastern San Joaquin Groundwater Subbasin, California, December 2009-June 2011","interactions":[],"lastModifiedDate":"2012-09-27T17:16:16","indexId":"ofr20121049","displayToPublicDate":"2012-09-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1049","title":"Test drilling and data collection in the Calaveras County portion of the Eastern San Joaquin Groundwater Subbasin, California, December 2009-June 2011","docAbstract":"Two multiple-well monitoring sites were drilled in the Calaveras County portion of the Eastern San Joaquin Groundwater Subbasin, about 100 miles east of San Francisco, California, during December 2009 and January 2010. Site 3N/9E-12G1-4 was drilled to a depth of 503 feet below land surface (bls), and four wells were installed. Site 4N/9E-36A1-3 was drilled to a depth of 400 feet bls, and three wells were installed. Lithologic and geophysical data collected during test drilling indicated the presence of volcanic sands interspersed with lahar deposits that are characteristic of the Mehrten Formation to about 420 feet bls at site 12G1-4, and the presence of volcanic sands interspersed with clay that are characteristic of the Valley Springs Formation at site 36A1-3. In January 2010, water levels at site 12G1-4 ranged from 120 to 127 feet bls (the shallowest well at the site, 12G4, screened from 90 to 110 feet bls, was dry). Between May and November 2010, water levels declined as much as 22 feet in wells 12G1 and 12G2, the deepest wells at this site, and declined about 6 feet in shallower well 12G3. During this same period, water-levels declined less than 8 feet in the three wells at site 36A1-3. Water levels in all monitoring wells recovered to near-May-2010 levels by mid-spring 2011. Dissolved solids in the six sampled monitoring wells (residue on evaporation) ranged from 154 to 239 milligrams per liter (mg/L); arsenic concentrations ranged from 1.8 to 13 micrograms per liter (&mu;g/L), and were greater than the U.S. Environmental Protection Agency Maximum Contaminant Level (MCL) for arsenic of 10 &mu;g/L in well 36A2. The oxygen-18 (&delta;<sup>18</sup>O) and deuterium (&delta;D) stable-isotopic composition of water from the six monitoring wells and from nine domestic and public-supply wells sampled as part of this study ranged from -6.7 to -8.2 per mil (&delta;<sup>18</sup>O), and -50 to -60 per mil (&delta;D), and was consistent with values expected for water recharged in the lower altitudes of the Sierra Nevada. Well 36A3, the shallowest well at site 36A1-3, was the only well that contained measurable tritium - indicative of water recharged after 1952. Carbon-14 activities from the six monitoring wells ranged from 76.0 to 18.9 percent modern carbon, and groundwater ages (time since recharge), not corrected for chemical reactions, ranged from 2,200 to 13,400 years before present.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121049","collaboration":"Prepared in cooperation with the Calaveras County Water District and the California Department of Water Resources","usgsCitation":"Metzger, L.F., Izbicki, J., and Nawikas, J., 2012, Test drilling and data collection in the Calaveras County portion of the Eastern San Joaquin Groundwater Subbasin, California, December 2009-June 2011: U.S. Geological Survey Open-File Report 2012-1049, iv, 26 p., https://doi.org/10.3133/ofr20121049.","productDescription":"iv, 26 p.","numberOfPages":"30","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":262138,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1049.jpg"},{"id":262132,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1049/","linkFileType":{"id":5,"text":"html"}},{"id":262133,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1049/pdf/ofr20121049.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","county":"Calaveras","otherGeospatial":"Eastern San Joaquin Groundwater Subbasin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.08333333333333,38 ], [ -121.08333333333333,38.25 ], [ -120.8,38.25 ], [ -120.8,38 ], [ -121.08333333333333,38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50662515e4b053bff18e1c10","contributors":{"authors":[{"text":"Metzger, Loren F. 0000-0003-2454-2966 lmetzger@usgs.gov","orcid":"https://orcid.org/0000-0003-2454-2966","contributorId":1378,"corporation":false,"usgs":true,"family":"Metzger","given":"Loren","email":"lmetzger@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":467699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":1375,"corporation":false,"usgs":true,"family":"Izbicki","given":"John A.","email":"jaizbick@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":467698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nawikas, Joseph M. 0000-0001-9061-6674","orcid":"https://orcid.org/0000-0001-9061-6674","contributorId":96528,"corporation":false,"usgs":true,"family":"Nawikas","given":"Joseph M.","affiliations":[],"preferred":false,"id":467700,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040067,"text":"ofr20121201 - 2012 - Geophysical investigation of sentinel lakes in Lake, Seminole, Orange, and Volusia Counties, Florida","interactions":[],"lastModifiedDate":"2012-09-27T17:16:16","indexId":"ofr20121201","displayToPublicDate":"2012-09-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1201","title":"Geophysical investigation of sentinel lakes in Lake, Seminole, Orange, and Volusia Counties, Florida","docAbstract":"This study was initiated in cooperation with the St. Johns River Water Management District (SJRWMD) to investigate groundwater and surface-water interaction in designated sentinel lakes in central Florida. Sentinel lakes are a SJRWMD established set of priority water bodies (lakes) for which minimum flows and levels (MFLs) are determined. Understanding both the structure and lithology beneath these lakes can ultimately lead to a better understanding of the MFLs and why water levels fluctuate in certain lakes more so than in other lakes. These sentinel lakes have become important water bodies to use as water-fluctuation indicators in the SJRWMD Minimum Flows and Levels program and will be used to define long-term hydrologic and ecologic performance measures. Geologic control on lake hydrology remains poorly understood in this study area. Therefore, the U.S. Geological Survey investigated 16 of the 21 water bodies on the SJRWMD priority list. Geologic information was obtained by the tandem use of high-resolution seismic profiling (HRSP) and direct-current (DC) resistivity profiling to isolate both the geologic framework (structure) and composition (lithology). Previous HRSP surveys from various lakes in the study area have been successful in identifying karst features, such as subsidence sinkholes. However, by using this method only, it is difficult to image highly irregular or chaotic surfaces, such as collapse sinkholes. Resistivity profiling was used to complement HRSP by detecting porosity change within fractured or collapsed structures and increase the ability to fully characterize the subsurface. Lake Saunders (Lake County) is an example of a lake composed of a series of north-south-trending sinkholes that have joined to form one lake body. HRSP shows surface depressions and deformation in the substrate. Resistivity data likewise show areas in the southern part of the lake where resistivity shifts abruptly from approximately 400 ohm meters (ohm-m) along the edges to approximately 12 ohm-m in the center. These well-defined areas may indicate a \"ravel\" zone of increased porosity or clay content. Within Lake Helen (Volusia County), a parallel set of seismic reflectors within a host of chaotic reflectors may represent fill within a large sinkhole. The feature extends to more than 50 meters (m) deep and contains very steep pinnacles within the center. Seismic data in Lake Helen are supported by high resistivity values from adjacent continuous resistivity profiles that show possible center collapse within the lake and infilling of sandy material. When used together, HRSP and DC resistivity techniques provide a composite image of structure and lithology to detect potential conduits for fluid flow.