The State of Michigan has more than 11,000 inland lakes; approximately 3,500 of these lakes are greater than 25 acres. The USGS, in cooperation with the Michigan Department of Environmental Quality (MDEQ), has been monitoring the quality of inland lakes in Michigan through the Lake Water Quality Assessment monitoring program. Approximately 100 inland lakes will be sampled per year from 2001 to 2015. Volunteers coordinated by MDEQ started sampling lakes in 1974, and continue to sample to date approximately 250 inland lakes each year through the Cooperative Lakes Monitoring Program (CLMP), Michigan’s volunteer lakes monitoring program. Despite this sampling effort, it is still impossible to physically collect the necessary water-quality measurements for all 3,500 Michigan inland lakes. Therefore, a technique was used by USGS, modeled after Olmanson and others (2001), in cooperation with MDEQ that uses satellite remote sensing to predict water quality in unsampled inland lakes greater than 25 acres.
Water-quality characteristics that are associated with water clarity can be predicted for Michigan inland lakes by relating sampled measurements of secchi-disk transparency (SDT) and chlorophyll a concentrations (Chl-a), to satellite imagery. The trophic state index (TSI) which is an indicator of the biological productivity can be calculated based on SDT measurements, Chl-a concentrations, and total phosphorus (TP) concentrations measured near the lake’s surface. Through this process, unsampled inland lakes within the fourteen Landsat satellite scenes encompassing Michigan can be translated into estimated TSI from either predicted SDT or Chl-a (fig. 1).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20073022","collaboration":"Prepared in cooperation with the Michigan Department of Environmental Quality","usgsCitation":"Fuller, L.M., and Minnerick, R., 2007, Predicting water quality by relating secchi-disk transparency and chlorophyll a measurements to Landsat satellite imagery for Michigan inland lakes, 2001-2006: U.S. Geological Survey Fact Sheet 2007-3022, 4 p., https://doi.org/10.3133/fs20073022.","productDescription":"4 p.","temporalStart":"2001-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":126269,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2007_3022.jpg"},{"id":10210,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2007/3022/","linkFileType":{"id":5,"text":"html"}}],"country":"United 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\"}}]}\n","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ab0e4b07f02db66d8ae","contributors":{"authors":[{"text":"Fuller, L. M.","contributorId":97987,"corporation":false,"usgs":true,"family":"Fuller","given":"L.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":292420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minnerick, R. J.","contributorId":52255,"corporation":false,"usgs":true,"family":"Minnerick","given":"R. J.","affiliations":[],"preferred":false,"id":292419,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80278,"text":"tm2G1 - 2007 - Protocol for Landsat-Based Monitoring of Landscape Dynamics at North Coast and Cascades Network Parks","interactions":[],"lastModifiedDate":"2012-02-02T00:14:19","indexId":"tm2G1","displayToPublicDate":"2007-08-30T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2-G1","title":"Protocol for Landsat-Based Monitoring of Landscape Dynamics at North Coast and Cascades Network Parks","docAbstract":"Background and Objectives\r\n\r\nAs part of the National Park Service's larger goal of developing long-term monitoring programs in response to the Natural Resource Challenge of 2000, the parks of the North Coast and Cascades Network (NCCN) have determined that monitoring of landscape dynamics is necessary to track ecosystem health (Weber and others, 2005). Landscape dynamics refer to a broad suite of ecological, geomorphological, and anthropogenic processes occurring across broad spatial scales. The NCCN has sought protocols that would leverage remote-sensing technologies to aid in monitoring landscape dynamics.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Chapter 1 of Book 2, Collection of Environmental Data, Section G, Remote Sensing","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/tm2G1","collaboration":"Prepared in cooperation with the North Coast and Cascades Network, National Park Service","usgsCitation":"Kennedy, R., Cohen, W.B., Kirschbaum, A.A., and Haunreiter, E., 2007, Protocol for Landsat-Based Monitoring of Landscape Dynamics at North Coast and Cascades Network Parks: U.S. Geological Survey Techniques and Methods 2-G1, iv, 127 p., https://doi.org/10.3133/tm2G1.","productDescription":"iv, 127 p.","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":194812,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":10099,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/2007/tm2g1/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae0e4b07f02db687ec2","contributors":{"authors":[{"text":"Kennedy, Robert