{"pageNumber":"1094","pageRowStart":"27325","pageSize":"25","recordCount":40845,"records":[{"id":70209812,"text":"70209812 - 2003 - U-series disequilibrium as a test for unsaturated-zone hydrologic models at Yucca Mountain, Nevada","interactions":[],"lastModifiedDate":"2020-05-01T17:56:42.647124","indexId":"70209812","displayToPublicDate":"2003-12-31T13:26:45","publicationYear":"2003","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"U-series disequilibrium as a test for unsaturated-zone hydrologic models at Yucca Mountain, Nevada","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 10th international high-level radioactive waste management conference (IHLRWM)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"10th International High-level Radioactive Waste Management Conference (IHLRWM)","conferenceDate":"Mar 30 - Apr 2, 2003","conferenceLocation":"Las Vegas, NV","language":"English","publisher":"American Nuclear Society","usgsCitation":"Paces, J.B., and Neymark, L., 2003, U-series disequilibrium as a test for unsaturated-zone hydrologic models at Yucca Mountain, Nevada, <i>in</i> Proceedings of the 10th international high-level radioactive waste management conference (IHLRWM), Las Vegas, NV, Mar 30 - Apr 2, 2003, p. 27-38.","productDescription":"12 p.","startPage":"27","endPage":"38","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":374370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Yucca Mountain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.48254394531249,\n              36.91352904330221\n            ],\n            [\n              -116.43602371215822,\n              36.91352904330221\n            ],\n            [\n              -116.43602371215822,\n              36.95757376878687\n            ],\n            [\n              -116.48254394531249,\n              36.95757376878687\n            ],\n            [\n              -116.48254394531249,\n              36.91352904330221\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":788130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neymark, Leonid A. 0000-0003-4190-0278 lneymark@usgs.gov","orcid":"https://orcid.org/0000-0003-4190-0278","contributorId":140338,"corporation":false,"usgs":true,"family":"Neymark","given":"Leonid A.","email":"lneymark@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":788131,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70205798,"text":"70205798 - 2003 - Application of artificial neural networks to complex groundwater management problems","interactions":[],"lastModifiedDate":"2019-10-03T13:30:09","indexId":"70205798","displayToPublicDate":"2003-12-31T13:23:28","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Application of artificial neural networks to complex groundwater management problems","docAbstract":"<p><span>As water quantity and quality problems become increasingly severe, accurate prediction and effective management of scarcer water resources will become critical. In this paper, the successful application of artificial neural network (ANN) technology is described for three types of groundwater prediction and management problems. In the first example, an ANN was trained with simulation data from a physically based numerical model to predict head (groundwater elevation) at locations of interest under variable pumping and climate conditions. The ANN achieved a high degree of predictive accuracy, and its derived state-transition equations were embedded into a multiobjective optimization formulation and solved to generate a trade-off curve depicting water supply in relation to contamination risk. In the second and third examples, ANNs were developed with real-world hydrologic and climate data for different hydrogeologic environments. For the second problem, an ANN was developed using data collected for a 5-year, 8-month period to predict heads in a multilayered surficial and limestone aquifer system under variable pumping, state, and climate conditions. Using weekly stress periods, the ANN substantially outperformed a well-calibrated numerical flow model for the 71-day validation period, and provided insights into the effects of climate and pumping on water levels. For the third problem, an ANN was developed with data collected automatically over a 6-week period to predict hourly heads in 11 high-capacity public supply wells tapping a semiconfined bedrock aquifer and subject to large well-interference effects. Using hourly stress periods, the ANN accurately predicted heads for 24-hour periods in all public supply wells. These test cases demonstrate that the ANN technology can solve a variety of complex groundwater management problems and overcome many of the problems and limitations associated with traditional physically based flow models.</span></p>","language":"English","publisher":"Springer","doi":"10.1023/B:NARR.0000007808.11860.7e","usgsCitation":"Coppola, E., Poulton, M., Charles, E.G., Dustman, J., and Szidarovszky, F., 2003, Application of artificial neural networks to complex groundwater management problems: Natural Resources Research, v. 12, no. 4, p. 303-320, https://doi.org/10.1023/B:NARR.0000007808.11860.7e.","productDescription":"18 p.","startPage":"303","endPage":"320","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":367974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coppola, Emery Jr.","contributorId":219496,"corporation":false,"usgs":false,"family":"Coppola","given":"Emery","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":772384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poulton, Mary","contributorId":219497,"corporation":false,"usgs":false,"family":"Poulton","given":"Mary","email":"","affiliations":[],"preferred":false,"id":772385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Charles, Emmanuel G. 0000-0002-3338-4958 echarles@usgs.gov","orcid":"https://orcid.org/0000-0002-3338-4958","contributorId":4280,"corporation":false,"usgs":true,"family":"Charles","given":"Emmanuel","email":"echarles@usgs.gov","middleInitial":"G.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dustman, John","contributorId":219498,"corporation":false,"usgs":false,"family":"Dustman","given":"John","email":"","affiliations":[],"preferred":false,"id":772387,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szidarovszky, F.","contributorId":30457,"corporation":false,"usgs":true,"family":"Szidarovszky","given":"F.","email":"","affiliations":[],"preferred":false,"id":772388,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226558,"text":"70226558 - 2003 - The Rocky Mountain glacial model; the Wind River Range, Wyoming","interactions":[],"lastModifiedDate":"2021-11-26T17:44:27.71353","indexId":"70226558","displayToPublicDate":"2003-12-31T11:21:43","publicationYear":"2003","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The Rocky Mountain glacial model; the Wind River Range, Wyoming","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Quaternary geology of the United States; INQUA 2003 field guide volume","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Desert Research Institute","usgsCitation":"Dahms, D.E., Hall, R.D., Shroba, R.R., Sorenson, C.J., Lynch, E.A., and Applegarth, M.T., 2003, The Rocky Mountain glacial model; the Wind River Range, Wyoming, chap. <i>of</i> Quaternary geology of the United States; INQUA 2003 field guide volume, p. 345-364.","productDescription":"20 p.","startPage":"345","endPage":"364","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":392131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Wind River Range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.6328125,\n              42.52069952914966\n            ],\n            [\n              -108.687744140625,\n              42.791369723650135\n            ],\n            [\n              -109.3414306640625,\n              43.35713822211053\n            ],\n            [\n              -109.68200683593749,\n              43.58834891179792\n            ],\n            [\n              -110.050048828125,\n              43.504736854976954\n            ],\n            [\n              -110.006103515625,\n              43.08493742707592\n            ],\n            [\n              -109.2974853515625,\n              42.52879629320373\n            ],\n            [\n              -108.687744140625,\n              42.47209690919285\n            ],\n            [\n              -108.6328125,\n              42.52069952914966\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dahms, D. E.","contributorId":269516,"corporation":false,"usgs":false,"family":"Dahms","given":"D.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":827346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, R. D.","contributorId":269517,"corporation":false,"usgs":false,"family":"Hall","given":"R.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":827347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shroba, Ralph R. 0000-0002-2664-1813 rshroba@usgs.gov","orcid":"https://orcid.org/0000-0002-2664-1813","contributorId":1266,"corporation":false,"usgs":true,"family":"Shroba","given":"Ralph","email":"rshroba@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":827348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sorenson, C. J.","contributorId":32535,"corporation":false,"usgs":true,"family":"Sorenson","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":827349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lynch, E. A.","contributorId":99167,"corporation":false,"usgs":true,"family":"Lynch","given":"E.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":827350,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Applegarth, M. T.","contributorId":269518,"corporation":false,"usgs":false,"family":"Applegarth","given":"M.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":827351,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70228910,"text":"70228910 - 2003 - Quaternary vegetation and climate change in the western United States: Developments, perspectives, and prospects","interactions":[],"lastModifiedDate":"2022-02-24T14:31:31.345977","indexId":"70228910","displayToPublicDate":"2003-12-31T08:26:25","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5919,"text":"Developments in Quaternary Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Quaternary vegetation and climate change in the western United States: Developments, perspectives, and prospects","docAbstract":"<p><span>This chapter explores the strengths and shortcomings of the major sources of data on Quaternary vegetation and climate change and discusses the use of models as a means to explore past and potential future environmental changes. The flora and major vegetation types of the western United States are present for several million years. Ongoing changes in&nbsp;</span>atmospheric chemistry<span>, climate, and human activities may lead to major vegetation changes over the coming decades to centuries. The combination of observations from the paleoenvironmental record, modern ecological studies, and modeling now permit assessments of the magnitude of potential future changes in the context of natural variability. They also provide opportunities for hypothesis testing and identification of the processes driving past changes in vegetation and climate. Understanding the dynamics of paleoenvironmental change can contribute to current conservation and&nbsp;natural resource management&nbsp;efforts and will help conservation and natural resource managers anticipate the potential rate, magnitude, and complexity of future vegetation change.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/S1571-0866(03)01018-2","usgsCitation":"Thompson, R.S., Shafer, S., Strickland, L.E., Van De Water, P.K., and Anderson, K.H., 2003, Quaternary vegetation and climate change in the western United States: Developments, perspectives, and prospects: Developments in Quaternary Sciences, v. 1, p. 403-426, https://doi.org/10.1016/S1571-0866(03)01018-2.","productDescription":"24 p.","startPage":"403","endPage":"426","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":396413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.98046874999999,\n              28.459033019728043\n            ],\n            [\n              -100,\n              28.459033019728043\n            ],\n            [\n              -100,\n              48.80686346108517\n            ],\n            [\n              -124.98046874999999,\n              48.80686346108517\n            ],\n            [\n              -124.98046874999999,\n              28.459033019728043\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Robert S. 0000-0001-9287-2954 rthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-9287-2954","contributorId":891,"corporation":false,"usgs":true,"family":"Thompson","given":"Robert","email":"rthompson@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":835863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":835864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strickland, Laura E. 0000-0002-1958-7273 lstrickland@usgs.gov","orcid":"https://orcid.org/0000-0002-1958-7273","contributorId":4682,"corporation":false,"usgs":true,"family":"Strickland","given":"Laura","email":"lstrickland@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":835865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van De Water, Peter K.","contributorId":51484,"corporation":false,"usgs":true,"family":"Van De Water","given":"Peter","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":835866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Katherine H. 0000-0003-2677-6109","orcid":"https://orcid.org/0000-0003-2677-6109","contributorId":52556,"corporation":false,"usgs":true,"family":"Anderson","given":"Katherine","email":"","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":835867,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70197328,"text":"70197328 - 2003 - Ophiolite and volcanic arc assemblages on the Vizcaino Peninsula and Cedros Island region, Baja California Sur, Mexico: Mesozoic forearc lithosphere of the Cordilleran magmatic arc","interactions":[],"lastModifiedDate":"2018-05-29T16:15:39","indexId":"70197328","displayToPublicDate":"2003-12-31T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ophiolite and volcanic arc assemblages on the Vizcaíno Peninsula and Cedros Island region, Baja California Sur, Mexico: Mesozoic forearc lithosphere of the Cordilleran magmatic arc","title":"Ophiolite and volcanic arc assemblages on the Vizcaino Peninsula and Cedros Island region, Baja California Sur, Mexico: Mesozoic forearc lithosphere of the Cordilleran magmatic arc","docAbstract":"<p><span>Mesozoic ophiolites in the Vizcaíno Peninsula and Cedros Island region of Baja California Sur are suprasubduction zone Cordilleran-type ophiolites structurally juxtaposed with underlying high pressure-temperature subduction complex assemblages. The region is divided into three separate tectonostratigraphic terranes, but here we recognize stratigraphic, intrusive, and petrologie links between these terranes and interpret the evolution of the entire region within the same Late Triassic to Early Cretaceous tectonic framework. Several phases of extension are recognized, including two major phases that resulted in development of distinct ophiolite assemblages. The Late Triassic Vizcaine Peninsula Ophiolite (221 ± 2 Ma) represents the earliest stage of this history and comprises a complete spreading center sequence with depleted upper mantle and mafie crustal rocks, including sheeted dike complex, Jurassic are magmatic rocks with low-Ti are tholelite and boninite geochemical affinities were intruded through and constructed on the Triassic ophiolite basement. Ultra-depleted are-ankaramites on Cedros Island may represent an initial phase of are rifting that was followed by major Middle Jurassic extension and production of the Cedros Island Ophiolite (173 ± 2 Ma). The Late Jurassic-Early Cretaceous Coloradito and Eugenia Formations contain mudflows and olistostrome blocks intercalated with are volcanogenic sediment and rift-related pillow lavas; these units record extension and/or transtension and provide the earliest definite evidence of are-continent interaction in the region.