Data on concentrations of chloride and sodium in groundwater in New Hampshire were assembled from various State and Federal agencies and organized into a database. This report provides documentation of many assumptions and limitations of disparate data that were collected to meet wide-ranging objectives and investigates temporal and spatial trends of the data. Data summaries presented in this report and analyses performed for this study needed to take into account the 27 percent of chloride and 5 percent of sodium data that were censored (less than a reporting limit) at multiple reporting limits that systematically decreased over time. Throughout New Hampshire, median concentrations of chloride were significantly greater during 2000-2011 than in every decade since the 1970s, and median concentrations of sodium were significantly greater during 2000-2011 than during the 1990s. Results of summary statistics showed that the 50th, 75th, and 90th percentiles of the median concentrations of chloride and sodium by source (well) from Rockingham and Strafford counties were the highest in the State; and the 75th and 90th percentiles from Carroll, Coos, and Grafton counties were the lowest. Large increases in median concentrations of chloride and sodium for individual wells after 1995 compared with concentrations for years before were found in parts of Belknap and Rockingham counties and in small clusters within Carroll, Hillsborough, and Merrimack counties.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121236","collaboration":"Prepared in cooperation with the New Hampshire Department of Environmental Services","usgsCitation":"Medalie, L., 2012, Temporal and spatial trends of chloride and sodium in groundwater in New Hampshire, 1960–2011: U.S. Geological Survey Open-File Report 2012-1236, v, 25 p., https://doi.org/10.3133/ofr20121236.","productDescription":"v, 25 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":263435,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1236/"},{"id":263436,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1236/pdf/ofr2012-1236_report_508.pdf","text":"Report","size":"1.73 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Hampshire\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4f4a3e4b0e8fec6ce763c","contributors":{"authors":[{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469193,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048348,"text":"70048348 - 2012 - Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters","interactions":[],"lastModifiedDate":"2016-11-30T13:30:53","indexId":"70048348","displayToPublicDate":"2012-11-27T11:41:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters","docAbstract":"Coastal and estuarine waters are the site of intense anthropogenic influence with concomitant use for recreation and seafood harvesting. Therefore, coastal and estuarine water quality has a direct impact on human health. In eastern North Carolina (NC) there are over 240 recreational and 1025 shellfish harvesting water quality monitoring sites that are regularly assessed. Because of the large number of sites, sampling frequency is often only on a weekly basis. This frequency, along with an 18–24 h incubation time for fecal indicator bacteria (FIB) enumeration via culture-based methods, reduces the efficiency of the public notification process. In states like NC where beach monitoring resources are limited but historical data are plentiful, predictive models may offer an improvement for monitoring and notification by providing real-time FIB estimates. In this study, water samples were collected during 12 dry (n = 88) and 13 wet (n = 66) weather events at up to 10 sites. Statistical predictive models for Escherichiacoli (EC), enterococci (ENT), and members of the Bacteroidales group were created and subsequently validated. Our results showed that models for EC and ENT (adjusted R2 were 0.61 and 0.64, respectively) incorporated a range of antecedent rainfall, climate, and environmental variables. The most important variables for EC and ENT models were 5-day antecedent rainfall, dissolved oxygen, and salinity. These models successfully predicted FIB levels over a wide range of conditions with a 3% (EC model) and 9% (ENT model) overall error rate for recreational threshold values and a 0% (EC model) overall error rate for shellfish threshold values. Though modeling of members of the Bacteroidales group had less predictive ability (adjusted R2 were 0.56 and 0.53 for fecal Bacteroides spp. and human Bacteroides spp., respectively), the modeling approach and testing provided information on Bacteroidales ecology. This is the first example of a set of successful statistical predictive models appropriate for assessment of both recreational and shellfish harvesting water quality in estuarine waters.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2012.07.050","usgsCitation":"Gonzalez, R., Conn, K., Crosswell, J., and Noble, R., 2012, Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters: Water Research, v. 46, no. 18, p. 5871-5882, https://doi.org/10.1016/j.watres.2012.07.050.","productDescription":"12 p.","startPage":"5871","endPage":"5882","ipdsId":"IP-036574","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":278005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278004,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.watres.2012.07.050"}],"country":"United States","state":"North Carolina","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.709756,34.769892 ], [ -76.709756,34.78618 ], [ -76.669006,34.78618 ], [ -76.669006,34.769892 ], [ -76.709756,34.769892 ] ] ] } } ] }","volume":"46","issue":"18","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524162e2e4b0ec672f073ad1","contributors":{"authors":[{"text":"Gonzalez, Raul","contributorId":17131,"corporation":false,"usgs":true,"family":"Gonzalez","given":"Raul","email":"","affiliations":[],"preferred":false,"id":484361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crosswell, Joey","contributorId":75437,"corporation":false,"usgs":true,"family":"Crosswell","given":"Joey","affiliations":[],"preferred":false,"id":484362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Rachel","contributorId":82212,"corporation":false,"usgs":true,"family":"Noble","given":"Rachel","affiliations":[],"preferred":false,"id":484363,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038918,"text":"70038918 - 2012 - Effect of survey design and catch rate estimation on total catch estimates in Chinook salmon fisheries","interactions":[],"lastModifiedDate":"2012-11-27T09:04:26","indexId":"70038918","displayToPublicDate":"2012-11-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effect of survey design and catch rate estimation on total catch estimates in Chinook salmon fisheries","docAbstract":"Roving–roving and roving–access creel surveys are the primary techniques used to obtain information on harvest of Chinook salmon Oncorhynchus tshawytscha in Idaho sport fisheries. Once interviews are conducted using roving–roving or roving–access survey designs, mean catch rate can be estimated with the ratio-of-means (ROM) estimator, the mean-of-ratios (MOR) estimator, or the MOR estimator with exclusion of short-duration (≤0.5 h) trips. Our objective was to examine the relative bias and precision of total catch estimates obtained from use of the two survey designs and three catch rate estimators for Idaho Chinook salmon fisheries. Information on angling populations was obtained by direct visual observation of portions of Chinook salmon fisheries in three Idaho river systems over an 18-d period. Based on data from the angling populations, Monte Carlo simulations were performed to evaluate the properties of the catch rate estimators and survey designs. Among the three estimators, the ROM estimator provided the most accurate and precise estimates of mean catch rate and total catch for both roving–roving and roving–access surveys. On average, the root mean square error of simulated total catch estimates was 1.42 times greater and relative bias was 160.13 times greater for roving–roving surveys than for roving–access surveys. Length-of-stay bias and nonstationary catch rates in roving–roving surveys both appeared to affect catch rate and total catch estimates. Our results suggest that use of the ROM estimator in combination with an estimate of angler effort provided the least biased and most precise estimates of total catch for both survey designs. However, roving–access surveys were more accurate than roving–roving surveys for Chinook salmon fisheries in Idaho.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/02755947.2012.716017","usgsCitation":"McCormick, J.L., Quist, M.C., and Schill, D.J., 2012, Effect of survey design and catch rate estimation on total catch estimates in Chinook salmon fisheries: North American Journal of Fisheries Management, v. 32, no. 6, p. 1090-1101, https://doi.org/10.1080/02755947.2012.716017.","productDescription":"12 p.","startPage":"1090","endPage":"1101","additionalOnlineFiles":"N","ipdsId":"IP-037567","costCenters":[{"id":342,"text":"Idaho Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":263401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263400,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2012.716017"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.0,42.0 ], [ -117.0,49.0 ], [ -111.0,49.0 ], [ -111.0,42.0 ], [ -117.0,42.0 ] ] ] } } ] }","volume":"32","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-10-31","publicationStatus":"PW","scienceBaseUri":"50db2804e4b0612706008dd2","contributors":{"authors":[{"text":"McCormick, Joshua L.","contributorId":105193,"corporation":false,"usgs":true,"family":"McCormick","given":"Joshua","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":465237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. mquist@usgs.gov","contributorId":4042,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":465235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schill, Daniel J.","contributorId":66562,"corporation":false,"usgs":true,"family":"Schill","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":465236,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70040977,"text":"sir20125139 - 2012 - Evaluation of volatile organic compound (VOC) blank data and application of study reporting levels to groundwater data collected for the California GAMA Priority Basin Project, May 2004 through September 2010","interactions":[],"lastModifiedDate":"2012-11-27T20:00:08","indexId":"sir20125139","displayToPublicDate":"2012-11-27T00:00:00","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":"2012-5139","title":"Evaluation of volatile organic compound (VOC) blank data and application of study reporting levels to groundwater data collected for the California GAMA Priority Basin Project, May 2004 through September 2010","docAbstract":"Volatile organic compounds (VOCs) were analyzed in quality-control samples collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project. From May 2004 through September 2010, a total of 2,026 groundwater samples, 211 field blanks, and 109 source-solution blanks were collected and analyzed for concentrations of 85 VOCs. Results from analyses of these field and source-solution blanks and of 2,411 laboratory instrument blanks during the same time period were used to assess the quality of data for the 2,026 groundwater samples. Eighteen VOCs were detected in field blanks or source-solution blanks: acetone, benzene, bromodichloromethane, 2-butanone, carbon disulfide, chloroform, 1,1-dichloroethene, dichloromethane, ethylbenzene, tetrachloroethene, styrene, tetrahydrofuran, toluene, trichloroethene, trichlorofluoromethane, 1,2,4-trimethylbenzene, m- and p-xylenes, and o-xylene.