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121201","collaboration":"Prepared in cooperation with the St. Johns River Water Management District","usgsCitation":"Reich, C., Flocks, J., and Davis, J., 2012, Geophysical investigation of sentinel lakes in Lake, Seminole, Orange, and Volusia Counties, Florida: U.S. Geological Survey Open-File Report 2012-1201, viii; 58 p.; PDF Appendix, https://doi.org/10.3133/ofr20121201.","productDescription":"viii; 58 p.; PDF Appendix","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":262119,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1201.gif"},{"id":262109,"rank":9999,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2012/1201/pdf/Reich_OFR2012_1201_appendix-sm.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262107,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1201/pdf/Reich_OFR2012_1201-sm.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262108,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1201/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","county":"Lake County;Marion County;Orange County;Seminole County;Sumter County;Volusia County","otherGeospatial":"Cherry Lake;Lake Louisa;Johns Lake;Lake Avalon;Lake Hiawassee;Crooked Lake;Prevatt Lake;Lake Saunders;Sylvan Lake;Trout Lake;Big Lake;Lake Colby;Lake Helen","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82,28.666666666666668 ], [ -82,29.25 ], [ -81,29.25 ], [ -81,28.666666666666668 ], [ -82,28.666666666666668 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50662510e4b053bff18e1bf8","contributors":{"authors":[{"text":"Reich, Christopher","contributorId":12942,"corporation":false,"usgs":true,"family":"Reich","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":467665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flocks, James","contributorId":62266,"corporation":false,"usgs":true,"family":"Flocks","given":"James","affiliations":[],"preferred":false,"id":467667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Jeffrey","contributorId":20204,"corporation":false,"usgs":true,"family":"Davis","given":"Jeffrey","affiliations":[],"preferred":false,"id":467666,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040194,"text":"ofr20121209 - 2012 - Structures data collection for the national map using volunteered geographic information","interactions":[],"lastModifiedDate":"2019-12-27T10:37:04","indexId":"ofr20121209","displayToPublicDate":"2012-09-26T09:42:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1209","displayTitle":"Structures data collection for <i>The National Map</i> using volunteered geographic information","title":"Structures data collection for the national map using volunteered geographic information","docAbstract":"The U.S. Geological Survey (USGS) has historically sponsored volunteered data collection projects to enhance its topographic paper and digital map products. This report describes one phase of an ongoing project to encourage volunteers to contribute data to <i>The National Map</i> using online editing tools. The USGS recruited students studying geographic information systems (GIS) at the University of Colorado Denver and the University of Denver in the spring of 2011 to add data on structures - manmade features such as schools, hospitals, and libraries - to four quadrangles covering metropolitan Denver. The USGS customized a version of the online Potlatch editor created by the OpenStreetMap project and populated it with 30 structure types drawn from the Geographic Names Information System (GNIS), a USGS database of geographic features. The students corrected the location and attributes of these points and added information on structures that were missing. There were two rounds of quality control. Student volunteers reviewed each point, and an in-house review of each point by the USGS followed. Nine-hundred and thirty-eight structure points were initially downloaded from the USGS database. Editing and quality control resulted in 1,214 structure points that were subsequently added to <i>The National Map</i>. A post-project analysis of the data shows that after student edit and peer review, 92 percent of the points contributed by volunteers met National Map Accuracy Standards for horizontal accuracy. Lessons from this project will be applied to later phases. These include: simplifying editing tasks and the user interfaces, stressing to volunteers the importance of adding structures that are missing, and emphasizing the importance of conforming to editorial guidelines for formatting names and addresses of structures. The next phase of the project will encompass the entire State of Colorado and will allow any citizen to contribute structures data. Volunteers will benefit from this project by engaging with their local geography and contributing to a national resource of topographic information that remains in the public domain for anyone to download.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121209","usgsCitation":"Poore, B.S., Wolf, E.B., Korris, E.M., Walter, J.L., and Matthews, G.D., 2012, Structures data collection for the national map using volunteered geographic information: U.S. Geological Survey Open-File Report 2012-1209, ii, 30 p., https://doi.org/10.3133/ofr20121209.","productDescription":"ii, 30 p.","numberOfPages":"34","onlineOnly":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":262292,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1209.gif"},{"id":262291,"rank":299,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1209/pdf/ofr2012-1209.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Denver","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.32867431640625,\n              39.308800296002914\n            ],\n            [\n              -104.5733642578125,\n              39.308800296002914\n            ],\n            [\n              -104.5733642578125,\n              40.027614437486655\n            ],\n            [\n              -105.32867431640625,\n              40.027614437486655\n            ],\n            [\n              -105.32867431640625,\n              39.308800296002914\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"508a51c8e4b07fc5688448b9","contributors":{"authors":[{"text":"Poore, Barbara S. bspoore@usgs.gov","contributorId":2541,"corporation":false,"usgs":true,"family":"Poore","given":"Barbara","email":"bspoore@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":467864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolf, Eric B. ebwolf@usgs.gov","contributorId":4535,"corporation":false,"usgs":true,"family":"Wolf","given":"Eric","email":"ebwolf@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":467865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Korris, Erin M. 0000-0002-1254-9696 ekorris@usgs.gov","orcid":"https://orcid.org/0000-0002-1254-9696","contributorId":4923,"corporation":false,"usgs":true,"family":"Korris","given":"Erin","email":"ekorris@usgs.gov","middleInitial":"M.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":467867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walter, Jennifer L. 0000-0001-8183-5015 jlwalter@usgs.gov","orcid":"https://orcid.org/0000-0001-8183-5015","contributorId":5217,"corporation":false,"usgs":true,"family":"Walter","given":"Jennifer","email":"jlwalter@usgs.gov","middleInitial":"L.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":467868,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matthews, Greg D. 0000-0002-5287-3888 gdmatthews@usgs.gov","orcid":"https://orcid.org/0000-0002-5287-3888","contributorId":4922,"corporation":false,"usgs":true,"family":"Matthews","given":"Greg","email":"gdmatthews@usgs.gov","middleInitial":"D.