</span></p><p><span>Middle Jurassic to Early Cretaceous are plutonic rocks (ca. 165-135 Ma) were shallowly intruded into low greenschist-facies ophiolite and are volcanic basement. Plutonic rocks range in composition from gabbro to granodiorite, but tonalite dominates. These intrusions are typical I-type Cordilleran batholithic rocks with relatively primitive are geochemical affinities (initial Sr</span><span>87</span><span>/</span><span>86</span><span>Sr range from ~0.704 to 0.706), but they are distinctly calcic in nature, a feature common to the adjacent Cretaceous Peninsular Ranges batholith.</span></p><p><span>The Vizca</span><span>í</span><span>no-Cedros region correlates to ophiolitic terranes of the western Sierra Klamath belt and Coast Ranges of California and Oregon that were constructed in part across the North American margin. Age, stratigraphic, and petrochemical data from the Vizca</span><span>í</span><span>no-Cedros region support previously proposed forearc rifting models developed for the U.S. sector of the Cordilleran orogen that interpret the ophiolite assemblages as autochthonous or parautochthonous forearc lithosphere constructed outboard of the Mesozoic continental margin arc.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tectonic evolution of northwestern Mexico and the southwestern USA","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","usgsCitation":"Kimbrough, D., and Moore, T.E., 2003, Ophiolite and volcanic arc assemblages on the Vizcaino Peninsula and Cedros Island region, Baja California Sur, Mexico: Mesozoic forearc lithosphere of the Cordilleran magmatic arc: GSA Special Papers, v. 374, p. 43-71.","productDescription":"29 p.","startPage":"43","endPage":"71","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":354547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"374","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b1584f0e4b092d9651e210f","contributors":{"authors":[{"text":"Kimbrough, D.L.","contributorId":25332,"corporation":false,"usgs":true,"family":"Kimbrough","given":"D.L.","email":"","affiliations":[],"preferred":false,"id":736687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Thomas E. 0000-0002-0878-0457 tmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-0878-0457","contributorId":1033,"corporation":false,"usgs":true,"family":"Moore","given":"Thomas","email":"tmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":736688,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70185153,"text":"70185153 - 2003 - The behavior of U- and Th-series nuclides in groundwater","interactions":[],"lastModifiedDate":"2017-03-15T13:12:34","indexId":"70185153","displayToPublicDate":"2003-12-31T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3281,"text":"Reviews in Mineralogy and Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"The behavior of U- and Th-series nuclides in groundwater","docAbstract":"<p><span>Groundwater has long been an active area of research driven by its importance both as a societal resource and as a component in the global hydrological cycle. Key issues in groundwater research include inferring rates of transport of chemical constituents, determining the ages of groundwater, and tracing water masses using chemical fingerprints. While information on the trace elements pertinent to these topics can be obtained from aquifer tests using experimentally introduced tracers, and from laboratory experiments on aquifer materials, these studies are necessarily limited in time and space. Regional studies of aquifers can focus on greater scales and time periods, but must contend with greater complexities and variations. In this regard, the isotopic systematics of the naturally occurring radionuclides in the U- and Th- decay series have been invaluable in investigating aquifer behavior of U, Th, and Ra. These nuclides are present in all groundwaters and are each represented by several isotopes with very different half-lives, so that processes occurring over a range of time-scales can be studied (Table 1</span><a id=\"xref-table-wrap-1-1\" class=\"xref-down-link\" href=\"http://rimg.geoscienceworld.org/content/52/1/317#T1\" data-mce-href=\"http://rimg.geoscienceworld.org/content/52/1/317#T1\"><span>⇓</span></a><span>). Within the host aquifer minerals, the radionuclides in each decay series are generally expected to be in secular equilibrium and so have equal activities (see </span>Bourdon et al. 2003<span>). In contrast, these nuclides exhibit strong relative fractionations within the surrounding groundwaters that reflect contrasting behavior during release into the water and during interaction with the surrounding host aquifer rocks. Radionuclide data can be used, within the framework of models of the processes involved, to obtain quantitative assessments of radionuclide release from aquifer rocks and groundwater migration rates. The isotopic variations that are generated also have the potential for providing fingerprints for groundwaters from specific aquifer environments, and have even been explored as a means for calculating groundwater ages.</span></p>","language":"English","publisher":" Mineralogical Society of America (MSA) and the Geochemical Society","doi":"10.2113/0520317","usgsCitation":"Porcelli, D., and Swarzenski, P., 2003, The behavior of U- and Th-series nuclides in groundwater: Reviews in Mineralogy and Geochemistry, v. 52, no. 1, p. 317-361, https://doi.org/10.2113/0520317.","productDescription":"45 p.","startPage":"317","endPage":"361","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":337637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ca52d1e4b0849ce97c86d2","contributors":{"authors":[{"text":"Porcelli, D.","contributorId":35912,"corporation":false,"usgs":true,"family":"Porcelli","given":"D.","email":"","affiliations":[],"preferred":false,"id":684548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, P.W. 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":29487,"corporation":false,"usgs":true,"family":"Swarzenski","given":"P.W.","affiliations":[],"preferred":false,"id":684549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70188358,"text":"70188358 - 2003 - Population genetic structure of Santa Ynez rainbow trout – 2001 based on microsatellite and mtDNA analyses ","interactions":[],"lastModifiedDate":"2017-06-07T10:10:00","indexId":"70188358","displayToPublicDate":"2003-12-31T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Population genetic structure of Santa Ynez rainbow trout – 2001 based on microsatellite and mtDNA analyses ","docAbstract":"<p>Microsatellite allelic and mitochondrial DNA (mtDNA) haplotype diversity are analyzed in eight rainbow trout (<i>Oncorhynchus mykiss</i>) collections: two from tributaries flowing into the upper Santa Ynez River watershed at Gibraltar Reservoir (Camuesa and Gidney creeks); three from tributaries between Gibraltar and Jameson reservoirs (Fox, Blue Canyon, and Alder creeks); one from a tributary above Jameson Reservoir (Juncal Creek); Jameson Reservoir; and one from the mainstem Santa Ynez River above the Jameson Reservoir. Both analyses reveal a high degree of population structure. Thirteen microsatellite loci are amplified from 376 fish. Population pairwise comparisons show significant differences in allelic frequency among all populations with the exception of Juncal Creek and Jameson Reservoir (p = 0.4). Pairwise<i> F<sub>st</sub></i> values range from 0.001 (Juncal Creek and Jameson Reservoir) to 0.17 (Camuesa and Juncal creeks) with an overall value of 0.021. Regression analyses (Slatkin 1993) supports an isolation-bydistance model in the five populations below Jameson Reservoir (intercept = 1.187, slope = -0.41, r2 = 0.67). A neighbor-joining bootstrap value of 100% (based on 2000 replicate trees) separates the populations sampled above and below Juncal Dam. </p><p>Composite haplotypes from 321 fish generated using mtDNA sequence data (Dloop) reveal four previously described haplotypes (MYS1, MYS3, MYS5 and MYS8; Nielsen et al. 1994a), and one (MYS5) was found in all populations. Mean haplotype diversity is 0.48. Pairwise <i>F<sub>st</sub></i> values from mtDNA range from -0.019 to 0.530 (0.177 over all populations) and are larger than those for microsatellites in 26 of 28 pairwise comparisons. In addition, the mtDNA and microsatellites provide contrasting evidence of the relationship of Fox and Alder creeks to the other six populations. Discrepancies between the two markers are likely due to the unique properties of the two marker types and their value in revealing historic (mtDNA) versus contemporary (microsatellites) genetic relationships. The contrasting results may indicate how relationships among the upper Santa Ynez River populations have changed since the installation of Juncal Dam. </p><p>Comparisons of mtDNA haplotype frequencies from fish collected for this study with samples analyzed previously in JLN’s laboratory (1993) reveal significant differences in mtDNA haplotypes for Fox and Alder creeks. In the 2001 samples from this study, there is a loss of three haplotypes despite larger sample sizes. AMOVA analysis of what we term “upper” (Alder, Fox, Blue Canyon, Camuesa, Gidney creeks and the upper Santa Ynez mainstem) and “lower” (Hilton, Salsipuedes and the lower mainstem Santa Ynez River) Santa Ynez River populations (1993-2001) reveal that 11% of the variance in haplotypes is found between the upper and lower drainage. A comparison of the mtDNA data from this study with those available for southern California coastal and California hatchery<i> O. mykiss</i> populations yields <i>F<sub>st</sub></i> values of 0.15 and 0.47, respectively. Differentiation of mtDNA haplotypes for population pairs of Santa Ynez River and hatchery fish show no significant differentiation between wild and at least one hatchery strain in Cachuma Reservoir, Hilton Creek, and the Lower Santa Ynez River. </p>","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Nielsen, J.L., Zimmerman, C.E., Olsen, J.B., Wiacek, T., Kretschmer, E., Greenwald, G.M., and Wenburg, J.K., 2003, Population genetic structure of Santa Ynez rainbow trout – 2001 based on microsatellite and mtDNA analyses , 29 p.","productDescription":"29 p.","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":342199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Ynes River drainage","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": 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L.","contributorId":43722,"corporation":false,"usgs":true,"family":"Nielsen","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":697373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":697374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olsen, Jeffrey B.","contributorId":174632,"corporation":false,"usgs":false,"family":"Olsen","given":"Jeffrey","email":"","middleInitial":"B.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":697375,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiacek, Talia","contributorId":174037,"corporation":false,"usgs":false,"family":"Wiacek","given":"Talia","email":"","affiliations":[],"preferred":false,"id":697376,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kretschmer, E.J.","contributorId":192687,"corporation":false,"usgs":false,"family":"Kretschmer","given":"E.J.","email":"","affiliations":[],"preferred":false,"id":697377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greenwald, Glenn M.","contributorId":192688,"corporation":false,"usgs":false,"family":"Greenwald","given":"Glenn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697378,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wenburg, John K.","contributorId":174634,"corporation":false,"usgs":false,"family":"Wenburg","given":"John","email":"","middleInitial":"K.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":697379,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70187742,"text":"70187742 - 2003 - New mapping near Iron Creek, Talkeetna Mountains, indicates presence of Nikolai greenstone","interactions":[],"lastModifiedDate":"2017-05-24T15:48:53","indexId":"70187742","displayToPublicDate":"2003-12-31T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5404,"text":"Alaska Division of Geological & Geophysical Surveys Professional Reports","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"DGGS PR 120","chapter":"J","title":"New mapping near Iron Creek, Talkeetna Mountains, indicates presence of Nikolai greenstone","docAbstract":"<p>Detailed geologic mapping in the Iron Creek area, Talkeetna Mountains B-5 Quadrangle, has documented several intrusive bodies and rock units not previously recognized and has extended the geologic history of the area through the Mesozoic and into the Tertiary era. Greenschist-facies metabasalt and metagabbro previously thought to be Paleozoic are intruded by Late Cretaceous to Paleocene dioritic to granitic plutons. The metabasalts are massive to amygdaloidal, commonly contain abundant magnetite, and large areas are patchily altered to epidote ± quartz. They host numerous copper oxide–copper sulfide–quartz–hematite veins and amygdule fillings. These lithologic features, recognized in the field, suggested a correlation of the metamafic rocks with the Late Triassic Nikolai Greenstone, which had not previously been mapped in the Iron Creek area. Thin, discontinuous metalimestones that overlie the metabasalt sequence had previously been assigned a Pennsylvanian(?) and Early Permian age on the basis of correlation with marbles to the north, which yielded Late Paleozoic or Permian macrofossils, or both. Three new samples from the metalimestones near Iron Creek yielded Late Triassic conodonts, which confirms the correlation of the underlying metamafic rocks with Nikolai Greenstone. These new data extend the occurrence of Nikolai Greenstone about 70 km southwest of its previously mapped extent.