E.","contributorId":41916,"corporation":false,"usgs":true,"family":"Kennedy","given":"Robert E.","affiliations":[],"preferred":false,"id":292159,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Warren B.","contributorId":100093,"corporation":false,"usgs":true,"family":"Cohen","given":"Warren","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":292162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kirschbaum, Alan A.","contributorId":48659,"corporation":false,"usgs":true,"family":"Kirschbaum","given":"Alan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":292160,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haunreiter, Erik","contributorId":63113,"corporation":false,"usgs":true,"family":"Haunreiter","given":"Erik","email":"","affiliations":[],"preferred":false,"id":292161,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70258396,"text":"70258396 - 2007 - Radiometric recalibration procedure for Landsat-5 Thematic Mapper data","interactions":[],"lastModifiedDate":"2024-09-16T16:48:06.938317","indexId":"70258396","displayToPublicDate":"2007-07-31T11:36:47","publicationYear":"2007","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Radiometric recalibration procedure for Landsat-5 Thematic Mapper data","docAbstract":"The Landsat-5 (L5) satellite was launched on March 01, 1984, with a design life of three years. Incredibly, the L5 Thematic Mapper (TM) has collected data for 23 years. Over this time, the detectors have aged, and its radiometric characteristics have changed since launch. The calibration procedures and parameters have also changed with time. Revised radiometric calibrations have improved the radiometric accuracy of recently processed data; however, users with data that were processed prior to the calibration update do not benefit from the revisions. A procedure has been developed to give users the ability to recalibrate their existing Level 1 (Ll) products without having to purchase reprocessed data from the U.S. Geological Survey (USGS). The accuracy of the recalibration is dependent on the knowledge of the prior calibration applied to the data. The “Work Order” File, included with standard National Land Archive Production System (NLAPS) data products, gives parameters that define the applied calibration. These are the Internal Calibrator (IC) calibration parameters or the default prelaunch calibration, if there were problems with the IC calibration. This paper details the recalibration procedure for data processed using IC, in which users have the Work Order file.
","conferenceTitle":"2007 IEEE International Geoscience and Remote Sensing Symposium","conferenceDate":"July 23-28, 2007","conferenceLocation":"Barcelona, Spain","language":"English","publisher":"IEEE","doi":"10.1109/IGARSS.2007.4423759","usgsCitation":"Chander, G., Micijevic, E., Hayes, R.W., and Barsi, J.A., 2007, Radiometric recalibration procedure for Landsat-5 Thematic Mapper data, 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain, July 23-28, 2007, p. 4132-4135, https://doi.org/10.1109/IGARSS.2007.4423759.","productDescription":"4 p","startPage":"4132","endPage":"4135","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":434789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":913196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Micijevic, Esad 0000-0002-3828-9239 emicijevic@usgs.gov","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":3075,"corporation":false,"usgs":true,"family":"Micijevic","given":"Esad","email":"emicijevic@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":913197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Ronald W. 0000-0002-7187-0682 hayes@usgs.gov","orcid":"https://orcid.org/0000-0002-7187-0682","contributorId":4804,"corporation":false,"usgs":true,"family":"Hayes","given":"Ronald","email":"hayes@usgs.gov","middleInitial":"W.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":913198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barsi, Julia A.","contributorId":71822,"corporation":false,"usgs":false,"family":"Barsi","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":12721,"text":"NASA GSFC SSAI","active":true,"usgs":false}],"preferred":false,"id":913199,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":80140,"text":"ds281 - 2007 - Satellite Images and Aerial Photographs of the Effects of Hurricanes Katrina and Rita on Coastal Louisiana","interactions":[],"lastModifiedDate":"2012-02-02T00:14:13","indexId":"ds281","displayToPublicDate":"2007-07-26T00:00:00","publicationYear":"2007","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":"281","title":"Satellite Images and Aerial Photographs of the Effects of Hurricanes Katrina and Rita on Coastal Louisiana","docAbstract":"Introduction\r\n\r\nHurricane Katrina made landfall on the eastern coastline of Louisiana on August 29, 2005; Hurricane Rita made landfall on the western coastline of Louisiana on September 24, 2005. Comparison of Landsat Thematic Mapper (TM) satellite imagery acquired before and after the landfalls of Katrina and Rita