The U.S. Geological Survey, in cooperation with researchers from several universities, has been studying the sediments of Bear Lake since 1996. The general purpose of this effort is to reconstruct past limnological conditions and regional climate on a range of timescales, from hundreds of years to hundreds of thousands of years. The objectives of the September, 2002 operations, preliminarily reported here, were (1) to compile a detailed bathymetric map of the lake using swath-mapping techniques, in order to provide baseline data for a variety of applications and studies, and (2) to complete a sidescan-sonar survey of the lake, providing a nearly complete acoustic image of the lake floor. Limited amounts of subbottom acoustic-reflection data (chirp) were also collected, along with samples of lake-floor sediments representative of different kinds of backscatter patterns.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr03150","isbn":"0607941847","usgsCitation":"Denny, J.F., and Colman, S.M., 2003, Geophysical surveys of Bear Lake, Utah-Idaho, September, 2002: U.S. Geological Survey Open-File Report 2003-150, HTML Document; CD-ROM, https://doi.org/10.3133/ofr03150.","productDescription":"HTML Document; CD-ROM","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":181491,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5247,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2003/of03-150/","linkFileType":{"id":5,"text":"html"}},{"id":391823,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_59415.htm"}],"country":"United States","state":"Idaho, Utah","otherGeospatial":"Bear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.4167,\n 41.83375828633243\n ],\n [\n -111.24549865722656,\n 41.83375828633243\n ],\n [\n -111.24549865722656,\n 42.12521956084993\n ],\n [\n -111.4167,\n 42.12521956084993\n ],\n [\n -111.4167,\n 41.83375828633243\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1ae4b07f02db6a8307","contributors":{"authors":[{"text":"Denny, Jane F. 0000-0002-3472-618X jdenny@usgs.gov","orcid":"https://orcid.org/0000-0002-3472-618X","contributorId":418,"corporation":false,"usgs":true,"family":"Denny","given":"Jane","email":"jdenny@usgs.gov","middleInitial":"F.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":246476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colman, Steve M.","contributorId":49807,"corporation":false,"usgs":true,"family":"Colman","given":"Steve","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":246477,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":53064,"text":"ofr032 - 2003 - Texture, Carbonate Content, and Preliminary Maps of Surficial Sediments of the Flower Garden Banks Area, Northwestern Gulf of Mexico Outer Shelf","interactions":[],"lastModifiedDate":"2017-11-10T18:28:58","indexId":"ofr032","displayToPublicDate":"2003-10-01T00:00:00","publicationYear":"2003","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":"2003-2","title":"Texture, Carbonate Content, and Preliminary Maps of Surficial Sediments of the Flower Garden Banks Area, Northwestern Gulf of Mexico Outer Shelf","docAbstract":"The purpose of this report is to release texture and carbonate content analyses of 107 seafloor sediments collected within and near the East and West Flower Garden Banks areas of the Sanctuary and to show relationships between these data and existing bathymetric data. The sediment data, in conjunction with previously collected geological, geophysical and biological data were used to construct a reconnaissance-scale map of the distribution of seafloor sediment types. This map will be useful for resource managers and can be used, with additional data, as a basis for future habitat mapping.
","language":"ENGLISH","doi":"10.3133/ofr032","isbn":"0607937211","usgsCitation":"Scanlon, K.M., Ackerman, S.D., and Rozycki, J.E., 2003, Texture, Carbonate Content, and Preliminary Maps of Surficial Sediments of the Flower Garden Banks Area, Northwestern Gulf of Mexico Outer Shelf: U.S. Geological Survey Open-File Report 2003-2, 1 CD-ROM ; 4 3/4 in., https://doi.org/10.3133/ofr032.","productDescription":"1 CD-ROM ; 4 3/4 in.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":177465,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":297450,"rank":101,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2003/of03-002/"},{"id":5204,"rank":100,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2003/of03-002/of03_002metafaq.htm","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad5e4b07f02db683712","contributors":{"authors":[{"text":"Scanlon, Kathryn M.","contributorId":6816,"corporation":false,"usgs":true,"family":"Scanlon","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":246468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Seth D. 0000-0003-0945-2794 sackerman@usgs.gov","orcid":"https://orcid.org/0000-0003-0945-2794","contributorId":178676,"corporation":false,"usgs":true,"family":"Ackerman","given":"Seth","email":"sackerman@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":246469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rozycki, Jill E.","contributorId":78397,"corporation":false,"usgs":true,"family":"Rozycki","given":"Jill","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":246470,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":53062,"text":"wri034123 - 2003 - A summary report of sediment processes in Chesapeake Bay and watershed","interactions":[],"lastModifiedDate":"2018-02-26T15:34:45","indexId":"wri034123","displayToPublicDate":"2003-10-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4123","title":"A summary report of sediment processes in Chesapeake Bay and watershed","docAbstract":"The Chesapeake Bay, the Nation's largest estuary, has been degraded because of diminished water quality, loss of habitat, and over-harvesting of living resources. Consequently, the bay was listed as an impaired water body due to excess nutrients and sediment. The Chesapeake Bay Program (CBP), a multi-jurisdictional partnership, completed an agreement called \"Chesapeake 2000\" that revises and establishes new restoration goals through 2010 in the bay and its watershed. The goal of this commitment is the removal of the bay from the list of impaired waterbodies by the year 2010. The CBP is committed to developing sediment and nutrient allocations for major basins within the bay watershed and to the process of examining new and innovative management plans in the estuary itself and along the coastal zones of the bay. However, additional information is required on the sources, transport, and deposition of sediment that affect water clarity. Because the information and data on sediment processes in the bay were not readily accessible to the CBP or to state, and local managers, a Sediment Workgroup (SWGP) was created in 2001.
The primary objective of this report, therefore, is to provide a review of the literature on the sources, transport, and delivery of sediment in Chesapeake Bay and its watershed with discussion of potential implications for various management alternatives. The authors of the report have extracted, discussed, and summarized the important aspects of sediment and sedimentation that are most relevant to the CBP and other sediment related-issues with which resources managers are involved. This report summarizes the most relevant studies concerning sediment sources, transport and deposition in the watershed and estuary, sediments and relation to water clarity, and provides an extensive list of references for those wanting more information.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/wri034123","usgsCitation":"2003, A summary report of sediment processes in Chesapeake Bay and watershed: U.S. Geological Survey Water-Resources Investigations Report 2003-4123, x, 109 p., https://doi.org/10.3133/wri034123.","productDescription":"x, 109 p.","onlineOnly":"Y","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":177809,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/wri/2003/4123/coverthb.jpg"},{"id":5203,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wri/2003/4123/wri20034123.pdf","text":"Report","size":"7.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"WRI 2003-4123"}],"contact":"Director, Pennsylvania Water Science Center U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
The USGS Place Based Studies Program for San Francisco Bay investigates this sensitive estuarine system to aid in resource management. As part of the inter-disciplinary research program, the USGS collected side-scan sonar data and bed-sediment samples from north San Francisco Bay to characterize bed-sediment texture and investigate temporal trends in sedimentation. The study area is located in central California and consists of Suisun Bay, and Grizzly and Honker Bays, sub-embayments of Suisun Bay. During the study (1998-2002), the USGS collected three side-scan sonar data sets and approximately 300 sediment samples. The side-scan data revealed predominantly fine-grained material on the bayfloor. We also mapped five different bottom types from the data set, categorized as featureless, furrows, sand waves, machine-made, and miscellaneous. We performed detailed grain-size and statistical analyses on the sediment samples. Overall, we found that grain size ranged from clay to fine sand, with the coarsest material in the channels and finer material located in the shallow bays. Grain-size analyses revealed high spatial variability in size distributions in the channel areas. In contrast, the shallow regions exhibited low spatial variability and consistent sediment size over time.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr03250","usgsCitation":"Hampton, M.A., Snyder, N., Chin, J., Allison, D.W., and Rubin, D.M., 2003, Bed-sediment grain-size and morphologic data from Suisun, Grizzly, and Honker Bays, CA, 1998-2002: U.S. Geological Survey Open-File Report 2003-250, Report: 25 p.; Plate: 22.58 x 14.82 inches, https://doi.org/10.3133/ofr03250.","productDescription":"Report: 25 p.; Plate: 22.58 x 14.82 inches","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":173864,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr03250.jpg"},{"id":285697,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2003/0250/pdf/of03-250.pdf"},{"id":4669,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2003/0250/","linkFileType":{"id":5,"text":"html"}},{"id":285698,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2003/0250/pdf/plate1.pdf"}],"country":"United States","state":"California","otherGeospatial":"Grizzly Bay, Honker Bay, San Francisco Bay, Suisun Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.153356,38.010233 ], [ -122.153356,38.167784 ], [ -121.879103,38.167784 ], [ -121.879103,38.010233 ], [ -122.153356,38.010233 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a6be4b07f02db63dc05","contributors":{"authors":[{"text":"Hampton, Margaret A.","contributorId":13688,"corporation":false,"usgs":true,"family":"Hampton","given":"Margaret","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":246660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snyder, Noah P.","contributorId":43848,"corporation":false,"usgs":true,"family":"Snyder","given":"Noah P.","affiliations":[],"preferred":false,"id":246662,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chin, John L.","contributorId":98291,"corporation":false,"usgs":true,"family":"Chin","given":"John L.","affiliations":[],"preferred":false,"id":246663,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allison, Dan