</p><p>Five to 10 km north of the conodont sample localities, numerous microgabbro and diabase sills intrude siliceous and locally calcareous metasedimentary rocks of uncertain age. These sills probably represent feeder zones to the Nikolai Greenstone. In the Mt. Hayes quadrangle 150 km to the northeast, large sill-form mafic and ultramafic feeders (for example, the Fish Lake complex) to the Nikolai Greenstone in the Amphitheatre Mountains host magmatic sulfide nickel–copper–platinum-group-element (PGE) mineralization. This new recognition of Nikolai Greenstone and possible magmatic feeders in the Iron Creek area suggests a much greater potential for large PGE, copper, or nickel deposits in the Talkeetna Mountains than previous mineral resource appraisals of the area have suggested, and requires reevaluation of large-scale tectonic models for the area.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Short Notes on Alaska Geology 2003 (DGGS PR 120)","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"Alaska Division of Geological & Geophysical Surveys","publisherLocation":"Fairbanks, AK","doi":"10.14509/2917","usgsCitation":"Schmidt, J.M., Werdon, M., and Wardlaw, B.R., 2003, New mapping near Iron Creek, Talkeetna Mountains, indicates presence of Nikolai greenstone: Alaska Division of Geological & Geophysical Surveys Professional Reports DGGS PR 120, 8 p., https://doi.org/10.14509/2917.","productDescription":"8 p.","startPage":"101","endPage":"108","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":341377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Iron Creek, Talkeenta Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -150,\n              62\n            ],\n            [\n              -147,\n              62\n            ],\n            [\n              -147,\n              63\n            ],\n            [\n              -150,\n              63\n            ],\n            [\n              -150,\n              62\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591c0fcee4b0a7fdb43ddf0a","contributors":{"authors":[{"text":"Schmidt, Jeanine M. jschmidt@usgs.gov","contributorId":3138,"corporation":false,"usgs":true,"family":"Schmidt","given":"Jeanine","email":"jschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":695394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werdon, Melanie B.","contributorId":53345,"corporation":false,"usgs":true,"family":"Werdon","given":"Melanie B.","affiliations":[],"preferred":false,"id":695395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":695396,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70240592,"text":"70240592 - 2003 - Shallow water table fluctuations in relation to soil penetration resistance","interactions":[],"lastModifiedDate":"2023-02-09T20:31:04.2917","indexId":"70240592","displayToPublicDate":"2003-12-01T14:23:10","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Shallow water table fluctuations in relation to soil penetration resistance","docAbstract":"<p><span>Hydrologic modeling of catchments is frequently hampered by lack of information on subsurface stratigraphy and zones of preferred flow. We evaluated the usefulness of soil penetration resistance, easily measured by a dynamic cone penetrometer, together with measurements of ground water level fluctuations, as a cost-effective means to infer subsurface flow patterns. At our field site at Sleepers River, Vermont, penetration resistance was lowest in the surficial 10 to 30 cm, then typically increased to a local maximum at 60 to 80 cm, which we interpreted as the soil/till interface. Below this depth usually lies a zone of decreased resistance in the till, giving way to either a gradual or abrupt increase in resistance toward the bedrock surface at 1 to 4.5 m depth. Penetration resistance had a weak but significant negative correlation with saturated hydraulic conductivity determined by bail tests (r</span><sup>2</sup><span>= 0.25,&nbsp;</span><i>p</i><span>&nbsp;&lt; 0.05). At many wells, monthly ground water levels tended to cluster at or just above the resistant zone near the soil/till interface. Chemical and isotopic dynamics in nested wells finished above and below the resistant zone suggest that the zone may temporarily isolate the deeper ground water reservoir from meltwater inputs, which were clearly identified by low δ</span><sup>18</sup><span>O values. In ground water discharge zones, δ</span><sup>18</sup><span>O values tended to converge throughout the profile. In contrast, dissolved organic carbon (DOC) maintained a gradient of increasing concentration toward land surface, even in otherwise well-mixed waters, reflecting its rapid release from organic horizons. Understanding the effect of soil penetration resistance on ground water behavior may be useful in future catchment modeling efforts.</span></p>","language":"English","publisher":"National Ground Water Association","usgsCitation":"Shanley, J.B., Hjerdt, K.N., McDonnell, J.J., and Kendall, C., 2003, Shallow water table fluctuations in relation to soil penetration resistance: Groundwater, v. 41, no. 7, p. 964-972.","productDescription":"9 p.","startPage":"964","endPage":"972","costCenters":[],"links":[{"id":412918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Sleepers River Research Watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -72.80107041929911,\n              44.807565523241294\n            ],\n            [\n              -72.80107041929911,\n              44.35469178581053\n            ],\n            [\n              -72.03477403258064,\n              44.35469178581053\n            ],\n            [\n              -72.03477403258064,\n              44.807565523241294\n            ],\n            [\n              -72.80107041929911,\n              44.807565523241294\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"41","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hjerdt, K. Niclas","contributorId":302313,"corporation":false,"usgs":false,"family":"Hjerdt","given":"K.","email":"","middleInitial":"Niclas","affiliations":[],"preferred":false,"id":864001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDonnell, Jeffrey J.","contributorId":202934,"corporation":false,"usgs":false,"family":"McDonnell","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[{"id":36551,"text":"University of Saskatchewan, Canada, and University of Aberdeen, Scotland","active":true,"usgs":false}],"preferred":false,"id":864002,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, Carol 0000-0002-0247-3405 ckendall@usgs.gov","orcid":"https://orcid.org/0000-0002-0247-3405","contributorId":1462,"corporation":false,"usgs":true,"family":"Kendall","given":"Carol","email":"ckendall@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":864003,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70263738,"text":"70263738 - 2003 - A strategy for mapping mid-scale existing vegetation in support of national fire fuel assessment","interactions":[],"lastModifiedDate":"2025-02-20T17:32:19.678199","indexId":"70263738","displayToPublicDate":"2003-12-01T11:28:29","publicationYear":"2003","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A strategy for mapping mid-scale existing vegetation in support of national fire fuel assessment","docAbstract":"<p>Geospatial distribution of natural vegetation is among the very important environmental parameters required for applications ranging from global climate change to monitoring of natural hazards, monitoring of ecosystem vitality, and fire management practices. Increasingly sophisticated applications require vegetation datasets to cover large areas at a suitable scale and provide sufficiently detailed information. In this paper, we describe a research effort to develop a remote sensing methodology capable of producing 30-meter resolution, wall-to-wall coverage of existing vegetation types and structure variables in support of a multi-agency fire fuels and fire risks assessment project. Success of this remote sensing research effort is dependent on improved sensor and data qualities, a thorough understanding of regional and local vegetation ecology, successful integration of remote sensing with a large amount of field plot data, and flexible mapping algorithms. Preliminary results produced in the Wasatch Range and Uinta Mountains of central Utah include 28 vegetation types with an overall accuracy of 60% (average by life forms), percent canopy density (sub-pixel density) of forest, shrub, and herbaceous cover (correlation coefficient of 89, 60, and 55% respectively), and average top canopy height of forest, shrub, and herbaceous cover (correlation coefficient of 73, 50, 20% respectively). Techniques to improve the first-round results are discussed, including refinements of mapping models and use of relevant environmental gradients and potential vegetation classification associated with actual vegetation types. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Technology- Converging at the top of the world","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","usgsCitation":"Huang, C., Vogelmann, J., Tolk, B.L., Menakis, J.P., and Moisen, G.G., 2003, A strategy for mapping mid-scale existing vegetation in support of national fire fuel assessment, <i>in</i> Technology- Converging at the top of the world, 9 p.","productDescription":"9 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":482290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Huang, Chengquan","contributorId":25378,"corporation":false,"usgs":true,"family":"Huang","given":"Chengquan","affiliations":[],"preferred":false,"id":928018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":928019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tolk, Brian L. 0000-0002-9060-0266 tolk@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0266","contributorId":2992,"corporation":false,"usgs":true,"family":"Tolk","given":"Brian","email":"tolk@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":928020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Menakis, James P.","contributorId":344955,"corporation":false,"usgs":false,"family":"Menakis","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":928021,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moisen, Gretchen G.","contributorId":15781,"corporation":false,"usgs":false,"family":"Moisen","given":"Gretchen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":928022,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70263736,"text":"70263736 - 2003 - Deriving rangeland structural attributes using Landsat ETM+, ERS-1/ERS-2","interactions":[],"lastModifiedDate":"2026-01-29T21:20:16.95806","indexId":"70263736","displayToPublicDate":"2003-12-01T11:17:31","publicationYear":"2003","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Deriving rangeland structural attributes using Landsat ETM+, ERS-1/ERS-2","docAbstract":"<p>The purpose of this study is to determine if Synthetic Aperture Radar (SAR) can be used independently, or in conjunction with Landsat Enhanced Thematic Mapper Plus (ETM+) to improve the classification accuracy of structural attributes of rangeland vegetation, particularly percent shrub cover and top shrub canopy height. Such information, if mapped accurately, can be used in models to better characterize fuel conditions and fire regimes, as well as to evaluate fire hazard status, called for by the U.S. National Fire Plan. The input datasets utilized in this investigation included eighteen bands of Landsat ETM+ path 38 / row 32 (three image dates, six bands each), backscattering and interferometic data derived from tandem ERS-1/2 SAR image pairs (C-band), and extensive field point data. The results showed the use of SAR data provided no significant improvement over the ETM+ data for estimating percent cover or shrub canopy height. The lack of improvement in classification accuracy is possibly due to the influence of topography on the radar backscattering signal. Additional results demonstrated improved model accuracies when a 3x3-averaging filter was applied to the eighteen bands of ETM+ imagery. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Technology- Converging at the top of the world","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","usgsCitation":"Tolk, B.L., Huang, C., Lu, Z., Rykhus, R.P., and Vogelmann, J., 2003, Deriving rangeland structural attributes using Landsat ETM+, ERS-1/ERS-2, <i>in</i> Technology- Converging at the top of the world, 7 p.","productDescription":"7 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":482288,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tolk, Brian L. 0000-0002-9060-0266 tolk@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0266","contributorId":2992,"corporation":false,"usgs":true,"family":"Tolk","given":"Brian","email":"tolk@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":928008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Chengquan 0000-0003-0055-9798","orcid":"https://orcid.org/0000-0003-0055-9798","contributorId":198972,"corporation":false,"usgs":false,"family":"Huang","given":"Chengquan","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":928009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":928010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rykhus, Russell P.","contributorId":27337,"corporation":false,"usgs":true,"family":"Rykhus","given":"Russell","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":928011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":928012,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70263734,"text":"70263734 - 2003 - Studies of Alaskan volcanoes using synthetic aperature radar and Landsat imagery","interactions":[],"lastModifiedDate":"2025-02-20T17:09:03.925353","indexId":"70263734","displayToPublicDate":"2003-12-01T11:05:37","publicationYear":"2003","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Studies of Alaskan volcanoes using synthetic aperature radar and Landsat imagery","docAbstract":"<p>Approximately 10 percent of the world’s active volcanoes are located in the Alaskan Aleutian arc and produce about 3-4 explosive eruptions per year. Even with this high amount of volcanic activity, the remote locations and harsh environments of the Aleutian volcanoes conspire to keep them among some of the most poorly studied volcanoes in the world. Space-borne remote sensed imagery can play a significant role in improving our understanding of activity at these volcanoes. Synthetic aperture radar (SAR), Landsat imagery, and Digital Elevation Models (DEMs) derived from SRTM and the National Elevation Database (NED) are used to study several Alaskan volcanoes. Interferometric SAR (InSAR) techniques with ERS-1 and ERS-2 SAR imagery are used to measure ground-surface deformation, which enables the construction of detailed mechanical models that enhance the study of magmatic and tectonic processes. The 30-year historical archive of Landsat data is used to study land cover change, visualize the ash plumes of Aleutian volcanic eruptions, and to map the extent of lava flows. Differencing two DEMs that represent volcano topography before and after an eruption makes it possible to calculate the volume of extruded materials. This paper provides a progress report on how InSAR, Landsat imagery and digital elevation data can be used to better understand the volcanic processes at three Aleutian volcanoes.