and classified to identify land and water demonstrated that water area increased by 217 mi2 (562 km2) in coastal Louisiana as a result of the storms. Approximately 82 mi2 (212 km2) of new water areas were in areas primarily impacted by Hurricane Katrina (Mississippi River Delta basin, Breton Sound basin, Pontchartrain basin, and Pearl River basin), whereas 99 mi2 (256 km2) were in areas primarily impacted by Hurricane Rita (Calcasieu/Sabine basin, Mermentau basin, Teche/Vermilion basin, Atchafalaya basin, and Terrebonne basin). Barataria basin contained new water areas caused by both hurricanes, resulting in some 18 mi2 (46.6 km2) of new water areas. The fresh marsh and intermediate marsh communities' land areas decreased by 122 mi2 (316 km2) and 90 mi2 (233.1 km2), respectively, and the brackish marsh and saline marsh communities' land areas decreased by 33 mi2 (85.5 km2) and 28 mi2 (72.5 km2), respectively. \r\n\r\nThese new water areas represent land losses caused by direct removal of wetlands. They also indicate transitory changes in water area caused by remnant flooding, removal of aquatic vegetation, scouring of marsh vegetation, and water-level variation attributed to normal tidal and meteorological variation between satellite images. \r\n\r\nPermanent losses cannot be estimated until several growing seasons have passed and the transitory impacts of the hurricanes are minimized. The purpose of this study was to provide preliminary information on water area changes in coastal Louisiana acquired shortly after the landfalls of both hurricanes (detectable with Landsat TM imagery) and to serve as a regional baseline for monitoring posthurricane wetland recovery. The land-water datasets derived from the Landsat TM satellite imagery were combined with 2001 marsh vegetative communities (Chabreck and others, unpub. data, 2001) to identify land-water configurations by marsh community before and after the hurricanes. \r\n\r\nLinks to the Landsat TM images and aerial photographs are given below (figs. 1-29). Comparison of land area before the storms to land area after the storms is made possible by the inclusion of Landsat TM images and aerial photographs taken in the years and months before the storms. The figures are arranged geographically from east to west to follow the chronology of the effects of the storms. For a more detailed analysis of the changes wrought by these storms, see 'Land Area Changes in Coastal Louisiana After Hurricanes Katrina and Rita' (Barras, in press).","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ds281","usgsCitation":"Barras, J., 2007, Satellite Images and Aerial Photographs of the Effects of Hurricanes Katrina and Rita on Coastal Louisiana (Version 1.0): U.S. Geological Survey Data Series 281, Introduction; 85 Images (in JPEG & PDF format), https://doi.org/10.3133/ds281.","productDescription":"Introduction; 85 Images (in JPEG & PDF format)","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":190511,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9954,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/2007/281/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a7fe4b07f02db6486d2","contributors":{"authors":[{"text":"Barras, John A. jbarras@usgs.gov","contributorId":2425,"corporation":false,"usgs":true,"family":"Barras","given":"John A.","email":"jbarras@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":291826,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":80111,"text":"ofr20071207 - 2007 - Using a remote sensing/GIS model to predict southwestern Willow Flycatcher breeding habitat along the Rio Grande, New Mexico","interactions":[],"lastModifiedDate":"2016-12-27T13:05:05","indexId":"ofr20071207","displayToPublicDate":"2007-07-20T00:00:00","publicationYear":"2007","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":"2007-1207","title":"Using a remote sensing/GIS model to predict southwestern Willow Flycatcher breeding habitat along the Rio Grande, New Mexico","docAbstract":"Introduction\r\n\r\nThe Southwestern Willow Flycatcher (Empidonax traillii extimus; hereafter SWFL) is a federally endangered bird (USFWS 1995) that breeds in riparian areas in portions of New Mexico, Arizona, southwestern Colorado, extreme southern Utah and Nevada, and southern California (USFWS 2002). Across this range, it uses a variety of plant species as nesting/breeding habitat, but in all cases prefers sites with dense vegetation, high canopy, and proximity to surface water or saturated soils (Sogge and Marshall 2000). As of 2005, the known rangewide breeding population of SWFLs was roughly 1,214 territories, with approximately 393 territories distributed among 36 sites in New Mexico (Durst et al. 2006), primarily along the Rio Grande.