The U.S. Geological Survey (USGS) collects streamflow, groundwater levels, and water-quality data for the State of Illinois and the Nation. Much of these data are collected every 15 minutes (real-time) as a part of the national network, so that water-resource managers can make decisions in a timely and reliable manner. Coupled with modeling and other water-resource investigations, the USGS provides data to the State during droughts and other hydrologic events. The types of data, capabilities, and presentation of these materials are described in this document as USGS Real-Time Data, Supplementary Data Collection and Analysis, and National Resources Available.
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"571f3fe7e4b071321fe56a95","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128037,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":627609,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70039685,"text":"ds707 - 2012 - Occurrence of pesticides in water and sediment collected from amphibian habitats located throughout the United States, 2009-10","interactions":[],"lastModifiedDate":"2012-08-28T15:38:19","indexId":"ds707","displayToPublicDate":"2012-08-23T00:00:00","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":"707","title":"Occurrence of pesticides in water and sediment collected from amphibian habitats located throughout the United States, 2009-10","docAbstract":"Water and bed-sediment samples were collected by the U.S. Geological Survey (USGS) in 2009 and 2010 from 11 sites within California and 18 sites total in Colorado, Georgia, Idaho, Louisiana, Maine, and Oregon, and were analyzed for a suite of pesticides by the USGS. Water samples and bed-sediment samples were collected from perennial or seasonal ponds located in amphibian habitats in conjunction with research conducted by the USGS Amphibian Research and Monitoring Initiative and the USGS Toxic Substances Hydrology Program. Sites selected for this study in three of the states (California, Colorado, and Orgeon) have no direct pesticide application and are considered undeveloped and remote. Sites selected in Georgia, Idaho, Louisiana, and Maine were in close proximity to either agricultural or suburban areas. Water and sediment samples were collected once in 2009 during amphibian breeding seasons. In 2010, water samples were collected twice. The first sampling event coincided with the beginning of the frog breeding season for the species of interest, and the second event occurred 10-12 weeks later when pesticides were being applied to the surrounding areas. Additionally, water was collected during each sampling event to measure dissolved organic carbon, nutrients, and the fungus, Batrachochytrium dendrobatidis, which has been linked to amphibian declines worldwide. Bed-sediment samples were collected once during the beginning of the frog breeding season, when the amphibians are thought to be most at risk to pesticides. Results of this study are reported for the following two geographic scales: (1) for a national scale, by using data from the 29 sites that were sampled from seven states, and (2) for California, by using data from the 11 sampled sites in that state. Water samples were analyzed for 96 pesticides by using gas chromatography/mass spectrometry. A total of 24 pesticides were detected in one or more of the 54 water samples, including 7 fungicides, 10 herbicides, 4 insecticides, 1 synergist, and 2 pesticide degradates. On a national scale, aminomethylphosphonic acid (AMPA), the primary degradate of the herbicide glyphosate, which is the active ingredient in Roundup®, was the most frequently detected pesticide in water (16 of 54 samples) followed by glyphosate (8 of 54 samples). The maximum number of pesticides observed at a single site was nine compounds in a water sample from a site in Louisiana. The maximum concentration of a pesticide or degradate observed in water was 2,880 nanograms per liter of clomazone (a herbicide) at a site in Louisiana. In California, a total of eight pesticides were detected among all of the low and high elevation sites; AMPA was the most frequently detected pesticide, but glyphosate was detected at the highest concentrations (1.1 micrograms per liter). Bed-sediment samples were analyzed for 94 pesticides by using accelerated solvent extraction, gel permeation chromatography for sulfur removal, and carbon/alumina stacked solid-phase extraction cartridges to remove interfering sediment matrices. In bed sediment, 22 pesticides were detected in one or more of the samples, including 9 fungicides, 3 pyrethroid insecticides, p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT) and its major degradates, as well as several herbicides. Pyraclostrobin, a strobilurin fungicide, and bifenthrin, a pyrethroid insecticide, were detected most frequently. Maximum pesticide concentrations ranged from less than their respective method detection limits to 1,380 micrograms per kilogram (tebuconazole in California). The number of pesticides detected in samples from each site ranged from zero to six compounds. The sites with the greatest number of pesticides were in Maine and Oregon with six pesticides detected in one sample from each state, followed by Georgia with four pesticides in one sample. For California, a total of 10 pesticides were detected among all sites, and 4 pesticides were detected at both low and high elevation sites; tebuconazole and pyraclostrobin were the two most frequently detected pesticides in California. For the other six selected states, the most frequently detected pesticides in bed sediment were pyraclostrobin (detected in 17 of 42 samples), bifenthrin (detected in 14 of 42 samples), and tebuconazole (detected in 10 of 42 samples). The fungus, Batrachochytrium dendrobatidis (Bd), was detected in water samples in sites from four of the seven states during 2009 and 2010, and the number of zoospore equivalents per liter of water in samples where Bd was detected ranged from 1.6 to 343. Bd was not detected in water samples from sites in Georgia, Louisiana, and Oregon.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds707","usgsCitation":"Smalling, K., Orlando, J., Calhoun, D., Battaglin, W.A., and Kuivila, K., 2012, Occurrence of pesticides in water and sediment collected from amphibian habitats located throughout the United States, 2009-10: U.S. Geological Survey Data Series 707, viii, 36 p., https://doi.org/10.3133/ds707.","productDescription":"viii, 36 p.","numberOfPages":"44","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":259785,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_707.jpg"},{"id":259783,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/707/","linkFileType":{"id":5,"text":"html"}},{"id":259784,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/707/pdf/ds707.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125,24 ], [ -125,49 ], [ -65,49 ], [ -65,24 ], [ -125,24 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6c23e4b0c8380cd74a88","contributors":{"authors":[{"text":"Smalling, Kelly L.","contributorId":16105,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[],"preferred":false,"id":466726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":466728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calhoun, Daniel","contributorId":92913,"corporation":false,"usgs":true,"family":"Calhoun","given":"Daniel","affiliations":[],"preferred":false,"id":466727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kuivila, Kathryn 0000-0001-7940-489X kkuivila@usgs.gov","orcid":"https://orcid.org/0000-0001-7940-489X","contributorId":1367,"corporation":false,"usgs":true,"family":"Kuivila","given":"Kathryn ","email":"kkuivila@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":466724,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70039696,"text":"sir20125165 - 2012 - Potentiometric surface and water-level difference maps of selected confined aquifers of Southern Maryland and Maryland's Eastern Shore, 1975-2011","interactions":[],"lastModifiedDate":"2023-03-09T20:18:10.940749","indexId":"sir20125165","displayToPublicDate":"2012-08-23T00:00:00","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":"2012-5165","title":"Potentiometric surface and water-level difference maps of selected confined aquifers of Southern Maryland and Maryland's Eastern Shore, 1975-2011","docAbstract":"Groundwater is the principal source of freshwater supply in most of Southern Maryland and Maryland's Eastern Shore. It is also the source of freshwater supply used in the operation of the Calvert Cliffs, Chalk Point, and Morgantown power plants. Increased groundwater withdrawals over the last several decades have caused groundwater levels to decline. This report presents potentiometric surface maps of the Aquia, Magothy, upper Patapsco, lower Patapsco, and Patuxent aquifers using water levels measured during September 2011. Water-level difference maps also are presented for the first four of these aquifers. The water-level differences in the Aquia aquifer are shown using groundwater-level data from 1982 and 2011, whereas the water-level differences in the Magothy aquifer are presented using data from 1975 and 2011. Water-level difference maps in both the upper Patapsco and lower Patapsco aquifers are presented using data from 1990 and 2011. These maps show cones of depression ranging from 25 to 198 feet (ft) below sea level centered on areas of major withdrawals. Water levels have declined by as much as 112 ft in the Aquia aquifer since 1982, 85 ft in the Magothy aquifer since 1975, and 47 and 71 ft in the upper Patapsco and lower Patapsco aquifers, respectively, since 1990.