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Technology- Converging at the top of the world","largerWorkSubtype":{"id":12,"text":"Conference publication"},"publisher":"American Society for Photogrammetry and Remote Sensing","usgsCitation":"Rykhus, R.P., and Lu, Z., 2003, Studies of Alaskan volcanoes using synthetic aperature radar and Landsat imagery, <i>in</i> Technology- Converging at the top of the world, 6 p.","productDescription":"6 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":482286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -152.33036874483844,\n              59.70347743188694\n            ],\n            [\n              -169.1695521105382,\n              59.70347743188694\n            ],\n            [\n              -169.1695521105382,\n              52.600812738063496\n            ],\n            [\n              -152.33036874483844,\n              52.600812738063496\n            ],\n            [\n              -152.33036874483844,\n              59.70347743188694\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rykhus, Russell P.","contributorId":27337,"corporation":false,"usgs":true,"family":"Rykhus","given":"Russell","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":928003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":928004,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70263459,"text":"70263459 - 2003 - Predictive modeling of forest cover type and tree canopy height in the central Rocky Mountains of Utah","interactions":[],"lastModifiedDate":"2025-02-11T17:01:06.536601","indexId":"70263459","displayToPublicDate":"2003-12-01T10:56:32","publicationYear":"2003","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Predictive modeling of forest cover type and tree canopy height in the central Rocky Mountains of Utah","docAbstract":"<p>Maps of forest cover type and canopy height are needed for LANDFIRE, a multi-scale fire risk assessment project designed to generate intermediate-resolution data of vegetation and fire fuel characteristics for the U.S. Here we describe an evaluation study in the central Rockies of Utah, comparing tree-based methods, multivariate adaptive regression splines (MARS), and a hybrid method for mapping forest cover and canopy height on the basis of more than 2,000 forest inventory ground plots in the seven million ha mapping zone. The two forest attributes were modeled as functions of a variety of predictor variables, including: Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images acquired at three different seasons; Tasseled-cap brightness, greenness, and wetness; a forest type group map; and topographic variables derived from Digital Elevation Models (DEMs); and other ancillary variables. The hybrid modeling approach showed a marked increase in overall and within forest cover type accuracies, outperforming the tree-based and MARS approaches. Little difference was seen in global performance measures of forest canopy height models, but patterns in residual plots resulting from different modeling approaches raise questions about utility of height predictions in different applications. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Technology—Converging at the top of the world","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","usgsCitation":"Moisen, G.G., Frescino, T., Huang, C., Vogelmann, J., and Zhu, Z., 2003, Predictive modeling of forest cover type and tree canopy height in the central Rocky Mountains of Utah, <i>in</i> Technology—Converging at the top of the world, 11 p.","productDescription":"11 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":481936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Utah, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.0738784907244,\n              38.225155891159375\n            ],\n            [\n              -112.61007871413581,\n              37.098860827796145\n            ],\n            [\n              -110.96829079907438,\n              37.62290231925077\n            ],\n            [\n              -109.23145339633764,\n              40.90410931035362\n            ],\n            [\n              -109.90854382084767,\n              41.713850737183066\n            ],\n            [\n              -111.22792548102528,\n              41.75190845730722\n            ],\n            [\n              -111.55059786157618,\n              42.97031458161342\n            ],\n            [\n              -112.42823065667831,\n              42.94139537473612\n            ],\n            [\n              -112.34462551318505,\n              40.397107371779725\n            ],\n            [\n              -113.0738784907244,\n              38.225155891159375\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moisen, Gretchen G.","contributorId":15781,"corporation":false,"usgs":false,"family":"Moisen","given":"Gretchen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":927051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frescino, T.S.","contributorId":94485,"corporation":false,"usgs":true,"family":"Frescino","given":"T.S.","email":"","affiliations":[],"preferred":false,"id":927052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huang, Chengquan","contributorId":25378,"corporation":false,"usgs":true,"family":"Huang","given":"Chengquan","affiliations":[],"preferred":false,"id":927053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":927054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":927055,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70263457,"text":"70263457 - 2003 - Deriving annual integrated NDVI greenness at 30 m spatial resolution","interactions":[],"lastModifiedDate":"2025-02-12T14:18:18.839655","indexId":"70263457","displayToPublicDate":"2003-12-01T10:40:52","publicationYear":"2003","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Deriving annual integrated NDVI greenness at 30 m spatial resolution","docAbstract":"<p>Temporal greenness matrics have been found useful for characterizing vegetation phenology, and have been used to discriminate vegetation cover types and to estimate key vegetation attributes including percent cover and green biomass. So far, however, such matrics have been calculated only from coarse resolution satellite data. Intermediate spatial resolution satellites like Landsat cannot provide the temporal resolutions needed for directly calculating such greenness matrics. In this study, we developed a method to indirectly derive annual integrated NDVI at 30 m spatial resolution using 250 m MODIS data and 30 m Landsat ETM+ imagery. Results showed that more than 90% of the variance of the annual integrated NDVI calculated using one full year’s MODIS data could be explained using as few as 3 appropriately selected observations, demonstrating the feasibility of indirectly estimating the annual integrated NDVI at intermediate spatial resolutions, as normally only limited number of useful observations would be available within the life cycle of a typical project at such spatial resolutions. The developed method was applied to two ETM+ paths/rows, for each of which 3 ETM+ images were acquired in roughly spring, summer and fall/winter seasons around the year 2000. Of the total variance of the MODIS annual integrated NDVI, 81% was explained by the three ETM+ images for one path/row and 74% for the other. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Technology - Converging at the top of the world","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","usgsCitation":"Huang, C., Tolk, B.L., Vogelmann, J., Knuppe, M., and Zhu, Z., 2003, Deriving annual integrated NDVI greenness at 30 m spatial resolution, <i>in</i> Technology - Converging at the top of the world, 7 p.","productDescription":"7 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":481934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Huang, Chengquan","contributorId":25378,"corporation":false,"usgs":true,"family":"Huang","given":"Chengquan","affiliations":[],"preferred":false,"id":927041,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tolk, Brian L. 0000-0002-9060-0266 tolk@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0266","contributorId":2992,"corporation":false,"usgs":true,"family":"Tolk","given":"Brian","email":"tolk@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":927042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":927043,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knuppe, Michelle L. 0000-0002-0374-9477 knuppe@usgs.gov","orcid":"https://orcid.org/0000-0002-0374-9477","contributorId":5148,"corporation":false,"usgs":true,"family":"Knuppe","given":"Michelle L.","email":"knuppe@usgs.gov","affiliations":[],"preferred":true,"id":927044,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":927045,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70185658,"text":"70185658 - 2003 - Microbial mercury cycling in sediments of the San Francisco Bay-Delta","interactions":[],"lastModifiedDate":"2017-03-27T11:25:07","indexId":"70185658","displayToPublicDate":"2003-12-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1583,"text":"Estuaries","active":true,"publicationSubtype":{"id":10}},"title":"Microbial mercury cycling in sediments of the San Francisco Bay-Delta","docAbstract":"<p><span>Microbial mercury (Hg) methylation and methylmercury (MeHg) degradation processes were examined using radiolabled model Hg compounds in San Francisco Bay-Delta surface sediments during three seasonal periods: late winter, spring, and fall. Strong seasonal and spatial differences were evident for both processes. MeHg production rates were positively correlated with microbial sulfate reduction rates during late winter only. MeHg production potential was also greatest during this period and decreased during spring and fall. This temporal trend was related both to an increase in gross MeHg degradation, driven by increasing temperature, and to a build-up in pore water sulfide and solid phase reduced sulfur driven by increased sulfate reduction during the warmer seasons. MeHg production decreased sharply with depth at two of three sites, both of which exhibited a corresponding increase in reduced sulfur compounds with depth. One site that was comparatively oxidized and alkaline exhibited little propensity for net MeHg production. These results support the hypothesis that net MeHg production is greatest when and where gross MeHg degradation rates are low and dissolved and solid phase reduced sulfur concentrations are low.</span></p>","language":"English","publisher":"Estuarine Research Federation","doi":"10.1007/BF02803660","usgsCitation":"Marvin-DiPasquale, M., and Agee, J.L., 2003, Microbial mercury cycling in sediments of the San Francisco Bay-Delta: Estuaries, v. 26, no. 6, p. 1517-1528, https://doi.org/10.1007/BF02803660.","productDescription":"12 p. ","startPage":"1517","endPage":"1528","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":338362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay-Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.90155029296875,\n              37.77505678240509\n            ],\n            [\n              -121.26983642578124,\n              37.77505678240509\n            ],\n            [\n              -121.26983642578124,\n              38.34165619279595\n            ],\n            [\n              -121.90155029296875,\n              38.34165619279595\n            ],\n            [\n              -121.90155029296875,\n              37.77505678240509\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58da251be4b0543bf7fda80a","contributors":{"authors":[{"text":"Marvin-DiPasquale, Mark 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":149175,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":686258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agee, Jennifer L. 0000-0002-5964-5079 jlagee@usgs.gov","orcid":"https://orcid.org/0000-0002-5964-5079","contributorId":2586,"corporation":false,"usgs":true,"family":"Agee","given":"Jennifer","email":"jlagee@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":686259,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":53123,"text":"wri034241 - 2003 - Atmospheric deposition of nutrients, pesticides, and mercury in Rocky Mountain National Park, Colorado, 2002","interactions":[],"lastModifiedDate":"2020-02-11T07:02:48","indexId":"wri034241","displayToPublicDate":"2003-12-01T00:00:00","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":"2003-4241","title":"Atmospheric deposition of nutrients, pesticides, and mercury in Rocky Mountain National Park, Colorado, 2002","docAbstract":"Nutrients, current-use pesticides, and mercury were measured in atmospheric deposition during summer in Rocky Mountain National Park in Colorado to improve understanding of the type and magnitude of atmospheric contaminants being deposited in the park. Two deposition sites were established on the east side of the park: one at an elevation of 2,902 meters near Bear Lake for nutrients and pesticides, and one at an elevation of 3,159 meters in the Loch Vale watershed for mercury. Concentrations of nutrients in summer precipitation at Bear Lake ranged from less than 0.007 to 1.29 mg N/L (milligrams of nitrogen per liter) for ammonium and 0.17 to 4.59 mg N/L for nitrate and were similar to those measured at the Loch Vale National Atmospheric Deposition Network station, where nitrogen concentrations in precipitation are among the highest in the Rocky Mountains. Atrazine, dacthal, and carbaryl were the most frequently detected pesticides at Bear Lake, with carbaryl present at the highest concentrations (0.0079 to 0.0952 ?g/L (micrograms per liter), followed by atrazine (less than 0.0070 to 0.0604 ?g/L), and dacthal (0.0030 to 0.0093 ?g/L). Mercury was detected in weekly bulk deposition samples from Loch Vale in concentrations ranging from 2.6 to 36.2 ng/L (nanograms per liter). \r\n\r\nConcentrations in summer precipitation were combined with snowpack data from a separate study to estimate annual deposition rates of these contaminants in 2002. Annual bulk nitrogen deposition in 2002 was 2.28 kg N/ha (kilograms of nitrogen per hectare) at Bear Lake and 3.35 kg N/ha at Loch Vale. Comparison of wet and bulk deposition indicated that dry deposition may account for as much as 28 percent of annual nitrogen deposition, most of which was deposited during the summer months. Annual deposition rates for three pesticides were estimated as 45.8 mg/ha (milligrams per hectare) of atrazine, 14.2 mg/ha of dacthal, and 54.8 mg/ha of carbaryl. Because of much higher pesticide concentrations in summer precipitation than in winter snow, between 80 to 90 percent of the annual pesticide deposition occurs during summer. Mercury deposition to Loch Vale was estimated at 7.1 ?g/m2 (micrograms per square meter) of which nearly 70 percent of the annual mercury deposition occurred during summer. Despite the fact that most precipitation at high-elevations falls during winter, these results emphasize the importance of monitoring precipitation chemistry during summer to improve estimates of contaminant deposition to high-elevation ecosystems in Rocky Mountain National Park.