\r\n\r\nOne of the key challenges facing the management and conservation of the Southwestern Willow Flycatcher is that riparian areas are dynamic, with individual habitat patches subject to cycles of creation, growth, and loss due to drought, flooding, fire, and other disturbances. Former breeding patches can lose suitability, and new habitat can develop within a matter of only a few years, especially in reservoir drawdown zones. Therefore, measuring and predicting flycatcher habitat - either to discover areas that might support SWFLs, or to identify areas that may develop into appropriate habitat - requires knowledge of recent/current habitat conditions and an understanding of the factors that determine flycatcher use of riparian breeding sites.\r\n\r\nIn the past, much of the determination of whether a riparian site is likely to support breeding flycatchers has been based on qualitative criteria (for example, 'dense vegetation' or 'large patches'). These determinations often require on-the-ground field evaluations by local or regional SWFL experts. While this has proven valuable in locating many of the currently known breeding sites, it is difficult or impossible to apply this approach effectively over large geographic areas (for example, the middle Rio Grande). The SWFL Recovery Plan (USFWS 2002) recognizes the importance of developing new approaches to habitat identification, and recommends the development of drainage-scale, quantitative habitat models. In particular, the plan suggests using models based on remote sensing and Geographic Information System (GIS) technology that can capture the relatively dynamic habitat changes that occur in southwestern riparian systems.\r\n\r\nIn 1999, Arizona Game and Fish Department (AGFD) developed a GIS-based model (Hatten and Paradzick 2003) to identify SWFL breeding habitat from Landsat Thematic Mapper imagery and 30-m resolution digital elevation models (DEMs). The model was developed with presence/absence survey data acquired along the San Pedro and Gila rivers, and from the Salt River and Tonto Creek inlets to Roosevelt Lake in southern Arizona (collectively called the project area). The GIS-based model used a logistic regression equation to divide riparian vegetation into 5 probability classes based upon characteristics of riparian vegetation and floodplain size. This model was tested by predicting SWFL breeding habitat at Alamo Lake, Arizona, located 200 km from the project area (Hatten and Paradzick 2003). The GIS-based model performed as expected by identifying riparian areas with the highest SWFL nest densities, located in the higher probability classes.\r\n\r\nIn 2002, AGFD applied the GIS-based model throughout Arizona, for riparian areas below 1,524 m (5,000 ft) elevation and within 1.6 km of perennial or intermittent waters (Dockens et al. 2004). Overall model accuracy (using probability classes 1-5, with class 5 having the greatest probability of nesting activity) for predicting the location of 2001 nest sites was 96.5 percent; accuracy decreased when fewer probability classes were defined as suitable. Map accuracy, determined from errors of commission, increased in higher probability classes in a fashion similar to errors of omission. Map accuracy, li","language":"English","publisher":"U.S Geological Survey ","doi":"10.3133/ofr20071207","collaboration":"Prepared for the Bureau of Reclamation, Upper Colorado River Region","usgsCitation":"Hatten, J.R., and Sogge, M.K., 2007, Using a remote sensing/GIS model to predict southwestern Willow Flycatcher breeding habitat along the Rio Grande, New Mexico (Version 1.0): U.S. Geological Survey Open-File Report 2007-1207, ii., 27 p., https://doi.org/10.3133/ofr20071207.","productDescription":"ii., 27 p.","onlineOnly":"Y","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":190997,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9939,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1207/","linkFileType":{"id":5,"text":"html"}}],"scale":"250000","country":"United States","state":"Colorado, New Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109,31.3 ], [ -109,38 ], [ -103,38 ], [ -103,31.3 ], [ -109,31.3 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a16e4b07f02db603cec","contributors":{"authors":[{"text":"Hatten, James R. 0000-0003-4676-8093 jhatten@usgs.gov","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":3431,"corporation":false,"usgs":true,"family":"Hatten","given":"James","email":"jhatten@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":291758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sogge, Mark K. 0000-0002-8337-5689 mark_sogge@usgs.gov","orcid":"https://orcid.org/0000-0002-8337-5689","contributorId":3710,"corporation":false,"usgs":true,"family":"Sogge","given":"Mark","email":"mark_sogge@usgs.gov","middleInitial":"K.","affiliations":[{"id":5079,"text":"Pacific Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":291759,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":80051,"text":"gip51 - 2007 - Ride the Rockies Postcard","interactions":[],"lastModifiedDate":"2012-02-02T00:14:18","indexId":"gip51","displayToPublicDate":"2007-06-20T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"51","title":"Ride the Rockies Postcard","docAbstract":"2007 Ride The Rockies route on shaded-relief