{"pageNumber":"1194","pageRowStart":"29825","pageSize":"25","recordCount":40894,"records":[{"id":70023199,"text":"70023199 - 2000 - Comparison of phase velocities from array measurements of Rayleigh waves associated with microtremor and results calculated from borehole shear-wave velocity profiles","interactions":[],"lastModifiedDate":"2014-01-21T15:09:17","indexId":"70023199","displayToPublicDate":"2000-06-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of phase velocities from array measurements of Rayleigh waves associated with microtremor and results calculated from borehole shear-wave velocity profiles","docAbstract":"Shear-wave velocities (V<sub>S</sub>) are widely used for earthquake ground-motion site characterization. V<sub>S</sub> data are now largely obtained using borehole methods. Drilling holes, however, is expensive. Nonintrusive surface methods are inexpensive for obtaining V<sub>S</sub> information, but not many comparisons with direct borehole measurements have been published. Because different assumptions are used in data interpretation of each surface method and public safety is involved in site characterization for engineering structures, it is important to validate the surface methods by additional comparisons with borehole measurements. We compare results obtained from a particular surface method (array measurement of surface waves associated with microtremor) with results obtained from borehole methods. Using a 10-element nested-triangular array of 100-m aperture, we measured surface-wave phase velocities at two California sites, Garner Valley near Hemet and Hollister Municipal Airport. The Garner Valley site is located at an ancient lake bed where water-saturated sediment overlies decomposed granite on top of granite bedrock. Our array was deployed at a location where seismic velocities had been determined to a depth of 500 m by borehole methods. At Hollister, where the near-surface sediment consists of clay, sand, and gravel, we determined phase velocities using an array located close to a 60-m deep borehole where downhole velocity logs already exist. Because we want to assess the measurements uncomplicated by uncertainties introduced by the inversion process, we compare our phase-velocity results with the borehole V<sub>S</sub> depth profile by calculating fundamental-mode Rayleigh-wave phase velocities from an earth model constructed from the borehole data. For wavelengths less than ~2 times of the array aperture at Garner Valley, phase-velocity results from array measurements agree with the calculated Rayleigh-wave velocities to better than 11%. Measurement errors become larger for wavelengths 2 times greater than the array aperture. At Hollister, the measured phase velocity at 3.9 Hz (near the upper edge of the microtremor frequency band) is within 20% of the calculated Rayleigh-wave velocity. Because shear-wave velocity is the predominant factor controlling Rayleigh-wave phase velocities, the comparisons suggest that this nonintrusive method can provide V<sub>S</sub> information adequate for ground-motion estimation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","doi":"10.1785/0119980186","issn":"00371106","usgsCitation":"Liu, H., Boore, D.M., Joyner, W.B., Oppenheimer, D.H., Warrick, R.E., Zhang, W., Hamilton, J.C., and Brown, L.T., 2000, Comparison of phase velocities from array measurements of Rayleigh waves associated with microtremor and results calculated from borehole shear-wave velocity profiles: Bulletin of the Seismological Society of America, v. 90, no. 3, p. 666-678, https://doi.org/10.1785/0119980186.","productDescription":"13 p.","startPage":"666","endPage":"678","numberOfPages":"13","costCenters":[],"links":[{"id":233411,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281345,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0119980186"}],"scale":"24000","country":"United States","state":"California","city":"Hemet;Hollister","otherGeospatial":"Garner Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.709005,33.62999 ], [ -116.709005,33.677531 ], [ -116.646886,33.677531 ], [ -116.646886,33.62999 ], [ -116.709005,33.62999 ] ] ] } } ] }","volume":"90","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f880e4b0c8380cd4d148","contributors":{"authors":[{"text":"Liu, Hsi-Ping","contributorId":82705,"corporation":false,"usgs":true,"family":"Liu","given":"Hsi-Ping","email":"","affiliations":[],"preferred":false,"id":396812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":396806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joyner, William B.","contributorId":39786,"corporation":false,"usgs":true,"family":"Joyner","given":"William","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":396808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oppenheimer, David H. oppen@usgs.gov","contributorId":1112,"corporation":false,"usgs":true,"family":"Oppenheimer","given":"David","email":"oppen@usgs.gov","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":396805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warrick, Richard E.","contributorId":56228,"corporation":false,"usgs":true,"family":"Warrick","given":"Richard","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":396810,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhang, Wenbo","contributorId":54235,"corporation":false,"usgs":true,"family":"Zhang","given":"Wenbo","email":"","affiliations":[],"preferred":false,"id":396809,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hamilton, John C. jhamilton@usgs.gov","contributorId":4202,"corporation":false,"usgs":true,"family":"Hamilton","given":"John","email":"jhamilton@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":396807,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Leo T.","contributorId":75727,"corporation":false,"usgs":true,"family":"Brown","given":"Leo","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":396811,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70201976,"text":"70201976 - 2000 - Digital elevation models derived from small format lunar images","interactions":[],"lastModifiedDate":"2019-02-04T09:58:42","indexId":"70201976","displayToPublicDate":"2000-05-30T09:58:05","publicationYear":"2000","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Digital elevation models derived from small format lunar images","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"ASPRS 2000 proceedings : start the 21st century : launching the geospatial information age","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"ASPRS 2000: Start the 21st centry: Launching the geospatial information age","conferenceDate":"May 21-26, 2000","conferenceLocation":"Washington, DC","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","isbn":"9781570830617","usgsCitation":"Rosiek, M.R., Kirk, R.L., and Howington-Kraus, E., 2000, Digital elevation models derived from small format lunar images, <i>in</i> ASPRS 2000 proceedings : start the 21st century : launching the geospatial information age, Washington, DC, May 21-26, 2000, CD-ROM.","productDescription":"CD-ROM","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":360958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosiek, Mark R. mrosiek@usgs.gov","contributorId":824,"corporation":false,"usgs":true,"family":"Rosiek","given":"Mark","email":"mrosiek@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":756401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":756402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howington-Kraus, Elpitha 0000-0001-5787-6554 ahowington@usgs.gov","orcid":"https://orcid.org/0000-0001-5787-6554","contributorId":2815,"corporation":false,"usgs":true,"family":"Howington-Kraus","given":"Elpitha","email":"ahowington@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":756403,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70164506,"text":"70164506 - 2000 - Nutrients discharged to the Mississippi River from eastern Iowa watersheds, 1996-1997","interactions":[],"lastModifiedDate":"2018-05-29T13:08:53","indexId":"70164506","displayToPublicDate":"2000-05-01T17:30:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Nutrients discharged to the Mississippi River from eastern Iowa watersheds, 1996-1997","docAbstract":"<p>The introduction of nutrients from chemical fertilizer, animal manure, wastewater, and atmospheric deposition to the eastern Iowa environment creates a large potential for nutrient transport in watersheds. Agriculture constitutes 93 percent of all land use in eastern Iowa. As part of the U.S. Geological Survey National Water Quality Assessment Program, water samples were collected (typically monthly) from six small and six large watersheds in eastern Iowa between March 1996 and September 1997. A Geographic Information System (GIS) was used to determine land use and quantify inputs of nitrogen and phosphorus within the study area. Streamliow from the watersheds is to the Mississippi River. Chemical fertilizer and animal manure account for 92 percent of the estimated total nitrogen and 99.9 percent of the estimated total phosphorus input in the study area. Total nitrogen and total phosphorus loads for 1996 were estimated for nine of the 12 rivers and creeks using a minimum variance unbiased estimator model. A seasonal pattern of concentrations and loads was observed. The greatest concentrations and loads occur in the late spring to early summer in conjunction with row-crop fertilizer applications and spring nmoff and again in the late fall to early winter as vegetation goes into dormancy and additional fertilizer is applied to row-crop fields. The three largest rivers in eastern Iowa transported an estimated total of 79,000 metric tons of total nitrogen and 6,800 metric tons of total phosphorus to the Mississippi River in 1996. The estimated mass of total nitrogen and total phosphorus transported to the Mississippi River represents about 19 percent of all estimated nitrogen and 9 percent of all estimated phosphorus input to the study area.