\r\n\r\nAir-parcel back trajectories were calculated using an atmospheric transport model to identify potential source regions for contaminants reaching the park. The results indicate that during the winter, the most likely source of contami-nants is from areas northwest of the park, but during summer, contaminants are most likely coming from sources to the southwest and east.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri034241","usgsCitation":"Mast, M.A., Campbell, D.H., Ingersoll, G.P., Foreman, W., and Krabbenhoft, D.P., 2003, Atmospheric deposition of nutrients, pesticides, and mercury in Rocky Mountain National Park, Colorado, 2002 (Online Only): U.S. Geological Survey Water-Resources Investigations Report 2003-4241, 15 p., https://doi.org/10.3133/wri034241.","productDescription":"15 p.","onlineOnly":"Y","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":177674,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":4702,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri034241/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.93017578125,\n              40.14109012528468\n            ],\n            [\n              -105.48110961914062,\n              40.14109012528468\n            ],\n            [\n              -105.48110961914062,\n              40.57224011776902\n            ],\n            [\n              -105.93017578125,\n              40.57224011776902\n            ],\n            [\n              -105.93017578125,\n              40.14109012528468\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Online Only","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9ae4b07f02db65d878","contributors":{"authors":[{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":246697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Donald H. dhcampbe@usgs.gov","contributorId":1670,"corporation":false,"usgs":true,"family":"Campbell","given":"Donald","email":"dhcampbe@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":246701,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ingersoll, George P. gpingers@usgs.gov","contributorId":1469,"corporation":false,"usgs":true,"family":"Ingersoll","given":"George","email":"gpingers@usgs.gov","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":246698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":246699,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":246700,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":53110,"text":"wri034138 - 2003 - Simulation of streamflow and water quality in the Red Clay Creek subbasin of the Christina River Basin, Pennsylvania and Delaware, 1994-98","interactions":[],"lastModifiedDate":"2018-02-26T15:31:41","indexId":"wri034138","displayToPublicDate":"2003-12-01T00:00:00","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":"2003-4138","title":"Simulation of streamflow and water quality in the Red Clay Creek subbasin of the Christina River Basin, Pennsylvania and Delaware, 1994-98","docAbstract":"<p>The Christina River Basin drains 565 square miles (mi<sup>2</sup>) in Pennsylvania and Delaware and includes the major subbasins of Red Clay Creek, White Clay Creek, Brandywine Creek, and Christina River. The Red Clay Creek is the smallest of the subbasins and drains an area of 54 mi<sup>2</sup>. Streams in the Christina River Basin are used for recreation, drinking-water supply, and to support aquatic life. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the stream. A multi-agency, waterquality management strategy included a modeling component to evaluate the effects of point and nonpointsource contributions of nutrients and suspended sediment on stream water quality. To assist in nonpointsource evaluation, four independent models, one for each of the four main subbasins of the Christina River Basin, 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 1 site in the Red Clay Creek subbasin and at 10 sites elsewhere in the Christina River Basin.</p><p>The HSPF model for the Red Clay Creek subbasin 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 nine reaches draining areas that ranged from 1.7 to 10 mi<sup>2</sup>. One of the reaches contains a regulated reservoir. 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 Red Clay Creek subbasin are agricultural, forested, residential, and urban.</p><p>The hydrologic component of the model was run at an hourly time step and calibrated using streamflow data from three U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Daily precipitation data from one National Oceanic and Atmospheric Administration (NOAA) gage and hourly data from one NOAA gage were used for model input. The difference between observed and simulated stream- flow volume ranged from -0.8 to 2.1 percent for the 4-year period at the three calibration sites. Annual differences between observed and simulated streamflow generally were greater than the overall error for the 4-year period. For example, at a site near Stanton, Del., near the bottom of the basin (drainage area of 50.2 mi<sup>2</sup>), annual differences between observed and simulated streamflow ranged from -5.8 to 6.0 percent and the overall error for the 4-year period was -0.8 percent. Calibration errors for 36 storm periods at the three calibration sites for total volume, low-flow-recession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the rainfall data.</p><p>The water-quality component of the model was calibrated using nonpoint-source monitoring data collected in 1998 at one USGS streamflowmeasurement station and other water-quality monitoring data collected at three USGS streamflowmeasurement stations. The period of record for waterquality monitoring was variable at the stations, with an end date of October 1998 but the start date ranging from October 1994 to January 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspendedsediment concentrations, although suspended solids may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulation. Comparison of observed to simulated loads for five storms in 1998 at the one nonpoint-source monitoring site at Wooddale, Del., indicates that simulation error commonly is as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved utrients than 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 storm events. Assessment of the accuracy of the water-quality calibration under stormflow conditions is limited by the sparsity of available water-quality data in the basin.</p><p>Users of the Red Clay Creek HSPF model should be aware of model limitations and consider the following when predictive scenarios are desired: streamflow-duration curves indicate the model simulates stream-flow reasonably well when evaluated over a broad range of conditions and time, although streamflow and the corresponding water quality for individual storm events may not be well simulated; streamflow-duration curves for the simulation period compare well with duration curves for the 57.5-year period ending in 2001 at Wooddale, Del., and include all but the extreme high-flow and low-flow events; calibration for water quality was based on sparse data, with the result of increasing uncertainty in the water-quality simulation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/wri034138","collaboration":"Prepared in cooperation with 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 Red Clay Creek subbasin of the Christina River Basin, Pennsylvania and Delaware, 1994-98: U.S. Geological Survey Water-Resources Investigations Report 2003-4138, x, 119 p., https://doi.org/10.3133/wri034138.","productDescription":"x, 119 p.","numberOfPages":"129","onlineOnly":"Y","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":122082,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/wri/2003/4138/coverthb.jpg"},{"id":4671,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wri/2003/4138/wri20034138.pdf","text":"Report","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"WRI 2003-4138"}],"contact":"<p><a href=\"mailto:dc_pa@usgs.gov\" data-mce-href=\"mailto:dc_pa@usgs.gov\">Director</a>, <a href=\"https://pa.water.usgs.gov/\" data-mce-href=\"https://pa.water.usgs.gov/\">Pennsylvania Water Science Center</a> U.S. Geological Survey<br> 215 Limekiln Road<br> New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Description of study area</li><li>Description of model</li><li>Data for model input and calibration</li><li>Simulation of streamflow</li><li>Simulation of water quality</li><li>Model applications</li><li>Summary</li><li>References cited&nbsp;</li><li>Appendixes&nbsp;</li></ul>","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b06e4b07f02db69a04e","contributors":{"authors":[{"text":"Senior, Lisa A. 0000-0003-2629-1996 lasenior@usgs.gov","orcid":"https://orcid.org/0000-0003-2629-1996","contributorId":2150,"corporation":false,"usgs":true,"family":"Senior","given":"Lisa","email":"lasenior@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":246670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koerkle, Edward H. ekoerkle@usgs.gov","contributorId":2014,"corporation":false,"usgs":true,"family":"Koerkle","given":"Edward","email":"ekoerkle@usgs.gov","middleInitial":"H.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":246669,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":53017,"text":"wri034225 - 2003 - August Median Streamflow on Ungaged Streams in Eastern Aroostook County, Maine","interactions":[],"lastModifiedDate":"2012-02-02T00:11:26","indexId":"wri034225","displayToPublicDate":"2003-12-01T00:00:00","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":"2003-4225","title":"August Median Streamflow on Ungaged Streams in Eastern Aroostook County, Maine","docAbstract":"Methods for estimating August median streamflow were developed for ungaged, unregulated streams in the eastern part of Aroostook County, Maine, with drainage areas from 0.38 to 43 square miles and mean basin elevations from 437 to 1,024 feet. Few long-term, continuous-record streamflow-gaging stations with small drainage areas were available from which to develop the equations; therefore, 24 partial-record gaging stations were established in this investigation. A mathematical technique for estimating a standard low-flow statistic, August median streamflow, at partial-record stations was applied by relating base-flow measurements at these stations to concurrent daily flows at nearby long-term, continuous-record streamflow- gaging stations (index stations). Generalized least-squares regression analysis (GLS) was used to relate estimates of August median streamflow at gaging stations to basin characteristics at these same stations to develop equations that can be applied to estimate August median streamflow on ungaged streams. GLS accounts for varying periods of record at the gaging stations and the cross correlation of concurrent streamflows among gaging stations. Twenty-three partial-record stations and one continuous-record station were used for the final regression equations.\r\n\r\nThe basin characteristics of drainage area and mean basin elevation are used in the calculated regression equation for ungaged streams to estimate August median flow. The equation has an average standard error of prediction from -38 to 62 percent. A one-variable equation uses only drainage area to estimate August median streamflow when less accuracy is acceptable. This equation has an average standard error of prediction from -40 to 67 percent. Model error is larger than sampling error for both equations, indicating that additional basin characteristics could be important to improved estimates of low-flow statistics. \r\n\r\nWeighted estimates of August median streamflow, which can be used when making estimates at partial-record or continuous-record gaging stations, range from 0.03 to 11.7 cubic feet per second or from 0.1 to 0.4 cubic feet per second per square mile. Estimates of August median streamflow on ungaged streams in the eastern part of Aroostook County, within the range of acceptable explanatory variables, range from 0.03 to 30 cubic feet per second or 0.1 to 0.7 cubic feet per second per square mile. Estimates of August median streamflow per square mile of drainage area generally increase as mean elevation and drainage area increase.","language":"ENGLISH","doi":"10.3133/wri034225","usgsCitation":"Lombard, P., Tasker, G.D., and Nielsen, M.G., 2003, August Median Streamflow on Ungaged Streams in Eastern Aroostook County, Maine: U.S. Geological Survey Water-Resources Investigations Report 2003-4225, 20 p., https://doi.org/10.3133/wri034225.","productDescription":"20 p.","costCenters":[],"links":[{"id":179355,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5125,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri034225/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4ce4b07f02db626368","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":23899,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela J.","affiliations":[],"preferred":false,"id":246388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tasker, Gary D.","contributorId":95035,"corporation":false,"usgs":true,"family":"Tasker","given":"Gary","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":246389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":246387,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":52917,"text":"wri034124 - 2003 - Development, calibration, and analysis of a hydrologic and water-quality model of the Delaware Inland Bays watershed","interactions":[],"lastModifiedDate":"2018-03-21T15:39:06","indexId":"wri034124","displayToPublicDate":"2003-12-01T00:00:00","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":"2003-4124","title":"Development, calibration, and analysis of a hydrologic and water-quality model of the Delaware Inland Bays watershed","docAbstract":"Excessive nutrients and sediment are among the most significant environmental stressors in the Delaware Inland Bays (Rehoboth, Indian River, and Little Assawoman Bays). Sources of nutrients, sediment, and other contaminants within the Inland Bays watershed include point-source discharges from industries and wastewater-treatment plants, runoff and infiltration to ground water from agricultural fields and poultry operations, effluent from on-site wastewater disposal systems, and atmospheric deposition. To determine the most effective restoration methods for the Inland Bays, it is necessary to understand the relative distribution and contribution of each of the possible sources of nutrients, sediment, and other contaminants.