W.","contributorId":26969,"corporation":false,"usgs":true,"family":"Allison","given":"Dan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":246661,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rubin, David M. 0000-0003-1169-1452 drubin@usgs.gov","orcid":"https://orcid.org/0000-0003-1169-1452","contributorId":3159,"corporation":false,"usgs":true,"family":"Rubin","given":"David","email":"drubin@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":246659,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":48851,"text":"ofr03172 - 2003 - User's Manual for the National Water-Quality Assessment Program Invertebrate Data Analysis System (IDAS) Software: Version 3","interactions":[],"lastModifiedDate":"2012-02-02T00:10:22","indexId":"ofr03172","displayToPublicDate":"2003-10-01T00:00:00","publicationYear":"2003","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":"2003-172","title":"User's Manual for the National Water-Quality Assessment Program Invertebrate Data Analysis System (IDAS) Software: Version 3","docAbstract":"The Invertebrate Data Analysis System (IDAS) software provides an accurate, consistent, and efficient mechanism for analyzing invertebrate data collected as part of the National Water-Quality Assessment Program and stored in the Biological Transactional Database (Bio-TDB). The IDAS software is a stand-alone program for personal computers that run Microsoft (MS) Windows?. It allows users to read data downloaded from Bio-TDB and stored either as MS Excel? or MS Access? files. The program consists of five modules. The Edit Data module allows the user to subset, combine, delete, and summarize community data. The Data Preparation module allows the user to select the type(s) of sample(s) to process, calculate densities, delete taxa based on laboratory processing notes, combine lifestages or keep them separate, select a lowest taxonomic level for analysis, delete rare taxa, and resolve taxonomic ambiguities. The Calculate Community Metrics module allows the user to calculate over 130 community metrics, including metrics based on organism tolerances and functional feeding groups. The Calculate Diversities and Similarities module allows the user to calculate nine diversity and eight similarity indices. The Data export module allows the user to export data to other software packages and produce tables of community data that can be imported into spreadsheet and word-processing programs. Though the IDAS program was developed to process invertebrate data downloaded from USGS databases, it will work with other data sets that are converted to the USGS (Bio-TDB) format. Consequently, the data manipulation, analysis, and export procedures provided by the IDAS program can be used by anyone involved in using benthic macroinvertebrates in applied or basic research.","language":"ENGLISH","doi":"10.3133/ofr03172","usgsCitation":"Cuffney, T.F., 2003, User's Manual for the National Water-Quality Assessment Program Invertebrate Data Analysis System (IDAS) Software: Version 3 (Version 3): U.S. Geological Survey Open-File Report 2003-172, 114 p., https://doi.org/10.3133/ofr03172.","productDescription":"114 p.","costCenters":[],"links":[{"id":169785,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":4071,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/ofr03172/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a17e4b07f02db603f9c","contributors":{"authors":[{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":238429,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":69696,"text":"i2790 - 2003 - Crater Lake revealed","interactions":[],"lastModifiedDate":"2018-10-24T09:40:00","indexId":"i2790","displayToPublicDate":"2003-10-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":320,"text":"IMAP","code":"I","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2790","title":"Crater Lake revealed","docAbstract":"Around 500,000 people each year visit Crater Lake National Park in the Cascade Range of southern Oregon. Volcanic peaks, evergreen forests, and Crater Lake’s incredibly blue water are the park’s main attractions. Crater Lake partially fills the caldera that formed approximately 7,700 years ago by the eruption and subsequent collapse of a 12,000-foot volcano called Mount Mazama. The caldera-forming or climactic eruption of Mount Mazama drastically changed the landscape all around the volcano and spread a blanket of volcanic ash at least as far away as southern Canada.
Prior to the climactic event, Mount Mazama had a 400,000 year history of cone building activity like that of other Cascade volcanoes such as Mount Shasta. Since the climactic eruption, there have been several less violent, smaller postcaldera eruptions within the caldera itself. However, relatively little was known about the specifics of these eruptions because their products were obscured beneath Crater Lake’s surface. As the Crater Lake region is still potentially volcanically active, understanding past eruptive events is important to understanding future eruptions, which could threaten facilities and people at Crater Lake National Park and the major transportation corridor east of the Cascades.
Recently, the lake bottom was mapped with a high-resolution multibeam echo sounder. The new bathymetric survey provides a 2m/pixel view of the lake floor from its deepest basins virtually to the shoreline. Using Geographic Information Systems (GIS) applications, the bathymetry data can be visualized and analyzed to shed light on the geology, geomorphology, and geologic history of Crater Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/i2790","isbn":"0607906502","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Ramsey, D.W., Dartnell, P., Bacon, C.R., Robinson, J., and Gardner, J.V., 2003, Crater Lake revealed: U.S. Geological Survey IMAP 2790, 38.01 x 25.01 inches, https://doi.org/10.3133/i2790.","productDescription":"38.01 x 25.01 inches","costCenters":[{"id":412,"text":"National Cooperative Geologic Mapping Program","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":191366,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":280491,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/imap/2790/pdf/i2790.pdf","text":"Map","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":110429,"rank":700,"type":{"id":15,"text":"Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_55153.htm","linkFileType":{"id":5,"text":"html"},"description":"55153"},{"id":6369,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/imap/2790/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Cascade Range, Crater Lake, Crater Lake National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.17964,42.891988 ], [ -122.17964,42.988538 ], [ -122.032809,42.988538 ], [ -122.032809,42.891988 ], [ -122.17964,42.891988 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad5e4b07f02db683773","contributors":{"authors":[{"text":"Ramsey, David W. 0000-0003-1698-2523 dramsey@usgs.gov","orcid":"https://orcid.org/0000-0003-1698-2523","contributorId":3819,"corporation":false,"usgs":true,"family":"Ramsey","given":"David","email":"dramsey@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":280919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":280916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bacon, Charles R. 0000-0002-2165-5618 cbacon@usgs.gov","orcid":"https://orcid.org/0000-0002-2165-5618","contributorId":2909,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"cbacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":280918,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinson, Joel E. 0000-0002-5193-3666 jrobins@usgs.gov","orcid":"https://orcid.org/0000-0002-5193-3666","contributorId":2757,"corporation":false,"usgs":true,"family":"Robinson","given":"Joel E.","email":"jrobins@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":280917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, James V.","contributorId":93035,"corporation":false,"usgs":true,"family":"Gardner","given":"James","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":280920,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":69662,"text":"i2788 - 2003 - Geologic map of the Big Delta B-2 quadrangle, east-central Alaska","interactions":[],"lastModifiedDate":"2018-10-22T11:31:43","indexId":"i2788","displayToPublicDate":"2003-10-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":320,"text":"IMAP","code":"I","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2788","title":"Geologic map of the Big Delta B-2 quadrangle, east-central Alaska","docAbstract":" New 1:63,360-scale geologic mapping of the Big Delta B-2 quadrangle provides important data on the structural setting and age of geologic units, as well as on the timing of gold mineralization plutonism within the Yukon-Tanana Upland of east-central Alaska. Gold exploration has remained active throughout the region in response to the discovery of the Pogo gold deposit, which lies within the northwestern part of the quadrangle near the south bank of the Goodpaster River. Geologic mapping and associated geochronological and geochemical studies by the U.S. Geological Survey (USGS) and the Alaska Department of Natural Resources, Division of Mining and Water Management, provide baseline data to help understand the regional geologic framework. Teck Cominco Limited geologists have provided the geologic mapping for the area that overlies the Pogo gold deposit as well as logistical support, which has lead to a much improved and informative product.\r\n The Yukon-Tanana Upland lies within the Tintina province in Alaska and consists of Paleozoic and possibly older(?) supracrustal rocks intruded by Paleozoic (Devonian to Mississippian) and Cretaceous plutons. The oldest rocks in the Big Delta B-2 quadrangle are Paleozoic gneisses of both plutonic and sedimentary origin. Paleozoic deformation, potentially associated with plutonism, was obscured by intense Mesozoic deformation and metamorphism. At least some of the rocks in the quadrangle underwent tectonism during the Middle Jurassic (about 188 Ma), and were subsequently deformed in an Early Cretaceous contractional event between about 130 and 116 Ma. New U-Pb SHRIMP data presented here on zircons from the Paleozoic biotite gneisses record inherited cores that range from 363 Ma to about 2,130 Ma and have rims of euhedral Early Cretaceous metamorphic overgrowths (116 +/- 4 Ma), interpreted to record recrystallization during Cretaceous west-northwest-directed thrusting and folding. U-Pb SHRIMP dating of monazite from a Paleozoic gneiss sample yields an age of 112 +/- 2 Ma; the monazite presumably grew during the waning stages of the intense regional Cretaceous ductile deformation. The Cretaceous ductile deformation was followed closely by granite plutonism and gold mineralization. The main pulse of gold mineralization is temporally and spatially associated with the Cretaceous granitic dikes and plutons and occurred during regional uplift and extension.","language":"ENGLISH","doi":"10.3133/i2788","isbn":"0607900695","usgsCitation":"Day, W.C., Aleinikoff, J.N., Roberts, P., Smith, M., Gamble, B.M., Henning, M.W., Gough, L.P., and Morath, L.C., 2003, Geologic map of the Big Delta B-2 quadrangle, east-central Alaska: U.S. Geological Survey IMAP 2788, 1 map : col. ; 44 x 39 cm., on sheet 84 x 99 cm., folded in envelope 30 x 24 cm., https://doi.org/10.3133/i2788.","productDescription":"1 map : col. ; 44 x 39 cm., on sheet 84 x 99 cm., folded in envelope 30 x 24 cm.","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":187456,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":110404,"rank":700,"type":{"id":15,"text":"Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_54573.htm","linkFileType":{"id":5,"text":"html"},"description":"54573"},{"id":6334,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/imap/2003/i-2788/","linkFileType":{"id":5,"text":"html"}}],"scale":"63360","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -145,64.25 ], [ -145,64.5 ], [ -144.5,64.5 ], [ -144.5,64.25 ], [ -145,64.