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of the American Water Resources Association","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Water Resources Association","publisherLocation":"Herndon, VA","doi":"10.1111/j.1752-1688.2000.tb04257.x","usgsCitation":"Becher, K., Schnoebelen, D.J., and Akers, K., 2000, Nutrients discharged to the Mississippi River from eastern Iowa watersheds, 1996-1997: Journal of the American Water Resources Association, v. 36, no. 1, p. 161-173, https://doi.org/10.1111/j.1752-1688.2000.tb04257.x.","productDescription":"13 p.","startPage":"161","endPage":"173","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":316713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.2906494140625,\n              43.249203966977845\n            ],\n            [\n              -92.48291015625,\n              43.44893105587766\n            ],\n            [\n              -92.6531982421875,\n              43.64800079902171\n            ],\n            [\n              -92.74108886718749,\n              43.74728909225906\n            ],\n            [\n              -92.8179931640625,\n              43.77902662160831\n            ],\n            [\n              -92.9058837890625,\n              43.878097874251736\n            ],\n            [\n              -93.03771972656249,\n              43.909765943908\n            ],\n            [\n              -93.2080078125,\n              43.9058083561574\n            ],\n            [\n              -93.1915283203125,\n              43.79488907226601\n            ],\n            [\n              -93.3453369140625,\n              43.8028187190472\n            ],\n            [\n              -93.6090087890625,\n              43.80678314779554\n            ],\n            [\n              -93.7518310546875,\n              43.70362249839005\n            ],\n            [\n              -93.878173828125,\n              43.64005063334694\n            ],\n            [\n              -93.9825439453125,\n              43.520671902437606\n            ],\n            [\n              -94.053955078125,\n              43.432977075795606\n            ],\n            [\n              -94.130859375,\n              43.27320591705845\n            ],\n            [\n              -94.1802978515625,\n              43.12905229628564\n            ],\n            [\n              -94.09790039062499,\n              43.04881979669318\n            ],\n            [\n              -93.9990234375,\n              42.96044267380142\n            ],\n            [\n              -93.9056396484375,\n              42.81555136172695\n            ],\n            [\n              -93.84521484375,\n              42.581399679665054\n            ],\n            [\n              -93.7847900390625,\n              42.42345651793833\n            ],\n            [\n              -93.85620117187499,\n              42.32200108060303\n            ],\n            [\n              -94.02099609375,\n              42.24478535602799\n            ],\n            [\n              -93.93310546875,\n              42.09822241118974\n            ],\n            [\n              -93.88916015625,\n              41.96765920367816\n            ],\n            [\n              -93.834228515625,\n              41.795888098191426\n            ],\n            [\n              -93.724365234375,\n              41.72623044860004\n            ],\n            [\n              -93.526611328125,\n              41.541477666790286\n            ],\n            [\n              -93.3782958984375,\n              41.492120839687786\n            ],\n            [\n              -93.218994140625,\n              41.46742831254425\n            ],\n            [\n              -93.0816650390625,\n              41.40153558289846\n            ],\n            [\n              -92.9498291015625,\n              41.343824581185686\n            ],\n            [\n              -92.8948974609375,\n              41.25716209782705\n            ],\n            [\n              -92.6971435546875,\n              41.22824901518532\n            ],\n            [\n              -92.5872802734375,\n              41.15384235711447\n            ],\n            [\n              -92.43896484375,\n              41.07935114946899\n            ],\n            [\n              -92.35107421874999,\n              40.94671366508002\n            ],\n            [\n              -92.230224609375,\n              40.89275342420696\n            ],\n            [\n              -91.966552734375,\n              40.79301881008675\n            ],\n            [\n              -91.95556640625,\n              40.75974059207392\n            ],\n            [\n              -91.82373046875,\n              40.72228267283148\n            ],\n            [\n              -91.7303466796875,\n              40.63896734381723\n            ],\n            [\n              -91.5216064453125,\n              40.538851525354666\n            ],\n            [\n              -91.5545654296875,\n              40.65980593837855\n            ],\n            [\n              -91.593017578125,\n              40.76390128094589\n            ],\n            [\n              -91.47216796875,\n              40.76390128094589\n            ],\n            [\n              -91.34033203125,\n              40.75557964275591\n            ],\n            [\n              -91.20849609375,\n              40.79717741518769\n            ],\n            [\n              -91.153564453125,\n              40.851215574282456\n            ],\n            [\n              -91.20849609375,\n              40.942564441333296\n            ],\n            [\n              -91.2744140625,\n              41.01721057822846\n            ],\n            [\n              -91.29638671875,\n              41.10005163093046\n            ],\n            [\n              -91.29089355468749,\n              41.20758898181025\n            ],\n            [\n              -91.351318359375,\n              41.32320110223851\n            ],\n            [\n              -91.2689208984375,\n              41.46742831254425\n            ],\n            [\n              -91.16455078125,\n              41.51269075845857\n            ],\n            [\n              -91.03271484375,\n              41.549700145132725\n            ],\n            [\n              -90.90087890624999,\n              41.52091689636249\n            ],\n            [\n              -90.758056640625,\n              41.56203190200195\n            ],\n            [\n              -90.560302734375,\n              41.60312076451184\n            ],\n            [\n              -90.450439453125,\n              41.6770148220322\n            ],\n            [\n              -90.428466796875,\n              41.759019938155404\n            ],\n            [\n              -90.32409667968749,\n              41.81636125072054\n            ],\n            [\n              -90.2911376953125,\n              41.902277040963696\n            ],\n            [\n              -90.46142578125,\n              41.92271616673924\n            ],\n            [\n              -90.6317138671875,\n              41.90636538970964\n            ],\n            [\n              -90.90087890624999,\n              41.99624282178583\n            ],\n            [\n              -91.153564453125,\n              42.07783959017503\n            ],\n            [\n              -91.2689208984375,\n              42.17561739661684\n            ],\n            [\n              -91.483154296875,\n              42.33012354634199\n            ],\n            [\n              -91.6534423828125,\n              42.53689200787317\n            ],\n            [\n              -91.8017578125,\n              42.72683914955442\n            ],\n            [\n              -91.9390869140625,\n              42.879989517714826\n            ],\n            [\n              -92.208251953125,\n              43.137069765760344\n            ],\n            [\n              -92.2906494140625,\n              43.249203966977845\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"1","noUsgsAuthors":false,"publicationDate":"2007-06-08","publicationStatus":"PW","scienceBaseUri":"56b9ca7be4b08d617f63a845","contributors":{"authors":[{"text":"Becher, Kent 0000-0002-3947-0793 kdbecher@usgs.gov","orcid":"https://orcid.org/0000-0002-3947-0793","contributorId":3863,"corporation":false,"usgs":true,"family":"Becher","given":"Kent","email":"kdbecher@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schnoebelen, Douglas J.","contributorId":87514,"corporation":false,"usgs":true,"family":"Schnoebelen","given":"Douglas","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":597647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akers, Kimberlee K.","contributorId":43379,"corporation":false,"usgs":true,"family":"Akers","given":"Kimberlee K.","affiliations":[],"preferred":false,"id":597648,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70156747,"text":"70156747 - 2000 - Basin level statistical properties of topographic index for North America","interactions":[],"lastModifiedDate":"2015-08-27T11:41:46","indexId":"70156747","displayToPublicDate":"2000-05-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Basin level statistical properties of topographic index for North America","docAbstract":"<div class=\"abstract svAbstract \" data-etype=\"ab\">\n<p id=\"\">For land&ndash;atmosphere interaction studies several&nbsp;<i>Topmodel</i>&nbsp;based land-surface schemes have been proposed. For the implementation of such models over the continental (and global) scales, statistical properties of the topographic indices are derived using GTOPO30 (30-arc-second; 1 km resolution) DEM data for North America. River basins and drainage network extracted using this dataset are overlaid on computed topographic indices for the continent and statistics are extracted for each basin. A total of 5020 basins are used to cover the entire continent with an average basin size of 3640 km<span id=\"mmlsi2\" class=\"mathmlsrc\"><span class=\"formulatext stixSupport mathImg\" title=\"Click to view the MathML source\" data-mathurl=\"/science?_ob=MathURL&amp;_method=retrieve&amp;_eid=1-s2.0-S0309170899000494&amp;_mathId=si2.gif&amp;_user=111111111&amp;_pii=S0309170899000494&amp;_rdoc=1&amp;_issn=03091708&amp;md5=5fef45e445874a36c60ec34c6fa0229d\"><sup>2</sup></span></span>. Typically, the first three statistical moments of the distribution of the topographic indices for each basin are required for modeling. Departures of these statistical moments to those obtained using high resolution data have important implications for the prediction of soil-moisture states in the hydrologic models and consequently on the dynamics of the land&ndash;atmosphere interaction. It is found that a simple relationship between the statistics obtained at the 1 km and 90 m resolutions can be developed. The mean, standard deviation, skewness, L-scale and L-skewness all show approximate linear relationships between the two resolutions making it possible to use the moment estimates from the GTOPO30 data for hydrologic studies by applying a simple linear downscaling scheme. This significantly increases the utility value of the GTOPO30 datasets for hydrologic modeling studies.