\r\n\r\nA cooperative study involving the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was initiated in 2000 to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed that can be used as a water-resources planning and management tool. The model code Hydrological Simulation Program - FORTRAN (HSPF) was used. The 719-square-kilometer watershed was divided into 45 model segments, and the model was calibrated using streamflow and water-quality data for January 1999 through April 2000 from six U.S. Geological Survey stream-gaging stations within the watershed. Calibration for some parameters was accomplished using PEST, a model-independent parameter estimator. Model parameters were adjusted systematically so that the discrepancies between the simulated values and the corresponding observations were minimized.\r\n\r\nModeling results indicate that soil and aquifer permeability, ditching, dominant land-use class, and land-use practices affect the amount of runoff, the mechanism or flow path (surface flow, interflow, or base flow), and the loads of sediment and nutrients. In general, the edge-of-stream total suspended solids yields in the Inland Bays watershed are low in comparison to yields reported for the Eastern Shore from the Chesapeake Bay watershed model. The flatness of the terrain and the low annual surface runoff are important factors in determining the amount of detached sediment from the land that is delivered to streams. The highest total suspended solids yields were found in the southern part of the watershed, associated with high total streamflow and a high surface runoff component, and related to soil and aquifer permeability and land use. Nutrient yields from watershed model segments in the southern part of the Inland Bays watershed were the highest of all calibrated segments, due to high runoff and the substantial amount of available organic fertilizer (animal waste), which results in over-application of organic fertilizer to crops.\r\n\r\nTime series of simulated hourly total nitrogen concentrations and observed instantaneous values indicate a seasonal pattern, with the lowest values occurring during the summer and the highest during the winter months. Total phosphorus and total suspended solids concentrations are somewhat less seasonal. During storm events, total nitrogen concentrations tend to be diluted and total phosphorus concentrations tend to rise sharply. Nitrogen is transported mainly in the aqueous phase and primarily through ground water, whereas phosphorus is strongly associated with sediment, which washes off during precipitation events.","language":"ENGLISH","doi":"10.3133/wri034124","usgsCitation":"Gutierrez-Magness, A.L., and Raffensperger, J.P., 2003, Development, calibration, and analysis of a hydrologic and water-quality model of the Delaware Inland Bays watershed: U.S. Geological Survey Water-Resources Investigations Report 2003-4124, 50 p., https://doi.org/10.3133/wri034124.","productDescription":"50 p.","costCenters":[],"links":[{"id":5006,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri034124/","linkFileType":{"id":5,"text":"html"}},{"id":124841,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/wri_2003_4124.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9be4b07f02db65dda5","contributors":{"authors":[{"text":"Gutierrez-Magness, Angelica L.","contributorId":36995,"corporation":false,"usgs":true,"family":"Gutierrez-Magness","given":"Angelica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":246226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raffensperger, Jeff P. 0000-0001-9275-6646 jpraffen@usgs.gov","orcid":"https://orcid.org/0000-0001-9275-6646","contributorId":199119,"corporation":false,"usgs":true,"family":"Raffensperger","given":"Jeff","email":"jpraffen@usgs.gov","middleInitial":"P.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":246227,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":52924,"text":"wri034035 - 2003 - Residence times and nitrate transport in ground water discharging to streams in the Chesapeake Bay Watershed","interactions":[],"lastModifiedDate":"2021-07-02T14:15:01.692846","indexId":"wri034035","displayToPublicDate":"2003-12-01T00:00:00","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":"2003-4035","title":"Residence times and nitrate transport in ground water discharging to streams in the Chesapeake Bay Watershed","docAbstract":"<p>One of the major water-quality problems in the Chesapeake Bay is an overabundance of nutrients from the streams and rivers that discharge to the Bay. Some of these nutrients are from nonpoint sources such as atmospheric deposition, agricultural manure and fertilizer, and septic systems. The effects of efforts to control nonpoint sources, however, can be difficult to quantify because of the lag time between changes at the land surface and the response in the base-flow (ground water) component of streams. To help resource managers understand the lag time between implementation of management practices and subsequent response in the nutrient concentrations in the base-flow component of streamflow, a study of ground-water discharge, residence time, and nitrate transport in springs throughout the Chesapeake Bay Watershed and in four smaller watersheds in selected hydrogeomorphic regions (HGMRs) was conducted. The four watersheds were in the Coastal Plain Uplands, Piedmont crystalline, Valley and Ridge carbonate, and Valley and Ridge siliciclastic HGMRs.</p><p>A study of springs to estimate an apparent age of the ground water was based on analyses for concentrations of chlorofluorocarbons in water samples collected from 48 springs in the Chesapeake Bay Watershed. Results of the analysis indicate that median age for all the samples was 10 years, with the 25th percentile having an age of 7 years and the 75th percentile having an age of 13 years. Although the number of samples collected in each HGMR was limited, there did not appear to be distinct differences in the ages between the HGMRs. The ranges were similar between the major HGMRs above the Fall Line (modern to about 50 years), with only two HGMRs of small geographic extent (Piedmont carbonate and Mesozoic Lowland) having ranges of modern to about 10 years. The median values of all the HGMRs ranged from 7 to 11 years. Not enough samples were collected in the Coastal Plain for comparison. Spring samples showed slightly younger water under wet conditions than under dry conditions. The apparent age of water from wells, springs, and other ground-water discharge points in the four targeted watersheds was modern to 60 years, which was similar to the apparent ages from the spring study. In the Pocomoke River Watershed in the Coastal Plain Uplands HGMR, the apparent age of ground-water samples ranged from 0 to 60 years; the ages in the vicinity of the streams ranged from 0 to 23 years.</p><p>The apparent ages of ground water in the Polecat Creek Watershed in the Piedmont crystalline HGMR ranged from 2 to 30 years. The apparent ages of water from wells in the Muddy Creek Watershed in the Valley and Ridge carbonate HGMR ranged from 10 to 20 years (except for a single sample that was 45 years). The ages in the East Mahantango Creek Watershed in the Valley and Ridge siliciclastic HGMR ranged from 0 to 50 years. The distribution in apparent age of water from wells in the targeted watersheds, however, generally is older than that for water from the springs. The median age of water from wells in the Muddy Creek Watershed, for example, was 15 years, compared to 11 years for the water from the springs in that watershed, and less than 10 years for water from all springs in the spring study. The similarity in the ranges in apparent age of water from the wells and from the springs shows that the samples from the targeted watersheds and springs have bracketed the range of apparent ages that would be expected in the shallow ground-water-flow systems throughout the Chesapeake Bay Watershed.</p><p>The apparent age of water from individual wells does not necessarily represent the entire distribution of ages of the discharging ground water, and it is this distribution of ages that affects the response of nutrient concentrations in stream base flow. Nutrient-reduction scenarios were modeled for two watersheds for which the distribution of apparent ground-water ages was available, the East Mahantango Creek Watershed in the Valley and Ridge siliciclastic HGMR and the Locust Grove Watershed in the Coastal Plain Uplands HGMR. A nutrient-reduction scenario was created for East Mahantango Creek, where the average residence time was determined to be approximately 10 years on the basis of the output of particle tracking from a ground-water-flow model. This scenario showed decreases of nearly 50 percent in base-flow concentrations of nitrate in streams within the first year after the reduction in nitrogen input; smaller reductions in nitrate concentration occurred in each subsequent year. A second scenario for that same watershed, in which the same 10-year average residence time was assumed and an exponential model was used for analysis, showed that a 50-percent reduction in base-flow concentrations of nitrate could take up to 5 years. For the Locust Grove Watershed, in which an average residence time of 32 years was assumed, simulation with the exponential model showed that it may take more than 20 years to achieve a 50-percent reduction in base-flow concentra-tions of nitrate. Although it was not possible to construct such scenarios for all watersheds, these examples show the range of possible responses to changes in nutrient inputs in two very different types of watersheds.</p><p>Findings from this study include information on factors that affect ground-water age, spatial distribution of ages, and nitrogen transport. In the East Mahantango Creek Watershed and the Polecat Creek Watershed, the residence time varied spatially depending on the position of the flow path, and temporally depending on the recharge conditions. Generally, ground water in areas near the stream had short residence times and the water in upland areas had longer residence times. Water traveling through deep layers had longer residence times than water traveling through shallow layers, and residence times were faster under high recharge conditions than low recharge conditions. Ground water in the Pocomoke Watershed exhibits a similar pattern: younger water discharges to small order streams in headwater basins and older water discharges to larger streams near the basin outlet.</p><p>Factors affecting nitrogen transport in ground water include spatial and temporal variation in input sources, ground-water age, and aquifer processes that lead to denitrification. Spatial and temporal variations in nitrogen sources affect all the watersheds. Tributaries with higher inputs of nitrogen have higher concentrations in stream base flow. Areas where nitrogen application rates have increased over time show an age-nitrate relation in ground-water samples. The age-nitrate relation can be affected by denitrification, which occurs in Pocomoke and East Mahantango Creeks but is not evident in Polecat and Muddy Creeks. In East Mahantango Creek, the level of denitrification is significant in water with residence times greater than 20 years, but because this is a small component of overall ground-water discharge to a stream, it may not remove a significant quantity of nitrogen from the system. Denitrification in Pocomoke Creek is significant and appears to affect mostly older water discharging to streams. Therefore, if most of the nitrogen entering these two streams is associated with the discharge of younger ground water, denitrification may not greatly affect the overall nitrogen delivery to these streams.</p><p>Other findings of this study show that nitrate in ground water discharging along preferential flow paths may not be affected by natural processes, such as denitrification or uptake by riparian vegetation. Seeps to swales and ditches beneath the north uplands at Polecat Creek indicate a shallow water table and discharge of young ground water whereas the absence of such seeps on the south side indicates a deep water table and a lack of young ground water. Similarly, discharge at the base of the slope and to the valley wetland south of the creek but not north of the creek indicates a different role for the riparian forest on the two sides of the creek. In many of the systems where water discharges at the base of slopes to wetlands, ditches have been dug to drain the valley. Such drainage circumvents possible removal of nitrate by riparian vegetation.</p><p>Because ground-water residence times do not appear directly related to the HGMRs, the targeting of management practices will achieve the most rapid response in water quality if directed at 1) watersheds with large agricultural sources of nitrate, 2) areas with the shortest ground-water-flow paths and 3) areas not affected by significant denitrification. The fastest response in stream base-flow concentrations of nitrogen to implementation of management practices would be to implement practices in those areas with the highest loads rather than attempt to target practices on the basis of HGMR stratification. Overall findings of the study indicate that 1) ground-water contributions to nitrogen in streamflow are significant, 2) some response to management practices should be evident in base-flow concentrations of nitrogen and loads within 1 to 5 years in watersheds with the shortest average residence times, but response time may be closer to 20 years in watersheds with longer average ground-water residence times, 3) the majority of the response in ground-water discharge to any changes in management practices will be distributed over a 10-year time period even in the watersheds with the fastest response times, and 4) given that half the streamflow is from ground-water discharge and the other half is runoff or soil water, about 90 percent of total water being discharged to a stream will be less than about a decade old; therefore, full implementation of nutrient reductions may result in improved streamwater quality in about a decade. In the more-likely scenario of gradual source reduction, the reduction in concentrations of nitrate in streams and aquifers would take longer than the examples shown here.