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b0be4b07f02db69d972","contributors":{"authors":[{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":280829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":280830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Paul","contributorId":54300,"corporation":false,"usgs":true,"family":"Roberts","given":"Paul","email":"","affiliations":[],"preferred":false,"id":280833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Moira","contributorId":17313,"corporation":false,"usgs":true,"family":"Smith","given":"Moira","affiliations":[],"preferred":false,"id":280831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gamble, Bruce M. bgamble@usgs.gov","contributorId":560,"corporation":false,"usgs":true,"family":"Gamble","given":"Bruce","email":"bgamble@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":280827,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henning, Mitchell W.","contributorId":48641,"corporation":false,"usgs":true,"family":"Henning","given":"Mitchell","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":280832,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gough, Larry P. lgough@usgs.gov","contributorId":1230,"corporation":false,"usgs":true,"family":"Gough","given":"Larry","email":"lgough@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":280828,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morath, Laurie C.","contributorId":99225,"corporation":false,"usgs":true,"family":"Morath","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":280834,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70156743,"text":"70156743 - 2003 - The National Map: from geography to mapping and back again","interactions":[],"lastModifiedDate":"2015-08-27T11:21:03","indexId":"70156743","displayToPublicDate":"2003-10-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The National Map: from geography to mapping and back again","docAbstract":"When the means of production for national base mapping were capital intensive, required large production facilities, and had ill-defined markets, Federal Government mapping agencies were the primary providers of the spatial data needed for economic development, environmental management, and national defense. With desktop geographic information systems now ubiquitous, source data available as a commodity from private industry, and the realization that many complex problems faced by society need far more and different kinds of spatial data for their solutions, national mapping organizations must realign their business strategies to meet growing demand and anticipate the needs of a rapidly changing geographic information environment. The National Map of the United States builds on a sound historic foundation of describing and monitoring the land surface and adds a focused effort to produce improved understanding, modeling, and prediction of land-surface change. These added dimensions bring to bear a broader spectrum of geographic science to address extant and emerging issues. Within the overarching construct of The National Map, the U.S. Geological Survey (USGS) is making a transition from data collector to guarantor of national data completeness; from producing paper maps to supporting an online, seamless, integrated database; and from simply describing the Nation’s landscape to linking these descriptions with increased scientific understanding. Implementing the full spectrum of geographic science addresses a myriad of public policy issues, including land and natural resource management, recreation, urban growth, human health, and emergency planning, response, and recovery. Neither these issues nor the science and technologies needed to deal with them are static. A robust research agenda is needed to understand these changes and realize The National Map vision. Initial successes have been achieved. These accomplishments demonstrate the utility of The National Map to the Nation and give confidence in evolving its future applications.
","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.69.10.1109","usgsCitation":"Kelmelis, J.A., DeMulder, M.L., Ogrosky, C.E., Van Driel, J.N., and Ryan, B.J., 2003, The National Map: from geography to mapping and back again: Photogrammetric Engineering and Remote Sensing, v. 69, no. 10, p. 1109-1118, https://doi.org/10.14358/PERS.69.10.1109.","productDescription":"10 p.","startPage":"1109","endPage":"1118","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":478340,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.69.10.1109","text":"Publisher Index Page"},{"id":307613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e034c3e4b0f42e3d040e50","contributors":{"authors":[{"text":"Kelmelis, John A.","contributorId":40893,"corporation":false,"usgs":true,"family":"Kelmelis","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":570332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeMulder, Mark L. mdemulder@usgs.gov","contributorId":3748,"corporation":false,"usgs":true,"family":"DeMulder","given":"Mark","email":"mdemulder@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":570333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ogrosky, Charles E.","contributorId":28477,"corporation":false,"usgs":true,"family":"Ogrosky","given":"Charles","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":570334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Driel, J. Nicholas","contributorId":80688,"corporation":false,"usgs":true,"family":"Van Driel","given":"J.","email":"","middleInitial":"Nicholas","affiliations":[],"preferred":false,"id":570335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ryan, Barbara J.","contributorId":62989,"corporation":false,"usgs":true,"family":"Ryan","given":"Barbara","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":570336,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70125312,"text":"70125312 - 2003 - Introduction to physical properties and elasticity models","interactions":[],"lastModifiedDate":"2022-12-30T15:23:17.414054","indexId":"70125312","displayToPublicDate":"2003-09-16T09:23:00","publicationYear":"2003","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"20","title":"Introduction to physical properties and elasticity models","docAbstract":"Estimating the in situ methane hydrate volume from seismic surveys requires knowledge of the rock physics relations between wave speeds and elastic moduli in hydrate/sediment mixtures. The elastic moduli of hydrate/sediment mixtures depend on the elastic properties of the individual sedimentary particles and the manner in which they are arranged. In this chapter, we present some rock physics data currently available from literature. The unreferenced values in Table I were not measured directly, but were derived from other values in Tables I and II using standard relationships between elastic properties for homogeneous, isotropic material. These derivations allow us to extend the list of physical property estimates, but at the expense of introducing uncertainties due to combining property values measured under different physical conditions. This is most apparent in the case of structure II (sII) hydrate for which very few physical properties have been measured under identical conditions.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Natural gas hydrate in oceanic and permafrost environments","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-94-011-4387-5_20","usgsCitation":"Dvorkin, J., Helgerud, M.B., Waite, W., Kirby, S.H., and Nur, A., 2003, Introduction to physical properties and elasticity models, chap. 20 of Natural gas hydrate in oceanic and permafrost environments, v. 5, p. 245-260, https://doi.org/10.1007/978-94-011-4387-5_20.","productDescription":"16 p.","startPage":"245","endPage":"260","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":293892,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54195142e4b091c7ffc8e735","contributors":{"authors":[{"text":"Dvorkin, Jack","contributorId":51221,"corporation":false,"usgs":true,"family":"Dvorkin","given":"Jack","email":"","affiliations":[],"preferred":false,"id":501229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helgerud, Michael B.","contributorId":59361,"corporation":false,"usgs":true,"family":"Helgerud","given":"Michael","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":501230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":501226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirby, Stephen H. 0000-0003-1636-4688 skirby@usgs.gov","orcid":"https://orcid.org/0000-0003-1636-4688","contributorId":2752,"corporation":false,"usgs":true,"family":"Kirby","given":"Stephen","email":"skirby@usgs.gov","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":501227,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nur, Amos","contributorId":34444,"corporation":false,"usgs":true,"family":"Nur","given":"Amos","email":"","affiliations":[],"preferred":false,"id":501228,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159930,"text":"70159930 - 2003 - Reproductive maturation and senescence in the female brown bear","interactions":[],"lastModifiedDate":"2021-02-08T16:38:28.751633","indexId":"70159930","displayToPublicDate":"2003-09-07T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3671,"text":"Ursus","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive maturation and senescence in the female brown bear","docAbstract":"Changes in age-specific reproductive rates can have important implications for managing populations, but the number of female brown (grizzly) bears (Ursus arctos) observed in any one study is usually inadequate to quantify such patterns, especially for older females and in hunted areas. We examined patterns of reproductive maturation and senescence in female brown bears by combining data from 20 study areas from Sweden, Alaska, Canada, and the continental United States. We assessed reproductive performance based on 4,726 radiocollared years for free-ranging female brown bears (age ≥3); 482 of these were for bears ≥20 years of age. We modeled age-specific probability of litter production using extreme value distributions to describe probabilities for young- and old-age classes, and a power distribution function to describe probabilities for prime-aged animals. We then fit 4 models to pooled observations from our 20 study areas. We used Akaike's Information Criterion (AIC) to select the best model. Inflection points suggest that major shifts in litter production occur at 4-5 and 28-29 years of age. The estimated model asymptote (0.332, 95% CI = 0.319-0.344) was consistent with the expected reproductive cycle of a cub litter every 3 years (0.333). We discuss assumptions and biases in data collection relative to the shape of the model curve. Our results conform to senescence theory and suggest that female age structure in contemporary brown bear populations is considerably younger than would be expected in the absence of modern man. This implies that selective pressures today differ from those that influenced brown bear evolution.