\n\nThe objective of the evaluation of the VOC-blank data was to determine if study reporting levels (SRLs) were needed for any of the VOCs detected in blanks to ensure the quality of the data from groundwater samples. An SRL is equivalent to a raised reporting level that is used in place of the reporting level used by the analyzing laboratory [long‑term method detection level (LT-MDL) or laboratory reporting level (LRL)] to reduce the probability of reporting false-positive detections. Evaluation of VOC-blank data was done in three stages: (1) identification of a set of representative quality‑control field blanks (QCFBs) to be used for calculation of SRLs and identification of VOCs amenable to the SRL approach, (2) evaluation of potential sources of contamination to blanks and groundwater samples by VOCs detected in field blanks, and (3) selection of appropriate SRLs from among four potential SRLs for VOCs detected in field blanks and application of those SRLs to the groundwater data. An important conclusion from this study is that to ensure the quality of the data from groundwater samples, it was necessary to apply different methods of determining SRLs from field blank data to different VOCs, rather than use the same method for all VOCs.\n\nFour potential SRL values were defined by using three approaches: two values were defined by using a binomial probability method based on one-sided, nonparametric upper confidence limits, one was defined as equal to the maximum concentration detected in the field blanks, and one was defined as equal to the maximum laboratory method detection level used during the period when samples were collected for the project. The differences in detection frequencies and concentrations among different types of blanks (laboratory instrument blanks, source-solution blanks, and field blanks collected with three different sampling equipment configurations) and groundwater samples were used to infer the sources and mechanisms of contamination for each VOC detection in field blanks. Other chemical data for the groundwater samples (oxidation-reduction state, co-occurrence of VOCs, groundwater age) and ancillary information about the well sites (land use, presence of known sources of contamination) were used to evaluate whether the patterns of detections of VOCs in groundwater samples before and after application of potential SRLs were plausible. On this basis, the appropriate SRL was selected for each VOC that was determined to require an SRL.\n\nThe SRLs for ethylbenzene [0.06 microgram per liter (μg/L)], m- and p-xylenes (0.33 μg/L), o-xylene (0.12 μg/L), toluene (0.69 μg/L), and 1,2,4-trimethylbenzene (0.56 μg/L) corresponded to the highest concentrations detected in the QCFBs and were selected because they resulted in the most censoring of groundwater data. Comparisons of hydrocarbon ratios in groundwater samples and blanks and comparisons between detection frequencies of the five hydrocarbons in groundwater samples and different types of blanks suggested three dominant sources of contamination that affected groundwater samples and blanks: (1) ethylbenzene, m- and p-xylenes, o-xylene, and toluene from fuel or exhaust components sorbed onto sampling lines, (2) toluene from vials and the source blank water, and (3) 1,2,4-trimethylbenzene from materials used for collection of samples for radon-222 analysis.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125139","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S., Olsen, L., and Belitz, K., 2012, Evaluation of volatile organic compound (VOC) blank data and application of study reporting levels to groundwater data collected for the California GAMA Priority Basin Project, May 2004 through September 2010: U.S. Geological Survey Scientific Investigations Report 2012-5139, viii, 94 p.; col. ill.; maps (col.), https://doi.org/10.3133/sir20125139.","productDescription":"viii, 94 p.; col. ill.; maps (col.)","startPage":"i","endPage":"94","numberOfPages":"106","additionalOnlineFiles":"N","temporalStart":"2004-05-01","temporalEnd":"2010-09-30","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":263432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5139.jpg"},{"id":263430,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5139/"},{"id":263431,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5139/pdf/sir20125139.pdf"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50dca8b1e4b0d55926e3ec23","contributors":{"authors":[{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olsen, Lisa D. ldolsen@usgs.gov","contributorId":2707,"corporation":false,"usgs":true,"family":"Olsen","given":"Lisa D.","email":"ldolsen@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":469185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469183,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70040911,"text":"70040911 - 2012 - Spatial and temporal trends of freshwater mussel assemblages in the Meramec River Basin, Missouri, USA","interactions":[],"lastModifiedDate":"2017-05-22T14:53:44","indexId":"70040911","displayToPublicDate":"2012-11-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal trends of freshwater mussel assemblages in the Meramec River Basin, Missouri, USA","docAbstract":"The Meramec River basin in east-central Missouri has one of the most diverse unionoid mussel faunas in the central United States with >40 species identified. Data were analyzed from historical surveys to test whether diversity and abundance of mussels in the Meramec River basin (Big, Bourbeuse, and Meramec rivers, representing >400 river miles) decreased between 1978 and 1997. We found that over 20y, species richness and diversity decreased significantly in the Bourbeuse and Meramec rivers but not in the Big River. Most species were found at fewer sites and in lower numbers in 1997 than in 1978. Federally endangered species and Missouri Species of Conservation Concern with the most severe temporal declines were Alasmidonta viridis, Arcidens confragosus, Elliptio crassidens, Epioblasma triquetra, Fusconaia ebena, Lampsilis abrupta, Lampsilis brittsi, and Simpsonaias ambigua. Averaged across all species, mussels were generally being extirpated from historical sampling sites more rapidly than colonization was occurring. An exception was one reach of the Meramec River between river miles 28.4 and 59.5, where mussel abundance and diversity were greater than in other reaches and where colonization of Margaritiferidae, Lampsilini, and Quadrulini exceeded extirpation. The exact reasons mussel diversity and abundance have remained robust in this 30- mile reach is uncertain, but the reach is associated with increased gradients, few long pools, and vertical rock faces, all of which are preferable for mussels. Complete loss of mussel communities at eight sites (16%) with relatively diverse historical assemblages was attributed to physical habitat changes including bank erosion, unstable substrate, and sedimentation. Mussel conservation efforts, including restoring and protecting riparian habitats, limiting the effects of in-stream sand and gravel mining, monitoring and controlling invasive species, and protecting water quality, may be warranted in the Meramec River basin.","language":"English","publisher":"Scientific Journals","doi":"10.3996/052012-JFWM-038","usgsCitation":"Hinck, J.E., McMurray, S., Roberts, A.D., Barnhart, M., Ingersoll, C.G., Wang, N., and Augspurger, T., 2012, Spatial and temporal trends of freshwater mussel assemblages in the Meramec River Basin, Missouri, USA: Journal of Fish and Wildlife Management, v. 3, no. 2, p. 319-331, https://doi.org/10.3996/052012-JFWM-038.","productDescription":"13 p.","startPage":"319","endPage":"331","ipdsId":"IP-035423","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":474255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052012-jfwm-038","text":"Publisher Index Page"},{"id":263420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263419,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3996/052012-JFWM-038"}],"country":"United States","state":"Missouri","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.77,36.0 ], [ -95.77,40.61 ], [ -89.1,40.61 ], [ -89.1,36.0 ], [ -95.77,36.0 ] ] ] } } ] }","volume":"3","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4ce19e4b0e8fec6ce2279","contributors":{"authors":[{"text":"Hinck, Jo Ellen 0000-0002-4912-5766","orcid":"https://orcid.org/0000-0002-4912-5766","contributorId":38507,"corporation":false,"usgs":true,"family":"Hinck","given":"Jo","email":"","middleInitial":"Ellen","affiliations":[],"preferred":false,"id":469173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMurray, Stephen E.","contributorId":38687,"corporation":false,"usgs":true,"family":"McMurray","given":"Stephen E.","affiliations":[],"preferred":false,"id":469174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Andrew D.","contributorId":52304,"corporation":false,"usgs":true,"family":"Roberts","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":469175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, M. Christopher","contributorId":78061,"corporation":false,"usgs":true,"family":"Barnhart","given":"M. Christopher","affiliations":[],"preferred":false,"id":469177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":469171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":469172,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Augspurger, Tom","contributorId":63921,"corporation":false,"usgs":true,"family":"Augspurger","given":"Tom","affiliations":[],"preferred":false,"id":469176,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70040902,"text":"sir20125249 - 2012 - Hydrogeology and water quality of the Floridan aquifer system and effect of Lower Floridan aquifer pumping on the Upper Floridan aquifer, Pooler, Chatham County, Georgia, 2011–2012","interactions":[],"lastModifiedDate":"2021-03-24T17:17:41.465185","indexId":"sir20125249","displayToPublicDate":"2012-11-27T00:00:00","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":"2012-5249","title":"Hydrogeology and water quality of the Floridan aquifer system and effect of Lower Floridan aquifer pumping on the Upper Floridan aquifer, Pooler, Chatham County, Georgia, 2011–2012","docAbstract":"Two test wells were completed in Pooler, Georgia, in 2011 to investigate the potential of using the Lower Floridan aquifer as a source of water for municipal use. One well was completed in the Lower Floridan aquifer at a depth of 1,120 feet (ft) below land surface; the other well was completed in the Upper Floridan aquifer at a depth of 486 ft below land surface. At the Pooler test site, the U.S. Geological Survey performed flowmeter surveys, packer-isolated slug tests within the Lower Floridan confining unit, slug tests of the entire Floridan aquifer system, and aquifer tests of the Upper and Lower Floridan aquifers. Drill cuttings, geophysical logs, and borehole flowmeter surveys indicate that the Upper Floridan aquifer extends 333 –515 ft below land surface, the Lower Floridan confining unit extends 515–702 ft below land surface, and the Lower Floridan aquifer extends 702–1,040 ft below land surface. Flowmeter surveys indicate that the Upper Floridan aquifer