</p>","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri034035","collaboration":"Prepared in cooperation with the Chesapeake Bay Program","usgsCitation":"Lindsey, B., Phillips, S., Donnelly, C.A., Speiran, G.K., Plummer, N., Bohlke, J., Focazio, M.J., Burton, W.C., and Busenberg, E., 2003, Residence times and nitrate transport in ground water discharging to streams in the Chesapeake Bay Watershed: U.S. Geological Survey Water-Resources Investigations Report 2003-4035, xiv, 201 p., https://doi.org/10.3133/wri034035.","productDescription":"xiv, 201 p.","onlineOnly":"Y","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology 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href=\"mailto:dc_pa@usgs.gov\" data-mce-href=\"mailto:dc_pa@usgs.gov\">Director</a>, <a href=\"https://pa.water.usgs.gov/\" data-mce-href=\"https://pa.water.usgs.gov/\">Pennsylvania Water Science Center</a> U.S. Geological Survey<br> 215 Limekiln Road<br> New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Study design and data-collection methods&nbsp;</li><li>Approaches for ground-water dating, by L. Niel Plummer, John-Karl Böhlke, and Eurybiades Busenberg</li><li>Sources, transport, and reaction of nitrate, by John-Karl Böhlke&nbsp;</li><li>Ground-water residence time and nitrogen concentration&nbsp;</li><li>Summary</li><li>Conclusion</li><li>References cited&nbsp;</li></ul>","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a53e4b07f02db62ba1d","contributors":{"authors":[{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":434,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce D.","email":"blindsey@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":246237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Scott swphilli@usgs.gov","contributorId":3515,"corporation":false,"usgs":true,"family":"Phillips","given":"Scott","email":"swphilli@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":246242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donnelly, Colleen A.","contributorId":62240,"corporation":false,"usgs":true,"family":"Donnelly","given":"Colleen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":246244,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Speiran, Gary K. 0000-0002-6505-1170 gspeiran@usgs.gov","orcid":"https://orcid.org/0000-0002-6505-1170","contributorId":3233,"corporation":false,"usgs":true,"family":"Speiran","given":"Gary","email":"gspeiran@usgs.gov","middleInitial":"K.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":246241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plummer, Niel 0000-0002-4020-1013 nplummer@usgs.gov","orcid":"https://orcid.org/0000-0002-4020-1013","contributorId":190100,"corporation":false,"usgs":true,"family":"Plummer","given":"Niel","email":"nplummer@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":246243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bohlke, John Karl 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":66293,"corporation":false,"usgs":true,"family":"Bohlke","given":"John Karl","affiliations":[],"preferred":false,"id":246245,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":246238,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burton, William C. 0000-0001-7519-5787 bburton@usgs.gov","orcid":"https://orcid.org/0000-0001-7519-5787","contributorId":1293,"corporation":false,"usgs":true,"family":"Burton","given":"William","email":"bburton@usgs.gov","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":246239,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Busenberg, Eurybiades ebusenbe@usgs.gov","contributorId":2271,"corporation":false,"usgs":true,"family":"Busenberg","given":"Eurybiades","email":"ebusenbe@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":246240,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":53171,"text":"pp1683 - 2003 - The Role of Geoscience Information in Reducing Catastrophic Loss Using a Web-Based Economics Experiment","interactions":[],"lastModifiedDate":"2012-02-02T00:11:46","indexId":"pp1683","displayToPublicDate":"2003-12-01T00:00:00","publicationYear":"2003","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1683","title":"The Role of Geoscience Information in Reducing Catastrophic Loss Using a Web-Based Economics Experiment","docAbstract":"What role can geoscience information play in the assessment of risk and the value of insurance, especially for natural hazard type risks? In an earlier, related paper Ganderton and others (2000) provided subjects with relatively simple geoscience information concerning natural hazard-type risks. Their research looked at how subjects purchase insurance when faced with relatively low probability but high loss risks of the kind that characterize natural hazards and now, increasingly, manmade disasters. They found evidence to support the expected utility theory (definitions of economics terms can be found in a glossary at the end of report), yet there remained the implication that subjects with excessive aversion to risk were willing to pay considerably more for insurance than the actuarially fair price plus any reasonable risk premium. Here, we report the results of additional experiments that provide further support for the basic postulates of expected utility theory. However, these new experiments add considerably to the decision environment facing subjects by offering an option to purchase geoscientific information that would assist them when calculating expected losses from hazards more accurately. \r\n\r\nUsing an Internet-based mechanism to present information and gather data in an experimental setting, this research provided subjects with considerable textual and graphical information, and time to process it. Over a period of three months, almost 400 subjects participated in on-line experiments that generated approximately 22,000 usable data points for the empirical analysis discussed in this report. \r\n\r\nIn the design of the experiment, we modeled the decisions to purchase (1) a detailed map giving subjects more information regarding the distribution of losses from a hazard and (2) insurance to indemnify them from any losses should they occur. On the basis of this design, we find strong evidence in support of the expected utility theory. Many of the findings reinforce those found in the early, similar study (Ganderton and others, 2000). However, this research also finds interactions between the decision to become better informed and the decision to insure. We chose an empirical framework that allows for both explicit and implicit (unobservable) correlations between the two decisions. The results suggest that at the end of the computer game subjects recognize the benefits of greater geoscience information. They take advantage of it, but are sensitive to its cost. When subjects use the more detailed information, they are more likely to purchase insurance when it offers a net benefit. ","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/pp1683","usgsCitation":"Bernknopf, R.L., Brookshire, D.S., and Ganderton, P.T., 2003, The Role of Geoscience Information in Reducing Catastrophic Loss Using a Web-Based Economics Experiment (Version 1.0): U.S. Geological Survey Professional Paper 1683, v, 29 p., https://doi.org/10.3133/pp1683.","productDescription":"v, 29 p.","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":124591,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1683.jpg"},{"id":11437,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1683/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac7e4b07f02db67ac91","contributors":{"authors":[{"text":"Bernknopf, Richard L.","contributorId":97061,"corporation":false,"usgs":true,"family":"Bernknopf","given":"Richard","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":246819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brookshire, David S.","contributorId":32537,"corporation":false,"usgs":true,"family":"Brookshire","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":246818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganderton, Philip T.","contributorId":11062,"corporation":false,"usgs":true,"family":"Ganderton","given":"Philip","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":246817,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":53184,"text":"wri034191 - 2003 - Nutrient and chlorophyll relations in selected streams of the New England coastal basins in Massachusetts and New Hampshire, June-September 2001","interactions":[],"lastModifiedDate":"2023-03-15T20:27:11.312632","indexId":"wri034191","displayToPublicDate":"2003-12-01T00:00:00","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":"2003-4191","title":"Nutrient and chlorophyll relations in selected streams of the New England coastal basins in Massachusetts and New Hampshire, June-September 2001","docAbstract":"<p>The U.S. Environmental Protection Agency is developing guidance to assist states with defining nutrient criteria for rivers and streams and to better describe nutrient-algal relations. As part of this effort, 13 wadeable stream sites were selected, primarily in eastern Massachusetts, for a nutrient-assessment study during the summer of 2001. The sites represent a range of water-quality impairment conditions (reference, moderately impaired, impaired) based on state regulatory agency assessments and previously assessed nitrogen, phosphorus, and dissolved-oxygen data. In addition, a combination of open- and closed-canopy locations were sampled at six of the sites to investigate the effect of sunlight on algal growth. Samples for nutrients and for chlorophyll I from phytoplankton and periphyton were collected at all stream sites.</p><p>Total nitrogen (dissolved nitrite + nitrate + total ammonia + organic nitrogen) and total phosphorus (phosphorus in an unfiltered water sample) concentrations were lowest at reference sites and highest at impaired sites. There were statistically significant differences (p &lt; 0.05) among reference, moderately impaired, and impaired sites for total nitrogen and total phosphorus. Chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>concentrations from phytoplankton were not significantly different among site impairment designations. Concentrations of chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>from periphyton were highest at nutrient-impaired open-canopy sites. Chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>concentrations from periphyton samples were positively correlated with total nitrogen and total phosphorus at the open- and closed-canopy sites. Correlations were higher at open-canopy sites (p &lt; 0.05, rho = 0.64 to 0.71) than at closed-canopy sites (p &lt; 0.05, rho = 0.36 to 0.40). Statistically significant differences in the median concentrations of chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>from periphyton samples were observed between the open- and closed-canopy sites (p &lt; 0.05).</p><p>Total nitrogen and total phosphorus data from moderately impaired and impaired sites in this study exceeded the preliminary U.S. Environmental Protection Agency nutrient criteria values for the coastal region of New England. In an effort to establish more appropriate nutrient and chlorophyll criteria for streams in the New England coastal region, relations between total nitrogen and total phosphorus to periphyton chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>in wadeable streams from this study were quantified to present potential techniques for determining nutrient concentrations. Linear regression was used to estimate the total nitrogen and total phosphorus concentrations that corresponded to various chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>concentrations. On the basis of this relation, a median concentration for moderately enriched streams of 21 milligrams per square meter (mg/m<sup>2</sup>) of periphyton chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>from the literature corresponded to estimated concentrations of 1.3 milligrams per liter (mg/L) for total nitrogen and 0.12 mg/L for total phosphorus. The median concentration for periphyton chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>from the literature is similar to the 50<sup>th</sup>-percentile concentration of periphyton chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>(17 mg/m<sup>2</sup>) calculated with the data from open-canopy sites in this study. The 25<sup>th</sup>-percentile concentration for periphyton chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>of all open-canopy sites (5.2 mg/m<sup>2</sup>) and the 75<sup>th</sup>-percentile concentration for periphyton chlorophyll<span>&nbsp;</span><i>a</i><span>&nbsp;</span>of open-canopy reference sites (16 mg/m<sup>2</sup>) also were plotted to provide additional estimates and methods for developing total nitrogen and total phosphorus criteria.</p><p>The 25<sup>th</sup>-percentile concentrations of total nitrogen and total phosphorus were calculated based on all sites in this study and were used as another potential criteria estimation. A concentration of 0.64 mg/L for total nitrogen and 0.030 mg/L for total phosphorus were calculated. As another possible method to develop threshold concentrations, the 10<sup>th</sup>-percentile concentrations of total nitrogen and total phosphorus were calculated based on all the impaired sites in this study. A concentration threshold of 0.73 mg/L for total nitrogen and 0.036 mg/L for total phosphorus were calculated. Ultimately, a combination of these techniques may be appropriate for water-resources managers to use to set regional nutrient criteria to limit undesirable levels of algal growth in streams.</p>","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri034191","usgsCitation":"Riskin, M.L., Deacon, J.R., Liebman, M., and Robinson, K.W., 2003, Nutrient and chlorophyll relations in selected streams of the New England coastal basins in Massachusetts and New Hampshire, June-September 2001: U.S. Geological Survey Water-Resources Investigations Report 2003-4191, vii, 16 p., https://doi.org/10.3133/wri034191.","productDescription":"vii, 16 p.","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":177850,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":414256,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_61980.htm","linkFileType":{"id":5,"text":"html"}},{"id":4764,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri034191/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts, New Hampshire","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -72,\n              43.0833\n            ],\n            [\n              -72,\n              41.9\n            ],\n            [\n              -70.8333,\n              41.9\n            ],\n            [\n              -70.8333,\n              43.0833\n            ],\n            [\n              -72,\n              43.0833\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1ae4b07f02db6a7ffa","contributors":{"authors":[{"text":"Riskin, Melissa L. 0000-0001-6499-3775 mriskin@usgs.gov","orcid":"https://orcid.org/0000-0001-6499-3775","contributorId":654,"corporation":false,"usgs":true,"family":"Riskin","given":"Melissa","email":"mriskin@usgs.gov","middleInitial":"L.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":246850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deacon, J. R.","contributorId":67110,"corporation":false,"usgs":true,"family":"Deacon","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":246852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liebman, M. L.","contributorId":81926,"corporation":false,"usgs":true,"family":"Liebman","given":"M. L.","affiliations":[],"preferred":false,"id":246853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinson, K. W.","contributorId":27488,"corporation":false,"usgs":true,"family":"Robinson","given":"K.