","language":"English","publisher":"International Association for Bear Research & Management","usgsCitation":"Schwartz, C.C., Keating, K.A., Reynolds III, H., Barnes, V.G., Sellers, R.A., Swenson, J.E., Miller, S.D., McLellan, B.N., Keay, J.A., McCann, R., Gibeau, M., Wakkinen, W.F., Mace, R.D., Kasworm, W., Smith, R., and Herrero, S., 2003, Reproductive maturation and senescence in the female brown bear: Ursus, v. 14, no. 2, p. 109-119.","productDescription":"11 p.","startPage":"109","endPage":"119","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":311890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383098,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.jstor.org/stable/3873012"}],"country":"Canada, Sweden, United States","volume":"14","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566175e0e4b06a3ea36c56e6","contributors":{"authors":[{"text":"Schwartz, Charles C.","contributorId":124574,"corporation":false,"usgs":false,"family":"Schwartz","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":5119,"text":"Retired from U.S. Geological Survey, Interagency Grizzly Bear Study Team, Northern Rocky Mountain Science Center, 2327 University Way, suite 2, Bozeman, MT 59715","active":true,"usgs":false}],"preferred":false,"id":581120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keating, Kim A.","contributorId":44660,"corporation":false,"usgs":true,"family":"Keating","given":"Kim","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":581121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds III, Harry V.","contributorId":150230,"corporation":false,"usgs":false,"family":"Reynolds III","given":"Harry V.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":581122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnes, Victor G. Jr.","contributorId":95113,"corporation":false,"usgs":true,"family":"Barnes","given":"Victor","suffix":"Jr.","email":"","middleInitial":"G.","affiliations":[{"id":35655,"text":"Kodiak Brown Bear Trust, Westcliffe, CO","active":true,"usgs":false}],"preferred":false,"id":581123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sellers, Richard A.","contributorId":150231,"corporation":false,"usgs":false,"family":"Sellers","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":581124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Swenson, J. E.","contributorId":45518,"corporation":false,"usgs":false,"family":"Swenson","given":"J.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":581125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Sterling D.","contributorId":7205,"corporation":false,"usgs":true,"family":"Miller","given":"Sterling","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":581126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McLellan, B. N.","contributorId":82929,"corporation":false,"usgs":false,"family":"McLellan","given":"B.","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":581127,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Keay, Jeffrey A. jkeay@usgs.gov","contributorId":331,"corporation":false,"usgs":true,"family":"Keay","given":"Jeffrey","email":"jkeay@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":581128,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCann, Robert","contributorId":150232,"corporation":false,"usgs":false,"family":"McCann","given":"Robert","email":"","affiliations":[],"preferred":false,"id":581129,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gibeau, Michael","contributorId":150233,"corporation":false,"usgs":false,"family":"Gibeau","given":"Michael","email":"","affiliations":[{"id":6658,"text":"Parks Canada","active":true,"usgs":false}],"preferred":false,"id":581130,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wakkinen, Wayne F.","contributorId":150234,"corporation":false,"usgs":false,"family":"Wakkinen","given":"Wayne","email":"","middleInitial":"F.","affiliations":[{"id":16279,"text":"Idaho Department of Fish & Game","active":true,"usgs":false}],"preferred":false,"id":581131,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mace, Richard D.","contributorId":150235,"corporation":false,"usgs":false,"family":"Mace","given":"Richard","email":"","middleInitial":"D.","affiliations":[{"id":5099,"text":"Montana Department of Fish, Wildlife, and Parks","active":true,"usgs":false}],"preferred":false,"id":581132,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Kasworm, Wayne","contributorId":150237,"corporation":false,"usgs":false,"family":"Kasworm","given":"Wayne","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":581133,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Smith, Rodger","contributorId":150238,"corporation":false,"usgs":false,"family":"Smith","given":"Rodger","email":"","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":581134,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Herrero, Steven","contributorId":150239,"corporation":false,"usgs":false,"family":"Herrero","given":"Steven","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":581135,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70156746,"text":"70156746 - 2003 - Carbon dynamics and land-use choices: building a regional-scale multidisciplinary model","interactions":[],"lastModifiedDate":"2015-08-27T11:33:47","indexId":"70156746","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Carbon dynamics and land-use choices: building a regional-scale multidisciplinary model","docAbstract":"Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over 50 years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.
","language":"English","publisher":"Elsevier","doi":"10.1016/S0301-4797(03)00106-3","usgsCitation":"Kerr, S., Liu, S., Pfaff, A.S., and Hughes, R., 2003, Carbon dynamics and land-use choices: building a regional-scale multidisciplinary model: Journal of Environmental Management, v. 69, no. 1, p. 25-37, https://doi.org/10.1016/S0301-4797(03)00106-3.","productDescription":"13 p.","startPage":"25","endPage":"37","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":478342,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://ageconsearch.umn.edu/record/293008","text":"External Repository"},{"id":307615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e034b2e4b0f42e3d040df2","contributors":{"authors":[{"text":"Kerr, Suzi","contributorId":147107,"corporation":false,"usgs":false,"family":"Kerr","given":"Suzi","email":"","affiliations":[],"preferred":false,"id":570347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":570348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pfaff, Alexander S.P.","contributorId":77492,"corporation":false,"usgs":true,"family":"Pfaff","given":"Alexander","email":"","middleInitial":"S.P.","affiliations":[],"preferred":false,"id":570349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, R. Flint","contributorId":111314,"corporation":false,"usgs":true,"family":"Hughes","given":"R. Flint","affiliations":[],"preferred":false,"id":570350,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156737,"text":"70156737 - 2003 - Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices","interactions":[],"lastModifiedDate":"2015-08-27T10:54:10","indexId":"70156737","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices","docAbstract":"The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.