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":467866,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040050,"text":"ofr20111209 - 2012 - Data visualization, time-series analysis, and mass-balance modeling of hydrologic and water-quality data for the McTier Creek watershed, South Carolina, 2007-2009","interactions":[],"lastModifiedDate":"2016-12-08T14:49:32","indexId":"ofr20111209","displayToPublicDate":"2012-09-26T00:00:00","publicationYear":"2012","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":"2011-1209","title":"Data visualization, time-series analysis, and mass-balance modeling of hydrologic and water-quality data for the McTier Creek watershed, South Carolina, 2007-2009","docAbstract":"The McTier Creek watershed is located in the headwaters of the Edisto River Basin, which is in the Coastal Plain region of South Carolina. The Edisto ecosystem has some of the highest recorded fish-tissue mercury concentrations in the United States. In an effort to advance the understanding of the fate and transport of mercury in stream ecosystems, the U.S. Geological Survey, as part of its National Water-Quality Assessment Program, initiated a field investigation of mercury in the McTier Creek watershed in 2006. The initial efforts of the investigation included the collection of extensive hydrologic and water-quality field data, along with the development of several hydrologic and water-quality models. This series of measured and modeled data forms the primary source of information for this investigation to assess the fate and transport of mercury within the McTier Creek watershed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111209","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency National Exposure Research Laboratory","usgsCitation":"Benedict, S., Conrads, P., Feaster, T., Journey, C.A., Golden, H., Knightes, C.D., Davis, G.M., and Bradley, P.M., 2012, Data visualization, time-series analysis, and mass-balance modeling of hydrologic and water-quality data for the McTier Creek watershed, South Carolina, 2007-2009: U.S. Geological Survey Open-File Report 2011-1209, vi, 21 p.; col. ill.; maps (col.), https://doi.org/10.3133/ofr20111209.","productDescription":"vi, 21 p.; col. ill.; maps (col.)","startPage":"i","endPage":"21","numberOfPages":"32","additionalOnlineFiles":"N","temporalStart":"2007-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":262092,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1209/pdf/ofr20111209_book_09262012.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262093,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1209/","linkFileType":{"id":5,"text":"html"}},{"id":262099,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1209.jpg"}],"country":"United States","state":"South Carolina","otherGeospatial":"Mctier Creek 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Stephen T. benedict@usgs.gov","contributorId":3198,"corporation":false,"usgs":true,"family":"Benedict","given":"Stephen T.","email":"benedict@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":467566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":467563,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feaster, Toby D. 0000-0002-5626-5011 tfeaster@usgs.gov","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":1109,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby D.","email":"tfeaster@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":467564,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":467565,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Golden, Heather E.","contributorId":94914,"corporation":false,"usgs":true,"family":"Golden","given":"Heather E.","affiliations":[],"preferred":false,"id":467569,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knightes, Christopher D.","contributorId":32666,"corporation":false,"usgs":true,"family":"Knightes","given":"Christopher","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":467568,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davis, Gary M.","contributorId":12741,"corporation":false,"usgs":true,"family":"Davis","given":"Gary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":467567,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467562,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70040046,"text":"sir20125142 - 2012 - Estimation of baseline daily mean streamflows for ungaged locations on Pennsylvania streams, water years 1960-2008","interactions":[],"lastModifiedDate":"2016-08-10T21:28:25","indexId":"sir20125142","displayToPublicDate":"2012-09-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5142","title":"Estimation of baseline daily mean streamflows for ungaged locations on Pennsylvania streams, water years 1960-2008","docAbstract":"<p>Water-resource managers use daily mean streamflows to generate streamflow statistics and analyze streamflow conditions. An in-depth evaluation of flow regimes to promote instream ecological health often requires streamflow information obtainable only from a time series hydrograph. Historically, it has been difficult to estimate daily mean streamflow for an ungaged location. The U.S. Geological Survey (USGS), in cooperation with the Pennsylvania Department of Environmental Protection, Susquehanna River Basin Commission, and The Nature Conservancy, has developed the&nbsp;<strong>Ba</strong>seline&nbsp;<strong>S</strong>treamflow&nbsp;<strong>E</strong>stimator (BaSE) to estimate baseline streamflow at a daily time scale for ungaged streams in Pennsylvania using data collected during water years 1960&ndash;2008. Baseline streamflow is minimally altered by regulation, diversion, or mining, and other anthropogenic activities. Daily mean streamflow is estimated in BaSE using a methodology that equates streamflow as a percentile from a flow duration curve for a particular day at an ungaged location with streamflow as a percentile from the flow duration curve for the same day at a reference streamgage that is considered to be hydrologically similar to the ungaged location. An appropriate reference streamgage is selected using map correlation, in which variogram models are developed that correlate streamflow at one streamgage with streamflows at all other streamgages. The percentiles from a flow duration curve for the ungaged location are converted to streamflow through the use of regression equations. Regression equations used to predict 17 flow-duration exceedance probabilities were developed for Pennsylvania using geographic information system-derived basin characteristics. The standard error of prediction for the regression equations ranged from 11&nbsp;percent to 92&nbsp;percent with the mean of 31&nbsp;percent.</p>\n<p>The map correlation method for estimating streamflow was tested at locations within two pilot basins, the Upper Delaware River Basin and the Lower Susquehanna River Basin, before being applied statewide. Reference streamgages within the pilot basins were used as ungaged locations for analyzing the map correlation method. Correlation using Spearman&rsquo;s rho and centroid distance performed as well as, or better than, the method using the closest streamgage as a reference streamgage. Map correlation using the correlation metrics identified in the pilot basins was applied to 156 streamgages in and near&nbsp;Pennsylvania.