</p>\n<p>&nbsp;</p>\n</div>","language":"English","publisher":"Elsevier","doi":"10.1016/S0309-1708(99)00049-4","usgsCitation":"Kumar, P., Verdin, K.L., and Greenlee, S.K., 2000, Basin level statistical properties of topographic index for North America: Advances in Water Resources, v. 23, no. 6, p. 571-578, https://doi.org/10.1016/S0309-1708(99)00049-4.","productDescription":"8 p.","startPage":"571","endPage":"578","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e034b2e4b0f42e3d040df0","contributors":{"authors":[{"text":"Kumar, Praveen","contributorId":81405,"corporation":false,"usgs":true,"family":"Kumar","given":"Praveen","affiliations":[],"preferred":false,"id":570351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verdin, Kristine L. 0000-0002-6114-4660 kverdin@usgs.gov","orcid":"https://orcid.org/0000-0002-6114-4660","contributorId":3070,"corporation":false,"usgs":true,"family":"Verdin","given":"Kristine","email":"kverdin@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":570352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greenlee, Susan K. sgreenlee@usgs.gov","contributorId":3326,"corporation":false,"usgs":true,"family":"Greenlee","given":"Susan","email":"sgreenlee@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":570353,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70185675,"text":"70185675 - 2000 - Chamber measurement of surface-atmosphere trace gas exchange: Numerical evaluation of dependence on soil interfacial layer, and source/sink products","interactions":[],"lastModifiedDate":"2018-12-10T07:48:37","indexId":"70185675","displayToPublicDate":"2000-04-16T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2316,"text":"Journal of Geophysical Research D: Atmospheres","active":true,"publicationSubtype":{"id":10}},"title":"Chamber measurement of surface-atmosphere trace gas exchange: Numerical evaluation of dependence on soil interfacial layer, and source/sink products","docAbstract":"<p> We employed a three-dimensional finite difference gas diffusion model to simulate the performance of chambers used to measure surface-atmosphere tace gas exchange. We found that systematic errors often result from conventional chamber design and deployment protocols, as well as key assumptions behind the estimation of trace gas exchange rates from observed concentration data. Specifically, our simulationshowed that (1) when a chamber significantly alters atmospheric mixing processes operating near the soil surface, it also nearly instantaneously enhances or suppresses the postdeployment gas exchange rate, (2) any change resulting in greater soil gas diffusivity, or greater partitioning of the diffusing gas to solid or liquid soil fractions, increases the potential for chamber-induced measurement error, and (3) all such errors are independent of the magnitude, kinetics, and/or distribution of trace gas sources, but greater for trace gas sinks with the same initial absolute flux. Finally, and most importantly, we found that our results apply to steady state as well as non-steady-state chambers, because the slow rate of gas diffusion in soil inhibits recovery of the former from their initial non-steady-state condition. Over a range of representative conditions, the error in steady state chamber estimates of the trace gas flux varied from -30 to +32%, while estimates computed by linear regression from non-steadystate chamber concentrations were 2 to 31% too small. Although such errors are relatively small in comparison to the temporal and spatial variability characteristic of trace gas exchange, they bias the summary statistics for each experiment as well as larger scale trace gas flux estimates based on them. </p>","language":"English","publisher":"Wiley","doi":"10.1029/1999JD901204","usgsCitation":"Hutchinson, G., Livingston, G., Healy, R.W., and Striegl, R.G., 2000, Chamber measurement of surface-atmosphere trace gas exchange: Numerical evaluation of dependence on soil interfacial layer, and source/sink products: Journal of Geophysical Research D: Atmospheres, v. 105, no. D7, p. 8865-8875, https://doi.org/10.1029/1999JD901204.","productDescription":"11 p. ","startPage":"8865","endPage":"8875","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":479138,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/1999jd901204","text":"Publisher Index Page"},{"id":338386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"D7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58da253ae4b0543bf7fda851","contributors":{"authors":[{"text":"Hutchinson, G.L.","contributorId":189877,"corporation":false,"usgs":false,"family":"Hutchinson","given":"G.L.","email":"","affiliations":[],"preferred":false,"id":686324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Livingston, G.P.","contributorId":189878,"corporation":false,"usgs":false,"family":"Livingston","given":"G.P.","email":"","affiliations":[],"preferred":false,"id":686325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Healy, R. W.","contributorId":89872,"corporation":false,"usgs":true,"family":"Healy","given":"R.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":686326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":false,"id":686327,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209550,"text":"70209550 - 2000 - Age and Pb-Sr-Nd isotopic systematics of plutonic rocks from the Green Mountain magmatic arc, southeastern Wyoming: Isotopic characterization of a Paleoproterozoic island arc system","interactions":[],"lastModifiedDate":"2020-04-13T16:57:54.80266","indexId":"70209550","displayToPublicDate":"2000-04-01T11:51:49","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3310,"text":"Rocky Mountain Geology","active":true,"publicationSubtype":{"id":10}},"title":"Age and Pb-Sr-Nd isotopic systematics of plutonic rocks from the Green Mountain magmatic arc, southeastern Wyoming: Isotopic characterization of a Paleoproterozoic island arc system","docAbstract":"<p>Three new U-Pb zircon ages and the Pb-Sr-Nd isotopic systematics of 24 whole-rock samples from mainly plutonic rocks of the Sierra Madre and Medicine Bow Mountains near the Colorado-Wyoming border help establish the Green Mountain magmatic arc as a Paleoproterozoic, variably eroded, island arc terrane. The Green Mountain magmatic arc, a terrane composed of variably metamorphosed volcanic and volcaniclastic rocks, minor metasedimentary rocks, high-grade gneisses, and plutons ranging from gabbro to granodiorite, was formed between ca. 1792 and 1744 Ma. It is the northernmost and oldest part of the Colorado province and is separated from Archean rocks to the north by the east-west-trending Cheyenne belt.</p><p>New U-Pb zircon ages were determined for two dioritic samples of the Mullen Creek complex (1778 ±2 and 1778 ±17 Ma; an ultramafic/mafic layered intrusion) and for a sample of the Rambler granite (1771 ±3.4 Ma); both units are exposed in the Medicine Bow Mountains. A Sm-Nd internal isochron age of 1750 ±24 Ma (ϵ<sub>Nd</sub><sup>i</sup><span>&nbsp;</span>= + 3.8) was determined that is within error of the Sm-Nd whole-rock isochron age for the entire Lake Owen sample database (1775 ±45 Ma). Initial Nd signatures (+ 3.3 to 4.8) indicate that the bulk of the arc rocks was derived from a depleted mantle source at 1.78 Ga. Although the Rb-Sr systematics appear disturbed, data from extremely low Rb/Sr, non-hydrous, ultramafic layered units indicate an initial<span>&nbsp;</span><sup>87</sup>Sr/<sup>86</sup>Sr value of 0.7024. The range of initial Sr isotopic values for these rocks is elevated relative to depleted mantle sources at 1.78 Ga, an isotopic distinction of modern primitive oceanic island arc systems. The U-Pb data on the same mafic rock samples are consistent with the other isotopic results. The values define average initial Pb values of<span>&nbsp;</span><sup>206</sup>Pb/<sup>204</sup>Pb = 15.7 and<span>&nbsp;</span><sup>207</sup>Pb/<sup>204</sup>Pb = 15.3, indicative of a depleted mantle source at 1.78 Ga.</p><p>Felsic plutonic arc rocks exhibit disturbed Pb and Sr isotopic behavior. They are characterized by the same depleted mantle signature with initial ϵ<sub>Nd</sub><span>&nbsp;</span>values of ∼2.9–4.4, however, indicating little crustal contamination of source magmas for granites and precluding their derivation by subduction of Archean crustal components during collisional accretion of the arc.</p>","language":"English","publisher":"University of Wyoming","doi":"10.2113/35.1.51","usgsCitation":"Premo, W.R., and Loucks, R.R., 2000, Age and Pb-Sr-Nd isotopic systematics of plutonic rocks from the Green Mountain magmatic arc, southeastern Wyoming: Isotopic characterization of a Paleoproterozoic island arc system: Rocky Mountain Geology, v. 35, no. 1, p. 51-70, https://doi.org/10.2113/35.1.51.","productDescription":"20 p.","startPage":"51","endPage":"70","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":373919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","otherGeospatial":"Green Mountain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.97412109375,\n              40.18307014852534\n            ],\n            [\n              -104.0679931640625,\n              40.18307014852534\n            ],\n            [\n              -104.0679931640625,\n              41.51269075845857\n            ],\n            [\n              -105.97412109375,\n              41.51269075845857\n            ],\n            [\n              -105.97412109375,\n              40.18307014852534\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Premo, Wayne R. 0000-0001-9904-4801 wpremo@usgs.gov","orcid":"https://orcid.org/0000-0001-9904-4801","contributorId":1697,"corporation":false,"usgs":true,"family":"Premo","given":"Wayne","email":"wpremo@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":786773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loucks, R. R.","contributorId":223988,"corporation":false,"usgs":false,"family":"Loucks","given":"R.