","language":"English","publisher":"Elsevier","doi":"10.1016/S0034-4257(03)00174-3","usgsCitation":"Ji, L., and Peters, A.J., 2003, Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices: Remote Sensing of Environment, v. 87, no. 1, p. 85-98, https://doi.org/10.1016/S0034-4257(03)00174-3.","productDescription":"14 p.","startPage":"85","endPage":"98","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e034b2e4b0f42e3d040dee","contributors":{"authors":[{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":139587,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":570316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peters, Albert J.","contributorId":92517,"corporation":false,"usgs":true,"family":"Peters","given":"Albert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":570317,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159451,"text":"70159451 - 2003 - Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data","interactions":[],"lastModifiedDate":"2015-10-30T10:17:19","indexId":"70159451","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data","docAbstract":"We developed a Sub-pixel Imperviousness Change Detection (SICD) approach to detect urban land-cover changes using Landsat and high-resolution imagery. The sub-pixel percent imperviousness was mapped for two dates (09 March 1993 and 11 March 2001) over western Georgia using a regression tree algorithm. The accuracy of the predicted imperviousness was reasonable based on a comparison using independent reference data. The average absolute error between predicted and reference data was 16.4 percent for 1993 and 15.3 percent for 2001. The correlation coefficient (r) was 0.73 for 1993 and 0.78 for 2001, respectively. Areas with a significant increase (greater than 20 percent) in impervious surface from 1993 to 2001 were mostly related to known land-cover/land-use changes that occurred in this area, suggesting that the spatial change of an impervious surface is a useful indicator for identifying spatial extent, intensity, and, potentially, type of urban land-cover/land-use changes. Compared to other pixel-based change-detection methods (band differencing, rationing, change vector, post-classification), information on changes in sub-pixel percent imperviousness allow users to quantify and interpret urban land-cover/land-use changes based on their own definition. Such information is considered complementary to products generated using other change-detection methods. In addition, the procedure for mapping imperviousness is objective and repeatable, hence, can be used for monitoring urban land-cover/land-use change over a large geographic area. Potential applications and limitations of the products developed through this study in urban environmental studies are also discussed.
","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.69.9.1003","usgsCitation":"Yang, L., Xian, G.Z., Klaver, J.M., and Deal, B., 2003, Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data: Photogrammetric Engineering and Remote Sensing, v. 69, no. 9, p. 1003-1010, https://doi.org/10.14358/PERS.69.9.1003.","productDescription":"8 p.","startPage":"1003","endPage":"1010","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":478346,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.69.9.1003","text":"Publisher Index Page"},{"id":310794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563496bfe4b048076348009b","contributors":{"authors":[{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":578754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":578755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Jacqueline M.","contributorId":25423,"corporation":false,"usgs":true,"family":"Klaver","given":"Jacqueline","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":578756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deal, Brian","contributorId":149537,"corporation":false,"usgs":false,"family":"Deal","given":"Brian","email":"","affiliations":[],"preferred":false,"id":578757,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":69716,"text":"mf2420 - 2003 - Maps and data from a trench investigation of the Utsalady Point Fault, Whidbey Island, Washington","interactions":[],"lastModifiedDate":"2018-08-21T16:21:54","indexId":"mf2420","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":325,"text":"Miscellaneous Field Studies Map","code":"MF","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2420","title":"Maps and data from a trench investigation of the Utsalady Point Fault, Whidbey Island, Washington","docAbstract":"No abstract available.
More than 33,000 salmon and steelhead died in the lower Klamath River in late September 2002 on their way to spawning areas upstream. According to the California Department of Fish and Game, the cause of death was infection by protozoan and bacterial pathogens. Two factors that may have contributed to the disease incidence are low streamflow and high water temperature.
\nSeptember streamflows throughout the Klamath Basin were low, among the four lowest September flows recorded on the main stem since 1960. The low streamflows were caused by below-average snowpack and long-term drought, with resulting reduced ground-water discharge to streams.
\nOn the basis of historical climate data from the Klamath Basin and historical water temperature data from an adjacent basin, September 2002 water temperatures were above the long-term average. Temperatures in the Klamath River above the fish die-off reach exceeded 65 degrees Fahrenheit for nearly all of September; multiple days of exposure by fish to temperatures at or above that level can greatly increase disease incidence.
\nThis report characterizes streamflow and water temperature conditions during the period leading up to the die-off and compares them to historical conditions in the Klamath River. This report is not an exploration of the causative mechanism of the die-off; rather, it is intended to provide detailed documentation of these conditions to be used by those examining the cause(s) of the die-off and to provide information that can contribute to decisions about future water management in the Klamath Basin.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri034099","usgsCitation":"Lynch, D.D. and Risley, J.C., 2003, Klamath River Basin hydrologic conditions prior to the September 2002\ndie-off of salmon and steelhead: U.S. Geological Survey Water-Resources Investigations Report 03–4099, 10 p.","productDescription":"17 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":161564,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":4069,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wri/2003/4099/wri03-4099.pdf","text":"Report","size":"880 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PDF of report"}],"contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
The Christina River Basin drains 565 square miles (mi2) in Pennsylvania, Maryland, and Delaware. Water from the basin is used for recreation, drinking water supply, and to support aquatic life. The Christina River Basin includes the major subbasins of Brandywine Creek, White Clay Creek, and Red Clay Creek. The White Clay Creek is the second largest of the subbasins and drains an area of 108 mi2. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the streams. A multi-agency water-quality management strategy included a modeling component to evaluate the effects of point and nonpoint-source contributions of nutrients and suspended sediment on stream water quality. To assist in non point-source evaluation, four independent models, one for each of the three major subbasins and for the Christina River, were developed and calibrated using the model code Hydrological Simulation Program—Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in smaller subbasins predominantly covered by one land use following a nonpoint-source monitoring plan. Under this plan, stormflow and base- flow samples were collected during 1998 at two sites in the White Clay Creek subbasin and at nine sites in the other subbasins.
The HSPF model for the White Clay Creek Basin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into 17 reaches draining areas that ranged from 1.37 to 13 mi2. Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the White Clay Creek Basin are agricultural, forested, residential, and urban.
The hydrologic component of the model was run at an hourly time step and primarily calibrated using streamflow data from two U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Additional calibration was done using data from two other USGS streamflow-measurement stations with periods of record shorter than the calibration period. Daily precipitation data from two National Oceanic and Atmospheric Administration (NOAA) gages and hourly precipitation and other meteorological data for one NOAA gage were used for model input. The difference between simulated and observed streamflow volume ranged from -0.9 to 1.8 percent for the 4-year period at the two calibration sites with 4-year records. Annual differences between observed and simulated streamflow generally were greater than the overall error. For example, at a site near the bottom of the basin (drainage area of 89.1 mi2), annual differences between observed and simulated streamflow ranged from -5.8 to 14.4 percent and the overall error for the 4-year period was -0.9 percent. Calibration errors for 36 storm periods at the two calibration sites for total volume, low-flowrecession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were within the recommended criteria of 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the hourly rainfall data.
The water-quality component of the model was calibrated using data collected by the USGS and state agencies at three USGS streamflow-measurement stations with variable water-quality monitoring periods ending October 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspended-sediment concentrations, although suspended solids may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulation. Comparison of observed to simulated loads for up to five storms in 1998 at each of the two nonpoint-source monitoring sites in the White Clay Creek Basin indicate that simulation error is commonly as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved nutrients than for particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria, with much larger errors possible for individual events. The accuracy of the water-quality calibration under stormflow conditions is limited by the relatively small amount of water-quality data available for the White Clay Creek Basin.
Users of the White Clay Creek HSPF model should be aware of model limitations and consider the following if the model is used for predictive purposes: streamflow and water quality for individual storm events may not be well simulated, but the model performance is reasonable when evaluated over longer periods of time; the observed flow-duration curve for the simulation period is similar to the long-term flow-duration curve at White Clay Creek near Newark, Del., indicating that the calibration period is representative of all but highest 0.1 percent and lowest 0.1 percent of flows at that site; relative errors in streamflow and water-quality simulations are greater for smaller drainage areas than for larger areas; and calibration for water-quality was based on sparse data.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri034031","collaboration":"Prepared in cooperation with the Delaware River Basin Commission, Delaware Department of Natural Resources and Environmental Control, and the Pennsylvania Department of Environmental Protection","usgsCitation":"Senior, L.A., and Koerkle, E.H., 2003, Simulation of streamflow and water quality in the White Clay Creek subbasin of the Christina River Basin, Pennsylvania and Delaware, 1994-98: U.S. Geological Survey Water-Resources Investigations Report 2003-4031, x, 142 p., https://doi.org/10.3133/wri034031.","productDescription":"x, 142 p.","onlineOnly":"Y","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":179191,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/wri/2003/4031/coverthb.jpg"},{"id":4538,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wri/2003/4031/wri20034031.pdf","text":"Report","size":"2.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"WRI 2003-4031"}],"contact":"Director, Pennsylvania Water Science Center U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Sediment cores were extracted from three lakes in northeastern New Jersey and one lake on western Long Island, New York, as part of the U.S. Geological Survey National Water-Quality Assessment Program. Sediment layers were dated by use of cesium-137 (137Cs), copper, lead, or dichlorodiphenyl-trichloroethane (DDT) profiles. Sediment layers were analyzed for seven selected trace elements, including arsenic, cadmium, chromium, lead, mercury, nickel, and zinc, and five hydrophobic organochlorine compounds, including chlordane, dieldrin, total DDT, total polychlorinated biphenyls (PCBs), and total polycyclic aromatic hydrocarbons (PAHs).