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125165","collaboration":"Prepared in cooperation with the Power Plant Assessment Program of the Maryland Department of Natural Resources and the Maryland Geological Survey","usgsCitation":"Curtin, S.E., Andreasen, D., and Staley, A., 2012, Potentiometric surface and water-level difference maps of selected confined aquifers of Southern Maryland and Maryland's Eastern Shore, 1975-2011: U.S. Geological Survey Scientific Investigations Report 2012-5165, v, 36 p., https://doi.org/10.3133/sir20125165.","productDescription":"v, 36 p.","numberOfPages":"41","onlineOnly":"Y","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":259795,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5165/pdf/sir2012-5165_508.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259794,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5165/","linkFileType":{"id":5,"text":"html"}},{"id":259805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5165.gif"}],"scale":"250000","country":"United States","state":"Maryl","county":"Anne Arundel;Baltimore;Baltimore City;Caroline;Calvert;Cecil;Charles;Dorchester;Frederick;Harford;Howard;Kent;Montgomery;Prince George's;Queen Anne's;St. Mary's","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.5,38 ], [ -77.5,39.5 ], [ -75.75,39.5 ], [ -75.75,38 ], [ -77.5,38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a7fb6e4b0c8380cd7ac59","contributors":{"authors":[{"text":"Curtin, Stephen E. securtin@usgs.gov","contributorId":3703,"corporation":false,"usgs":true,"family":"Curtin","given":"Stephen","email":"securtin@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466762,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andreasen, David C.","contributorId":59003,"corporation":false,"usgs":true,"family":"Andreasen","given":"David C.","affiliations":[],"preferred":false,"id":466764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staley, Andrew W.","contributorId":43319,"corporation":false,"usgs":true,"family":"Staley","given":"Andrew W.","affiliations":[],"preferred":false,"id":466763,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70039676,"text":"sir20125160 - 2012 - A science plan for a comprehensive assessment of water supply in the region underlain by fractured rock in Maryland","interactions":[],"lastModifiedDate":"2023-03-09T20:18:33.990287","indexId":"sir20125160","displayToPublicDate":"2012-08-22T00:00:00","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":"2012-5160","title":"A science plan for a comprehensive assessment of water supply in the region underlain by fractured rock in Maryland","docAbstract":"The fractured rock region of Maryland, which includes land areas north and west of the Interstate 95 corridor, is the source of water supply for approximately 4.4 million Marylanders, or approximately 76 percent of the State's population. Whereas hundreds of thousands of residents rely on wells (both domestic and community), millions rely on surface-water sources. In this region, land use, geology, topography, water withdrawals, impoundments, and other factors affect water-flow characteristics. The unconfined groundwater systems are closely interconnected with rivers and streams, and are affected by seasonal and climatic variations. During droughts, groundwater levels drop, thereby decreasing well yields, and in some cases, wells have gone dry. Low ground-water levels contribute to reduced streamflows, which in turn, can lead to reduced habitat for aquatic life. Increased demand, over-allocation, population growth, and climate change can affect the future sustainability of water supplies in the region of Maryland underlain by fractured rock. In response to recommendations of the 2008 Advisory Committee on the Management and Protection of the State's Water Resources report, the Maryland Department of the Environment's Water Supply Program, the Maryland Geological Survey, the Maryland Department of Natural Resources, Monitoring and Non-Tidal Assessment (MANTA) Division, and the U.S. Geological Survey have developed a science plan for a comprehensive assessment that will provide new scientific information, new data analysis, and new tools for the State to better manage water resources in the fractured rock region of Maryland. The science plan lays out five goals for the comprehensive assessment: (1) develop tools for the improved management and investigation of groundwater and surface-water resources; (2) characterize factors affecting reliable yields of individual groundwater and surface-water supplies; (3) investigate impacts on nearby water withdrawal users caused by groundwater and surface-water withdrawals; (4) assess the role of streamflow and water withdrawals on the ecological integrity of streams; and (5) improve understanding of the distribution of water-quality conditions in fractured rock aquifers. To accomplish these goals, accurate data collection, review, and analysis are needed, including the study of \"Research Watersheds\" that can provide detailed information about the potential effects that climate change and water withdrawals may have on groundwater, streamflow, and aquatic life. The assessment planning started in 2009 and is being conducted with close interagency coordination. A Fractured Rock Aquifer Information System is currently (2012) undergoing initial development. Other major tasks that will be performed include the development of work plans for each science goal, the estimation of daily streamflow at ungaged streams, and the design and implementation of Research Watersheds. Finally, scenarios will be modeled to evaluate current water allocation permitting methodologies, investigate effects on nearby water withdrawal users caused by groundwater and surface-water withdrawals, and assess the potential impacts of climate change on water resources. Desktop and Web-based tools will be developed in order to meet the diverse research needs of the assessment. These tools, including the Fractured Rock Aquifer Information System will be continuously improved during the assessment to store relevant groundwater and surface-water data in spatially referenced databases, estimate streamflows, locate higher-yielding wells, estimate the impacts of withdrawals on nearby users, and assess the cumulative impacts of withdrawals on the aquatic resource. Tools will be developed to serve the needs of many audiences, including water resource managers, water suppliers, planners, policymakers, and other scientific investigators.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125160","collaboration":"Prepared in cooperation with the Maryland Department of the Environment and the Maryland Department of Natural Resources","usgsCitation":"Fleming, B.J., Hammond, P.A., Stranko, S.A., Duigon, M.T., and Kasraei, S., 2012, A science plan for a comprehensive assessment of water supply in the region underlain by fractured rock in Maryland: U.S. Geological Survey Scientific Investigations Report 2012-5160, vi, 29 p., https://doi.org/10.3133/sir20125160.","productDescription":"vi, 29 p.","numberOfPages":"29","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":259770,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5160/pdf/sir2012-5160-508.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259771,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5160/","linkFileType":{"id":5,"text":"html"}},{"id":259775,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5160.gif"}],"scale":"100000","projection":"Maryland State Plane Lambert Conformal Conic","datum":"North American Datum of 1983","country":"United States","state":"Maryl","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.55,39 ], [ -79.55,39.71666666666667 ], [ -75.75,39.71666666666667 ], [ -75.75,39 ], [ -79.55,39 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e57ae4b0c8380cd46d62","contributors":{"authors":[{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hammond, Patrick A.","contributorId":32390,"corporation":false,"usgs":true,"family":"Hammond","given":"Patrick","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":466705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stranko, Scott A.","contributorId":100675,"corporation":false,"usgs":true,"family":"Stranko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":466708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duigon, Mark T.","contributorId":79947,"corporation":false,"usgs":true,"family":"Duigon","given":"Mark","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":466707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kasraei, Saeid","contributorId":44252,"corporation":false,"usgs":true,"family":"Kasraei","given":"Saeid","email":"","affiliations":[],"preferred":false,"id":466706,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70039655,"text":"sir20125167 - 2012 - Creation of digital contours that approach the characteristics of cartographic contours","interactions":[],"lastModifiedDate":"2018-02-23T12:39:34","indexId":"sir20125167","displayToPublicDate":"2012-08-21T00:00:00","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":"2012-5167","title":"Creation of digital contours that approach the characteristics of cartographic contours","docAbstract":"The capability to easily create digital contours using commercial off-the-shelf (COTS) software has existed for decades. Out-of-the-box raw contours are suitable for many scientific applications without pre- or post-processing; however, cartographic applications typically require additional improvements. For example, raw contours generally require smoothing before placement on a map. Cartographic contours must also conform to certain spatial/logical rules; for example, contours may not cross waterbodies. The objective was to create contours that match as closely as possible the cartographic contours produced by manual methods on the 1:24,000-scale, 7.5-minute Topographic Map series. This report outlines the basic approach, describes a variety of problems that were encountered, and discusses solutions. Many of the challenges described herein were the result of imperfect input raster elevation data and the requirement to have the contours integrated with hydrographic features from the National Hydrography Dataset (NHD).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125167","usgsCitation":"Tyler, D., and Greenlee, S.K., 2012, Creation of digital contours that approach the characteristics of cartographic contours: U.S. Geological Survey Scientific Investigations Report 2012-5167, iv, 31 p., https://doi.org/10.3133/sir20125167.","productDescription":"iv, 31 p.","numberOfPages":"40","onlineOnly":"Y","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":259750,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5167.gif"},{"id":259744,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5167/","linkFileType":{"id":5,"text":"html"}},{"id":259745,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5167/sir2012-5167.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fc9fe4b0c8380cd4e352","contributors":{"authors":[{"text":"Tyler, Dean J. 0000-0002-1542-7539","orcid":"https://orcid.org/0000-0002-1542-7539","contributorId":96142,"corporation":false,"usgs":true,"family":"Tyler","given":"Dean J.","affiliations":[],"preferred":false,"id":466680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Greenlee, Susan K. sgreenlee@usgs.gov","contributorId":3326,"corporation":false,"usgs":true,"family":"Greenlee","given":"Susan","email":"sgreenlee@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":466679,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70039658,"text":"ofr20121134 - 2012 - Hydrologic data for an investigation of the Smith River Watershed through water year 2010","interactions":[],"lastModifiedDate":"2012-08-22T01:01:58","indexId":"ofr20121134","displayToPublicDate":"2012-08-21T00:00:00","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":"2012-1134","title":"Hydrologic data for an investigation of the Smith River Watershed through water year 2010","docAbstract":"Hydrologic data collected through water year 2010 and compiled as part of a U.S. Geological Survey study of the water resources of the Smith River watershed in west-central Montana are presented in this report. Tabulated data presented in this report were collected at 173 wells and 65 surface-water sites. Figures include location maps of data-collection sites and hydrographs of streamflow. Digital data files used to construct the figures, hydrographs, and data tables are included in the report. Data collected by the USGS are also stored in the USGS National Water Information System database and are available through the USGS National Water Information System Water Data for Montana Web page at http://waterdata.usgs.gov/mt/nwis/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121134","collaboration":"Prepared in cooperation with Meagher County Conservation District","usgsCitation":"Nilges, H.L., and Caldwell, R.R., 2012, Hydrologic data for an investigation of the Smith River Watershed through water year 2010: U.S. Geological Survey Open-File Report 2012-1134, vii; 44 p.; README.TXT; Appendix 1-10 XLS, https://doi.org/10.3133/ofr20121134.","productDescription":"vii; 44 p.; README.TXT; Appendix 1-10 XLS","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":400,"text":"Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":259752,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1134.gif"},{"id":259746,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1134/","linkFileType":{"id":5,"text":"html"}},{"id":259747,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1134/OF12-1134.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Lambert Conformal Conic Projection","datum":"North American Datum of 1983","country":"United States","state":"Montana","county":"Cascade;Meagher","city":"Fort Logan","otherGeospatial":"Smith River;Eagle Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112,46 ], [ -112,47.5 ], [ -110.5,47.5 ], [ -110.5,46 ], [ -112,46 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a35bfe4b0c8380cd60180","contributors":{"authors":[{"text":"Nilges, Hannah L. hnilges@usgs.gov","contributorId":4678,"corporation":false,"usgs":true,"family":"Nilges","given":"Hannah","email":"hnilges@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":466685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":466684,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70039659,"text":"ofr20121149 - 2012 - Water-quality and geophysical data for three study sites within the Williston Basin and Prairie Pothole Region","interactions":[],"lastModifiedDate":"2012-08-22T01:01:58","indexId":"ofr20121149","displayToPublicDate":"2012-08-21T00:00:00","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":"2012-1149","title":"Water-quality and geophysical data for three study sites within the Williston Basin and Prairie Pothole Region","docAbstract":"This report is a data release for water geochemical sample analyses and geophysical surveys for three sites within the Williston Basin and Prairie Pothole Region of Montana and North Dakota. The data collection sites and procedures are described.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121149","usgsCitation":"Preston, T.M., Smith, B.D., Thamke, J., and Chesley-Preston, T.L., 2012, Water-quality and geophysical data for three study sites within the Williston Basin and Prairie Pothole Region: U.S. Geological Survey Open-File Report 2012-1149, iv; 17 p.; Table 1-1 XLS; Table 1-2 XLS; Table 1-3 XLS; Table 1-4 XLS, https://doi.org/10.3133/ofr20121149.","productDescription":"iv; 17 p.; Table 1-1 XLS; Table 1-2 XLS; Table 1-3 XLS; Table 1-4 XLS","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":259751,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1149.gif"},{"id":259749,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1149/OF12-1149.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259748,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1149/","linkFileType":{"id":5,"text":"html"}}],"projection":"Albers Equal-Area Conic","country":"Canada;United States","state":"Alberta;Iowa;Manitoba;Minnesota;Montana;North Dakota;Saskatchewan;South Dakota","otherGeospatial":"Williston Basin;Bakken Formation;Prairie Pothole Region","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116,40 ], [ -116,55 ], [ -89,55 ], [ -89,40 ], [ -116,40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bcd92e4b08c986b32e066","contributors":{"authors":[{"text":"Preston, Todd M. 0000-0002-8812-9233 tmpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":1664,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"tmpreston@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":466688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":466686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thamke, Joanna N. 0000-0002-6917-1946 jothamke@usgs.gov","orcid":"https://orcid.org/0000-0002-6917-1946","contributorId":1012,"corporation":false,"usgs":true,"family":"Thamke","given":"Joanna N.","email":"jothamke@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":466687,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chesley-Preston, Tara L. tchesley-preston@usgs.gov","contributorId":5557,"corporation":false,"usgs":true,"family":"Chesley-Preston","given":"Tara","email":"tchesley-preston@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":466689,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70039646,"text":"sir20125170 - 2012 - Variability in stream chemistry in relation to urban development and biological condition in seven metropolitan areas of the United States, 1999-2004","interactions":[],"lastModifiedDate":"2012-08-21T01:02:01","indexId":"sir20125170","displayToPublicDate":"2012-08-20T00:00:00","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":"2012-5170","title":"Variability in stream chemistry in relation to urban development and biological