contains two water-bearing zones at depth intervals of 339 –350 and 375–515 ft; the Lower Floridan confining unit contains one zone at a depth interval of 550–620 ft; and the Lower Floridan aquifer contains five zones at depth intervals of 702–745, 745–925, 925–984, 984–1,015, and 1,015–1,040 ft. Flowmeter testing of the test borehole open to the entire Floridan aquifer system indicated that the Upper Floridan aquifer contributed 92.4 percent of the total flow rate of 708 gallons per minute; the Lower Floridan confining unit contributed 3.0 percent; and the Lower Floridan aquifer contributed 4.6 percent. Horizontal hydraulic conductivity of the Lower Floridan confining unit derived from slug tests within three packer-isolated intervals ranged from 0.5 to 10 feet per day (ft/d). Aquifer-test analyses yielded values of transmissivity for the Upper Floridan aquifer, Lower Floridan confining unit, and the Lower Floridan aquifer of 46,000, 700, and 4,000 feet squared per day (ft2/d), respectively. Horizontal hydraulic conductivity of 4 ft/d for the Lower Floridan confining unit, derived from aquifer-test analyses, is near the midrange for values derived from packer-isolated slug tests. The transmissivity of the entire Floridan aquifer system derived from aquifer-test analyses totals about 51,000 ft2/d, similar to the value of 58,000 ft2/d derived from open slug tests on the entire Floridan aquifer system. Water-level data for each aquifer test were filtered for external influences such as barometric pressure, earth-tide effects, and long-term trends to enable detection of small (less than 1 foot) water-level responses to aquifer-test pumping. During the 72-hour aquifer test of pumping the Lower Floridan aquifer, a drawdown response of 51.7 ft was observed in the Lower Floridan pumped well and a drawdown response of 0.9 foot was observed in the Upper Floridan observation well located 85 ft from the pumped well.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125249","collaboration":"Prepared in cooperation with the City of Pooler, Georgia","usgsCitation":"Gonthier, G., 2012, Hydrogeology and water quality of the Floridan aquifer system and effect of Lower Floridan aquifer pumping on the Upper Floridan aquifer, Pooler, Chatham County, Georgia, 2011–2012: U.S. Geological Survey Scientific Investigations Report 2012-5249, x, 62 p., https://doi.org/10.3133/sir20125249.","productDescription":"x, 62 p.","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":263411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5249.jpg"},{"id":263410,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5249/pdf/sir2012-5249.pdf"},{"id":263409,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5249/"}],"scale":"2000000","country":"United States","state":"Georgia","county":"Chatham County","city":"Pooler","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.75,31.75 ], [ -81.75,32.25 ], [ -80.75,32.25 ], [ -80.75,31.75 ], [ -81.75,31.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50deeeb0e4b0dfbe79e663f4","contributors":{"authors":[{"text":"Gonthier, Gerard 0000-0003-4078-8579 gonthier@usgs.gov","orcid":"https://orcid.org/0000-0003-4078-8579","contributorId":3141,"corporation":false,"usgs":true,"family":"Gonthier","given":"Gerard ","email":"gonthier@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":469170,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70040856,"text":"ofr20121249 - 2012 - Assessment of photographs from wildlife monitoring cameras in Drakes Estero, Point Reyes National Seashore, California","interactions":[],"lastModifiedDate":"2018-08-10T16:54:40","indexId":"ofr20121249","displayToPublicDate":"2012-11-26T00:00:00","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":"2012-1249","title":"Assessment of photographs from wildlife monitoring cameras in Drakes Estero, Point Reyes National Seashore, California","docAbstract":"Between 2007 and 2010, National Park Service (NPS) staff at the Point Reyes National Seashore, California, collected over 300,000 photographic images of Drakes Estero from remotely operated wildlife monitoring cameras. The purpose of the systems was to obtain photographic data to help understand possible relationships between anthropogenic activities and Pacific harbor seal (Phoca vitulina richardsi) behavior and distribution. \n\nThe value of the NPS photographs for use in assessing the frequency and impacts of seal disturbance and displacement in Drakes Estero has been debated. In September 2011, the NPS determined that the photographs did not provide meaningful information for development of a Draft Environmental Impact Statement (DEIS) for the Drakes Bay Oyster Company Special Use Permit. Limitations of the photographs included lack of study design, poor photographic quality, inadequate field of view, incomplete estuary coverage, camera obstructions, and weather limitations. \n\nThe Marine Mammal Commission (MMC) reviewed the scientific data underpinning the Drakes Bay Oyster Company DEIS in November 2011 and recommended further analysis of the NPS photographs for use in characterizing rates and consequences of seal disturbance (Marine Mammal Commission, 2011). In response to that recommendation, the NPS asked the U.S. Geological Survey (USGS) to conduct an independent review of the photographs and render an opinion on the utility of the remote camera data for informing the environmental impact analyses included in the DEIS.\n\nIn consultation with the NPS, we selected the 2008 photographic dataset for detailed evaluation because it covers a full harbor seal breeding season (March 1 to June 30), provides two fields of view (two cameras were deployed), and represents a time period when cameras were most consistently deployed and maintained. The NPS requested that the photographs be evaluated in absence of other data or information pertaining to seal and human activity in the estuary and that we focus on the extent to which the photographs could be used in understanding the relationship between human activity (including commercial oyster production) and harbor seal disturbance and distribution in the estuary.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121249","usgsCitation":"Lellis, W.A., Blakeslee, C.J., Allen, L.K., Molnia, B.F., Price, S.D., Bristol, R.S., and Stewart, B., 2012, Assessment of photographs from wildlife monitoring cameras in Drakes Estero, Point Reyes National Seashore, California: U.S. Geological Survey Open-File Report 2012-1249, iii, 24 p.; Appendix, https://doi.org/10.3133/ofr20121249.","productDescription":"iii, 24 p.; Appendix","costCenters":[{"id":410,"text":"National Center","active":false,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":263359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1249.jpg"},{"id":263355,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1249/"},{"id":263356,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1249/pdf/OFR2012-1249.pdf"}],"country":"United States","state":"California","otherGeospatial":"Drakes Estero;Point Reyes National Seashore","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f7de4b0b3fb1a229134","contributors":{"authors":[{"text":"Lellis, William A. 0000-0001-7806-2904 wlellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7806-2904","contributorId":2369,"corporation":false,"usgs":true,"family":"Lellis","given":"William","email":"wlellis@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":469137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":469142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Laurie K. lkallen@usgs.gov","contributorId":5134,"corporation":false,"usgs":true,"family":"Allen","given":"Laurie","email":"lkallen@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":469141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molnia, Bruce F. bmolnia@usgs.gov","contributorId":4002,"corporation":false,"usgs":true,"family":"Molnia","given":"Bruce","email":"bmolnia@usgs.gov","middleInitial":"F.","affiliations":[{"id":410,"text":"National Center","active":false,"usgs":true}],"preferred":false,"id":469140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Price, Susan D. sprice@usgs.gov","contributorId":3825,"corporation":false,"usgs":true,"family":"Price","given":"Susan","email":"sprice@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":469139,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bristol, R. Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":3585,"corporation":false,"usgs":true,"family":"Bristol","given":"R.","email":"sbristol@usgs.gov","middleInitial":"Sky","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":469138,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stewart, Brent","contributorId":69862,"corporation":false,"usgs":true,"family":"Stewart","given":"Brent","email":"","affiliations":[],"preferred":false,"id":469143,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70040857,"text":"sir20125256 - 2012 - Alluvial diamond resource potential and production capacity assessment of Guinea","interactions":[],"lastModifiedDate":"2022-05-27T15:40:31.211434","indexId":"sir20125256","displayToPublicDate":"2012-11-26T00:00:00","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":"2012-5256","title":"Alluvial diamond resource potential and production capacity assessment of Guinea","docAbstract":"In May of 2000, a meeting was convened in Kimberley, South Africa, by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that export shipments of rough diamonds were free of conflict concerns. Outcomes of the meeting were formally supported later in December of 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme (KPCS) was ratified and signed by diamond-producing and diamond-importing countries. The goal of this study was to estimate the alluvial diamond resource endowment and the current production capacity of the alluvial diamond mining sector of Guinea. A modified volume and grade methodology was used to estimate the remaining diamond reserves within Guinea's diamondiferous regions, while the diamond-production capacity of these zones was estimated by inputting the number of artisanal miners, the number of days artisans work per year, and the average grade of the deposits into a formulaic expression. Guinea's resource potential was estimated to be approximately 40 million carats, while the production capacity was estimated to lie within a range of 480,000 to 720,000 carats per year. While preliminary results have been produced by integrating historical documents, five fieldwork campaigns, and remote sensing and GIS analysis, significant data gaps remain. The artisanal mining sector is dynamic and is affected by a variety of internal and external factors. Estimates of the number of artisans and deposit variables, such as grade, vary from site to site and from zone to zone. This report has been developed on the basis of the most detailed information available at this time. However, continued fieldwork and evaluation of artisanally mined deposits would increase the accuracy of the results.","language":"English, French","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125256","collaboration":"Prepared in cooperation with the Ministère des Mines et de la Géologie of Guinea under the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., Malpeli, K., Van Bockstael, M., Diaby, M., Cisse, K., Diallo, T.A., and Sano, M., 2012, Alluvial diamond resource potential and production capacity assessment of Guinea (Originally posted November 