\nAll seven trace elements were detected throughout the cores from all four lakes. Concentrations of all elements, except arsenic, were elevated in the three cores from lakes within urbanized watersheds (Packanack Lake, Orange Reservoir, and Newbridge Pond) relative to the concentrations in the lake core collected below the largely forested, reference watershed (Clyde Potts Reservoir). Results of trend analyses indicate that concentrations of all trace elements, with the exception of arsenic and lead, were relatively constant throughout the core from the minimally urbanized Clyde Potts Reservoir. In urban lakes, significant upward trends in concentrations from deeper to shallower sediments were observed either to peak concentrations or throughout the core for all elements, with the exception of chromium at all lakes and arsenic and nickel at Orange Reservoir. This finding indicates that changes in population and land use in the urbanized watersheds over the period of sedimentary record have contributed to upward trends in trace-element concentrations. Although downward trends in concentrations were observed for some trace elements in the years after their concentrations peaked, concentrations of all trace elements in urban lake cores were higher in the most recently deposited sediments than at the base of each respective core.
\nLead concentrations over time were highly correlated with the population in the vicinity of the lake until the concentration peak in sediment deposited in the mid-1970’s. Concentrations of lead in lake sediment appear to be closely related to the use of leaded gasoline because lead concentrations generally decreased after the use of leaded gasoline was phased-out in the mid-1970’s. Zinc concentrations were highly correlated with population over the entire length of the core. In general, zinc concentrations increased in the three urbanized watersheds, probably in response to increasing population and vehicular use. This trend was not evident at Clyde Potts Reservoir, however, where vehicular traffic in the watershed is minimal.
\nDetectable concentrations of chlordane, total DDT, and total PCBs were present in cores from all lakes; however, dieldrin was detected only in the Newbridge Pond and Packanack Lake cores. Concentrations generally were higher in cores from the urbanized Newbridge Pond and Orange Reservoir watersheds than in those from the minimally urbanized Clyde Potts Reservoir watershed. With the exception of chlordane in the Clyde Potts and Orange Reservoir cores, concentrations of the four organochlorine compounds had significant downward trends from peak concentrations to recently deposited sediment or non-significant trends throughout the core. On the basis of these findings and as a result of regulatory actions prohibiting the production and use of these compounds, downward trends in sedimentary concentrations are expected to continue; however, the persistence of these compounds indicates that a substantial amount of time may be required to purge them from the watersheds.
\nConcentrations of PAHs in sediment generally increased with population growth and urbanization, probably as a result of increased fossil-fuel combustion (gasoline and home-heating fuels and other uses (roads and parking lots paved with asphalt) associated with increased urban development and vehicular traffic. This finding is supported by low concentrations of PAHs in Packanack Lake sediments in the 1930’s, before the watershed was urbanized and when automobiles were comparatively rare. As vehicular use and urbanization increase in these watersheds, the general increase of PAH concentrations in lake sediments can be expected to continue.
\nData from this study indicate that changes in population, land use, and chemical use in the urbanized watersheds over the period of sedimentary record have contributed to upward trends in concentrations of trace elements and hydrophobic organic compounds. Although downward trends were observed for some constituents in the years after their concentrations peaked, concentrations of most constituents in urban lake cores were higher in the most recently deposited sediments than at the base of each respective core and in the reference lake cores. Similar trends in concentrations of these constituents have been observed in sediment cores from other urban lakes across the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"West Trenton, NJ","doi":"10.3133/wri024272","usgsCitation":"Long, G.R., Callender, E.C., Ayers, M.A., and Van Metre, P., 2003, Trends in chemical concentration in sediment cores from three lakes in New Jersey and one lake on Long Island, New York: U.S. Geological Survey Water-Resources Investigations Report 2002-4272, vi, 23 p., https://doi.org/10.3133/wri024272.","productDescription":"vi, 23 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":178580,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/wri024272.PNG"},{"id":4618,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wri/2002/4272/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"New Jersey, New York","otherGeospatial":"Clyde Potts Reservoir, Long Island, Newbridge Pond, Orange Reservoir, Packanack Lake,","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4ce4b07f02db6265c1","contributors":{"authors":[{"text":"Long, Gary R.","contributorId":77190,"corporation":false,"usgs":true,"family":"Long","given":"Gary","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":242438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Callender, Edward C.","contributorId":40208,"corporation":false,"usgs":true,"family":"Callender","given":"Edward","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":749475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ayers, Mark A.","contributorId":84730,"corporation":false,"usgs":true,"family":"Ayers","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":242439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":197363,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":false,"id":749474,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":50992,"text":"fs05903 - 2003 - Collecting peak-flow data in Ohio through the use of crest-stage gages","interactions":[],"lastModifiedDate":"2012-02-02T00:11:22","indexId":"fs05903","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"059-03","title":"Collecting peak-flow data in Ohio through the use of crest-stage gages","language":"ENGLISH","doi":"10.3133/fs05903","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2003, Collecting peak-flow data in Ohio through the use of crest-stage gages: U.S. Geological Survey Fact Sheet 059-03, 1 sheet ([2] p.) : col. ill., col. map ; 28 cm., https://doi.org/10.3133/fs05903.","productDescription":"1 sheet ([2] p.) : col. ill., col. map ; 28 cm.","costCenters":[],"links":[{"id":120588,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2003/0059/report-thumb.jpg"},{"id":86421,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2003/0059/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae90a","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":532097,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":51412,"text":"ofr03217 - 2003 - Reconnaissance data for glyphosate, other selected herbicides, their degradation products, and antibiotics in 51 streams in nine midwestern states, 2002","interactions":[],"lastModifiedDate":"2020-02-12T06:25:02","indexId":"ofr03217","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","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":"2003-217","title":"Reconnaissance data for glyphosate, other selected herbicides, their degradation products, and antibiotics in 51 streams in nine midwestern states, 2002","docAbstract":"Since 1989, the U.S. Geological Survey has conducted periodic reconnaissance studies of streams in the Midwestern United States to determine the geographic and seasonal distribution of herbicide compounds. These studies have documented that large amounts of acetochlor, alachlor, atrazine, cyanazine, metolachlor, and their degradation products are flushed into streams during post-application runoff. Additional studies show that peak herbicide concentrations tend to occur during the first runoff after herbicide application and that herbicide flushes can occur during runoff for several weeks to months following application.\r\nSince the first stream study conducted in 1989, several significant changes in herbicide use have occurred. The most substantial change is the tripling in the use of glyphosate during the past 5 years. Over this same time period (1997-2001), usage of acetochlor and atrazine increased slightly, whereas alachlor, cyanazine, and metolachlor usage decreased. \r\n\r\nDuring 2002, 154 samples were collected from 51 streams in nine Midwestern States during three periods of runoff. This report provides a compilation of the analytical results of five laboratory methods. Results show that glyphosate was detected in 55 (36 percent) of the samples, and aminomethylphosphonic acid (a degradation product of glyphosate) was detected in 107 (69 percent) of the samples. Atrazine, the most frequently detected herbicide, was found in 93 percent of the samples, followed by metolachlor, found in 73 percent of the samples; metolachlor ethanesulfonic acid (ESA) and oxanilic acid (OXA) were the most frequently detected herbicide degradation products, both being found in more than 95 percent of the samples. The data presented here are valuable for comparison with results from the earlier reconnaissance studies.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr03217","usgsCitation":"Scribner, E.A., Battaglin, W.A., Dietze, J.E., and Thurman, E., 2003, Reconnaissance data for glyphosate, other selected herbicides, their degradation products, and antibiotics in 51 streams in nine midwestern states, 2002: U.S. Geological Survey Open-File Report 2003-217, vi, 101 p. , https://doi.org/10.3133/ofr03217.","productDescription":"vi, 101 p. ","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":86543,"rank":298,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2003/0217/report.