</p>\n<p>BaSE uses the map correlation method and flow-duration exceedance probability regression equations to estimate baseline daily mean streamflow for an ungaged location. The output from BaSE is a Microsoft Excel&reg; report file that summarizes the reference streamgage and ungaged location information, including basin characteristics, percent difference in basin characteristics between the two locations, any warning associated with the basin characteristics, mean and median streamflow for the ungaged location, and a daily hydrograph of streamflow for water years 1960&ndash;2008 for the ungaged location. The daily mean streamflow for the ungaged location can be exported as a text file to be used as input into other statistical software packages. BaSE estimates daily mean streamflow for baseline conditions only, and any alterations to streamflow from regulation, large water use, or substantial mining are not reflected in the estimated&nbsp;streamflow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125142","collaboration":"Prepared in cooperation with the Pennsylvania Department of Environmental Protection, the Susquehanna River Basin Commission, and The Nature Conservancy","usgsCitation":"Stuckey, M.H., Koerkle, E.H., and Ulrich, J.E., 2012, Estimation of baseline daily mean streamflows for ungaged locations on Pennsylvania streams, water years 1960-2008 (First posted September 26, 2012; Revised and reposted August 11, 2014, version 1.1): U.S. Geological Survey Scientific Investigations Report 2012-5142, Report: viii, 56 p.; Appendix 5; Baseline Streamflow Estimator (v1.1), https://doi.org/10.3133/sir20125142.","productDescription":"Report: viii, 56 p.; 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,{"id":70040043,"text":"70040043 - 2012 - Neighborhood and habitat effects on vital rates: expansion of the Barred Owl in the Oregon Coast Ranges","interactions":[],"lastModifiedDate":"2012-09-26T17:16:49","indexId":"70040043","displayToPublicDate":"2012-09-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Neighborhood and habitat effects on vital rates: expansion of the Barred Owl in the Oregon Coast Ranges","docAbstract":"In this paper, we modify dynamic occupancy models developed for detection-nondetection data to allow for the dependence of local vital rates on neighborhood occupancy, where neighborhood is defined very flexibly. Such dependence of occupancy dynamics on the status of a relevant neighborhood is pervasive, yet frequently ignored. Our framework permits joint inference about the importance of neighborhood effects and habitat covariates in determining colonization and extinction rates. Our specific motivation is the recent expansion of the Barred Owl (Strix varia) in western Oregon, USA, over the period 1990-2010. Because the focal period was one of dramatic range expansion and local population increase, the use of models that incorporate regional occupancy (sources of colonists) as determinants of dynamic rate parameters is especially appropriate. We began our analysis of 21 years of Barred Owl presence/nondetection data in the Tyee Density Study Area (TDSA) by testing a suite of six models that varied only in the covariates included in the modeling of detection probability. We then tested whether models that used regional occupancy as a covariate for colonization and extinction outperformed models with constant or year-specific colonization or extinction rates. Finally we tested whether habitat covariates improved the AIC of our models, focusing on which habitat covariates performed best, and whether the signs of habitat effects are consistent with a priori hypotheses. We conclude that all covariates used to model detection probability lead to improved AIC, that regional occupancy influences colonization and extinction rates, and that habitat plays an important role in determining extinction and colonization rates. As occupancy increases from low levels toward equilibrium, colonization increases and extinction decreases, presumably because there are more and more dispersing juveniles. While both rates are affected, colonization increases more than extinction decreases. Colonization is higher and extinction is lower in survey polygons with more riparian forest. The effects of riparian forest on extinction rates are greater than on colonization rates. Model results have implications for management of the invading Barred Owl, both through habitat alteration and removal.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ESA","publisherLocation":"Ithaca, NY","doi":"10.1890/11-1709.1","usgsCitation":"Yackulic, C.B., Reid, J., Davis, R., Hines, J., Nichols, J., and Forsman, E., 2012, Neighborhood and habitat effects on vital rates: expansion of the Barred Owl in the Oregon Coast Ranges: Ecology, v. 93, no. 8, p. 1953-1966, https://doi.org/10.1890/11-1709.1.","productDescription":"14 p.","startPage":"1953","endPage":"1966","numberOfPages":"14","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":262070,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262067,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/11-1709.1","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","volume":"93","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-08-03","publicationStatus":"PW","scienceBaseUri":"50e0970fe4b0fec3206ee88b","contributors":{"authors":[{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":467545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Janice","contributorId":89391,"corporation":false,"usgs":false,"family":"Reid","given":"Janice","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":467547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Raymond","contributorId":91349,"corporation":false,"usgs":true,"family":"Davis","given":"Raymond","affiliations":[],"preferred":false,"id":467548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hines, James E. jhines@usgs.gov","contributorId":3506,"corporation":false,"usgs":true,"family":"Hines","given":"James E.","email":"jhines@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":467544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":467543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Forsman, Eric","contributorId":28470,"corporation":false,"usgs":true,"family":"Forsman","given":"Eric","affiliations":[],"preferred":false,"id":467546,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70040041,"text":"sir20125192 - 2012 - Spatial and seasonal variability of base flow in the Verde Valley, central Arizona, 2007 and 2011","interactions":[],"lastModifiedDate":"2012-09-26T17:16:49","indexId":"sir20125192","displayToPublicDate":"2012-09-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5192","title":"Spatial and seasonal variability of base flow in the Verde Valley, central Arizona, 2007 and 2011","docAbstract":"Synoptic base-flow surveys were conducted on streams in the Verde Valley, central Arizona, in June 2007 and February 2011 by the U.S. Geological Survey (USGS), in cooperation with the Verde River Basin Partnership, the Town of Clarkdale, and Yavapai County. These surveys, also known as seepage runs, measured streamflow under base-flow conditions at many locations over a short period of time. Surveys were conducted on a segment of the Verde River that flows through the Verde Valley, between USGS streamflow-gaging stations 09504000 and 09506000, a distance of 51 river miles. Data from the surveys were used to investigate the dominant controls on Verde River base flow, spatial variability in gaining and losing reaches, and the effects that human alterations have on base flow in the surface-water system. The most prominent human alterations in the Verde Valley are dozens of surface-water diversions from streams, including gravity-fed ditch diversions along the Verde River.Base flow that entered the Verde River from the tributary streams of Oak Creek, Beaver Creek, and West Clear Creek was found to be a major source of base flow in the Verde River. Groundwater discharge directly into the Verde River near these three confluences also was an important contributor of base flow to the Verde River, particularly near the confluence with Beaver Creek. An examination of individual reaches of the Verde River in the Verde Valley found three reaches (largely unaffected by ditch diversions) exhibiting a similar pattern: a small net groundwater discharge in February 2011 (12 cubic feet per second or less) and a small net streamflow loss in June 2007 (11 cubic feet per second or less). Two reaches heavily affected by ditch diversions were difficult to interpret because of the large number of confounding human factors. Possible lower and upper bounds of net groundwater flux were calculated for all reaches, including those heavily affected by ditches.