mosaic of USGS Landsat 7 satellite images, northwestern Colorado. To download other USGS materials related to Ride The Rockies, go to http://www.cr.usgs.gov/rtr/index.htm","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/gip51","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2007, Ride the Rockies Postcard (Version 1.0): U.S. Geological Survey General Information Product 51, Postcard, https://doi.org/10.3133/gip51.","productDescription":"Postcard","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":122375,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_51.jpg"},{"id":10128,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/2007/51/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a13e4b07f02db60193f","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":534865,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":79995,"text":"ds273 - 2007 - Irrigated Acreage Within the Basin and Range Carbonate-Rock Aquifer System, White Pine County, Nevada, and Adjacent Areas in Nevada and Utah","interactions":[],"lastModifiedDate":"2013-06-04T10:37:06","indexId":"ds273","displayToPublicDate":"2007-06-06T00:00:00","publicationYear":"2007","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":"273","title":"Irrigated Acreage Within the Basin and Range Carbonate-Rock Aquifer System, White Pine County, Nevada, and Adjacent Areas in Nevada and Utah","docAbstract":"Accurate delineations of irrigated acreage are needed for the development of water-use estimates and in determining water-budget calculations for the Basin and Range carbonate-rock aquifer system (BARCAS) study. Irrigated acreage is estimated routinely for only a few basins in the study area. Satellite imagery from the Landsat Thematic Mapper and Enhanced Thematic Mapper platforms were used to delineate irrigated acreage on a field-by-field basis for the entire study area. Six hundred and forty-three fields were delineated. The water source, irrigation system, crop type, and field activity for 2005 were identified and verified through field reconnaissance. These data were integrated in a geodatabase and analyzed to develop estimates of irrigated acreage for the 2000, 2002, and 2005 growing seasons by hydrographic area and subbasin. Estimated average annual potential evapotranspiration and average annual precipitation also were estimated for each field.The geodatabase was analyzed to determine the spatial distribution of field locations, the total amount of irrigated acreage by potential irrigation water source, by irrigation system, and by crop type. Irrigated acreage in 2005 totaled nearly 32,000 acres ranging from less than 200 acres in Butte, Cave, Jakes, Long, and Tippett Valleys to 9,300 acres in Snake Valley. Irrigated acreage increased about 20 percent between 2000 and 2005 and increased the most in Snake and White River Valleys. Ground-water supplies as much as 80 percent of irrigation water during dry years. Almost 90 percent of the irrigated acreage was planted with alfalfa.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ds273","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Welborn, T.L., and Moreo, M.T., 2007, Irrigated Acreage Within the Basin and Range Carbonate-Rock Aquifer System, White Pine County, Nevada, and Adjacent Areas in Nevada and Utah: U.S. Geological Survey Data Series 273, vi, 19 p., https://doi.org/10.3133/ds273.","productDescription":"vi, 19 p.","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":273171,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds273_NV_StateWellLog.xml"},{"id":190523,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9735,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/2007/273/","linkFileType":{"id":5,"text":"html"}},{"id":273166,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds273_Ag_Irrigation.xml"},{"id":273167,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds273_CropInventory.xml"},{"id":273168,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds273_DelineatedIrrigatedAcreage_Geodatabase.xml"},{"id":273172,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds273_Utah_POD.xml"},{"id":273170,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds273_IrrigationFieldCheck.xml"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4ae4b07f02db62512c","contributors":{"authors":[{"text":"Welborn, Toby L. 0000-0003-4839-2405 tlwelbor@usgs.gov","orcid":"https://orcid.org/0000-0003-4839-2405","contributorId":2295,"corporation":false,"usgs":true,"family":"Welborn","given":"Toby","email":"tlwelbor@usgs.gov","middleInitial":"L.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":291410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moreo, Michael T. 0000-0002-9122-6958 mtmoreo@usgs.gov","orcid":"https://orcid.org/0000-0002-9122-6958","contributorId":2363,"corporation":false,"usgs":true,"family":"Moreo","given":"Michael","email":"mtmoreo@usgs.gov","middleInitial":"T.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":291411,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}