26, 2012; French Translation April 30, 2014): U.S. Geological Survey Scientific Investigations Report 2012-5256, vi, 49 p., https://doi.org/10.3133/sir20125256.","productDescription":"vi, 49 p.","numberOfPages":"59","additionalOnlineFiles":"N","costCenters":[{"id":240,"text":"Eastern Earth Surface Processes Team","active":false,"usgs":true}],"links":[{"id":263366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125256.gif"},{"id":263364,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5256/","linkFileType":{"id":5,"text":"html"}},{"id":263365,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5256/pdf/sir2012-5256.pdf","text":"Report (English)","linkFileType":{"id":1,"text":"pdf"}},{"id":286835,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5256/french/pdf/sir2012-5256_frenchversion.pdf","text":"Report (French)","linkFileType":{"id":1,"text":"pdf"}}],"country":"Guinea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -15.0,7.0 ], [ -15.0,13.0 ], [ -7.25,13.0 ], [ -7.25,7.0 ], [ -15.0,7.0 ] ] ] } } ] }","edition":"Originally posted November 26, 2012; French Translation April 30, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f69e4b0b3fb1a22912c","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":469146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":469148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Bockstael, Mark","contributorId":8351,"corporation":false,"usgs":true,"family":"Van Bockstael","given":"Mark","email":"","affiliations":[],"preferred":false,"id":469144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diaby, Mamadou","contributorId":50057,"corporation":false,"usgs":true,"family":"Diaby","given":"Mamadou","email":"","affiliations":[],"preferred":false,"id":469147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cisse, Kabinet","contributorId":66140,"corporation":false,"usgs":true,"family":"Cisse","given":"Kabinet","email":"","affiliations":[],"preferred":false,"id":469149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diallo, Thierno Amadou","contributorId":80987,"corporation":false,"usgs":true,"family":"Diallo","given":"Thierno","email":"","middleInitial":"Amadou","affiliations":[],"preferred":false,"id":469150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sano, Mahmoud","contributorId":23406,"corporation":false,"usgs":true,"family":"Sano","given":"Mahmoud","email":"","affiliations":[],"preferred":false,"id":469145,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70040860,"text":"sir20125164 - 2012 - Global exploration and production capacity for platinum-group metals from 1995 through 2015","interactions":[],"lastModifiedDate":"2012-12-20T08:59:45","indexId":"sir20125164","displayToPublicDate":"2012-11-26T00:00:00","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":"2012-5164","title":"Global exploration and production capacity for platinum-group metals from 1995 through 2015","docAbstract":"Platinum-group metals (PGMs) are required in a variety of commercial, industrial, and military applications for many existing and emerging technologies, yet the United States is highly dependent on foreign sources of PGMs. Information on global exploration for PGMs since 1995 has been used in this study as a basis for identifying locations where the industry has determined that exploration has provided data sufficient to warrant development of a new mine or expansion of an existing operation or where a significant increase in capacity for PGMs is anticipated by 2015. Discussions include an overview of the industry and the selected sites, factors affecting mineral supply, and circumstances leading to the development of mineral properties with the potential to affect mineral supply. Of the 52 sites or regional operations that were considered in this analysis, 16 sites were producing before 1995, 28 sites commenced production from 1995 through 2010, and 8 sites were expected to begin production from 2011 through 2015 if development plans came to fruition. The United States imports PGMs primarily from Canada, Russia, South Africa, and Zimbabwe to meet increasing demand for these materials in a variety of specialized and high-tech applications. Feed sources of PGMs are changing in South Africa and Russia, which together accounted for about 89 percent of platinum production and 82 percent of palladium production in 2009. A greater amount of South African PGM capacity is likely to come from deeper, higher cost Upper Group Reef seam 2 deposits and deposits in the Eastern Bushveld area. Future Russian PGM capacity is likely to come from ore zones with generally lower PGM content and different platinum-to-palladium ratios than the nickel-rich ore that dominated PGM supply in the 1990s. Because PGM supply from Canada and Russia is derived as a byproduct of copper and nickel mining, the PGM supply from these countries is influenced by economic, environmental, political, and technological factors affecting exploration for and development of copper and nickel, as well as factors affecting the PGM industry. The recovery of PGMs from mill tailings since 2004 and the recycling of PGMs from catalytic converters, electrical components, and jewelry has increased since 1995 so that recycled PGMs recovered from these products accounted for about 30 percent of the supply of platinum worldwide and 29 percent of the supply of palladium worldwide in 2010. Economic and geopolitical conditions have influenced PGM supply and demand. The global recession of 2008 and 2009 temporarily decreased demand for PGMs and constrained PGM mine exploration and development, at least through 2010. Legislation regulating the structure of the mining sector has affected mining in Russia, South Africa, and Zimbabwe. Stricter vehicle emissions standards in established markets since the 1980s have led to mandatory use of pollution control devices, such as catalytic converters, that contain PGMs and are required on vehicles in expanding markets, such as China and India. It is expected that South Africa, Russia, Canada, and Zimbabwe will continue to be the principal sources of PGM at least for the next decade. Based on this review of the PGM industry, the world’s platinum capacity, expressed in terms of recoverable platinum metal, increased from 1995 through 2010 by 77,000 kilograms (kg) in South Africa, 9,000 kg in Zimbabwe, 6,000 kg in Russia, 2,000 kg in Botswana, and 2,000 kg in Canada. For the same period, palladium capacity worldwide increased by 44,000 kg in South Africa, 22,000 kg in Russia, 8,000 kg in Canada, 8,000 kg in the United States, 7,000 kg in Zimbabwe, and 3,000 kg in Botswana. Platinum capacity worldwide is expected to further increase by 24,000 kg in South Africa, 9,000 kg in Russia, 3,000 kg in Canada, and 2,000 kg in Zimbabwe from 2011 through 2015. Palladium capacity worldwide is likewise expected to increase an additional 16,000 kg in Russia, 14,000 kg in South Africa, 4,000 kg in Zimbabwe, and 1,000 kg in Canada if new or expanded mine and associated processing capacity comes into production as planned. It is likely that the magnitude of these changes in PGM capacity has been influenced by such factors as the global economy, electrical capacity shortages and mine safety concerns in South Africa, and geopolitical conditions in the major PGM producing countries.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125164","usgsCitation":"Wilburn, D.R., 2012, Global exploration and production capacity for platinum-group metals from 1995 through 2015 (Originally posted November 26, 2012; Revised December 14, 2012): U.S. Geological Survey Scientific Investigations Report 2012-5164, iv, 26 p., https://doi.org/10.3133/sir20125164.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1995-01-01","temporalEnd":"2015-12-31","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":264658,"type":{"id":18,"text":"Project Site"},"url":"https://minerals.usgs.gov/minerals/"},{"id":263371,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5164/"},{"id":263372,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5164/pdf/sir2012-5164.pdf"},{"id":263373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5164.gif"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","edition":"Originally posted November 26, 2012; Revised December 14, 2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f8ae4b0b3fb1a229140","contributors":{"authors":[{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":469151,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70182150,"text":"70182150 - 2012 - Soil-water dynamics and unsaturated storage during snowmelt following wildfire","interactions":[],"lastModifiedDate":"2017-02-17T10:02:03","indexId":"70182150","displayToPublicDate":"2012-11-22T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Soil-water dynamics and unsaturated storage during snowmelt following wildfire","docAbstract":"Many forested watersheds with a substantial fraction of precipitation delivered as snow have the potential for landscape disturbance by wildfire. Little is known about the immediate effects of wildfire on snowmelt and near-surface hydrologic responses, including soil-water storage. Montane systems at the rain-snow transition have soil-water dynamics that are further complicated during the snowmelt period by strong aspect controls on snowmelt and soil thawing. Here we present data from field measurements of snow hydrology and subsurface hydrologic and temperature responses during the first winter and spring after the September 2010 Fourmile Canyon Fire in Colorado, USA. Our observations of soil-water content and soil temperature show sharp contrasts in hydrologic and thermal conditions between north- and south-facing slopes. South-facing burned soils were ∼1–2 °C warmer on average than north-facing burned soils and ∼1.5 °C warmer than south-facing unburned soils, which affected soil thawing during the snowmelt period. Soil-water dynamics also differed by aspect: in response to soil thawing, soil-water content increased approximately one month earlier on south-facing burned slopes than on north-facing burned slopes. While aspect and wildfire affect soil-water dynamics during snowmelt, soil-water storage at the end of the snowmelt period reached the value at field capacity for each plot, suggesting that post-snowmelt unsaturated storage was not substantially influenced by aspect in wildfire-affected areas. Our data and analysis indicate that the amount of snowmelt-driven groundwater recharge may be larger in wildfire-impacted areas, especially on south-facing slopes, because of earlier soil thaw and longer durations of soil-water contents above field capacity in those areas.