condition in seven metropolitan areas of the United States, 1999-2004","docAbstract":"Beginning in 1999, the U.S. Geological Survey National Water Quality Assessment Program investigated the effects of urban development on stream ecosystems in nine metropolitan study areas across the United States. In seven of these study areas, stream-chemistry samples were collected every other month for 1 year at 6 to 10 sites. Within a study area, the sites collectively represented a gradient of urban development from minimally to highly developed watersheds, based on the percentage of urban land cover; depending on study area, the land cover before urban development was either forested or agricultural. The stream-chemistry factors measured in the samples were total nitrogen, total phosphorus, chloride, and pesticide toxicity. These data were used to characterize the stream-chemistry factors in four ways (hereafter referred to as characterizations)—seasonal high-flow value, seasonal low-flow value, the median value (representing a single integrated value of the factor over the year), and the standard deviation of values (representing the variation of the factor over the year). Aquatic macroinvertebrate communities were sampled at each site to infer the biological condition of the stream based on the relative sensitivity of the community to environmental stressors. A Spearman correlation analysis was used to evaluate relations between (1) urban development and each characterization of the stream-chemistry factors and (2) the biological condition of a stream and the different characterizations of chloride and pesticide toxicity. Overall, the study areas where the land cover before urban development was primarily forested had a greater number of moderate and strong relations compared with the study areas where the land cover before urban development was primarily agriculture; this was true when urban development was correlated with the stream-chemistry factors (except chloride) and when chloride and pesticide toxicity was correlated with the biological condition. Except for primarily phosphorus in two study areas, stream-chemistry factors generally increased with urban development, and among the different characterizations, the median value typically indicated the strongest relations. The variation in stream-chemistry factors throughout the year generally increased with urban development, indicating that water quality became less consistent as watersheds were developed. In study areas with high annual snow fall, the variation in chloride concentrations throughout the year was particularly strongly related to urban development, likely a result of road salt applications during the winter. The relations of the biological condition to chloride and pesticide toxicity were calculated irrespective of urban development, but the overall results indicated that the relations were still stronger in the study areas that had been forested before urban development. The weaker relations in the study areas that had been agricultural before urban development were likely the results of biological communities having been degraded from agricultural practices in the watersheds. Collectively, these results indicated that, compared with sampling a stream at a single point in time, sampling at regular intervals during a year may provide a more representative measure of water quality, especially in the areas of high urban development where water quality fluctuated more widely between samples. Furthermore, the use of \"integrated\" values of stream chemistry factors may be more appropriate when assessing relations to the biological condition of a stream because the taxa composition of a biological community typically reflects the water-quality conditions over time.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125170","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Beaulieu, K., Bell, A.H., and Coles, J.F., 2012, Variability in stream chemistry in relation to urban development and biological condition in seven metropolitan areas of the United States, 1999-2004: U.S. Geological Survey Scientific Investigations Report 2012-5170, vi, 27 p.; col. ill.; maps (col.); Appendix, https://doi.org/10.3133/sir20125170.","productDescription":"vi, 27 p.; col. ill.; maps (col.); Appendix","startPage":"i","endPage":"27","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":259731,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5170.gif"},{"id":259730,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5170/pdf/sir2012-5170_beaulieu_508.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259729,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5170/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bc12fe4b08c986b32a48f","contributors":{"authors":[{"text":"Beaulieu, Karen M. kmbeauli@usgs.gov","contributorId":2241,"corporation":false,"usgs":true,"family":"Beaulieu","given":"Karen M.","email":"kmbeauli@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coles, James F. 0000-0002-1953-012X jcoles@usgs.gov","orcid":"https://orcid.org/0000-0002-1953-012X","contributorId":2239,"corporation":false,"usgs":true,"family":"Coles","given":"James","email":"jcoles@usgs.gov","middleInitial":"F.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466665,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70039650,"text":"sir20125110 - 2012 - Estimating basin lagtime and hydrograph-timing indexes used to characterize stormflows for runoff-quality analysis","interactions":[],"lastModifiedDate":"2012-08-21T01:02:01","indexId":"sir20125110","displayToPublicDate":"2012-08-20T00:00:00","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":"2012-5110","title":"Estimating basin lagtime and hydrograph-timing indexes used to characterize stormflows for runoff-quality analysis","docAbstract":"A nationwide study to better define triangular-hydrograph statistics for use with runoff-quality and flood-flow studies was done by the U.S. Geological Survey (USGS) in cooperation with the Federal Highway Administration. Although the triangular hydrograph is a simple linear approximation, the cumulative distribution of stormflow with a triangular hydrograph is a curvilinear S-curve that closely approximates the cumulative distribution of stormflows from measured data. The temporal distribution of flow within a runoff event can be estimated using the basin lagtime, (which is the time from the centroid of rainfall excess to the centroid of the corresponding runoff hydrograph) and the hydrograph recession ratio (which is the ratio of the duration of the falling limb to the rising limb of the hydrograph). This report documents results of the study, methods used to estimate the variables, and electronic files that facilitate calculation of variables. Ten viable multiple-linear regression equations were developed to estimate basin lagtimes from readily determined drainage basin properties using data published in 37 stormflow studies. Regression equations using the basin lag factor (BLF, which is a variable calculated as the main-channel length, in miles, divided by the square root of the main-channel slope in feet per mile) and two variables describing development in the drainage basin were selected as the best candidates, because each equation explains about 70 percent of the variability in the data. The variables describing development are the USGS basin development factor (BDF, which is a function of the amount of channel modifications, storm sewers, and curb-and-gutter streets in a basin) and the total impervious area variable (IMPERV) in the basin. Two datasets were used to develop regression equations. The primary dataset included data from 493 sites that have values for the BLF, BDF, and IMPERV variables. This dataset was used to develop the best-fit regression equation using the BLF and BDF variables. The secondary dataset included data from 896 sites that have values for the BLF and IMPERV variables. This dataset was used to develop the best-fit regression equation using the BLF and IMPERV variables. Analysis of hydrograph recession ratios and basin characteristics for 41 sites indicated that recession ratios are random variables. Thus, recession ratios cannot be estimated quantitatively using multiple linear regression equations developed using the data available for these sites. The minimums of recession ratios for different streamgages are well characterized by a value of one. The most probable values and maximum values of recession ratios for different streamgages are, however, more variable than the minimums. The most probable values of recession ratios for the 41 streamgages analyzed ranged from 1.0 to 3.52 and had a median of 1.85. The maximum values ranged from 2.66 to 11.3 and had a median of 4.36.