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125192","collaboration":"Prepared in cooperation with the Verde River Basin Partnership, the Town of Clarkdale, and Yavapai County","usgsCitation":"Garner, B.D., and Bills, D., 2012, Spatial and seasonal variability of base flow in the Verde Valley, central Arizona, 2007 and 2011: U.S. Geological Survey Scientific Investigations Report 2012-5192, v, 33 p.; col. ill.; maps (col.); Appendices, https://doi.org/10.3133/sir20125192.","productDescription":"v, 33 p.; col. ill.; maps (col.); Appendices","startPage":"i","endPage":"33","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2007-06-01","temporalEnd":"2011-02-28","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":262062,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5192.gif"},{"id":262060,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5192/","linkFileType":{"id":5,"text":"html"}},{"id":262061,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5192/sir2012-5192.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Verde Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4cde8e4b0e8fec6ce21ff","contributors":{"authors":[{"text":"Garner, Bradley D. 0000-0002-6912-5093 bdgarner@usgs.gov","orcid":"https://orcid.org/0000-0002-6912-5093","contributorId":2133,"corporation":false,"usgs":true,"family":"Garner","given":"Bradley","email":"bdgarner@usgs.gov","middleInitial":"D.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":467536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bills, Donald J. djbills@usgs.gov","contributorId":4180,"corporation":false,"usgs":true,"family":"Bills","given":"Donald J.","email":"djbills@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":467537,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040047,"text":"fs20123100 - 2012 - The National Nonindigenous Aquatic Species Database","interactions":[],"lastModifiedDate":"2017-06-07T13:24:36","indexId":"fs20123100","displayToPublicDate":"2012-09-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3100","title":"The National Nonindigenous Aquatic Species Database","docAbstract":"<p><span>The U.S. Geological Survey (USGS) Nonindigenous Aquatic Species (NAS) Program maintains a database that monitors, records, and analyzes sightings of nonindigenous aquatic plant and animal species throughout the United States. The program is based at the USGS Wetland and Aquatic Research Center in Gainesville, Florida.</span></p><p><span>The initiative to maintain scientific information on nationwide occurrences of nonindigenous aquatic species began with the Aquatic Nuisance Species Task Force, created by Congress in 1990 to provide timely information to natural resource managers. Since then, the NAS database has been a clearinghouse of information for confirmed sightings of nonindigenous, also known as nonnative, aquatic species throughout the Nation. The database is used to produce email alerts, maps, summary graphs, publications, and other information products to support natural resource managers.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123100","usgsCitation":"Neilson, M.E., and Fuller, P.L., 2012, The National Nonindigenous Aquatic Species Database (Version 1.0: Originally posted September 26, 2012; Version 1.1: May 25, 2017): U.S. Geological Survey Fact Sheet 2012-3100, 4 p., https://doi.org/10.3133/fs20123100.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":262100,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3100.jpg"},{"id":262079,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3100/","text":"Index page","linkFileType":{"id":5,"text":"html"}},{"id":341963,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2012/3100/versionHist.txt","linkFileType":{"id":2,"text":"txt"}},{"id":341780,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3100/fs20123100.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":341781,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2012/3100/coverthb2.jpg"}],"edition":"Version 1.0: Originally posted September 26, 2012; Version 1.1: May 25, 2017","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4fd3ae4b0e8fec6ce87d8","contributors":{"authors":[{"text":"Neilson, Matthew E. 0000-0002-5139-5677 mneilson@usgs.gov","orcid":"https://orcid.org/0000-0002-5139-5677","contributorId":145623,"corporation":false,"usgs":false,"family":"Neilson","given":"Matthew","email":"mneilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":16178,"text":"Cherokee Nation Technology Services","active":true,"usgs":false}],"preferred":false,"id":467552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Pamela L. 0000-0002-9389-9144 pfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9389-9144","contributorId":3217,"corporation":false,"usgs":true,"family":"Fuller","given":"Pamela","email":"pfuller@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":467553,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040052,"text":"ofr20121197 - 2012 - Sampling and analysis plan for the characterization of groundwater quality in two monitoring wells near Pavillion, Wyoming","interactions":[],"lastModifiedDate":"2012-09-26T17:16:49","indexId":"ofr20121197","displayToPublicDate":"2012-09-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1197","title":"Sampling and analysis plan for the characterization of groundwater quality in two monitoring wells near Pavillion, Wyoming","docAbstract":"In June 2010, the U.S. Environmental Protection Agency installed two deep monitoring wells (MW01 and MW02) near Pavillion, Wyoming to study groundwater quality. The U.S Geological Survey, in cooperation with the Wyoming Department of Environmental Quality, designed a plan to collect groundwater data from these monitoring wells. This sampling and analysis plan describes the sampling equipment that will be used, well purging strategy, purge water disposal, sample collection and processing, field and laboratory sample analysis, equipment decontamination, and quality-assurance and quality-control procedures.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121197","collaboration":"Prepared in cooperation with the Wyoming Department of Environmental Quality","usgsCitation":"Wright, P., and McMahon, P.B., 2012, Sampling and analysis plan for the characterization of groundwater quality in two monitoring wells near Pavillion, Wyoming: U.S. Geological Survey Open-File Report 2012-1197, vii, 90 p.; map (col.), https://doi.org/10.3133/ofr20121197.","productDescription":"vii, 90 p.; map (col.)","startPage":"i","endPage":"90","numberOfPages":"97","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":684,"text":"Wyoming Water Science Center","active":false,"usgs":true}],"links":[{"id":262103,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1197.gif"},{"id":262097,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1197/OF12-1197.