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":786774,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70243620,"text":"70243620 - 2000 - Geomorphometry-Diversity in quantitative surface analysis","interactions":[],"lastModifiedDate":"2023-05-15T16:40:56.147709","indexId":"70243620","displayToPublicDate":"2000-03-01T11:38:34","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5866,"text":"Progress in Physical Geography: Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphometry-Diversity in quantitative surface analysis","docAbstract":"<p><span>A widening variety of applications is diversifying geomorphometry (</span><i>digital terrain modelling</i><span>), the quantitative study of topography. An amalgam of earth science, mathematics, engineering and computer science, the discipline has been revolutionized by the computer manipulation of gridded terrain heights, or digital elevation models (DEMs). Its rapid expansion continues. This article reviews the remarkable diversity of recent morphometric work in 15 selected topics and discusses their significance and prospects. The quantitative analysis of industrial microsurface topography is introduced to the earth science community. The 14 other topics are Internet access to geomorphometry; global DEMs; DEM modelling of channel networks; self-organized criticality; fractal and wavelet analysis; soil resources; landslide hazards; barchan dunes; harvesting wind energy; sea-ice surfaces; sea-floor abyssal hills; Japanese work in morphometry; and the emerging fields of landscape ecology and image understanding. Closing remarks note reasons for the diversity within geomorphometry, speculate on future trends and recommend creating a unified field of surface representation.</span></p>","language":"English","publisher":"Sage","doi":"10.1177/030913330002400101","usgsCitation":"Pike, R.J., 2000, Geomorphometry-Diversity in quantitative surface analysis: Progress in Physical Geography: Earth and Environment, v. 24, no. 1, p. 1-20, https://doi.org/10.1177/030913330002400101.","productDescription":"20 p.","startPage":"1","endPage":"20","costCenters":[],"links":[{"id":417042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"1","noUsgsAuthors":false,"publicationDate":"2000-03-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Pike, Richard J. rpike@usgs.gov","contributorId":5753,"corporation":false,"usgs":true,"family":"Pike","given":"Richard","email":"rpike@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":872639,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70243662,"text":"70243662 - 2000 - Monitoring beach morphology changes using small-format aerial photography and digital softcopy photogrammetry","interactions":[],"lastModifiedDate":"2026-04-20T15:41:23.454614","indexId":"70243662","displayToPublicDate":"2000-03-01T11:22:49","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1541,"text":"Environmental Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring beach morphology changes using small-format aerial photography and digital softcopy photogrammetry","docAbstract":"<p>Current methods of monitoring beach morphology changes commonly involve the establishment of Global Positioning System profiles that are surveyed on a regular basis. Although this method produces precise measurements of coastal topography, it is costly in time and effort and may result in large data gaps between profiles. Much of our understanding of coastal dynamics is thus limited by profile spacing and survey frequency. Softcopy photogrammetry is increasingly being used as an alternative to assess shoreline change and study beach morphodynamics. This method of producing three-dimensional topographic models and orthophotographs from digitized aerial photography can aid in filling in the gaps between established profiles. A limiting factor to this technology is the cost of obtaining high-resolution aerial photography.</p><p>We have developed an aerial mapping system designed to collect data in an efficient and cost-effective way. We use a small-format aerial photography system that can be mounted on a variety of small aircraft on short notice. After a flight, the photographs are scanned, and softcopy photogrammetry software is used to create both DTMs (Digital Terrain Models) and orthophotographs. The DTMs can be compared with existing profiles for accuracy, and volumetric changes can be computed. The orthophotos are used to make precise measurements of the position and morphology of shoreline features. This aerial mapping system is advantageous over previous methods of beach morphology change monitoring because it allows for rapid response to storm events and provides a cost-effective method of establishing a continual monitoring program in erosion hazard areas.</p>","language":"English","publisher":"Wiley","doi":"10.1046/j.1526-0984.2000.71001.x","usgsCitation":"Hapke, C., and Richmond, B.M., 2000, Monitoring beach morphology changes using small-format aerial photography and digital softcopy photogrammetry: Environmental Geosciences, v. 7, no. 1, p. 32-37, https://doi.org/10.1046/j.1526-0984.2000.71001.x.","productDescription":"6 p.","startPage":"32","endPage":"37","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":417101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2000-03-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Hapke, Cheryl 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":139949,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872835,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":68449,"text":"ha725 - 2000 - Water levels and ground-water discharge, regional aquifer system of the midwestern Basins and Arches Region, in parts of Indiana, Ohio, Illinois, and Michigan","interactions":[],"lastModifiedDate":"2015-10-28T11:15:29","indexId":"ha725","displayToPublicDate":"2000-03-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":318,"text":"Hydrologic Atlas","code":"HA","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"725","title":"Water levels and ground-water discharge, regional aquifer system of the midwestern Basins and Arches Region, in parts of Indiana, Ohio, Illinois, and Michigan","docAbstract":"<p>Aquifers in Quaternary glacial deposits and the underlying Silurian and Devonian carbonate bedrock in parts of Indiana, Ohio, Illinois, and Michigan compose the regional aquifer system under investigation as part of the Midwestern Basins and Arches Regional Aquifer System Analysis (Midwestern Basins and Arches&mdash;RASA) project of the U.S. Geological Survey (USGS). The Midwestern Basins and Arches&mdash;RASA is part of a USGS program to assess the regional hydrology, geology, and water quality of the Nation's most important aquifers (Sun, 1986). An objective specific to the Midwestern Basins and Arches&mdash;RASA project is to conceptualize and describe regional ground-water flow in the glacial-deposit and carbonate-bedrock aquifer system, including regional recharge and discharge areas and regional relations between surface and ground water (Bugliosi, 1990).<br />Water-level and ground-water discharge data were collected and (or) analyzed to help meet the above objective. Specifically, data from the USGS Ground-Water Site Inventory (GWSI) data base were used to determine relations between land-surface altitude and water levels in glacial-deposit aquifers. Water levels in the carbonate-bedrock aquifer were synoptically measured during July 1990, and the data were used to construct a potentiometric surface map of the aquifer. Regional hydraulic gradients and general directions of regional flow in the carbonate-bedrock aquifer can be inferred from this map. Steady-state groundwater discharge to streams that drain the area underlain by the glacial-deposit and carbonate bedrock aquifer system was estimated from base-flow daily values computed from streamflow records.<br />Water-level and ground-water-discharge data collectively form the sample information necessary to develop calibration targets for calibration of a ground-water-flow model (Anderson and Woessner, 1992). Such a ground-water-flow model of the glacial-deposit and carbonate-bedrock aquifer system was constructed to help conceptualize and describe regional ground-water flow in the aquifer system. The model was calibrated to the water-level and ground-water-discharge data presented in this atlas.</p>","language":"ENGLISH","doi":"10.3133/ha725","isbn":"0607926554","usgsCitation":"Eberts, S., 2000, Water levels and ground-water discharge, regional aquifer system of the midwestern Basins and Arches Region, in parts of Indiana, Ohio, Illinois, and Michigan: U.S. Geological Survey Hydrologic Atlas 725, 5 maps on 3 sheets :col. ;maps 50 x 48 cm., and 22 x 25 cm., sheets 77 x 102 cm., folded in envelope 30 x 24 cm., https://doi.org/10.3133/ha725.","productDescription":"5 maps on 3 sheets :col. ;maps 50 x 48 cm., and 22 x 25 cm., sheets 77 x 102 cm., folded in envelope 30 x 24 cm.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":186271,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":89985,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ha/725/plate-2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":89986,"rank":402,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ha/725/plate-3.