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125110","collaboration":"Prepared in cooperation with the Department of Transportation Federal Highway Administration","usgsCitation":"Granato, G., 2012, Estimating basin lagtime and hydrograph-timing indexes used to characterize stormflows for runoff-quality analysis: U.S. Geological Survey Scientific Investigations Report 2012-5110, vi, 47 p.; col. ill.; map (col.); Digital Media Directory; ISO Download of CD-ROM; GI Download of CD-ROM; PDF Download of Disk-Face Label; PDF Download of Door Card, https://doi.org/10.3133/sir20125110.","productDescription":"vi, 47 p.; col. ill.; map (col.); Digital Media Directory; ISO Download of CD-ROM; GI Download of CD-ROM; PDF Download of Disk-Face Label; PDF Download of Door Card","startPage":"i","endPage":"47","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true}],"links":[{"id":259742,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5110.gif"},{"id":259736,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5110/pdf/sir2012-5110_text.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259737,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5110/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0b0de4b0c8380cd5253d","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":466670,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70032285,"text":"70032285 - 2012 - A modeling framework for integrated harvest and habitat management of North American waterfowl: Case-study of northern pintail metapopulation dynamics","interactions":[],"lastModifiedDate":"2020-11-13T21:00:17.113683","indexId":"70032285","displayToPublicDate":"2012-08-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"A modeling framework for integrated harvest and habitat management of North American waterfowl: Case-study of northern pintail metapopulation dynamics","docAbstract":"We developed and evaluated the performance of a metapopulation model enabling managers to examine, for the first time, the consequences of alternative management strategies involving habitat conditions and hunting on both harvest opportunity and carrying capacity (i.e., equilibrium population size in the absence of harvest) for migratory waterfowl at a continental scale. Our focus is on the northern pintail (Anas acuta; hereafter, pintail), which serves as a useful model species to examine the potential for integrating waterfowl harvest and habitat management in North America. We developed submodel structure capturing important processes for pintail populations during breeding, fall migration, winter, and spring migration while encompassing spatial structure representing three core breeding areas and two core nonbreeding areas. A number of continental-scale predictions from our baseline parameterization (e.g., carrying capacity of 5.5 million, equilibrium population size of 2.9 million and harvest rate of 12% at maximum sustained yield [MSY]) were within 10% of those from the pintail harvest strategy under current use by the U.S. Fish and Wildlife Service. To begin investigating the interaction of harvest and habitat management, we examined equilibrium population conditions for pintail at the continental scale across a range of harvest rates while perturbing model parameters to represent: (1) a 10% increase in breeding habitat quality in the Prairie Pothole population (PR); and (2) a 10% increase in nonbreeding habitat quantity along in the Gulf Coast (GC). Based on our model and analysis, a greater increase in carrying capacity and sustainable harvest was seen when increasing a proxy for habitat quality in the Prairie Pothole population. This finding and underlying assumptions must be critically evaluated, however, before specific management recommendations can be made. To make such recommendations, we require (1) extended, refined submodels with additional parameters linking influences of habitat management and environmental conditions to key life-history parameters; (2) a formal sensitivity analysis of the revised model; (3) an integrated population model that incorporates empirical data for estimating key vital rates; and (4) cost estimates for changing these additional parameters through habitat management efforts. We foresee great utility in using an integrated modeling approach to predict habitat and harvest management influences on continental-scale population responses while explicitly considering putative effects of climate change. Such a model could be readily adapted for management of many habitat-limited species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2011.10.028","issn":"03043800","usgsCitation":"Mattsson, B.J., Runge, M.C., Devries, J., Boomer, G., Eadie, J., Haukos, D., Fleskes, J., Koons, D.N., Thogmartin, W.E., and Clark, R., 2012, A modeling framework for integrated harvest and habitat management of North American waterfowl: Case-study of northern pintail metapopulation dynamics: Ecological Modelling, v. 225, p. 146-158, https://doi.org/10.1016/j.ecolmodel.2011.10.028.","productDescription":"13 p.","startPage":"146","endPage":"158","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":242481,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214731,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2011.10.028"}],"volume":"225","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e482e4b0c8380cd46698","contributors":{"authors":[{"text":"Mattsson, Brady J.","contributorId":197269,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":435436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":435433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Devries, J.H.","contributorId":84175,"corporation":false,"usgs":true,"family":"Devries","given":"J.H.","email":"","affiliations":[],"preferred":false,"id":435437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boomer, G.S.","contributorId":48682,"corporation":false,"usgs":true,"family":"Boomer","given":"G.S.","email":"","affiliations":[],"preferred":false,"id":435432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eadie, J.M.","contributorId":8034,"corporation":false,"usgs":true,"family":"Eadie","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":435429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haukos, D.A.","contributorId":17188,"corporation":false,"usgs":true,"family":"Haukos","given":"D.A.","affiliations":[],"preferred":false,"id":435430,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fleskes, J. P.","contributorId":98661,"corporation":false,"usgs":true,"family":"Fleskes","given":"J. P.","affiliations":[],"preferred":false,"id":435438,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koons, D. N.","contributorId":68093,"corporation":false,"usgs":false,"family":"Koons","given":"D.","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":435434,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":435431,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Clark, R. G.","contributorId":81446,"corporation":false,"usgs":false,"family":"Clark","given":"R. G.","affiliations":[],"preferred":false,"id":435435,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70040328,"text":"ds709A - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:13:25","indexId":"ds709A","displayToPublicDate":"2012-08-17T00:00:00","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":"A","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A 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 Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Khanneshin) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the Khanneshin 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 Khanneshin study area, one subarea was designated for detailed field investigations (that is, the Khanneshin volcano subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.","largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709A","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 A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: DS 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 Khanneshin mineral district in Afghanistan: Chapter A 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; 2 Index Maps: 11 x 8.5 inches and 76.14 x 50.07 inches; 20 Image Files; 20 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709A.","productDescription":"Readme; 2 Index Maps: 11 x 8.5 inches and 76.14 x 50.07 inches; 20 Image Files; 20 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":262599,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_A.jpg"},{"id":262598,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/a/index_maps/Khanneshin_Image_Index_Map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262596,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/a/","linkFileType":{"id":5,"text":"html"}},{"id":262597,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/a/index_maps/Khanneshin_Area-of-Interest_Index_Map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":263615,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/a/1_readme.txt"},{"id":263616,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/a/image_files/image_files.html"},{"id":263617,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/a/metadata/metadata.html"},{"id":263618,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"},{"id":263619,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/a/shapefiles/shapefiles.html"}],"country":"Afghanistan","state":"Helm;Nimroz","otherGeospatial":"Khanneshin Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 62.75,29.916667 ], [ 62.75,30.833333 ], [ 64.416667,30.833333 ], [ 64.416667,29.916667 ], [ 