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":246851,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70210110,"text":"70210110 - 2003 - Thermal and chemical variations in subcrustal cratonic lithosphere: Evidence from crustal isostasy","interactions":[],"lastModifiedDate":"2020-05-14T15:49:36.352635","indexId":"70210110","displayToPublicDate":"2003-11-06T10:47:08","publicationYear":"2003","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2588,"text":"LITHOS","active":true,"publicationSubtype":{"id":10}},"title":"Thermal and chemical variations in subcrustal cratonic lithosphere: Evidence from crustal isostasy","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"aep-abstract-id5\" class=\"abstract author\"><div id=\"aep-abstract-sec-id6\"><p>The Earth's topography at short wavelengths results from active tectonic processes, whereas at long wavelengths it is largely determined by isostatic adjustment for the density and thickness of the crust. Using a global crustal model, we estimate the long-wavelength topography that is not due to crustal isostasy. Our most important finding is that cratons are generally depressed by 300 to 1500 m in comparison with predictions from pure crustal isostasy. We conclude that either: (1) cratonic roots may be 50 to 300 °C colder than previously suggested by thermal models, or (2) cratonic roots may be, on average, less depleted than suggested by studies of shallow mantle xenoliths. Alternatively, (3) some combination of these conditions may exist. The thermal explanation is consistent with recent geothermal studies that indicate low cratonic temperatures, as well as seismic studies that show very low seismic attenuation at long periods (150 s) beneath cratons. The petrologic explanation is consistent with recent studies of deep (&gt;140 km) mantle xenoliths from the Kaapvaal and Slave cratons that show 1–2% higher densities compared with shallow (&lt;140 km), highly depleted xenoliths.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2003.07.004","usgsCitation":"Mooney, W.D., and Vidale, J.E., 2003, Thermal and chemical variations in subcrustal cratonic lithosphere: Evidence from crustal isostasy: LITHOS, v. 71, no. 2-4, p. 185-193, https://doi.org/10.1016/j.lithos.2003.07.004.","productDescription":"9 p.","startPage":"185","endPage":"193","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":374827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"71","issue":"2-4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mooney, Walter D. 0000-0002-5310-3631 mooney@usgs.gov","orcid":"https://orcid.org/0000-0002-5310-3631","contributorId":3194,"corporation":false,"usgs":true,"family":"Mooney","given":"Walter","email":"mooney@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":789167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vidale, John E.","contributorId":48850,"corporation":false,"usgs":true,"family":"Vidale","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":789168,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":69708,"text":"i2766 - 2003 - Geologic map of the Mount Trumbull 30' X 60' quadrangle, Mohave and Coconino Counties, northwestern Arizona","interactions":[],"lastModifiedDate":"2022-04-14T18:33:04.692821","indexId":"i2766","displayToPublicDate":"2003-11-01T00:00:00","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":"2766","title":"Geologic map of the Mount Trumbull 30' X 60' quadrangle, Mohave and Coconino Counties, northwestern Arizona","docAbstract":"The geologic map of the Mount Trumbull 30' x 60' quadrangle is a cooperative product of the U.S. Geological Survey, the National Park Service, and the Bureau of Land Management that provides geologic map coverage and regional geologic information for visitor services and resource management of Grand Canyon National Park, Lake Mead Recreational Area, and Grand Canyon Parashant National Monument, Arizona. This map is a compilation of previous and new geologic mapping that encompasses the Mount Trumbull 30' x 60' quadrangle of Arizona.\n\n\n     This digital database, a compilation of previous and new geologic mapping, contains geologic data used to produce the 100,000-scale Geologic Map of the Mount Trumbull 30' x 60' Quadrangle, Mohave and Coconino Counties, Northwestern Arizona.  The geologic features that were mapped as part of this project include:  geologic contacts and faults, bedrock and surficial geologic units, structural data, fold axes, karst features, mines, and volcanic features.\n\n      This map was produced using 1:24,000-scale 1976 infrared aerial photographs followed by extensive field checking. Volcanic rocks were mapped as separate units when identified on aerial photographs as mappable and distinctly separate units associated with one or more pyroclastic cones and flows. Many of the Quaternary alluvial deposits that have similar lithology but different geomorphic characteristics were mapped almost entirely by photogeologic methods. Stratigraphic position and amount of erosional degradation were used to determine relative ages of alluvial deposits having similar lithologies. Each map unit and structure was investigated in detail in the field to ensure accuracy of description.\n\n      Punch-registered mylar sheets were scanned at the Flagstaff Field Center using an Optronics 5040 raster scanner at a resolution of 50 microns (508 dpi). The scans were output in .rle format, converted to .rlc, and then converted to ARC/INFO grids. A tic file was created in geographic coordinates and projected into the base map projection (Polyconic) using a central meridian of -113.500. The tic file was used to transform the grid into Universal Transverse Mercator projection.\n\n      The linework was vectorized using gridline. Scanned lines were edited interactively in ArcEdit. Polygons were attributed in ArcEdit and all artifacts and scanning errors visible at 1:100,000 were removed. Point data were digitized onscreen.\n\n      Due to the discovery of digital and geologic errors on the original files, the ARC/INFO coverages were converted to a personal geodatabase and corrected in ArcMap. The feature classes which define the geologic units, lines and polygons, are topologically related and maintained in the geodatabase by a set of validation rules.\n\n      The internal database structure and feature attributes were then modified to match other geologic map databases being created for the Grand Canyon region.  Faults were edited with the downthrown block, if known, on the 'right side' of the line.  The 'right' and 'left' sides of a line are determined from 'starting' at the line's 'from node' and moving to the line's end or 'to node'.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/i2766","usgsCitation":"Billingsley, G.H., and Wellmeyer, J.L., 2003, Geologic map of the Mount Trumbull 30' X 60' quadrangle, Mohave and Coconino Counties, northwestern Arizona: U.S. Geological Survey IMAP 2766, Report; 36 p.; 1 Plate: 38.50 × 54.51 inches: Database; Metadata; Readme, https://doi.org/10.3133/i2766.","productDescription":"Report; 36 p.; 1 Plate: 38.50 × 54.51 inches: Database; Metadata; Readme","additionalOnlineFiles":"Y","costCenters":[{"id":647,"text":"Western Earth Surface Processes","active":false,"usgs":true}],"links":[{"id":191350,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":398741,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_62285.htm"},{"id":263760,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/imap/i2766/mtr_shape.zip"},{"id":263759,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/imap/i2766/mtr_db.zip"},{"id":263758,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/imap/i2766/mtrmeta.txt"},{"id":263757,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/imap/i2766/i2766_pamphlet.pdf"},{"id":263756,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/imap/i2766/mtrreadme.txt"},{"id":263755,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/imap/i2766/i2766_map.pdf"},{"id":6379,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/imap/i2766","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","country":"United States","state":"Arizona","county":"Coconino County, Mohave County","otherGeospatial":"Mount Trumbull 30' X 60' quadrangle","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114,36 ], [ -114,36.5 ], [ -113,36.5 ], [ -113,36 ], [ -114,36 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b12e4b07f02db6a2cd7","contributors":{"authors":[{"text":"Billingsley, George H.","contributorId":20711,"corporation":false,"usgs":true,"family":"Billingsley","given":"George","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":280952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wellmeyer, Jessica L.","contributorId":8177,"corporation":false,"usgs":true,"family":"Wellmeyer","given":"Jessica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":280951,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":69710,"text":"i2600G - 2003 - Coastal-change and glaciological map of the Saunders Coast area, Antarctica: 1972-1997","interactions":[],"lastModifiedDate":"2019-11-14T16:18:07","indexId":"i2600G","displayToPublicDate":"2003-11-01T00:00:00","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":"2600","chapter":"G","title":"Coastal-change and glaciological map of the Saunders Coast area, Antarctica: 1972-1997","docAbstract":"Changes in the area and volume of polar ice sheets are intricately linked to changes in global climate, and the resulting changes in sea level may severely impact the densely populated coastal regions on Earth. Melting of the West Antarctic part alone of the Antarctic ice sheet could cause a sea-level rise of approximately 6 meters (m). The potential sea-level rise after melting of the entire Antarctic ice sheet is estimated to be 65 m (Lythe and others, 2001) to 73 m (Williams and Hall, 1993). In spite of its importance, the mass balance (the net volumetric gain or loss) of the Antarctic ice sheet is poorly known; it is not known for certain whether the ice sheet is growing or shrinking. In a review paper, Rignot and Thomas (2002) concluded that the West Antarctic part of the Antarctic ice sheet is probably becoming thinner overall; although the western part is thickening, the northern part is thinning. Joughin and Tulaczyk (2002), based on analysis of ice-flow velocities derived from synthetic aperture radar, concluded that most of the Ross ice streams (ice streams on the east side of the Ross Ice Shelf) have a positive mass balance. The mass balance of the East Antarctic is unknown, but thought to be in near equilibrium.\r\n\r\nMeasurement of changes in area and mass balance of the Antarctic ice sheet was given a very high priority in recommendations by the Polar Research Board of the National Research Council (1986), in subsequent recommendations by the Scientific Committee on Antarctic Research (SCAR) (1989, 1993), and by the National Science Foundation?s (1990) Division of Polar Programs. On the basis of these recommendations, the U.S. Geological Survey (USGS) decided that the archive of early 1970s Landsat 1, 2, and 3 Multispectral Scanner (MSS) images of Antarctica and the subsequent repeat coverage made possible with Landsat and other satellite images provided an excellent means of documenting changes in the coastline of Antarctica (Ferrigno and Gould, 1987). The availability of this information provided the impetus for carrying out a comprehensive analysis of the glaciological features of the coastal regions and changes in ice fronts of Antarctica (Swithinbank, 1988; Williams and Ferrigno, 1988). The project was later modified to include Landsat 4 and 5 MSS and Thematic Mapper (TM) (and in some areas Landsat 7 Enhanced Thematic Mapper Plus (ETM+)), RADARSAT images, and other data where available, to compare changes over a 20- to 25- or 30-year time interval (or longer where data were available, as in the Antarctic Peninsula). The results of the analysis are being used to produce a digital database and a series of USGS Geologic Investigations Series Maps consisting of 24 maps at 1:1,000,000 scale and 1 map at 1:5,000,000 scale, in both paper and digital format (Williams and others, 1995; Williams and Ferrigno, 1998; and Ferrigno and others, 2002).\r\n","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Coastal-change and glaciological maps of Antarctica","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/i2600G","isbn":"0607942800","usgsCitation":"Swithinbank, C., Williams, R., Ferrigno, J.G., Foley, K.M., Hallam, C.A., and Rosanova, C.E., 2003, Coastal-change and glaciological map of the Saunders Coast area, Antarctica: 1972-1997 (Version 1.0): U.S. Geological Survey IMAP 2600, Report: 9 p.; 1 Plate: 50.00 x 40.00 inches, https://doi.org/10.3133/i2600G.","productDescription":"Report: 9 p.; 1 Plate: 50.00 x 40.00 inches","temporalStart":"1972-01-01","temporalEnd":"1997-12-31","costCenters":[],"links":[{"id":191412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":369237,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/imap/2600/G/i2600g.pdf","text":"Report"},{"id":369238,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/imap/2600/G/SaundersCoast.pdf","text":"Plate 1"},{"id":6381,"rank":0,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/imap/2600/G/","linkFileType":{"id":5,"text":"html"}}],"scale":"1000000","projection":"Polar stereographic, MSL","otherGeospatial":"Antarctica","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.890625,\n              -70.95969716686398\n            ],\n            [\n              156.4453125,\n              -70.95969716686398\n            ],\n            [\n              156.4453125,\n              -67.74275906666388\n            ],\n            [\n              -87.890625,\n              -67.74275906666388\n            ],\n            [\n              -87.890625,\n              -70.95969716686398\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6aea04","contributors":{"authors":[{"text":"Swithinbank, Charles","contributorId":26368,"corporation":false,"usgs":true,"family":"Swithinbank","given":"Charles","email":"","affiliations":[],"preferred":false,"id":280956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Richard S. Jr.","contributorId":90679,"corporation":false,"usgs":true,"family":"Williams","given":"Richard S.","suffix":"Jr.","affiliations":[],"preferred":false,"id":280960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrigno, Jane G. jferrign@usgs.gov","contributorId":39825,"corporation":false,"usgs":true,"family":"Ferrigno","given":"Jane","email":"jferrign@usgs.gov","middleInitial":"G.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":280957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":280955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hallam, Cheryl A.","contributorId":59012,"corporation":false,"usgs":true,"family":"Hallam","given":"Cheryl","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":280958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosanova, Christine E.","contributorId":77239,"corporation":false,"usgs":true,"family":"Rosanova","given":"Christine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":280959,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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