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":179589,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2003/0217/report-thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin, Iowa, Illinois, Indiana, Ohio, Michigan, Missouri, Nebraska, Kansas","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-87.800477,42.49192],[-87.812461,42.232278],[-87.511043,41.696535],[-87.187651,41.629653],[-86.616978,41.896625],[-86.321803,42.310743],[-86.208309,42.762789],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.291346,45.062597],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.833103,44.036851],[-82.643166,43.852468],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-82.481214,41.381342],[-81.69325,41.514161],[-80.533774,41.973475],[-80.518991,40.638801],[-80.667957,40.582496],[-80.619297,40.26517],[-80.88036,39.620706],[-81.656138,39.277355],[-81.874857,38.881174],[-82.068864,38.984878],[-82.318111,38.457876],[-82.569368,38.406258],[-82.923694,38.750076],[-83.301951,38.598178],[-83.512571,38.701716],[-83.762445,38.652103],[-84.212904,38.805707],[-84.445242,39.114461],[-84.744149,39.147458],[-84.888873,39.066376],[-84.816506,38.80532],[-85.448862,38.713368],[-85.415272,38.555416],[-85.816164,38.282969],[-86.042354,37.958018],[-86.33281,38.182938],[-86.634271,37.843845],[-86.810913,37.99715],[-87.065388,37.810481],[-87.402632,37.942267],[-87.666522,37.827455],[-87.921744,37.907885],[-88.158374,37.639948],[-88.063311,37.515755],[-88.450127,37.411717],[-88.490068,37.067874],[-89.058036,37.188767],[-89.171881,37.068184],[-89.202607,36.601576],[-89.343753,36.630991],[-89.429311,36.481875],[-89.55264,36.577178],[-89.527029,36.341679],[-89.703511,36.243412],[-89.615128,36.113816],[-89.733095,36.000608],[-90.368718,35.995812],[-90.075934,36.281485],[-90.157136,36.484317],[-94.617919,36.499414],[-94.699735,36.998805],[-102.000447,36.993249],[-102.051614,41.002377],[-104.039238,41.001502],[-104.053177,41.089725],[-104.053127,43.000585],[-98.568936,42.998537],[-98.042011,42.767316],[-97.834172,42.868794],[-97.256752,42.853913],[-96.489497,42.480112],[-96.628741,42.757532],[-96.448134,43.104452],[-96.598396,43.495074],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.878454,49.333193],[-94.640803,48.741171],[-93.818375,48.534442],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.86827,47.5569],[-92.058888,46.809938],[-91.942988,46.679939],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.398478,46.575832],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192]]],[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Iowa\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a74e4b07f02db644439","contributors":{"authors":[{"text":"Scribner, Elisabeth A.","contributorId":80265,"corporation":false,"usgs":true,"family":"Scribner","given":"Elisabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":243500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":243498,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietze, Julie E. 0000-0002-5936-5739 juliec@usgs.gov","orcid":"https://orcid.org/0000-0002-5936-5739","contributorId":3939,"corporation":false,"usgs":true,"family":"Dietze","given":"Julie","email":"juliec@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":243499,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, E.M.","contributorId":102864,"corporation":false,"usgs":true,"family":"Thurman","given":"E.M.","affiliations":[],"preferred":false,"id":243501,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":50887,"text":"wri034086 - 2003 - Changes in streamflow and summary of major-ion chemistry and loads in the North Fork Red River basin upstream from Lake Altus, northwestern Texas and western Oklahoma, 1945-1999","interactions":[],"lastModifiedDate":"2017-06-14T16:42:36","indexId":"wri034086","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4086","title":"Changes in streamflow and summary of major-ion chemistry and loads in the North Fork Red River basin upstream from Lake Altus, northwestern Texas and western Oklahoma, 1945-1999","docAbstract":"Upstream from Lake Altus, the North Fork Red River drains an area of 2,515 square miles. The quantity and quality of surface water are major concerns at Lake Altus, and water-resource managers and consumers need historical information to make informed decisions about future development. The Lugert-Altus Irrigation District relies on withdrawals from the lake to sustain nearly 46,000 acres of agricultural land.
Kendall's tau tests of precipitation data indicated no statistically significant trend over the entire 100 years of available record. However, a significant increase in precipitation occurred in the last 51 years. Four streamflow-gaging stations with more than 10 years of record were maintained in the basin. These stations recorded no significant trends in annual streamflow volume. Two stations, however, had significant increasing trends in the base-flow index, and three had significant decreasing trends in annual peak flows.
Major-ion chemistry in the North Fork Red River is closely related to the chemical composition of the underlying bedrock. Two main lithologies are represented in the basin upstream from Lake Altus. In the upper reaches, young and poorly consolidated sediments include a range of sizes from coarse gravel to silt and clay. Nearsurface horizons commonly are cemented as calcium carbonate caliche. Finer-grained gypsiferous sandstones and shales dominate the lower reaches of the basin. A distinct increase in dissolved solids, specifically sodium, chloride, calcium, and sulfate, occurs as the river flows over rocks that contain substantial quantities of gypsum, anhydrite, and dolomite. These natural salts are the major dissolved constituents in the North Fork Red River.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri034086","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Smith, S.J., and Wahl, K.L., 2003, Changes in streamflow and summary of major-ion chemistry and loads in the North Fork Red River basin upstream from Lake Altus, northwestern Texas and western Oklahoma, 1945-1999: U.S. Geological Survey Water-Resources Investigations Report 2003-4086, vi, 36 p., https://doi.org/10.3133/wri034086.","productDescription":"vi, 36 p.","costCenters":[],"links":[{"id":175474,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":342521,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wri/wri034086/pdf/wri034086.pdf","text":"Report","size":"4.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":4652,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri034086/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oklahoma, Texas","otherGeospatial":"North Fork Red River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.01904296874999,\n 35.47856499535729\n ],\n [\n -102.0245361328125,\n 35.24561909420681\n ],\n [\n -101.9915771484375,\n 35.17380831799959\n ],\n [\n -101.568603515625,\n 35.15135442846945\n ],\n [\n -100.5853271484375,\n 35.14237113713991\n ],\n [\n -100.3106689453125,\n 35.106428057364255\n ],\n [\n -100.074462890625,\n 35.0254981588326\n ],\n [\n -99.88220214843749,\n 34.939985151560435\n ],\n [\n -99.5965576171875,\n 34.863397850419524\n ],\n [\n -99.3438720703125,\n 34.827332061981586\n ],\n [\n -99.0472412109375,\n 34.88142481679756\n ],\n [\n -98.975830078125,\n 35.003003395276714\n ],\n [\n -98.997802734375,\n 35.21869749632885\n ],\n [\n -99.11865234374999,\n 35.37561413174875\n ],\n [\n -99.2724609375,\n 35.53222622770337\n ],\n [\n -99.755859375,\n 35.75097043944926\n ],\n [\n -100.74462890625,\n 35.94688293218141\n ],\n [\n -101.0137939453125,\n 35.88014896488361\n ],\n [\n -101.546630859375,\n 35.67514743608467\n ],\n [\n -102.01904296874999,\n 35.47856499535729\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e5e4b07f02db5e6c61","contributors":{"authors":[{"text":"Smith, S. Jerrod 0000-0002-9379-8167 sjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9379-8167","contributorId":981,"corporation":false,"usgs":true,"family":"Smith","given":"S.","email":"sjsmith@usgs.gov","middleInitial":"Jerrod","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":242553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wahl, Kenneth L.","contributorId":61024,"corporation":false,"usgs":true,"family":"Wahl","given":"Kenneth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":242554,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":51976,"text":"wri034030 - 2003 - Simulation of streamflow and estimation of streamflow constituent loads in the San Antonio River watershed, Bexar County, Texas, 1997-2001","interactions":[],"lastModifiedDate":"2017-02-15T11:11:46","indexId":"wri034030","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4030","title":"Simulation of streamflow and estimation of streamflow constituent loads in the San Antonio River watershed, Bexar County, Texas, 1997-2001","docAbstract":"The U.S. Geological Survey developed watershed models (Hydrological Simulation Program—FORTRAN) to simulate streamflow and estimate streamflow constituent loads from five basins that compose the San Antonio River watershed in Bexar County, Texas. Rainfall and streamflow data collected during 1997–2001 were used to calibrate and test the model. The model was configured so that runoff from various land uses and discharges from other sources (such as wastewater recycling facilities) could be accounted for to indicate sources of streamflow. Simulated streamflow volumes were used with land-use-specific, water-quality data to compute streamflow loads of selected constituents from the various streamflow sources.