62.75,29.916667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"507ee039e4b022001d87bb7e","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":468097,"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":468098,"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":468100,"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":468099,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70039641,"text":"sir20125135 - 2012 - Estimation of natural historical flows for the Manitowish River near Manitowish Waters, Wisconsin","interactions":[],"lastModifiedDate":"2018-02-06T12:26:43","indexId":"sir20125135","displayToPublicDate":"2012-08-17T00:00:00","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":"2012-5135","title":"Estimation of natural historical flows for the Manitowish River near Manitowish Waters, Wisconsin","docAbstract":"The Wisconsin Department of Natural Resources is charged with oversight of dam operations throughout Wisconsin and is considering modifications to the operating orders for the Rest Lake Dam in Vilas County, Wisconsin. State law requires that the operation orders be tied to natural low flows at the dam. Because the presence of the dam confounds measurement of natural flows, the U.S. Geological Survey, in cooperation with the Wisconsin Department of Natural Resources, installed streamflow-gaging stations and developed two statistical methods to improve estimates of natural flows at the Rest Lake Dam. Two independent methods were used to estimate daily natural flow for the Manitowish River approximately 1 mile downstream of the Rest Lake Dam. The first method was an adjusted drainage-area ratio method, which used a regression analysis that related measured water yield (flow divided by watershed area) from short-term (2009–11) gaging stations upstream of the Manitowish Chain of Lakes to the water yield from two nearby long-term gaging stations in order to extend the flow record (1991–2011). In this approach, the computed flows into the Chain of Lakes at the upstream gaging stations were multiplied by a coefficient to account for the monthly hydrologic contributions (precipitation, evaporation, groundwater, and runoff) associated with the additional watershed area between the upstream gaging stations and the dam at the outlet of the Chain of Lakes (Rest Lake Dam). The second method used to estimate daily natural flow at the Rest Lake Dam was a water-budget approach, which used lake stage and dam outflow data provided by the dam operator. A water-budget model was constructed and then calibrated with an automated parameter-estimation program by matching simulated flow-duration statistics with measured flow-duration statistics at the upstream gaging stations. After calibration of the water-budget model, the model was used to compute natural flow at the dam from 1973 to 2011. Daily natural flows at the dam, as computed by the adjusted drainage-area ratio method and the water-budget method, were used to compute monthly flow-duration values for the period of historical data available for each method. Monthly flow-durations provide a means for evaluating the frequency and range in flows that have been observed for each month over the course of many years. Both methods described the pattern and timing of measured high-flow and low-flow events at the upstream gaging stations. The adjusted drainage-area ratio method generally had smaller residual errors across the full range of observed flows and had smaller monthly biases than the water-budget method. Although it is not possible to evaluate which method may be more \"correct\" for estimating monthly natural flows at the dam, comparisons between the results of each method indicate that the adjusted drainage-area ratio method may be susceptible to biases at high flows due to isolated storms outside of the Manitowish River watershed. Conversely, it appears that the water-budget method may be susceptible to biases at low flows because of its sensitivity to the accuracy of reported lake stage and outflows, as well as effects of upstream diversions that could not be fully compensated for with this method. Results from both methods are useful for understanding the natural flow patterns at the dam. Flows for both methods have similar patterns, with high median flows in spring and low median flows in late summer. Similarly, the range from monthly high-flow durations to low-flow durations increases during spring, decreases during summer, and increases again during fall. These seasonal patterns illustrate a challenge with interpreting a single value of natural low flow. That is, a natural low flow computed for September is not representative of a natural low flow in April. Moreover, alteration of natural flows caused by storing water in the Chain of Lakes during spring and releasing it in fall causes a change in the timing of high and low flows compared with natural conditions. That is, the lowest reported dam outflows occurred in spring and highest reported outflows occurred in fall, which is opposite the natural patterns.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125135","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Juckem, P.F., Reneau, P.C., and Robertson, D.M., 2012, Estimation of natural historical flows for the Manitowish River near Manitowish Waters, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2012-5135, vi, 32 p.; col. ill.; map (col.); Appendix, https://doi.org/10.3133/sir20125135.","productDescription":"vi, 32 p.; col. ill.; map (col.); Appendix","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":259724,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5135.jpg"},{"id":259716,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5135/","linkFileType":{"id":5,"text":"html"}},{"id":259717,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5135/pdf/sir2012-5135_web.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Wisconsin","otherGeospatial":"Manitowish River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0b99e4b0c8380cd527c1","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reneau, Paul C. 0000-0002-1335-7573 pcreneau@usgs.gov","orcid":"https://orcid.org/0000-0002-1335-7573","contributorId":4385,"corporation":false,"usgs":true,"family":"Reneau","given":"Paul","email":"pcreneau@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466656,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70039631,"text":"sir20125120 - 2012 - Comparison of TOPMODEL streamflow simulations using NEXRAD-based and measured rainfall data, McTier Creek watershed, South Carolina","interactions":[],"lastModifiedDate":"2017-01-17T17:47:11","indexId":"sir20125120","displayToPublicDate":"2012-08-17T00:00:00","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":"2012-5120","title":"Comparison of TOPMODEL streamflow simulations using NEXRAD-based and measured rainfall data, McTier Creek watershed, South Carolina","docAbstract":"Rainfall is an important forcing function in most watershed models. As part of a previous investigation to assess interactions among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations in the Edisto River Basin, the topography-based hydrological model (TOPMODEL) was applied in the McTier Creek watershed in Aiken County, South Carolina. Measured rainfall data from six National Weather Service (NWS) Cooperative (COOP) stations surrounding the McTier Creek watershed were used to calibrate the McTier Creek TOPMODEL. Since the 1990s, the next generation weather radar (NEXRAD) has provided rainfall estimates at a finer spatial and temporal resolution than the NWS COOP network. For this investigation, NEXRAD-based rainfall data were generated at the NWS COOP stations and compared with measured rainfall data for the period June 13, 2007, to September 30, 2009. Likewise, these NEXRAD-based rainfall data were used with TOPMODEL to simulate streamflow in the McTier Creek watershed and then compared with the simulations made using measured rainfall data. NEXRAD-based rainfall data for non-zero rainfall days were lower than measured rainfall data at all six NWS COOP locations. The total number of concurrent days for which both measured and NEXRAD-based data were available at the COOP stations ranged from 501 to 833, the number of non-zero days ranged from 139 to 209, and the total difference in rainfall ranged from -1.3 to -21.6 inches. With the calibrated TOPMODEL, simulations using NEXRAD-based rainfall data and those using measured rainfall data produce similar results with respect to matching the timing and shape of the hydrographs. Comparison of the bias, which is the mean of the residuals between observed and simulated streamflow, however, reveals that simulations using NEXRAD-based rainfall tended to underpredict streamflow overall. Given that the total NEXRAD-based rainfall data for the simulation period is lower than the total measured rainfall at the NWS COOP locations, this bias would be expected. Therefore, to better assess the use of NEXRAD-based rainfall estimates as compared to NWS COOP rainfall data on the hydrologic simulations, TOPMODEL was recalibrated and updated simulations were made using the NEXRAD-based rainfall data. Comparisons of observed and simulated streamflow show