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":89984,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ha/725/plate-1.pdf","linkFileType":{"id":1,"text":"pdf"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.46666666666667,38.63333333333333 ], [ -89.46666666666667,42.7 ], [ -83.38333333333334,42.7 ], [ -83.38333333333334,38.63333333333333 ], [ -89.46666666666667,38.63333333333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a08e4b07f02db5f9f44","contributors":{"authors":[{"text":"Eberts, Sandra M. smeberts@usgs.gov","contributorId":2264,"corporation":false,"usgs":true,"family":"Eberts","given":"Sandra M.","email":"smeberts@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":278241,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":5061,"text":"fs16899 - 2000 - Trends in surface-water quality during implementation of best-management practices in Mill Creek and Muddy Run Basins, Lancaster County, Pennsylvania","interactions":[],"lastModifiedDate":"2018-02-09T12:48:56","indexId":"fs16899","displayToPublicDate":"2000-03-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"168-99","title":"Trends in surface-water quality during implementation of best-management practices in Mill Creek and Muddy Run Basins, Lancaster County, Pennsylvania","docAbstract":"<p>Analyses of water samples collected over a 5-year period (1993-98) in the Mill Creek and Muddy Run Basins during implementation of agricultural best-management practices (BMP’s) indicate statistically significant trends in the concentrations of several nutrient species and in nonfilterable residue (suspended solids). The strongest trends identified were those indicated by a more than 50- percent decrease in the flow-adjusted concentrations of total and dissolved phosphorus and total residue in base flow in the two streams. Analyses of stormflow samples showed a 31-percent decrease in the flow-adjusted concentration of total phosphorus in Mill Creek and a 54-percent decrease in total nonfilterable residue in Muddy Run. A 58-percent increase in the flow-adjusted concentration of total ammonia nitrogen in stormflow was found at Muddy Run.</p><p>Although the effects of a specific BMP on the indicated trends is uncertain, results of statistical trend tests of the data suggest that stream fencing, possibly in concert with other practices, such as stream crossings for livestock, barnyard runoff control, manure-storage facilities, and rotational grazing, was effective in improving water quality during base flow and probably low to moderate stormflow conditions. Additional improvements in water quality in the Mill Creek and Muddy Run Basins seems likely as the implementation of BMP’s is expected to continue. Thus, the full effect of BMP implementation in the two basins may not be observed for some time.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs16899","collaboration":"Prepared in cooperation with the Pennsylvania Department of Environmental Protection","usgsCitation":"Koerkle, E.H., 2000, Trends in surface-water quality during implementation of best-management practices in Mill Creek and Muddy Run Basins, Lancaster County, Pennsylvania: U.S. Geological Survey Fact Sheet 168-99, 6 p., https://doi.org/10.3133/fs16899.","productDescription":"6 p.","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":117130,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/1999/0168/coverthb.jpg"},{"id":396,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/1999/0168/fs19990168.pdf","text":"Report","size":"411 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 1999-0168"}],"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> <br> U.S. Geological Survey <br> 215 Limekiln Road <br> New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Introduction</li><li>Site Description</li><li>Study Design</li><li>Data Analysis</li><li>Water Quality</li><li>Trends in Nutrient and Residue Concentrations</li><li>Loads and Yields</li><li>References Cited</li></ul>","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4ae4b07f02db625287","contributors":{"authors":[{"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":150355,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":4943,"text":"fs13899 - 2000 - Using OTIS to model solute transport in streams and rivers","interactions":[],"lastModifiedDate":"2020-02-26T19:19:23","indexId":"fs13899","displayToPublicDate":"2000-03-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"138-99","title":"Using OTIS to model solute transport in streams and rivers","docAbstract":"Solute transport in streams and rivers is governed by a suite of hydrologic and geochemical processes. Knowledge of these processes is needed when assessing the fate of contaminants that are released into surface waters. The study of solute fate and transport often is aided by solute transport models that mathematically describe the underlying processes. This fact sheet describes a model that considers One-Dimensional Transport with Inflow and Storage (OTIS). As shown by several example applications, OTIS may be used in conjunction with field-scale data to quantify hydrologic processes (advection, dispersion, and transient storage) and certain chemical reactions (sorption and first-order decay).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Denver, CO","doi":"10.3133/fs13899","usgsCitation":"Runkel, R.L., 2000, Using OTIS to model solute transport in streams and rivers: U.S. Geological Survey Fact Sheet 138-99, 4 p., https://doi.org/10.3133/fs13899.","productDescription":"4 p.","numberOfPages":"4","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":120757,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/1999/0138/report-thumb.jpg"},{"id":31805,"rank":299,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/0138-99/report.pdf","text":"Report","size":"2.6","linkFileType":{"id":1,"text":"pdf"},"description":"FS 138-99"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a16e4b07f02db603ccd","contributors":{"authors":[{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":150180,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70022891,"text":"70022891 - 2000 - Compositional analyses of small lunar pyroclastic deposits using Clementine multispectral data","interactions":[],"lastModifiedDate":"2019-02-11T10:45:58","indexId":"70022891","displayToPublicDate":"2000-02-25T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Compositional analyses of small lunar pyroclastic deposits using Clementine multispectral data","docAbstract":"<p>Clementine ultraviolet-visible (UVVIS) data are used to examine the compositions of 18 pyroclastic deposits (15 small, three large) at 13 sites on the Moon. Compositional variations among pyroclastic deposits largely result from differing amounts of new basaltic (or juvenile) material and reworked local material entrained in their ejecta upon eruption. Characterization of pyroclastic deposit compositions allows us to understand the mechanisms of lunar explosive volcanism. Evidence for compositional differences between small pyroclastic deposits at a single site is observed at Atlas crater. At all sites, compositional variation among the small pyroclastic deposits is consistent with earlier classification based on Earth-based spectra: three compositional groups can be observed, and the trend of increasing mafic absorption band strength from Group 1 to Group 2 to Group 3 is noted. As redefined here, Group 1 deposits include those of Alphonsus West, Alphonsus Southeast, Alphonsus Northeast 2, Atlas South, Crüger, Franklin, Grimaldi, Lavoisier, Oppenheimer, Orientale, and Riccioli. Group 1 deposits resemble lunar highlands, with weak mafic bands and relatively high UV/VIS ratios. Group 2 deposits include those of Alphonsus Northeast 1, Atlas North, Eastern Frigoris East and West, and Aristarchus Plateau; Group 2 deposits are similar to mature lunar maria, with moderate mafic band depths and intermediate UV/VIS ratios. The single Group 3 deposit, J. Herschel, has a relatively strong mafic band and a low UV/VIS ratio, and olivine is a likely juvenile component. Two of the deposits in these groups, Orientale and Aristarchus, are large pyroclastic deposits. The third large pyroclastic deposit, Apollo 17/Taurus Littrow, has a very weak mafic band and a high UV/VIS ratio and it does not belong to any of the compositional groups for small pyroclastic deposits. The observed compositional variations indicate that highland and mare materials are also present in many large and small pyroclastic deposits, and they suggest that volcanic glasses or spheres may not be dominant juvenile components in all large pyroclastic deposits.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research E: Planets","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1029/1999JE001070","issn":"01480227","usgsCitation":"Gaddis, L.R., Hawke, B.R., Robinson, M.S., and Coombs, C., 2000, Compositional analyses of small lunar pyroclastic deposits using Clementine multispectral data: Journal of Geophysical Research E: Planets, v. 105, no. E2, p. 4245-4262, https://doi.org/10.1029/1999JE001070.","productDescription":"18 p.","startPage":"4245","endPage":"4262","numberOfPages":"18","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":479141,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/1999je001070","text":"Publisher Index Page"},{"id":233794,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"E2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f934e4b0c8380cd4d4c7","contributors":{"authors":[{"text":"Gaddis, Lisa R. 0000-0001-9953-5483 lgaddis@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-5483","contributorId":2817,"corporation":false,"usgs":true,"family":"Gaddis","given":"Lisa","email":"lgaddis@usgs.gov","middleInitial":"R.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":395306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawke, Bernard Ray","contributorId":61506,"corporation":false,"usgs":true,"family":"Hawke","given":"Bernard","email":"","middleInitial":"Ray","affiliations":[],"preferred":false,"id":395305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, Mark S.","contributorId":167665,"corporation":false,"usgs":false,"family":"Robinson","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":395304,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coombs, Cassandra","contributorId":213080,"corporation":false,"usgs":false,"family":"Coombs","given":"Cassandra","email":"","affiliations":[],"preferred":false,"id":395303,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70260450,"text":"70260450 - 2000 - Evaluation of seismic slope-performance models using a regional case study","interactions":[],"lastModifiedDate":"2024-11-01T16:13:32.147663","indexId":"70260450","displayToPublicDate":"2000-02-01T11:07:18","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7559,"text":"Environmental and Engineering Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of seismic slope-performance models using a regional case study","docAbstract":"<p><span>This paper compares four permanent displacement models based on Newmark's sliding-block analogy for assessing regional seismic slope-performance. The models vary primarily by the ground motion descriptor used to correlate with Newmark displacement. The first uses peak ground-acceleration (PGA). The second uses PGA but normalizes displacements by predominant period and equivalent cycles. The third uses Arias intensity. The fourth calculates cumulative displacements from double-integrating simulated earthquake accelerograms. The models are implemented in a GIS to characterize seismic slope-performance for the Oakland East quadrangle near San Francisco, California. The resulting slope-performance maps are compared visually and through statistical analysis to expose potential differences and assess the effects of using a particular approach within a decision-making context. These maps were created for the purpose of comparison and are not suitable for use as critical decision-making tools. The models forecast notably different levels of slope-performance, with the PGA-based models predicting the greatest Newmark displacement on average. Thus, considering the variety of slope-performance models, it is suggested that practitioners avoid reliance on a single model. Instead, multiple models can be implemented in a GIS framework to gain a better perspective of the potential hazard and make a more informed decision.