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262098,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1197/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","city":"Pavillion","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4b52ae4b0e8fec6cde5f6","contributors":{"authors":[{"text":"Wright, Peter R. prwright@usgs.gov","contributorId":1828,"corporation":false,"usgs":true,"family":"Wright","given":"Peter R.","email":"prwright@usgs.gov","affiliations":[],"preferred":true,"id":467575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467574,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040042,"text":"70040042 - 2012 - Modeling habitat dynamics accounting for possible misclassification","interactions":[],"lastModifiedDate":"2012-09-26T17:16:49","indexId":"70040042","displayToPublicDate":"2012-09-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling habitat dynamics accounting for possible misclassification","docAbstract":"Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10980-012-9746-z","usgsCitation":"Veran, S., Kleiner, K., Choquet, R., Collazo, J., and Nichols, J., 2012, Modeling habitat dynamics accounting for possible misclassification: Landscape Ecology, v. 27, no. 7, p. 943-956, https://doi.org/10.1007/s10980-012-9746-z.","productDescription":"14 p.","startPage":"943","endPage":"956","numberOfPages":"14","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":262069,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262066,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10980-012-9746-z","linkFileType":{"id":5,"text":"html"}}],"volume":"27","issue":"7","noUsgsAuthors":false,"publicationDate":"2012-05-24","publicationStatus":"PW","scienceBaseUri":"50e06805e4b0fec3206ecd6f","contributors":{"authors":[{"text":"Veran, Sophie","contributorId":76983,"corporation":false,"usgs":true,"family":"Veran","given":"Sophie","email":"","affiliations":[],"preferred":false,"id":467541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleiner, Kevin J.","contributorId":7955,"corporation":false,"usgs":true,"family":"Kleiner","given":"Kevin J.","affiliations":[],"preferred":false,"id":467540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choquet, Remi","contributorId":88994,"corporation":false,"usgs":true,"family":"Choquet","given":"Remi","email":"","affiliations":[],"preferred":false,"id":467542,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collazo, Jaime jaime_collazo@usgs.gov","contributorId":2613,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":467539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":467538,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040051,"text":"ds718 - 2012 - Groundwater-quality and quality-control data for two monitoring wells near Pavillion, Wyoming, April and May 2012","interactions":[],"lastModifiedDate":"2012-09-26T17:16:49","indexId":"ds718","displayToPublicDate":"2012-09-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"718","title":"Groundwater-quality and quality-control data for two monitoring wells near Pavillion, Wyoming, April and May 2012","docAbstract":"In June 2010, the U.S. Environmental Protection Agency installed two deep monitoring wells (MW01 and MW02) near Pavillion, Wyoming, to study groundwater quality. During April and May 2012, the U.S Geological Survey, in cooperation with the Wyoming Department of Environmental Quality, collected groundwater-quality data and quality-control data from monitoring well MW01 and, following well redevelopment, quality-control data for monitoring well MW02. Two groundwater-quality samples were collected from well MW01&mdash;one sample was collected after purging about 1.5 borehole volumes, and a second sample was collected after purging 3 borehole volumes. Both samples were collected and processed using methods designed to minimize atmospheric contamination or changes to water chemistry. Groundwater-quality samples were analyzed for field water-quality properties (water temperature, pH, specific conductance, dissolved oxygen, oxidation potential); inorganic constituents including naturally occurring radioactive compounds (radon, radium-226 and radium-228); organic constituents; dissolved gasses; stable isotopes of methane, water, and dissolved inorganic carbon; and environmental tracers (carbon-14, chlorofluorocarbons, sulfur hexafluoride, tritium, helium, neon, argon, krypton, xenon, and the ratio of helium-3 to helium-4). Quality-control sample results associated with well MW01 were evaluated to determine the extent to which environmental sample analytical results were affected by bias and to evaluate the variability inherent to sample collection and laboratory analyses. Field documentation, environmental data, and quality-control data for activities that occurred at the two monitoring wells during April and May 2012 are presented.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds718","collaboration":"In cooperation with the Wyoming Department of Environmental Quality","usgsCitation":"Wright, P., McMahon, P.B., Mueller, D.K., and Clark, M.L., 2012, Groundwater-quality and quality-control data for two monitoring wells near Pavillion, Wyoming, April and May 2012: U.S. Geological Survey Data Series 718, vi, 23 p.; col. ill.; map (col.); Downloads Directory, https://doi.org/10.3133/ds718.","productDescription":"vi, 23 p.; col. ill.; map (col.); Downloads Directory","startPage":"i","endPage":"23","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":684,"text":"Wyoming Water Science Center","active":false,"usgs":true}],"links":[{"id":262102,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_718.gif"},{"id":262094,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/718/","linkFileType":{"id":5,"text":"html"}},{"id":262095,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/718/DS718_508.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262096,"rank":9999,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/718/downloads/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","city":"Pavillion","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50de6ad2e4b0e31bb02a30ab","contributors":{"authors":[{"text":"Wright, Peter R. prwright@usgs.gov","contributorId":1828,"corporation":false,"usgs":true,"family":"Wright","given":"Peter R.","email":"prwright@usgs.gov","affiliations":[],"preferred":true,"id":467573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467570,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, David K. mueller@usgs.gov","contributorId":1585,"corporation":false,"usgs":true,"family":"Mueller","given":"David","email":"mueller@usgs.gov","middleInitial":"K.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":467571,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Melanie L. mlclark@usgs.gov","contributorId":1827,"corporation":false,"usgs":true,"family":"Clark","given":"Melanie","email":"mlclark@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467572,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70255881,"text":"70255881 - 2012 - An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by combining Landsat, MODIS, and secondary data","interactions":[],"lastModifiedDate":"2024-07-09T13:32:55.362554","indexId":"70255881","displayToPublicDate":"2012-09-25T08:28:03","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by combining Landsat, MODIS, and secondary data","docAbstract":"<p><span>The overarching goal of this research was to develop and demonstrate an automated Cropland Classification Algorithm (ACCA) that will rapidly, routinely, and accurately classify agricultural cropland extent, areas, and characteristics (e.g., irrigated&nbsp;</span><span class=\"html-italic\">vs.</span><span>&nbsp;rainfed) over large areas such as a country or a region through combination of multi-sensor remote sensing and secondary data. In this research, a rule-based ACCA was conceptualized, developed, and demonstrated for the country of Tajikistan using mega file data cubes (MFDCs) involving data from Landsat Global Land Survey (GLS), Landsat Enhanced Thematic Mapper Plus (ETM+) 30 m, Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series, a suite of secondary data (e.g., elevation, slope, precipitation, temperature), and&nbsp;</span><span class=\"html-italic\">in situ</span><span>&nbsp;data. First, the process involved producing an accurate reference (or truth) cropland layer (TCL), consisting of cropland extent, areas, and irrigated&nbsp;</span><span class=\"html-italic\">vs.