Model simulations for 1997–2001 indicate that inflow from the upper Medina River (originating outside Bexar County) represents about 22 percent of total streamflow. Recycled wastewater discharges account for about 20 percent and base flow (ground-water inflow to streams) about 18 percent. Storm runoff from various land uses represents about 33 percent.
Estimates of sources of streamflow constituent loads indicate recycled wastewater as the largest source of dissolved solids and nitrate plus nitrite nitrogen (about 38 and 66 percent, respectively, of the total loads) during 1997–2001. Stormwater runoff from urban land produced about 49 percent of the 1997–2001 total suspended solids load. Stormwater runoff from residential and commercial land (about 23 percent of the land area) produced about 70 percent of the total lead streamflow load during 1997–2001.
","language":"English","publisher":"U.S. Geological Survey ","doi":"10.3133/wri034030","collaboration":"In cooperation with the San Antonio Water System ","usgsCitation":"Ockerman, D.J., and McNamara, K.C., 2003, Simulation of streamflow and estimation of streamflow constituent loads in the San Antonio River watershed, Bexar County, Texas, 1997-2001: U.S. Geological Survey Water-Resources Investigations Report 2003-4030, HTML Document; Report: iv, 37 p., https://doi.org/10.3133/wri034030.","productDescription":"HTML Document; Report: iv, 37 p.","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":4534,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri03-4030/","linkFileType":{"id":5,"text":"html"}},{"id":178769,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":335481,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wri/wri03-4030/pdf/wri03-4030.pdf","text":"Report","size":"19.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Texas","county":"Bexar County","otherGeospatial":"San Antonio River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.50616455078125,\n 29.739339757443286\n ],\n [\n -98.58993530273438,\n 29.736954896290666\n ],\n [\n -98.72451782226562,\n 29.71548859443817\n ],\n [\n -98.778076171875,\n 29.67015577117534\n ],\n [\n -98.82476806640625,\n 29.621221113784504\n ],\n [\n -98.865966796875,\n 29.554345125748267\n ],\n [\n -98.88656616210938,\n 29.434813598289637\n ],\n [\n -98.87969970703125,\n 29.388158098102554\n ],\n [\n -98.86184692382812,\n 29.334298230315675\n ],\n [\n -98.83438110351562,\n 29.26124274448168\n ],\n [\n -98.77944946289062,\n 29.216904948184734\n ],\n [\n -98.734130859375,\n 29.178543264303006\n ],\n [\n -98.64349365234374,\n 29.156958511360703\n ],\n [\n -98.5693359375,\n 29.159357041355424\n ],\n [\n -98.46084594726562,\n 29.185737173254434\n ],\n [\n -98.36196899414061,\n 29.204918463909035\n ],\n [\n -98.31939697265625,\n 29.263638834879824\n ],\n [\n -98.28231811523438,\n 29.3642238956322\n ],\n [\n -98.3056640625,\n 29.44438130948883\n ],\n [\n -98.2891845703125,\n 29.534034720259523\n ],\n [\n -98.34686279296874,\n 29.62360872200976\n ],\n [\n -98.3990478515625,\n 29.682087444299334\n ],\n [\n -98.45947265625,\n 29.71071768156533\n ],\n [\n -98.50616455078125,\n 29.739339757443286\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db699e32","contributors":{"authors":[{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":244591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNamara, Kenna C.","contributorId":51841,"corporation":false,"usgs":true,"family":"McNamara","given":"Kenna","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":244592,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":52708,"text":"wri034154 - 2003 - Numerical simulation of ground-water flow in La Crosse County, Wisconsin, and into nearby pools of the Mississippi River","interactions":[],"lastModifiedDate":"2015-11-13T12:36:43","indexId":"wri034154","displayToPublicDate":"2003-09-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4154","title":"Numerical simulation of ground-water flow in La Crosse County, Wisconsin, and into nearby pools of the Mississippi River","docAbstract":"This report describes a two-dimensional regional screening model and two associated three-dimensional ground-water flow models that were developed to simulate the ground-water flow systems in La Crosse County, Wisconsin, and Pool 8 of the Mississippi River. Although the geographic extents of the three-dimensional models were slightly different, both were derived from the same geologic interpretation and regional screening model, and their calibrations were performed concurrently. The objectives of the La Crosse County (LCC) model were to assess the effects of recent (1990s) and potential future ground-water withdrawals and to provide a tool suitable to evaluate the effects of proposed water-management programs. The Pool 8 model objectives were to quantify the magnitude and distribution of ground-water flow into the Pool. The Wisconsin Geological and Natural History Survey and the U.S. Geological Survey developed the models cooperatively. The report describes: 1) the conceptual hydrogeologic model; 2) the methods used in simulating flow; 3) model calibration and sensitivity analysis; and 4) model results, such as simulation of predevelopment conditions and location and magnitude of ground-water discharge into Pool 8 of the Mississippi.
\nThree aquifer units underlie the model area: 1) a shallow unconsolidated sand and gravel aquifer; 2) an upper bedrock aquifer, composed of Cambrian and Ordovician sandstone and dolomite; and 3) a lower bedrock aquifer composed of Cambrian sandstone of the Eau Claire Formation and the Mount Simon Formation. A shale layer that is part of the Eau Claire Formation forms a confining unit separating the upper and lower bedrock aquifers. This confining unit is absent in the Black River and parts of the La Crosse and Mississippi River valleys. Precambrian crystalline basement rock forms the lower base of the ground-water flow system.
\nThe U.S. Geological Survey ground-water flow model code, MODFLOW, was used to develop the La Crosse County (LCC) and Pool 8 ground-water flow models. Boundary conditions for the MODFLOW model were extracted from an analytic element screening model of the regional flow system surrounding La Crosse County. Model input was obtained from previously published and unpublished geologic and hydrologic data. Pumpages from municipal and high-capacity wells were also simulated.
\nModel calibration included a comparison of modeled and field-measured water levels and field-measured base flows to simulated stream flows. At calibration, most measured water levels compared favorably to model-calculated water levels. Simulated streamflows at two targets were within 3 percent of estimated measured base flows. Mass balance results from the LCC and Pool 8 models indicated that 63 to 74 percent of ground water was from recharge and 19 to 26 percent was from surface-water sources. Ground-water flow out of the model was to rivers and streams (85 to 87 percent) and pumping wells (11 and 13 percent).
\nThe model demonstrates the effects of development on ground water in the study area. The maximum simulated water-level decline in the city of La Crosse metropolitan area is 9.3 feet. Simulated stream losses are similar to the amount of ground water pumped by wells. This indicates that ground water withdrawn by La Crosse County wells is water that under predevelopment conditions discharged to streams and lakes.
\nThe models provide estimates of the locations and amount of ground-water flow into Pool 8 and the southern portion of Pool 7 of the Mississippi River. Ground-water discharges into all areas of the pools, except along the eastern shore in the vicinity of the city of La Crosse and immediately downgradient from lock and dam 7 and 8. Ground-water flow into the pools is generally greatest around the perimeter with decreasing amounts away from the perimeter. An area of relatively high ground-water discharge extends out towards the center of Pool 7 from the upper reaches of the pool and may
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri034154","collaboration":"Prepared in cooperation with La Crosse County, Wisconsin Department of Natural Resources, and Wisconsin Geological and Natural History Survey","usgsCitation":"Hunt, R.J., Saad, D.A., and Chapel, D.M., 2003, Numerical simulation of ground-water flow in La Crosse County, Wisconsin, and into nearby pools of the Mississippi River: U.S. Geological Survey Water-Resources Investigations Report 2003-4154, vi, 36 p., https://doi.org/10.3133/wri034154.","productDescription":"vi, 36 p.","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":677,"text":"Wisconsin Water Science 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