</span></p>","language":"English","publisher":"Association of Environmental & Engineering Geologists","doi":"10.2113/gseegeosci.6.1.25","usgsCitation":"Miles, S.B., and Keefer, D.K., 2000, Evaluation of seismic slope-performance models using a regional case study: Environmental and Engineering Geoscience, v. 6, no. 1, p. 25-39, https://doi.org/10.2113/gseegeosci.6.1.25.","productDescription":"15 p.","startPage":"25","endPage":"39","costCenters":[],"links":[{"id":463548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Oakland East quadrangle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.65411806022144,\n              38.04518653599146\n            ],\n            [\n              -122.65411806022144,\n              37.330806715923316\n            ],\n            [\n              -121.59715228156782,\n              37.330806715923316\n            ],\n            [\n              -121.59715228156782,\n              38.04518653599146\n            ],\n            [\n              -122.65411806022144,\n              38.04518653599146\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2000-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Miles, Scott B.","contributorId":38600,"corporation":false,"usgs":true,"family":"Miles","given":"Scott","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":917718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keefer, David K.","contributorId":77930,"corporation":false,"usgs":true,"family":"Keefer","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":917719,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70230879,"text":"70230879 - 2000 - National land-cover pattern data","interactions":[],"lastModifiedDate":"2022-04-27T16:01:12.849711","indexId":"70230879","displayToPublicDate":"2000-02-01T10:56:24","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"National land-cover pattern data","docAbstract":"<p><span>Land cover and its spatial patterns are key ingredients in ecological studies that consider large regions and the impacts of human activities. Because land-cover maps show only cover types and their locations, further processing is needed to extract pattern information and to characterize its spatial variability. We are producing a nationally consistent spatial database of six land-cover pattern indices: forest area density, forest connectivity, the&nbsp;</span><i>U</i><span>&nbsp;index (a measure of general land-use pressure by humans), land-cover connectivity, land-cover diversity, and landscape pattern types. We use the land-cover maps produced by the Multi-resolution Land Characteristics Consortium for the conterminous United States at 30-m resolution. The goal of this paper is to encourage use of the pattern data as: contextual information and independent variables for studies involving a set of field sites; indicators of landscape conditions for ecological assessments; and dependent variables in biogeographic and socioeconomic models. The new maps will be most useful in studies that require consistent and comparable land-cover pattern measurements over large regions and can be combined with the original land-cover maps and other data.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1890/0012-9658(2000)081[0604:NLCPD]2.0.CO;2","usgsCitation":"Riitters, K.H., Wickham, J.D., Vogelmann, J., and Jones, K.B., 2000, National land-cover pattern data: Ecology, v. 81, no. 2, https://doi.org/10.1890/0012-9658(2000)081[0604:NLCPD]2.0.CO;2.","productDescription":"1 p.","startPage":"604","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":399759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -130.67138671875,\n              54.686534234529695\n            ],\n            [\n              -129.9462890625,\n              55.36662484928637\n            ],\n            [\n              -130.1220703125,\n              56.145549500679074\n            ],\n            [\n              -131.9677734375,\n              56.9449741808516\n            ],\n            [\n              -135.3076171875,\n              59.833775202184206\n            ],\n            [\n              -136.38427734375,\n              59.65664225341022\n            ],\n            [\n              -136.6259765625,\n              59.23217626921806\n            ],\n            [\n              -137.52685546875,\n              58.938673187948304\n            ],\n            [\n              -137.65869140625,\n              59.33318942659219\n            ],\n            [\n              -138.8232421875,\n              60.009970961180386\n            ],\n            [\n              -139.21874999999997,\n              60.108670463036\n            ],\n            [\n              -139.04296875,\n              60.403001945865476\n            ],\n            [\n              -139.85595703125,\n              60.337823495982015\n            ],\n            [\n              -140.99853515625,\n              60.337823495982015\n            ],\n            [\n              -141.15234374999997,\n              69.71810669906763\n            ],\n            [\n              -143.4375,\n              70.17020068549206\n            ],\n            [\n              -145.1953125,\n              70.08056215839737\n            ],\n            [\n              -149.765625,\n              70.58341752317065\n            ],\n            [\n              -152.40234375,\n              70.61261423801925\n            ],\n            [\n              -152.314453125,\n              70.95969716686398\n            ],\n            [\n              -157.1484375,\n              71.35706654962706\n            ],\n            [\n              -159.9609375,\n              70.8734913192635\n            ],\n            [\n              -162.0703125,\n              70.31873847853124\n            ],\n            [\n              -163.916015625,\n              69.06856318696033\n            ],\n            [\n              -166.376953125,\n              68.942606818121\n            ],\n            [\n              -166.376953125,\n              68.26938680456564\n            ],\n            [\n              -163.30078125,\n              66.86108230224609\n            ],\n            [\n              -161.982421875,\n              66.47820814385636\n            ],\n            [\n              -163.564453125,\n              66.08936427047088\n            ],\n            [\n              -163.564453125,\n              66.6181218846659\n            ],\n            [\n              -165.76171875,\n              66.40795547978848\n            ],\n            [\n              -168.0908203125,\n              65.69447579373418\n            ],\n            [\n              -166.55273437499997,\n              65.14611484756372\n            ],\n            [\n              -166.904296875,\n              65.05360170595502\n            ],\n            [\n              -166.3330078125,\n              64.41592147626879\n            ],\n            [\n              -162.861328125,\n              64.39693778132846\n            ],\n            [\n              -160.927734375,\n              64.90491004905083\n            ],\n            [\n              -161.0595703125,\n              64.47279382008166\n            ],\n            [\n              -161.4990234375,\n              64.49172504435471\n            ],\n            [\n              -160.8837890625,\n              63.87939001720202\n            ],\n            [\n              -161.1474609375,\n              63.470144746565424\n            ],\n            [\n              -162.6416015625,\n              63.64625919492172\n            ],\n            [\n              -163.212890625,\n              63.05495931065107\n            ],\n            [\n              -164.2236328125,\n              63.37183226679281\n            ],\n            [\n              -166.1572265625,\n              61.75233128411639\n            ],\n            [\n              -165.3662109375,\n              60.54377524118842\n            ],\n            [\n              -167.431640625,\n              60.326947742998414\n            ],\n            [\n              -167.255859375,\n              59.866883195210214\n            ],\n            [\n              -165.8935546875,\n              59.7563950493563\n            ],\n            [\n              -162.68554687499997,\n              59.734253447591364\n            ],\n            [\n              -162.3779296875,\n              60.174306261926034\n            ],\n            [\n              -161.806640625,\n              59.46740794183739\n            ],\n            [\n              -162.0263671875,\n              59.108308258604964\n            ],\n            [\n              -161.806640625,\n              58.768200159239576\n            ],\n            [\n              -162.20214843749997,\n              58.65408464530598\n            ],\n            [\n              -160.83984375,\n              58.44773280389084\n            ],\n            [\n              -159.9609375,\n              58.6769376725869\n            ],\n            [\n              -159.08203125,\n              58.309488840677645\n            ],\n            [\n              -156.88476562499997,\n              58.92733441827545\n            ],\n            [\n              -157.5,\n              58.516651799363785\n            ],\n            [\n              -157.8076171875,\n              57.61010702068388\n            ],\n            [\n              -161.54296875,\n              56.022948079627454\n            ],\n            [\n              -168.6181640625,\n              53.4357192066942\n            ],\n            [\n              -174.9462890625,\n              52.26815737376817\n            ],\n            [\n              -178.2421875,\n              51.83577752045248\n            ],\n            [\n              -173.1884765625,\n              51.590722643120145\n            ],\n            [\n              -162.5537109375,\n              54.23955053156177\n            ],\n            [\n              -155.302734375,\n              55.52863052257191\n            ],\n            [\n              -151.4794921875,\n              57.51582286553883\n            ],\n            [\n              -146.9970703125,\n              60.08676274626006\n            ],\n            [\n              -145.546875,\n              60.21799073323445\n            ],\n            [\n              -144.228515625,\n              59.689926220143356\n            ],\n            [\n              -142.3828125,\n              59.93300042374631\n            ],\n            [\n              -138.3837890625,\n              58.83649009392136\n            ],\n            [\n              -135.6591796875,\n              56.31653672211301\n            ],\n            [\n              -133.2421875,\n              54.521081495443596\n            ],\n            [\n              -130.67138671875,\n              54.686534234529695\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -66.796875,\n              44.902577996288876\n            ],\n            [\n              -67.67578124999999,\n              45.583289756006316\n            ],\n            [\n              -67.939453125,\n              47.57652571374621\n            ],\n            [\n              -69.2578125,\n              47.338822694822\n            ],\n            [\n              -71.19140625,\n              45.27488643704891\n            ],\n            [\n              -75.146484375,\n              44.96479793033101\n            ],\n            [\n              -78.046875,\n              43.644025847699496\n            ],\n            [\n              -79.1015625,\n              43.51668853502906\n            ],\n            [\n              -79.1015625,\n              42.87596410238256\n            ],\n            [\n              -82.68310546875,\n              41.65649719441145\n            ],\n            [\n              -83.14453125,\n              42.049292638686836\n            ],\n            [\n              -83.07861328125,\n              42.374778361114195\n            ],\n            [\n              -82.529296875,\n              42.601619944327965\n            ],\n            [\n              -82.24365234375,\n              43.6599240747891\n            ],\n            [\n              -82.41943359375,\n              45.058001435398275\n            ],\n            [\n              -83.60595703125,\n              45.85941212790755\n            ],\n            [\n              -83.49609375,\n              46.027481852486645\n            ],\n            [\n              -83.7158203125,\n              46.164614496897094\n            ],\n            [\n              -83.95751953125,\n              46.07323062540835\n            ],\n            [\n              -84.24316406249999,\n              46.558860303117164\n            ],\n            [\n              -84.72656249999999,\n              46.558860303117164\n            ],\n            [\n              -84.90234375,\n              46.92025531537451\n            ],\n            [\n              -88.41796875,\n              48.3416461723746\n            ],\n            [\n              -89.3408203125,\n              47.96050238891509\n            ],\n            [\n              -90.76904296874999,\n              48.122101028190805\n            ],\n            [\n              -90.87890625,\n              48.22467264956519\n            ],\n            [\n              -91.51611328125,\n              48.10743118848039\n            ],\n            [\n              -92.2412109375,\n              48.37084770238366\n            ],\n            [\n              -92.39501953125,\n              48.23930899024907\n            ],\n            [\n              -92.94433593749999,\n              48.61838518688487\n            ],\n            [\n              -93.44970703125,\n              48.63290858589535\n            ],\n            [\n              -94.7021484375,\n              48.748945343432936\n            ],\n            [\n              -94.833984375,\n              49.23912083246698\n            ],\n            [\n              -95.1416015625,\n              49.396675075193976\n            ],\n            [\n              -95.20751953125,\n              49.009050809382046\n            ],\n            [\n              -123.22265625000001,\n              48.99463598353405\n            ],\n            [\n              -123.0908203125,\n              48.80686346108517\n            ],\n            [\n              -123.24462890625,\n              48.66194284607006\n            ],\n            [\n              -123.1787109375,\n              48.32703913063476\n            ],\n            [\n              -124.78271484375,\n              48.472921272487824\n            ],\n            [\n              -124.93652343749999,\n              48.16608541901253\n            ],\n            [\n              -124.365234375,\n              46.58906908309182\n            ],\n            [\n              -124.541015625,\n              44.15068115978094\n            ],\n            [\n              -124.93652343749999,\n              42.69858589169842\n            ],\n            [\n              -124.541015625,\n              41.22824901518529\n            ],\n            [\n              -124.73876953125,\n              40.43022363450862\n            ],\n            [\n              -124.03564453125,\n              39.35129035526705\n            ],\n            [\n              -124.01367187499999,\n              38.8225909761771\n            ],\n            [\n              -122.05810546875,\n              36.12012758978146\n            ],\n            [\n              -120.95947265624999,\n              34.88593094075317\n            ],\n            [\n              -120.80566406250001,\n              34.08906131584994\n            ],\n            [\n              -118.21289062499999,\n              32.2313896627376\n            ],\n            [\n              -117.22412109375,\n              32.54681317351514\n            ],\n            [\n              -114.78515624999999,\n              32.713355353177555\n            ],\n            [\n              -114.78515624999999,\n              32.491230287947594\n            ],\n            [\n              -110.98388671874999,\n              31.3348710339506\n            ],\n            [\n              -108.21533203125,\n              31.297327991404266\n            ],\n            [\n              -108.2373046875,\n              31.765537409484374\n            ],\n            [\n              -106.435546875,\n              31.765537409484374\n            ],\n            [\n              -104.9853515625,\n              30.600093873550072\n            ],\n            [\n              -104.47998046875,\n              29.592565403314087\n            ],\n            [\n              -103.20556640625,\n              28.94086176940557\n            ],\n            [\n              -102.65625,\n              29.76437737516313\n            ],\n            [\n              -102.3486328125,\n              29.84064389983441\n            ],\n            [\n              -101.49169921875,\n              29.7453016622136\n            ],\n            [\n              -100.83251953125,\n              29.267232865200878\n            ],\n            [\n              -100.30517578125,\n              28.246327971048842\n            ],\n            [\n              -99.60205078124999,\n              27.586197857692664\n            ],\n            [\n              -99.47021484375,\n              27.31321389856826\n            ],\n            [\n              -99.228515625,\n              26.52956523826758\n            ],\n            [\n              -98.2177734375,\n              26.05678288577881\n            ],\n            [\n              -97.75634765625,\n              26.03704188651584\n            ],\n            [\n              -97.44873046875,\n              25.839449402063185\n            ],\n            [\n              -97.20703125,\n              25.93828707492375\n            ],\n            [\n              -96.8994140625,\n              26.194876675795218\n            ],\n            [\n              -96.78955078125,\n              27.858503954841247\n            ],\n            [\n              -93.75732421875,\n              29.420460341013133\n            ],\n            [\n              -90.2197265625,\n              28.998531814051795\n            ],\n            [\n              -88.22021484375,\n              29.05616970274342\n            ],\n            [\n              -87.91259765625,\n              30.14512718337613\n            ],\n            [\n              -86.5283203125,\n              30.183121842195515\n            ],\n            [\n              -85.2978515625,\n              29.49698759653577\n            ],\n            [\n              -84.13330078125,\n              29.80251790576445\n            ],\n            [\n              -82.81494140625,\n              28.555576049185973\n            ],\n            [\n              -83.21044921875,\n              27.800209937418252\n            ],\n            [\n              -82.77099609375,\n              26.941659545381516\n            ],\n            [\n              -82.08984375,\n              25.878994400196202\n            ],\n            [\n              -81.5625,\n              25.264568475331583\n            ],\n            [\n              -82.28759765625,\n              24.467150664739002\n            ],\n            [\n              -82.0458984375,\n              24.046463999666567\n            ],\n            [\n              -80.6396484375,\n              24.56710835257599\n            ],\n            [\n              -79.78271484375,\n              