</span><span>&nbsp;rainfed cropland areas, for the entire country of Tajikistan based on MFDC of year 2005 (MFDC2005). The methods involved in producing TCL included using ISOCLASS clustering, Tasseled Cap bi-spectral plots, spectro-temporal characteristics from MODIS 250 m monthly normalized difference vegetation index (NDVI) maximum value composites (MVC) time-series, and textural characteristics of higher resolution imagery. The TCL statistics accurately matched with the national statistics of Tajikistan for irrigated and rainfed croplands, where about 70% of croplands were irrigated and the rest rainfed. Second, a rule-based ACCA was developed to replicate the TCL accurately (∼80% producer’s and user’s accuracies or within 20% quantity disagreement involving about 10 million Landsat 30 m sized cropland pixels of Tajikistan). Development of ACCA was an iterative process involving series of rules that are coded, refined, tweaked, and re-coded till ACCA derived croplands (ACLs) match accurately with TCLs. Third, the ACCA derived cropland layers of Tajikistan were produced for year 2005 (ACL2005), same year as the year used for developing ACCA, using MFDC2005. Fourth, TCL for year 2010 (TCL2010), an independent year, was produced using MFDC2010 using the same methods and approaches as the one used to produce TCL2005. Fifth, the ACCA was applied on MFDC2010 to derive ACL2010. The ACLs were then compared with TCLs (ACL2005&nbsp;</span><span class=\"html-italic\">vs.</span><span>&nbsp;TCL2005 and ACL2010&nbsp;</span><span class=\"html-italic\">vs.</span><span>&nbsp;TCL2010). The resulting accuracies and errors from error matrices involving about 152 million Landsat (30 m) pixels of the country of Tajikistan (of which about 10 million Landsat size, 30 m, cropland pixels) showed an overall accuracy of 99.6% (k</span><sub>hat</sub><span>&nbsp;= 0.97) for ACL2005&nbsp;</span><span class=\"html-italic\">vs.</span><span>&nbsp;TCL2005. For the 3 classes (irrigated, rainfed, and others) mapped in ACL2005, the producer’s accuracy was &gt;86.4% and users accuracy was &gt;93.6%. For ACL2010&nbsp;</span><span class=\"html-italic\">vs.</span><span>&nbsp;TCL2010, the error matrix showed an overall accuracy on 96.2% (k</span><sub>hat</sub><span>&nbsp;= 0.96). For the 3 classes (irrigated, rainfed, and others) mapped in ACL2010, the producer’s and user’s accuracies for the irrigated areas were ≥82.9%. Any intermixing was overwhelmingly between irrigated and rainfed croplands, indicating that croplands (irrigated plus rainfed areas) as well as irrigated areas were mapped with high levels of accuracies (∼90% or higher) even for the independent year. The ACL2005 and ACL2010, each, were produced using ACCA algorithm in ∼30 min using a Dell Precision desktop T7400 computer for the entire country of Tajikistan once the MFDCs for the years were ready. The ACCA algorithm for Tajikistan is made available through US Geological Survey’s ScienceBase:&nbsp;</span><a rel=\"noopener noreferrer\" href=\"https://www.sciencebase.gov/catalog/folder/4f79f1b7e4b0009bd827f548\" target=\"_blank\" data-mce-href=\"https://www.sciencebase.gov/catalog/folder/4f79f1b7e4b0009bd827f548\">http://www.sciencebase.gov/catalog/folder/4f79f1b7e4b0009bd827f548</a><span>&nbsp;or at:&nbsp;</span><a rel=\"noopener noreferrer\" href=\"https://powellcenter.usgs.gov/globalcroplandwater/content/models-algorithms\" target=\"_blank\" data-mce-href=\"https://powellcenter.usgs.gov/globalcroplandwater/content/models-algorithms\">https://powellcenter.usgs.gov/globalcroplandwater/content/models-algorithms</a><span>. The research contributes to the efforts of global food security through research on global croplands and their water use (e.g.,&nbsp;</span><a rel=\"noopener noreferrer\" href=\"https://powellcenter.usgs.gov/globalcroplandwater/\" target=\"_blank\" data-mce-href=\"https://powellcenter.usgs.gov/globalcroplandwater/\">https://powellcenter.usgs.gov/globalcroplandwater/</a><span>). The above results clearly demonstrated the ability of a rule-based ACCA to rapidly and accurately produce cropland data layer year after year (hindcast, nowcast, forecast) for the country it was developed using MFDCs that consist of combining multiple sensor data and secondary data. It needs to be noted that the ACCA is applicable to the area (e.g., country, region) for which it is developed. In this case, ACCA is applicable for the Country of Tajikistan to hindcast, nowcast, and forecast agricultural cropland extent, areas, and irrigated&nbsp;</span><span class=\"html-italic\">vs.</span><span>&nbsp;rainfed. The same fundamental concept of ACCA applies to other areas of the World where ACCA codes need to be modified to suite the area/region of interest. ACCA can also be expanded to compute other crop characteristics such as crop types, cropping intensities, and phenologies.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs4102890","usgsCitation":"Thenkabail, P.S., and Wu, Z., 2012, An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by combining Landsat, MODIS, and secondary data: Remote Sensing, v. 4, no. 10, p. 2890-2918, https://doi.org/10.3390/rs4102890.","productDescription":"29 p.","startPage":"2890","endPage":"2918","ipdsId":"IP-035313","costCenters":[{"id":273,"text":"Flagstaff Science Center","active":false,"usgs":true}],"links":[{"id":474346,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs4102890","text":"Publisher Index Page"},{"id":430841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Tajikistan","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[71.0142,40.24437],[70.64802,39.93575],[69.55961,40.10321],[69.46489,39.52668],[70.54916,39.6042],[71.78469,39.27946],[73.67538,39.43124],[73.92885,38.50582],[74.25751,38.60651],[74.86482,38.37885],[74.82999,37.99001],[74.98,37.41999],[73.9487,37.42157],[73.26006,37.49526],[72.63689,37.04756],[72.19304,36.94829],[71.84464,36.73817],[71.44869,37.06564],[71.54192,37.90577],[71.2394,37.95327],[71.34813,38.25891],[70.80682,38.48628],[70.3763,38.1384],[70.27057,37.73516],[70.11658,37.58822],[69.51879,37.609],[69.19627,37.15114],[68.85945,37.34434],[68.13556,37.02312],[67.83,37.14499],[68.39203,38.15703],[68.17603,38.90155],[67.44222,39.14014],[67.70143,39.58048],[68.53642,39.53345],[69.01163,40.08616],[69.32949,40.72782],[70.66662,40.96021],[70.45816,40.49649],[70.60141,40.21853],[71.0142,40.24437]]]},\"properties\":{\"name\":\"Tajikistan\"}}]}","volume":"4","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":905870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":905871,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040019,"text":"tm7C8 - 2012 - Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks","interactions":[],"lastModifiedDate":"2012-10-03T17:16:16","indexId":"tm7C8","displayToPublicDate":"2012-09-25T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C8","title":"Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks","docAbstract":"Models of environmental systems have become increasingly complex, incorporating increasingly large numbers of parameters in an effort to represent physical processes on a scale approaching that at which they occur in nature. Consequently, the inverse problem of parameter estimation (specifically, model calibration) and subsequent uncertainty analysis have become increasingly computation-intensive endeavors. Fortunately, advances in computing have made computational power equivalent to that of dozens to hundreds of desktop computers accessible through a variety of alternate means: modelers have various possibilities, ranging from traditional Local Area Networks (LANs) to cloud computing. Commonly used parameter estimation software is well suited to take advantage of the availability of such increased computing power. Unfortunately, logistical issues become increasingly important as an increasing number and variety of computers are brought to bear on the inverse problem. To facilitate efficient access to disparate computer resources, the