that the TOPMODEL results using measured rainfall data and NEXRAD-based rainfall are comparable. Nonetheless, TOPMODEL simulations using NEXRAD-based rainfall still tended to underpredict total streamflow volume, although the magnitude of differences were similar to the simulations using measured rainfall. The McTier Creek watershed was subdivided into 12 subwatersheds and NEXRAD-based rainfall data were generated for each subwatershed. Simulations of streamflow were generated for each subwatershed using NEXRAD-based rainfall and compared with subwatershed simulations using measured rainfall data, which unlike the NEXRAD-based rainfall were the same data for all subwatersheds (derived from a weighted average of the six NWS COOP stations surrounding the basin). For the two simulations, subwatershed streamflow were summed and compared to streamflow simulations at two U.S. Geological Survey streamgages. The percentage differences at the gage near Monetta, South Carolina, were the same for simulations using measured rainfall data and NEXRAD-based rainfall. At the gage near New Holland, South Carolina, the percentage differences using the NEXRAD-based rainfall were twice as much as those using the measured rainfall. Single-mass curve comparisons showed an increase in the total volume of rainfall from north to south. Similar comparisons of the measured rainfall at the NWS COOP stations showed similar percentage differences, but the NEXRAD-based rainfall variations occurred over a much smaller distance than the measured rainfall. Nonetheless, it was concluded that in some cases, using NEXRAD-based rainfall data in TOPMODEL streamflow simulations may provide an effective alternative to using measured rainfall data. For this investigation, however, TOPMODEL streamflow simulations using NEXRAD-based rainfall data for both calibration and simulations did not show significant improvements with respect to matching observed streamflow over simulations generated using measured rainfall data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125120","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Feaster, T., Westcott, N.E., Hudson, R.J., Conrads, P., and Bradley, P.M., 2012, Comparison of TOPMODEL streamflow simulations using NEXRAD-based and measured rainfall data, McTier Creek watershed, South Carolina: U.S. Geological Survey Scientific Investigations Report 2012-5120, x, 33 p., https://doi.org/10.3133/sir20125120.","productDescription":"x, 33 p.","numberOfPages":"48","onlineOnly":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":259706,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5120.gif"},{"id":259702,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5120/","linkFileType":{"id":5,"text":"html"}},{"id":259703,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5120/sir2012-5120.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Albers Equal Area","datum":"North American Datum 1983","country":"United States","state":"South Carolina","county":"Aiken County","otherGeospatial":"McTier Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.65,33.7 ], [ -81.65,33.88333333333333 ], [ -81.5,33.88333333333333 ], [ -81.5,33.7 ], [ -81.65,33.7 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f848e4b0c8380cd4cfbc","contributors":{"authors":[{"text":"Feaster, Toby D. 0000-0002-5626-5011 tfeaster@usgs.gov","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":1109,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby D.","email":"tfeaster@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":466639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westcott, Nancy E.","contributorId":95318,"corporation":false,"usgs":true,"family":"Westcott","given":"Nancy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":466640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudson, Robert J.M.","contributorId":101135,"corporation":false,"usgs":true,"family":"Hudson","given":"Robert","email":"","middleInitial":"J.M.","affiliations":[],"preferred":false,"id":466641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":466638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":466637,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70039629,"text":"ofr20121165 - 2012 - Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California: 2011","interactions":[],"lastModifiedDate":"2012-08-18T01:01:45","indexId":"ofr20121165","displayToPublicDate":"2012-08-17T00:00:00","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":"2012-1165","title":"Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California: 2011","docAbstract":"Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in South San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2011 to December 2011. These data serve as the basis for the City of Palo Alto's Near-Field Receiving Water Monitoring Program, initiated in 1994. Following significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and M. petalum appear to have stabilized. Data for other metals, including chromium, mercury, nickel, selenium, and zinc, have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2011, concentrations of Ag and Cu in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Hg, Ni, Se, and Zn, were generally similar in timing and magnitude as those for Ag and Cu. In 2011, metal concentrations in both sediments and clam tissue were among the lowest concentrations on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site. Analyses of the benthic community structure of a mudflat in South San Francisco Bay over a 38-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of the M. petalum community shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2011), with almost all animals initiating reproduction in the fall and spawning the following spring. The community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for those deep-dwelling animals like Macoma petalum. Animals immediately returned to the mudflat in 2008, which was the first indication that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2011 is reflective of the species that were available either as pelagic larvae or as mobile adults. Although egg layers were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2011 benthic community data, which show that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of animals that consume the sediment, filter feed, have pelagic larvae that must survive landing on the sediment, and brood their young. USGS scientists continue to observe the community's response to the 2008 defaunation event because it allows them to examine the response of the community to a natural disturbance (possible causes include sediment accretion or freshwater inundation) and compare this recovery to the long-term recovery observed in the 1970s when the decline in sediment pollutants was the dominating factor.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121165","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Dyke, J., Thompson, J.K., Cain, D.J., Kleckner, A.E., Parcheso, F., Luoma, S.N., and Hornberger, M.I., 2012, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California: 2011: U.S. Geological Survey Open-File Report 2012-1165, vii, 108 p.; col. ill.; Appendices; XLSX Download of Appendices 1-11, https://doi.org/10.3133/ofr20121165.","productDescription":"vii, 108 p.; col. ill.; Appendices; XLSX Download of Appendices 1-11","startPage":"i","endPage":"108","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true}],"links":[{"id":259694,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1165.gif"},{"id":259691,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1165/of2012-1165_text.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259690,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1165/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a63f5e4b0c8380cd727b4","contributors":{"authors":[{"text":"Dyke, Jessica jldyke@usgs.gov","contributorId":1035,"corporation":false,"usgs":true,"family":"Dyke","given":"Jessica","email":"jldyke@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":466629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":466628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":466631,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleckner, Amy E. kleckner@usgs.gov","contributorId":4258,"corporation":false,"usgs":true,"family":"Kleckner","given":"Amy","email":"kleckner@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":466634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parcheso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":2590,"corporation":false,"usgs":true,"family":"Parcheso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":466633,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":466632,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":466630,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70039628,"text":"sir20125067 - 2012 - Geologic and mineralogic controls on acid and metal-rich rock drainage in an alpine watershed, Handcart Gulch, Colorado","interactions":[],"lastModifiedDate":"2017-09-26T09:45:08","indexId":"sir20125067","displayToPublicDate":"2012-08-17T00:00:00","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":"2012-5067","title":"Geologic