","language":"English","publisher":"European Geophysical Society","publisherLocation":"Katlenburg-Lindau","doi":"10.5194/hess-16-1401-2012","usgsCitation":"Ebel, B.A., Hinckley, E., and Martin, D.A., 2012, Soil-water dynamics and unsaturated storage during snowmelt following wildfire: Hydrology and Earth System Sciences, v. 16, p. 1401-1417, https://doi.org/10.5194/hess-16-1401-2012.","productDescription":"17 p.","startPage":"1401","endPage":"1417","ipdsId":"IP-034382","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":474259,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-16-1401-2012","text":"Publisher Index Page"},{"id":335802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-05-15","publicationStatus":"PW","scienceBaseUri":"58a819b8e4b025c46429afd0","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":669794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hinckley, E.S.","contributorId":181852,"corporation":false,"usgs":false,"family":"Hinckley","given":"E.S.","email":"","affiliations":[],"preferred":false,"id":669824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":669795,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041372,"text":"ds709F - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:14:25","indexId":"ds709F","displayToPublicDate":"2012-11-21T00:00:00","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":"709","chapter":"F","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Badakhshan) and the WGS84 datum. The final image mosaics were subdivided into six overlapping tiles or quadrants because of the large size of the target area. The six image tiles (or quadrants) for the Badakhshan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Badakhshan study area, three subareas were designated for detailed field investigations (that is, the Bharak, Fayz-Abad, and Ragh subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709F","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 3 Maps: 11 x 8.5 inches and 45.64 x 48.46 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709F.","productDescription":"Readme; 3 Maps: 11 x 8.5 inches and 45.64 x 48.46 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":263684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_F.jpg"},{"id":263675,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/f/"},{"id":263676,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/f/1_readme.txt"},{"id":263677,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/f/index_maps/Badakhshan_Area-of-Interest_Index_Map.pdf"},{"id":263678,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/f/index_maps/Badakhshan_Image_Mosaic_Index_Map.pdf"},{"id":263679,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/f/index_maps/Badakhshan_Subarea_Image_Mosaic_Index_Map.pdf"},{"id":263680,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/f/image_files/image_files.html"},{"id":263681,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/f/metadata/metadata.html"},{"id":263682,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/f/shapefiles/shapefiles.html"},{"id":263683,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","state":"Badakhshan","otherGeospatial":"Badakhshan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 70.25,37.0 ], [ 70.25,37.75 ], [ 71.25,37.75 ], [ 71.25,37.0 ], [ 70.25,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bfbda6e4b01744973f7813","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":469650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":469651,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041250,"text":"ds709E - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:14:45","indexId":"ds709E","displayToPublicDate":"2012-11-21T00:00:00","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":"709","chapter":"E","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Aynak) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Aynak area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Aynak study area, five subareas were designated for detailed field investigations (that is, the Bakhel-Charwaz, Kelaghey-Kakhay, Kharuti-Dawrankhel, Logar Valley, and Yagh-Darra/Gul-Darra subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709E","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Cagney, L.E., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 3 Maps: 11 x 8.5 inches and 42.79 x 29.78 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709E.","productDescription":"Readme; 3 Maps: 11 x 8.5 inches and 42.79 x 29.78 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":263605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_E.jpg"},{"id":263595,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/e/"},{"id":263600,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Subarea_Image_Index_Map.pdf"},{"id":263601,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/e/image_files/image_files.html"},{"id":263597,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/e/1_readme.txt"},{"id":263598,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Area-of-Interest_Index_Map.pdf"},{"id":263599,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Image_Index_Map.pdf"},{"id":263602,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/e/metadata/metadata.html"},{"id":263603,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/e/shapefiles/shapefiles.html"},{"id":263604,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"}],"country":"Afghanistan","state":"Kabul;Logar;Paktya;Wardak","otherGeospatial":"Aynak Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 68.633333,34.083333 ], [ 68.633333,34.533333 ], [ 69.5,34.533333 ], [ 69.5,34.083333 ], [ 68.633333,34.083333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bd1396e4b069d93eefc4ec","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":469455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":469456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":469457,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040844,"text":"70040844 - 2012 - Reference hydrologic networks II. Using reference hydrologic networks to assess climate-driven changes in streamflow","interactions":[],"lastModifiedDate":"2012-11-20T20:02:57","indexId":"70040844","displayToPublicDate":"2012-11-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Reference hydrologic networks II. Using reference hydrologic networks to assess climate-driven changes in streamflow","docAbstract":"Reference hydrologic networks (RHNs) can play an important role in monitoring for changes in the hydrological regime related to climate variation and change. Currently, the literature concerning hydrological response to climate variations is complex and confounded by the combinations of many methods of analysis, wide variations in hydrology, and the inclusion of data series that include changes in land use, storage regulation and water use in addition to those of climate. Three case studies that illustrate a variety of approaches to the analysis of data from RHNs are presented and used, together with a summary of studies from the literature, to develop approaches for the investigation of changes in the hydrological regime at a continental or global scale, particularly for international comparison. We present recommendations for an analysis framework and the next steps to advance such an initiative. There is a particular focus on the desirability of establishing standardized procedures and methodologies for both the creation of new national RHNs and the systematic analysis of data derived from a collection of RHNs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Sciences Journal/Journal des Sciences Hydrologiques","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadelphia, PA","doi":"10.1080/02626667.2012.728705","usgsCitation":"Burn, D., Hannaford, J., Hodgkins, G.A., Whitfield, P., Thorne, R., and Marsh, T., 2012, Reference hydrologic networks II. Using reference hydrologic networks to assess climate-driven changes in streamflow: Hydrological Sciences Journal, v. 57, no. 8, p. 1-15, https://doi.org/10.1080/02626667.2012.728705.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-030086","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":474263,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02626667.2012.728705","text":"Publisher Index Page"},{"id":263332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263331,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02626667.2012.728705"}],"volume":"57","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-10-26","publicationStatus":"PW","scienceBaseUri":"50aca694e4b0ae6a8f88bbb4","contributors":{"authors":[{"text":"Burn, Donald H.","contributorId":66139,"corporation":false,"usgs":true,"family":"Burn","given":"Donald H.","affiliations":[],"preferred":false,"id":469126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hannaford, Jamie","contributorId":41305,"corporation":false,"usgs":true,"family":"Hannaford","given":"Jamie","affiliations":[],"preferred":false,"id":469125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitfield, Paul H.","contributorId":39264,"corporation":false,"usgs":true,"family":"Whitfield","given":"Paul H.","affiliations":[],"preferred":false,"id":469124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorne, Robin","contributorId":93789,"corporation":false,"usgs":true,"family":"Thorne","given":"Robin","email":"","affiliations":[],"preferred":false,"id":469128,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marsh, Terry","contributorId":86657,"corporation":false,"usgs":true,"family":"Marsh","given":"Terry","email":"","affiliations":[],"preferred":false,"id":469127,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70040846,"text":"sir20125245 - 2012 - Evaluation of streambed scour at bridges over tidal waterways in Alaska","interactions":[],"lastModifiedDate":"2018-04-21T13:39:55","indexId":"sir20125245","displayToPublicDate":"2012-11-20T00:00:00","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":"2012-5245","title":"Evaluation of streambed scour at bridges over tidal waterways in Alaska","docAbstract":"The potential for streambed scour was evaluated at 41 bridges that cross tidal waterways in Alaska. These bridges are subject to several coastal and riverine processes that have the potential, individually or in combination, to induce streambed scour or to damage the structure or adjacent channel. The proximity of a bridge to the ocean and water-surface elevation and velocity data collected over a tidal cycle were criteria used to identify the flow regime at each bridge, whether tidal, riverine, or mixed, that had the greatest potential to induce streambed scour. Water-surface elevations measured through at least one tide cycle at 32 bridges were correlated to water levels at the nearest tide station. Asymmetry of the tidal portion of the hydrograph during the outgoing tide at 12 bridges indicated that riverine flows were stored upstream of the bridge during the tidal exchange. This scenario results in greater discharges and velocities during the outgoing tide compared to those on the incoming tide. Velocity data were collected during outgoing tides at 10 bridges that experienced complete flow reversals, and measured velocities during the outgoing tide exceeded the critical velocity required to initiate sediment transport at three sites. The primary risk for streambed scour at most of the sites considered in this study is from riverine flows rather than tidal fluctuations. A scour evaluation for riverine flow was completed at 35 bridges. Scour from riverine flow was not the primary risk for six tidally-controlled bridges and therefore not evaluated at those sites. Field data including channel cross sections, a discharge measurement, and a water-surface slope were collected at the 35 bridges. Channel instability was identified at 14 bridges where measurable scour and or fill were noted in repeated surveys of channel cross sections at the bridge. Water-surface profiles for the 1-percent annual exceedance probability discharge were calculated by using the Hydrologic Engineering Center’s River Analysis System model, and scour depths were calculated using methods recommended by the Federal Highway Administration. Computed contraction-scour depths were greater than 2.0 feet at five bridges and computed pier-scour depths were 4.0 feet or greater at 15 bridges. The potential for streambed scour by both coastal and riverine processes at the bridges considered in this study were evaluated, ranked, and summed to determine a cumulative risk factor for each bridge. Possible factors that could mitigate the scour risks were investigated at 22 bridges that had high individual or cumulative rankings. Mitigating factors such as piers founded in bedrock, deep pier foundations relative to scour depths, and lack of observed scour during field measurements were documented for 13 sites, but additional study and monitoring is needed to better quantify the streambed scour potential for nine sites. Three bridges prone to being affected by storm surges will require more data collection and possibly complex hydrodynamic modeling to accurately quantify the streambed scour potential. Continuous monitoring of water-surface and streambed elevation at one or more piers is needed for two bridges to better understand the tidal and riverine influences on streambed scour.