PESTCommander program documented herein has been developed to provide a Graphical User Interface (GUI) that facilitates the management of model files (\"file management\") and remote launching and termination of \"slave\" computers across a distributed network of computers (\"run management\"). In version 1.0 described here, PESTCommander can access and ascertain resources across traditional Windows LANs: however, the architecture of PESTCommander has been developed with the intent that future releases will be able to access computing resources (1) via trusted domains established in Wide Area Networks (WANs) in multiple remote locations and (2) via heterogeneous networks of Windows- and Unix-based operating systems. The design of PESTCommander also makes it suitable for extension to other computational resources, such as those that are available via cloud computing. Version 1.0 of PESTCommander was developed primarily to work with the parameter estimation software PEST; the discussion presented in this report focuses on the use of the PESTCommander together with Parallel PEST. However, PESTCommander can be used with a wide variety of programs and models that require management, distribution, and cleanup of files before or after model execution. In addition to its use with the Parallel PEST program suite, discussion is also included in this report regarding the use of PESTCommander with the Global Run Manager GENIE, which was developed simultaneously with PESTCommander.","largerWorkTitle":"Automated Data Processing and Computations (Book 7)","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C8","collaboration":"Great Lakes Restoration Initiative.  This report is Chapter 8 of Section C in Book 7, Automated Data Processing and Computations.","usgsCitation":"Karanovic, M., Muffels, C.T., Tonkin, M.J., and Hunt, R.J., 2012, Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks: U.S. Geological Survey Techniques and Methods 7-C8, iii; 9 p.; PESTCommander Software, https://doi.org/10.3133/tm7C8.","productDescription":"iii; 9 p.; PESTCommander Software","numberOfPages":"18","onlineOnly":"Y","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":262049,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_7_c8.gif"},{"id":262044,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm7c8/","linkFileType":{"id":5,"text":"html"}},{"id":262045,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/tm7c8/pdf/TMBook7_ChapC8.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50788b9ae4b0cfc2d59f59d5","contributors":{"authors":[{"text":"Karanovic, Marinko","contributorId":54831,"corporation":false,"usgs":true,"family":"Karanovic","given":"Marinko","email":"","affiliations":[],"preferred":false,"id":467490,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muffels, Christopher T.","contributorId":105949,"corporation":false,"usgs":true,"family":"Muffels","given":"Christopher","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":467491,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tonkin, Matthew J.","contributorId":26376,"corporation":false,"usgs":true,"family":"Tonkin","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":467489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467488,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70040007,"text":"70040007 - 2012 - Subsurface gas hydrates in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2012-09-25T17:16:32","indexId":"70040007","displayToPublicDate":"2012-09-25T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface gas hydrates in the northern Gulf of Mexico","docAbstract":"The northernGulf of Mexico (GoM) has long been a focus area for the study of gashydrates. Throughout the 1980s and 1990s, work focused on massive gashydrates deposits that were found to form at and near the seafloor in association with hydrocarbon seeps. However, as global scientific and industrial interest in assessment of the drilling hazards and resource implications of gashydrate accelerated, focus shifted to understanding the nature and abundance of \"buried\" gashydrates. Through 2005, despite the drilling of more than 1200 oil and gas industry wells through the gashydrate stability zone, published evidence of significant sub-seafloor gashydrate in the GoM was lacking. A 2005 drilling program by the GoM GasHydrate Joint Industry Project (the JIP) provided an initial confirmation of the occurrence of gashydrates below the GoM seafloor. In 2006, release of data from a 2003 industry well in Alaminos Canyon 818 provided initial documentation of gashydrate occurrence at high concentrations in sand reservoirs in the GoM. From 2006 to 2008, the JIP facilitated the integration of geophysical and geological data to identify sites prospective for gashydrate-bearing sands, culminating in the recommendation of numerous drilling targets within four sites spanning a range of typical deepwater settings. Concurrent with, but independent of, the JIP prospecting effort, the Bureau of Ocean Energy Management (BOEM) conducted a preliminary assessment of the GoM gashydratepetroleum system, resulting in an estimate of 607 trillion cubic meters (21,444 trillion cubic feet) gas-in-place of which roughly one-third occurs at expected high concentrations in sand reservoirs. In 2009, the JIP drilled seven wells at three sites, discovering gashydrate at high saturation in sand reservoirs in four wells and suspected gashydrate at low to moderate saturations in two other wells. These results provide an initial confirmation of the complex nature and occurrence of gashydrate-bearing sands in the GoM, the efficacy of the integrated geological/geophysical prospecting approach used to identify the JIP drilling sites, and the relevance of the 2008 BOEM assessment.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.marpetgeo.2011.10.003","usgsCitation":"Boswell, R., Collett, T.S., Frye, M., Shedd, W., McConnell, D.R., and Shelander, D., 2012, Subsurface gas hydrates in the northern Gulf of Mexico: Marine and Petroleum Geology, v. 34, no. 1, p. 4-30, https://doi.org/10.1016/j.marpetgeo.2011.10.003.","productDescription":"27 p.","startPage":"4","endPage":"30","numberOfPages":"26","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":262046,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262043,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2011.10.003","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.85,18.166666666666668 ], [ -97.85,30.383333333333333 ], [ -81.03333333333333,30.383333333333333 ], [ -81.03333333333333,18.166666666666668 ], [ -97.85,18.166666666666668 ] ] ] } } ] }","volume":"34","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4dfa4e4b0e8fec6ce49b7","contributors":{"authors":[{"text":"Boswell, Ray","contributorId":12307,"corporation":false,"usgs":true,"family":"Boswell","given":"Ray","affiliations":[],"preferred":false,"id":467435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":467434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frye, Matthew","contributorId":48428,"corporation":false,"usgs":true,"family":"Frye","given":"Matthew","affiliations":[],"preferred":false,"id":467439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shedd, William","contributorId":13851,"corporation":false,"usgs":true,"family":"Shedd","given":"William","affiliations":[],"preferred":false,"id":467436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McConnell, Daniel R.","contributorId":47628,"corporation":false,"usgs":true,"family":"McConnell","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":467438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shelander, Dianna","contributorId":40463,"corporation":false,"usgs":true,"family":"Shelander","given":"Dianna","email":"","affiliations":[],"preferred":false,"id":467437,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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