and mineralogic controls on acid and metal-rich rock drainage in an alpine watershed, Handcart Gulch, Colorado","docAbstract":"The surface and subsurface geology, hydrothermal alteration, and mineralogy of the Handcart Gulch area was studied using map and drill core data as part of a multidisciplinary approach to understand the hydrology and affects of geology on acid-rock drainage in a mineralized alpine watershed. Handcart Gulch was the locus of intense hydrothermal alteration that affected an area of nearly 3 square kilometers. Hydrothermal alteration and accompanied weak mineralization are spatially and genetically associated with small dacite to low-silica rhyolite stocks and plugs emplaced about 37-36 Ma. Felsic lithologies are commonly altered to a quartz-sericite-pyrite mineral assemblage at the surface, but alteration is more variable in the subsurface, ranging from quartz-sericite-pyrite-dominant in upper core sections to a propylitic variant that is more typical in deeper drill core intervals. Late-stage, hydrothermal argillic alteration [kaolinite and(or) smectite] was superimposed over earlier-formed alteration assemblages in the felsic rocks. Smectite in this late stage assemblage is mostly neoformed resulting from dissolution of chlorite, plagioclase, and minor illite in more weakly altered rocks. Hydrothermally altered amphibolites are characterized by biotitic alteration of amphibole, and subsequent alteration of both primary and secondary biotite to chlorite. Whereas pyrite is present both as disseminations and in small veinlets in the felsic lithologies, it is mostly restricted to small veinlets in the amphibolites. Base-metal sulfides including molybdenite, chalcopyrite, sphalerite, and galena are present in minor to trace amounts in the altered rocks. However, geologic data in conjunction with water geochemical studies indicate that copper mineralization may be present in unknown abundance in two distinct areas. The altered rocks contain an average of 8 weight percent fine pyrite that is largely devoid of metals in the crystal structure, which can be a significant source of trace metals in other areas with acid rock drainage. Thus, elevated base-metal concentrations in the trunk stream and discrete springs in the study area, as determined in previous studies, are likely derived from discrete metal-rich sources, rather than the abundant pyrite veins or disseminations. Pyrite is oxidized in nearly all outcrops examined. Drill core data show that zones of pyrite oxidation range in depth from 100 meters below the surface at higher elevations to just a few meters depth at the lowest elevations in the study area. However, discrete pyrite oxidation zones are present in drill core to depths of several hundred meters below the pervasive near-surface oxidation zones. These deeper discrete oxidation zones, which are present where fresh pyrite predominates, are spatially associated with fractures, small faults, and breccias. Quartz-sericite-pyrite-altered rocks containing unoxidized pyrite likely have the highest acid-generating capacity of all alteration assemblages in the study area. Hydrothermal alteration has left these rocks base-cation leached and thus acid-neutralizing potential is negligible. In contrast, propylitic-altered felsic rocks commonly contain trace to minor calcite and abundant chlorite, which provide some amount of acid-neutralization despite the presence of a few percent pyrite.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125067","usgsCitation":"Bove, D.J., Caine, J.S., and Lowers, H., 2012, Geologic and mineralogic controls on acid and metal-rich rock drainage in an alpine watershed, Handcart Gulch, Colorado: U.S. Geological Survey Scientific Investigations Report 2012-5067, vi, 121 p.; col. ill.; maps (col.); Appendices; Downloads Directory, https://doi.org/10.3133/sir20125067.","productDescription":"vi, 121 p.; col. ill.; maps (col.); Appendices; Downloads Directory","startPage":"i","endPage":"121","numberOfPages":"130","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":259695,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5067.gif"},{"id":259688,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5067/","linkFileType":{"id":5,"text":"html"}},{"id":259689,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5067/SIR12-5067_508.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Colorado","otherGeospatial":"Handcart Gulch","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a18ffe4b0c8380cd5586f","contributors":{"authors":[{"text":"Bove, Dana J. dbove@usgs.gov","contributorId":4855,"corporation":false,"usgs":true,"family":"Bove","given":"Dana","email":"dbove@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":466626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caine, Jonathan S. 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":1272,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan","email":"jscaine@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":466627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowers, Heather 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":710,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":466625,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70039627,"text":"sir20125157 - 2012 - Podiform chromite deposits--database and grade and tonnage models","interactions":[],"lastModifiedDate":"2023-06-23T10:58:59.137351","indexId":"sir20125157","displayToPublicDate":"2012-08-17T00:00:00","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":"2012-5157","title":"Podiform chromite deposits--database and grade and tonnage models","docAbstract":"Chromite ((Mg, Fe++)(Cr, Al, Fe+++)2O4) is the only source for the metallic element chromium, which is used in the metallurgical, chemical, and refractory industries. Podiform chromite deposits are small magmatic chromite bodies formed in the ultramafic section of an ophiolite complex in the oceanic crust. These deposits have been found in midoceanic ridge, off-ridge, and suprasubduction tectonic settings. Most podiform chromite deposits are found in dunite or peridotite near the contact of the cumulate and tectonite zones in ophiolites. We have identified 1,124 individual podiform chromite deposits, based on a 100-meter spatial rule, and have compiled them in a database. Of these, 619 deposits have been used to create three new grade and tonnage models for podiform chromite deposits. The major podiform chromite model has a median tonnage of 11,000 metric tons and a mean grade of 45 percent Cr2O3. The minor podiform chromite model has a median tonnage of 100 metric tons and a mean grade of 43 percent Cr2O3. The banded podiform chromite model has a median tonnage of 650 metric tons and a mean grade of 42 percent Cr2O3. Observed frequency distributions are also given for grades of rhodium, iridium, ruthenium, palladium, and platinum. In resource assessment applications, both major and minor podiform chromite models may be used for any ophiolite complex regardless of its tectonic setting or ophiolite zone. Expected sizes of undiscovered podiform chromite deposits, with respect to degree of deformation or ore-forming process, may determine which model is appropriate. The banded podiform chromite model may be applicable for ophiolites in both suprasubduction and midoceanic ridge settings.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125157","usgsCitation":"Mosier, D.L., Singer, D.A., Moring, B.C., and Galloway, J.P., 2012, Podiform chromite deposits--database and grade and tonnage models: U.S. Geological Survey Scientific Investigations Report 2012-5157, iv, 45 p., https://doi.org/10.3133/sir20125157.","productDescription":"iv, 45 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":259692,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5157.gif"},{"id":259687,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5157/sir2012-5157_text.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259686,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5157/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a7caae4b0c8380cd79af3","contributors":{"authors":[{"text":"Mosier, Dan L.","contributorId":42593,"corporation":false,"usgs":true,"family":"Mosier","given":"Dan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":466624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Singer, Donald A. dsinger@usgs.gov","contributorId":5601,"corporation":false,"usgs":true,"family":"Singer","given":"Donald","email":"dsinger@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":466623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moring, Barry C. 0000-0001-6797-9258 moring@usgs.gov","orcid":"https://orcid.org/0000-0001-6797-9258","contributorId":2794,"corporation":false,"usgs":true,"family":"Moring","given":"Barry","email":"moring@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":466621,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galloway, John P. jgallway@usgs.gov","contributorId":3345,"corporation":false,"usgs":true,"family":"Galloway","given":"John","email":"jgallway@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":466622,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}