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125245","collaboration":"Prepared in cooperation with the Alaska Department of Transportation and Public Facilities","usgsCitation":"Conaway, J.S., and Schauer, P.V., 2012, Evaluation of streambed scour at bridges over tidal waterways in Alaska: U.S. Geological Survey Scientific Investigations Report 2012-5245, Report: vi, 38 p.; Appendixes A and B, https://doi.org/10.3133/sir20125245.","productDescription":"Report: vi, 38 p.; Appendixes A and B","numberOfPages":"48","additionalOnlineFiles":"Y","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":263327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5245.jpg"},{"id":263323,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5245/"},{"id":263324,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5245/pdf/sir20125245.pdf"},{"id":263325,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5245/sir20125245_AppendixA.xlsx"},{"id":263326,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5245/sir20125245_AppendixB.xlsx"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -170.0,51.0 ], [ -170.0,62.0 ], [ -130.0,62.0 ], [ -130.0,51.0 ], [ -170.0,51.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50aca678e4b0ae6a8f88bb9e","contributors":{"authors":[{"text":"Conaway, Jeffrey S. 0000-0002-3036-592X jconaway@usgs.gov","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":2026,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeffrey","email":"jconaway@usgs.gov","middleInitial":"S.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":469130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schauer, Paul V. 0000-0001-5529-4649 pschauer@usgs.gov","orcid":"https://orcid.org/0000-0001-5529-4649","contributorId":5779,"corporation":false,"usgs":true,"family":"Schauer","given":"Paul","email":"pschauer@usgs.gov","middleInitial":"V.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":469129,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70040843,"text":"70040843 - 2012 - Reference hydrologic networks I. The status and potential future directions of national reference hydrologic networks for detecting trends","interactions":[],"lastModifiedDate":"2012-11-20T20:15:49","indexId":"70040843","displayToPublicDate":"2012-11-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Reference hydrologic networks I. The status and potential future directions of national reference hydrologic networks for detecting trends","docAbstract":"Identifying climate-driven trends in river flows on a global basis is hampered by a lack of long, quality time series data for rivers with relatively undisturbed regimes. This is a global problem compounded by the lack of support for essential long-term monitoring. Experience demonstrates that, with clear strategic objectives, and the support of sponsoring organizations, reference hydrologic networks can constitute an exceptionally valuable data source to effectively identify, quantify and interpret hydrological change—the speed and magnitude of which is expected to a be a primary driver of water management and flood alleviation strategies through the future—and for additional applications. Reference hydrologic networks have been developed in many countries in the past few decades. These collections of streamflow gauging stations, that are maintained and operated with the intention of observing how the hydrology of watersheds responds to variations in climate, are described. The status of networks under development is summarized. We suggest a plan of actions to make more effective use of this collection of networks.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Sciences Journal/Journal des Sciences Hydrologiques","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadelphia, PA","doi":"10.1080/02626667.2012.728706","usgsCitation":"Whitfield, P., Burn, D., Hannaford, J., Higgins, H., Hodgkins, G.A., Marsh, T., and Looser, U., 2012, Reference hydrologic networks I. The status and potential future directions of national reference hydrologic networks for detecting trends: Hydrological Sciences Journal, v. 57, no. 8, p. 1-18, https://doi.org/10.1080/02626667.2012.728706.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-030088","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":474262,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1080/02626667.2012.728706","text":"External Repository"},{"id":263334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263333,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02626667.2012.728706"}],"volume":"57","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-10-26","publicationStatus":"PW","scienceBaseUri":"50aca690e4b0ae6a8f88bbb0","contributors":{"authors":[{"text":"Whitfield, Paul H.","contributorId":39264,"corporation":false,"usgs":true,"family":"Whitfield","given":"Paul H.","affiliations":[],"preferred":false,"id":469118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burn, Donald H.","contributorId":66139,"corporation":false,"usgs":true,"family":"Burn","given":"Donald H.","affiliations":[],"preferred":false,"id":469121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hannaford, Jamie","contributorId":41305,"corporation":false,"usgs":true,"family":"Hannaford","given":"Jamie","affiliations":[],"preferred":false,"id":469119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Higgins, Helene","contributorId":53670,"corporation":false,"usgs":true,"family":"Higgins","given":"Helene","email":"","affiliations":[],"preferred":false,"id":469120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469116,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marsh, Terry","contributorId":86657,"corporation":false,"usgs":true,"family":"Marsh","given":"Terry","email":"","affiliations":[],"preferred":false,"id":469122,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Looser, Ulrich","contributorId":14274,"corporation":false,"usgs":true,"family":"Looser","given":"Ulrich","email":"","affiliations":[],"preferred":false,"id":469117,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70040831,"text":"ofr20121220 - 2012 - Landscape consequences of natural gas extraction in Greene and Tioga Counties, Pennsylvania, 2004-2010","interactions":[],"lastModifiedDate":"2016-08-19T17:24:37","indexId":"ofr20121220","displayToPublicDate":"2012-11-20T00:00:00","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":"2012-1220","title":"Landscape consequences of natural gas extraction in Greene and Tioga Counties, Pennsylvania, 2004-2010","docAbstract":"Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in the area of Pennsylvania. Coalbed methane, which is sometimes extracted using the same technique, is commonly located in the same general area as the Marcellus Shale and is frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Greene County and Tioga County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics are also used to quantify these changes and are included in this publication.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121220","usgsCitation":"Slonecker, E., Milheim, L., Roig-Silva, C., and Fisher, G., 2012, Landscape consequences of natural gas extraction in Greene and Tioga Counties, Pennsylvania, 2004-2010: U.S. Geological Survey Open-File Report 2012-1220, v; 32 p., https://doi.org/10.3133/ofr20121220.","productDescription":"v; 32 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":263301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1220.gif"},{"id":263299,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1220/"},{"id":263300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1220/ofr2012-1220.pdf","text":"Report","size":"3.65 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50abfb81e4b0afbc75eb9810","contributors":{"authors":[{"text":"Slonecker, E.T.","contributorId":41132,"corporation":false,"usgs":true,"family":"Slonecker","given":"E.T.","email":"","affiliations":[],"preferred":false,"id":469091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milheim, L.E.","contributorId":106320,"corporation":false,"usgs":true,"family":"Milheim","given":"L.E.","email":"","affiliations":[],"preferred":false,"id":469094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roig-Silva, C.M.","contributorId":45176,"corporation":false,"usgs":true,"family":"Roig-Silva","given":"C.M.","affiliations":[],"preferred":false,"id":469092,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, G.B.","contributorId":70238,"corporation":false,"usgs":true,"family":"Fisher","given":"G.B.","email":"","affiliations":[],"preferred":false,"id":469093,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040830,"text":"fs20123130 - 2012 - Summary of the reconnaissance investigation of the diamond resource potential and production capacity of Côte d’Ivoire","interactions":[],"lastModifiedDate":"2012-11-20T10:02:31","indexId":"fs20123130","displayToPublicDate":"2012-11-20T00:00:00","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":"2012-3130","title":"Summary of the reconnaissance investigation of the diamond resource potential and production capacity of Côte d’Ivoire","docAbstract":"This study presents the results of a multiyear effort to monitor the diamond mining activities of Côte d’Ivoire’s two main diamond regions, Séguéla and Tortiya. The innovative approach developed for this study integrates archival reports and maps, high-resolution satellite imagery, and terrain modeling to assess the diamond resource potential and production capacity of the Séguéla and Tortiya deposits.\n\nA geologic resource assessment was conducted to calculate the remaining diamond reserves for Séguéla and Tortiya using archival geologic data, including gravel grade and thickness recorded by the Ivorian mining company Société pour le Développement Minier (SODEMI). These data were combined with terrain analysis and geomorphological maps in a geological process-driven model. After accounting for previous production, a total of 10,100,000 carats are estimated to be remaining in Séguéla and a total of 1,100,000 carats are estimated to be remaining in Tortiya, based on currently known deposits.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123130","collaboration":"Prepared under the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., and Malpeli, K., 2012, Summary of the reconnaissance investigation of the diamond resource potential and production capacity of Côte d’Ivoire: U.S. Geological Survey Fact Sheet 2012-3130, 2 p., https://doi.org/10.3133/fs20123130.","productDescription":"2 p.","startPage":"1","endPage":"2","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":229,"text":"Earth Surface Processes Team","active":false,"usgs":true}],"links":[{"id":263298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3130.gif"},{"id":263296,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3130/pdf/fs2012-3130.pdf"},{"id":263297,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3130/"}],"otherGeospatial":"C�te D�ivoire;Ivory Coast","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -8.6,4.35 ], [ -8.6,10.74 ], [ -2.49,10.74 ], [ -2.49,4.35 ], [ -8.6,4.35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50abfb8ee4b0afbc75eb981c","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":469089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":469090,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70040828,"text":"fs20123129 - 2012 - Summary of the diamond resource potential and production capacity assessment of Guinea","interactions":[],"lastModifiedDate":"2012-11-20T09:48:49","indexId":"fs20123129","displayToPublicDate":"2012-11-20T00:00:00","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":"2012-3129","title":"Summary of the diamond resource potential and production capacity assessment of Guinea","docAbstract":"In May of 2000, a meeting was convened in Kimberley, South Africa, by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that export shipments of rough diamonds were free of conflict concerns. Outcomes of the meeting were formally supported later in December of 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme (KPCS) was ratified and signed by diamond-producing and diamond-importing countries. As of August 2012, the Kimberley Process (KP) had 51 participants representing 77 countries. With the passing of the AD, the Plenary agreed that further efforts should be made to assess Guinea's diamond production capacity. In support of this objective, the U.S. Geological Survey (USGS) partnered with the Kimberley Process Working Group of Diamond Experts (WGDE) and Guinea's Ministry of Mines and Geology (MMG) to conduct a field campaign in Guinea from April 24 through May 2, 2010. The field team was composed of Mark Van Bockstael of the WGDE, Peter Chirico of the USGS, and several geologists from the MMG. The team visited diamond mining sites in western Guinea's Kindia, Forècariah, Coyah, and Tèlimèlè Prefectures, in which the Guinean government identified newly discovered deposits mined by artisans. Several mining sites within the Kissidougou Prefecture in southeastern Guinea were also visited as part of this study. Geologic and geomorphic information on the diamond deposits was collected at each site. The fieldwork conducted during this trip served as a means of acquiring critical data needed to conduct a full assessment of diamond resources and production capacity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123129","collaboration":"Prepared under the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., and Malpeli, K., 2012, Summary of the diamond resource potential and production capacity assessment of Guinea: U.S. Geological Survey Fact Sheet 2012-3129, 2 p., https://doi.org/10.3133/fs20123129.","productDescription":"2 p.","numberOfPages":"2","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":263295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3129.gif"},{"id":263293,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3129/"},{"id":263294,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3129/pdf/fs2012-3129.pdf"}],"country":"Guinea;West Africa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -15.0,6.0 ], [ -15.0,13.0 ], [ -7.0,13.0 ], [ -7.0,6.0 ], [ -15.0,6.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50abfb89e4b0afbc75eb9818","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":469087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":469088,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70094207,"text":"70094207 - 2012 - Modeling a thick unsaturated zone at San Gorgonio Pass, California: lessons learned after five years of artificial recharge","interactions":[],"lastModifiedDate":"2018-01-12T17:41:58","indexId":"70094207","displayToPublicDate":"2012-11-19T15:15:21","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Modeling a thick unsaturated zone at San Gorgonio Pass, California: lessons learned after five years of artificial recharge","docAbstract":"The information flow among the tasks of framework assessment, numerical modeling, model forecasting and hind casting, and system-performance monitoring is illustrated. Results provide an understanding of artificial recharge in high-altitude desert settings where large vertical distances may separate application ponds from their target aquifers.
Approximately 3.8 million cubic meters of surface water was applied to spreading ponds from 2003–2007 to artificially recharge the underlying aquifer through a 200-meter thick unsaturated zone in the San Gorgonio Pass area in southern California. A study was conducted between 1997 and 2003, and a numerical model was developed to help determine the suitability of the site for artificial recharge. Ongoing monitoring results indicated that the existing model needed to be modified and recalibrated to more accurately predict artificial recharge at the site. The objective of this work was to recalibrate the model by using observation of the application rates, the rise and fall of the water level above a perching layer, and the approximate arrival time to the water table during the 5-yr monitoring period following initiation of long-term artificial recharge. Continuous monitoring of soil-matric potential, temperature, and water levels beneath the site indicated that artificial recharge reached the underlying water table between 3.75 and 4.5 yr after the initial application of the recharge water. The model was modified to allow the simulation to more adequately match the perching layer dynamics and the time of arrival at the water table. The instrumentation also showed that the lag time between changes in application of water at the surface and the response at the perching layer decreased from about 4 mo to less than 1 mo due to the wet-up of the unsaturated zone and the increase in relative permeability. The results of this study demonstrate the importance of iteratively monitoring and modeling the unsaturated zone in layered alluvial systems in the context of artificial recharge. They show that adequate geologic and hydraulic-property data on perching layers are critical to success. Continuous monitoring in the unsaturated and saturated zones beneath a site provides data to develop and constrain numerical models, better understand local unsaturated zone process, manage artificial recharge operations, and to determine the timing and volume of recoverable water for consumptive use.
","language":"English","publisher":"Soil Science Society of America","publisherLocation":"Madison, WI","doi":"10.2136/vzj2012.0043","usgsCitation":"Flint, A.L., Ellett, K.M., Christensen, A.H., and Martin, P., 2012, Modeling a thick unsaturated zone at San Gorgonio Pass, California: lessons learned after five years of artificial recharge: Vadose Zone Journal, v. 11, no. 4, 12 p., https://doi.org/10.2136/vzj2012.0043.","productDescription":"12 p.","ipdsId":"IP-025507","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":282503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Gorgonio Pass","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.102671,33.857283 ], [ -117.102671,34.124403 ], [ -116.796983,34.124403 ], [ -116.796983,33.857283 ], [ -117.102671,33.857283 ] ] ] } } ] }","volume":"11","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-11-19","publicationStatus":"PW","scienceBaseUri":"53cd67d8e4b0b29085101a75","contributors":{"authors":[{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellett, Kevin M.","contributorId":68359,"corporation":false,"usgs":true,"family":"Ellett","given":"Kevin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":490564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Allen H. 0000-0002-7061-5591 ahchrist@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-5591","contributorId":1510,"corporation":false,"usgs":true,"family":"Christensen","given":"Allen","email":"ahchrist@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490561,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040809,"text":"sir20125186 - 2012 - Groundwater quality in West Virginia, 1993-2008","interactions":[],"lastModifiedDate":"2012-11-19T10:45:15","indexId":"sir20125186","displayToPublicDate":"2012-11-19T00:00:00","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":"2012-5186","title":"Groundwater quality in West Virginia, 1993-2008","docAbstract":"Approximately 42 percent of all West Virginians rely on groundwater for their domestic water supply. However, prior to 2008, the quality of the West Virginia’s groundwater resource was largely unknown. The need for a statewide assessment of groundwater quality prompted the U.S. Geological Survey (USGS), in cooperation with West Virginia Department of Environmental Protection (WVDEP), Division of Water and Waste Management, to develop an ambient groundwater-quality monitoring program.\n\nThe USGS West Virginia Water Science Center sampled 300 wells, of which 80 percent were public-supply wells, over a 10-year period, 1999–2008. Sites for this statewide ambient groundwater-quality monitoring program were selected to provide wide areal coverage and to represent a variety of environmental settings. The resulting 300 samples were supplemented with data from a related monitoring network of 24 wells and springs.\n\nAll samples were analyzed for field measurements (water temperature, pH, specific conductance, and dissolved oxygen), major ions, trace elements, nutrients, volatile organic compounds, fecal indicator bacteria, and radon-222. Sub-sets of samples were analyzed for pesticides or semi-volatile organic compounds; site selection was based on local land use.\n\nSamples were grouped for comparison by geologic age of the aquifer, Groups included Cambrian, Ordovician, Silurian, Devonian, Pennsylvanian, Permian, and Quaternary aquifers. A comparison of samples indicated that geologic age of the aquifer was the largest contributor to variability in groundwater quality.\n\nThis study did not attempt to characterize drinking water provided through public water systems. All samples were of raw, untreated groundwater. Drinking-water criteria apply to water that is served to the public, not to raw water. However, drinking water criteria, including U.S. Environmental Protection Agency (USEPA) maximum contaminant level (MCL), non-enforceable secondary maximum contaminant level (SMCL), non-enforceable proposed MCL, or non-enforceable advisory health-based screening level (HBSL), were used as benchmarks against which to compare analytical results.\n\nConstituent concentrations were less than the MCLs in most samples. However, some samples exceeded non-enforceable SMCLs, proposed MCLs, or advisory HBSLs. Radon-222 concentrations exceeded the proposed MCL of 300 pCi/L in 45 percent of samples, and iron concentrations exceeded the SMCL of 300 µg/L in 57 percent of samples. Manganese concentrations were greater than the SMCL (50 µg/L) in 62 percent of samples and greater than the HBSL (300 µg/L) in 25 percent of the samples. Other sampled constituents, including organic compounds and trace elements, exceeded drinking-water criteria at much lower frequencies.\n\nThe radon-222 median concentrations in samples from Cambrian, Ordovician, Silurian, Permian, and Quaternary aquifers exceeded the proposed 300 pCi/L MCL. Although median radon concentrations for wells in Devonian, Mississippian, and Pennsylvanian aquifers were less than the proposed MCL, radon concentrations greater than the proposed MCL were measured in samples from aquifers of all geologic ages.\n\nThe median iron concentrations for samples from Devonian and Pennsylvanian aquifers were greater than the 300 µg/L SMCL. Iron concentrations exceeded the SMCL in aquifers of all geologic ages, except Cambrian. Median concentrations of manganese exceeded the SMCL in samples from Devonian, Pennsylvanian, and Quaternary aquifers. As with iron, manganese concentrations were found to exceed the SMCL in at least one sample from aquifers of all geologic ages, except Cambrian.\n\nPesticides were detected most frequently and in higher concentrations in limestone-dominated areas. Most of West Virginia’s agriculture is concentrated in those areas.\n\nThis study, the most comprehensive assessment of West Virginia groundwater quality to date, indicates the water quality of West Virginia’s groundwater is generally good; in the majority of cases raw-water samples met primary drinking water-criteria. However, some constituents, notably iron and manganese, exceeded the secondary drinking criteria in more than half the samples.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125186","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection, Division of Water and Waste Management","usgsCitation":"Chambers, D., Kozar, M.D., White, J.S., and Paybins, K.S., 2012, Groundwater quality in West Virginia, 1993-2008: U.S. Geological Survey Scientific Investigations Report 2012-5186, viii, 47 p.; col. ill.; maps (col.), https://doi.org/10.3133/sir20125186.","productDescription":"viii, 47 p.; col. ill.; maps (col.)","startPage":"i","endPage":"47","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1993-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":263260,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5186/"},{"id":263261,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5186/pdf/sir2012-5186.pdf"},{"id":263262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5186.png"}],"country":"United States","state":"West Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.64,37.2 ], [ -82.64,40.64 ], [ -77.72,40.64 ], [ -77.72,37.2 ], [ -82.64,37.2 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50abfb7ce4b0afbc75eb980c","contributors":{"authors":[{"text":"Chambers, Douglas B. 0000-0002-5275-5427 dbchambe@usgs.gov","orcid":"https://orcid.org/0000-0002-5275-5427","contributorId":2520,"corporation":false,"usgs":true,"family":"Chambers","given":"Douglas B.","email":"dbchambe@usgs.gov","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":469067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Jeremy S. 0000-0002-1501-1074 jswhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1501-1074","contributorId":3905,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jswhite@usgs.gov","middleInitial":"S.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":469070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paybins, Katherine S. 0000-0002-3967-5043 kpaybins@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-5043","contributorId":2805,"corporation":false,"usgs":true,"family":"Paybins","given":"Katherine","email":"kpaybins@usgs.gov","middleInitial":"S.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469069,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040820,"text":"sir20125207 - 2012 - County-level estimates of nitrogen and phosphorus from commercial fertilizer for the Conterminous United States, 1987-2006","interactions":[],"lastModifiedDate":"2021-07-20T17:06:41.937664","indexId":"sir20125207","displayToPublicDate":"2012-11-19T00:00:00","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":"2012-5207","displayTitle":"County-level estimates of nitrogen and phosphorus from commercial fertilizer for the Conterminous United States, 1987–2006","title":"County-level estimates of nitrogen and phosphorus from commercial fertilizer for the Conterminous United States, 1987-2006","docAbstract":"The U.S. Geological Survey’s National Water-Quality Assessment program requires nutrient input for analysis of the national and regional assessment of water quality. Detailed information on nutrient inputs to the environment are needed to understand and address the many serious problems that arise from excess nutrients in the streams and groundwater of the Nation. This report updates estimated county-level farm and nonfarm nitrogen and phosphorus input from commercial fertilizer sales for the conterminous United States for 1987 through 2006. Estimates were calculated from the Association of American Plant Food Control Officials fertilizer sales data, Census of Agriculture fertilizer expenditures, and U.S. Census Bureau county population. A previous national approach for deriving farm and nonfarm fertilizer nutrient estimates was evaluated, and a revised method for selecting representative states to calculate national farm and nonfarm proportions was developed. A national approach was used to estimate farm and nonfarm fertilizer inputs because not all states distinguish between farm and nonfarm use, and the quality of fertilizer reporting varies from year to year. For states that distinguish between farm and nonfarm use, the spatial distribution of the ratios of nonfarm-to-total fertilizer estimates for nitrogen and phosphorus calculated using the national-based farm and nonfarm proportions were similar to the spatial distribution of the ratios generated using state-based farm and nonfarm proportions. In addition, the relative highs and lows in the temporal distribution of farm and nonfarm nitrogen and phosphorus input at the state level were maintained—the periods of high and low usage coincide between national- and state-based values. With a few exceptions, nonfarm nitrogen estimates were found to be reasonable when compared to the amounts that would result if the lawn application rates recommended by state and university agricultural agencies were used. Also, states with higher nonfarm-to-total fertilizer ratios for nitrogen and phosphorus tended to have higher urban land-use percentages.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125207","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Gronberg, J., and Spahr, N.E., 2012, County-level estimates of nitrogen and phosphorus from commercial fertilizer for the Conterminous United States, 1987-2006: U.S. Geological Survey Scientific Investigations Report 2012-5207, Report: vi, 20 p.; Appendixes 1-6; Database, https://doi.org/10.3133/sir20125207.","productDescription":"Report: vi, 20 p.; Appendixes 1-6; Database","numberOfPages":"30","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438804,"rank":12,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H41PKX","text":"USGS data release","linkHelpText":"County-Level Estimates of Nitrogen and Phosphorus from Commercial Fertilizer for the Conterminous United States, 1987-2012"},{"id":387305,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5207.jpg"},{"id":387310,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5207/pdf/sir20125207_appendix3.pdf","text":"Appendix 3","linkFileType":{"id":1,"text":"pdf"}},{"id":387309,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5207/pdf/sir20125207_appendix2.pdf","text":"Appendix 2","linkFileType":{"id":1,"text":"pdf"}},{"id":387315,"rank":11,"type":{"id":9,"text":"Database"},"url":"https://water.usgs.gov/GIS/dsdl/sir2012-5207_county_fertilizer.zip","text":"Database download","linkFileType":{"id":6,"text":"zip"}},{"id":387314,"rank":10,"type":{"id":9,"text":"Database"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sir2012-5207_county_fertilizer.xml","text":"Database metadata","linkFileType":{"id":8,"text":"xml"}},{"id":387313,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5207/pdf/sir20125207_appendix6.pdf","text":"Appendix 6","linkFileType":{"id":1,"text":"pdf"}},{"id":387312,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5207/pdf/sir20125207_appendix5.pdf","text":"Appendix 5","linkFileType":{"id":1,"text":"pdf"}},{"id":387311,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5207/pdf/sir20125207_appendix4.pdf","text":"Appendix 4","linkFileType":{"id":1,"text":"pdf"}},{"id":387308,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5207/pdf/sir20125207_appendix1.pdf","text":"Appendix 1","linkFileType":{"id":1,"text":"pdf"}},{"id":387307,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5207/pdf/sir20125207.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}},{"id":387306,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5207/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50abfb6ae4b0afbc75eb97fd","contributors":{"authors":[{"text":"Gronberg, Jo Ann M.","contributorId":18342,"corporation":false,"usgs":true,"family":"Gronberg","given":"Jo Ann M.","affiliations":[],"preferred":false,"id":469082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spahr, Norman E. nspahr@usgs.gov","contributorId":1977,"corporation":false,"usgs":true,"family":"Spahr","given":"Norman","email":"nspahr@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":469081,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043929,"text":"70043929 - 2012 - An accessible method for implementing hierarchical models with spatio-temporal abundance data","interactions":[],"lastModifiedDate":"2017-05-05T11:02:04","indexId":"70043929","displayToPublicDate":"2012-11-16T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"An accessible method for implementing hierarchical models with spatio-temporal abundance data","docAbstract":"A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time.","largerWorkTitle":"PLoS ONE","language":"English","doi":"10.1371/journal.pone.0049395","usgsCitation":"Ross, B., Hooten, M.B., and Koons, D.N., 2012, An accessible method for implementing hierarchical models with spatio-temporal abundance data: PLoS ONE, v. 7, no. 11, p. 1-8, https://doi.org/10.1371/journal.pone.0049395.","productDescription":"8 p.","startPage":"1","endPage":"8","ipdsId":"IP-037978","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":474266,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0049395","text":"Publisher Index Page"},{"id":268000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0049395"}],"volume":"7","issue":"11","noUsgsAuthors":false,"publicationDate":"2012-11-16","publicationStatus":"PW","scienceBaseUri":"5129f30ae4b04edf7e93f841","contributors":{"authors":[{"text":"Ross, Beth E.","contributorId":56124,"corporation":false,"usgs":true,"family":"Ross","given":"Beth E.","affiliations":[],"preferred":false,"id":474486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Melvin B.","contributorId":45978,"corporation":false,"usgs":true,"family":"Hooten","given":"Melvin","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":474485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koons, David N.","contributorId":28137,"corporation":false,"usgs":false,"family":"Koons","given":"David","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":474484,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}