25.34402602913433\n            ],\n            [\n              -79.60693359375,\n              27.27416111737468\n            ],\n            [\n              -80.68359375,\n              30.713503990354965\n            ],\n            [\n              -80.66162109375,\n              31.50362930577303\n            ],\n            [\n              -76.81640625,\n              34.07086232376631\n            ],\n            [\n              -75.16845703124999,\n              35.263561862152095\n            ],\n            [\n              -75.498046875,\n              37.055177106660814\n            ],\n            [\n              -73.58642578125,\n              39.90973623453719\n            ],\n            [\n              -71.3671875,\n              40.84706035607122\n            ],\n            [\n              -69.63134765625,\n              40.9964840143779\n            ],\n            [\n              -70.0048828125,\n              42.342305278572816\n            ],\n            [\n              -70.3564453125,\n              42.89206418807337\n            ],\n            [\n              -67.2802734375,\n              44.37098696297173\n            ],\n            [\n              -67.0166015625,\n              44.69989765840318\n            ],\n            [\n              -66.796875,\n              44.902577996288876\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.56640625,\n              18.771115062337024\n            ],\n            [\n              -154.68749999999997,\n              19.642587534013032\n            ],\n            [\n              -156.9287109375,\n              21.453068633086783\n            ],\n            [\n              -159.521484375,\n              22.43134015636061\n            ],\n            [\n              -160.5322265625,\n              21.983801417384697\n            ],\n            [\n              -159.9609375,\n              21.207458730482642\n            ],\n            [\n              -158.291015625,\n              20.92039691397189\n            ],\n            [\n              -156.97265625,\n              19.932041306115536\n            ],\n            [\n              -155.9619140625,\n              18.8543103618898\n            ],\n            [\n              -155.56640625,\n              18.771115062337024\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"81","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Riitters, Kurt H. 0000-0003-3901-4453","orcid":"https://orcid.org/0000-0003-3901-4453","contributorId":139788,"corporation":false,"usgs":false,"family":"Riitters","given":"Kurt","email":"","middleInitial":"H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":841544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wickham, James D.","contributorId":72278,"corporation":false,"usgs":false,"family":"Wickham","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":841545,"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":841546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, K. Bruce","contributorId":66105,"corporation":false,"usgs":true,"family":"Jones","given":"K.","email":"","middleInitial":"Bruce","affiliations":[],"preferred":false,"id":841547,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70185213,"text":"70185213 - 2000 - Development of a pore network simulation model to study nonaqueous phase liquid dissolution","interactions":[],"lastModifiedDate":"2018-03-27T17:18:24","indexId":"70185213","displayToPublicDate":"2000-02-01T00:00:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Development of a pore network simulation model to study nonaqueous phase liquid dissolution","docAbstract":"<p><span>A pore network simulation model was developed to investigate the fundamental physics of nonequilibrium nonaqueous phase liquid (NAPL) dissolution. The network model is a lattice of cubic chambers and rectangular tubes that represent pore bodies and pore throats, respectively. Experimental data obtained by&nbsp;</span><i>Powers</i><span><span>&nbsp;</span>[1992] were used to develop and validate the model. To ensure the network model was representative of a real porous medium, the pore size distribution of the network was calibrated by matching simulated and experimental drainage and imbibition capillary pressure‐saturation curves. The predicted network residual styrene blob‐size distribution was nearly identical to the observed distribution. The network model reproduced the observed hydraulic conductivity and produced relative permeability curves that were representative of a poorly consolidated sand. Aqueous‐phase transport was represented by applying the equation for solute flux to the network tubes and solving for solute concentrations in the network chambers. Complete mixing was found to be an appropriate approximation for calculation of chamber concentrations. Mass transfer from NAPL blobs was represented using a corner diffusion model. Predicted results of solute concentration versus Peclet number and of modified Sherwood number versus Peclet number for the network model compare favorably with experimental data for the case in which NAPL blob dissolution was negligible. Predicted results of normalized effluent concentration versus pore volume for the network were similar to the experimental data for the case in which NAPL blob dissolution occurred with time.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/1999WR900301","usgsCitation":"Dillard, L.A., and Blunt, M.J., 2000, Development of a pore network simulation model to study nonaqueous phase liquid dissolution: Water Resources Research, v. 36, no. 2, p. 439-454, https://doi.org/10.1029/1999WR900301.","productDescription":"16 p. ","startPage":"439","endPage":"454","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":479143,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/1999wr900301","text":"Publisher Index Page"},{"id":337728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58cba422e4b0849ce97dc78e","contributors":{"authors":[{"text":"Dillard, Leslie A.","contributorId":189405,"corporation":false,"usgs":false,"family":"Dillard","given":"Leslie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":684740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blunt, Martin J.","contributorId":189406,"corporation":false,"usgs":false,"family":"Blunt","given":"Martin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":684741,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70207885,"text":"70207885 - 2000 - Formation of submarine flat-topped volcanic cones in Hawai'i","interactions":[],"lastModifiedDate":"2020-01-16T16:04:43","indexId":"70207885","displayToPublicDate":"2000-01-16T15:58:23","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Formation of submarine flat-topped volcanic cones in Hawai'i","docAbstract":"<p><span>High-resolution bathymetric mapping has shown that submarine flat-topped volcanic cones, morphologically similar to ones on the deep sea floor and near mid-ocean ridges, are common on or near submarine rift zones of Kilauea, Kohala (or Mauna Kea), Mahukona, and Haleakala volcanoes. Four flat-topped cones on Kohala were explored and sampled with the&nbsp;</span><i>Pisces V</i><span>&nbsp;submersible in October 1998. Samples show that flat-topped cones on rift zones are constructed of tholeiitic basalt erupted during the shield stage. Similarly shaped flat-topped cones on the northwest submarine flank of Ni'ihau are apparently formed of alkalic basalt erupted during the rejuvenated stage. Submarine postshield-stage eruptions on Hilo Ridge, Mahukona, Hana Ridge, and offshore Ni'ihau form pointed cones of alkalic basalt and hawaiite. The shield stage flat-topped cones have steep (∼25°) sides, remarkably flat horizontal tops, basal diameters of 1–3 km, and heights &lt;300 m. The flat tops commonly have either a low mound or a deep crater in the center. The rejuvenated-stage flat-topped cones have the same shape with steep sides and flat horizontal tops, but are much larger with basal diameters up to 5.5 km and heights commonly greater than 200 m. The flat tops have a central low mound, shallow crater, or levees that surrounded lava ponds as large as 1 km across. Most of the rejuvenated-stage flat-topped cones formed on slopes &lt;10° and formed adjacent semicircular steps down the flank of Ni'ihau, rather than circular structures. All the flat-topped cones appear to be monogenetic and formed during steady effusive eruptions lasting years to decades. These, and other submarine volcanic cones of similar size and shape, apparently form as continuously overflowing submarine lava ponds. A lava pond surrounded by a levee forms above a sea-floor vent. As lava continues to flow into the pond, the lava flow surface rises and overflows the lowest point on the levee, forming elongate pillow lava flows that simultaneously build the rim outward and upward, but also dam and fill in the low point on the rim. The process repeats at the new lowest point, forming a circular structure with a flat horizontal top and steep pillowed margins. There is a delicate balance between lava (heat) supply to the pond and cooling and thickening of the floating crust. Factors that facilitate construction of such landforms include effusive eruption of lava with low volatile contents, moderate to high confining pressure at moderate to great ocean depth, long-lived steady eruption (years to decades), moderate effusion rates (probably ca. 0.1 km</span><sup>3</sup><span>/year), and low, but not necessarily flat, slopes. With higher effusion rates, sheet flows flood the slope. With lower effusion rates, pillow mounds form. Hawaiian shield-stage eruptions begin as fissure eruptions. If the eruption is too brief, it will not consolidate activity at a point, and fissure-fed flows will form a pond with irregular levees. The pond will solidify between eruptive pulses if the eruption is not steady. Lava that is too volatile rich or that is erupted in too shallow water will produce fragmental and highly vesicular lava that will accumulate to form steep pointed cones, as occurs during the post-shield stage. The steady effusion of lava on land constructs lava shields, which are probably the subaerial analogs to submarine flat-topped cones but formed under different cooling conditions.</span></p>","language":"English","publisher":"Springer Nature Switzerland ","doi":"10.1007/s004450000088","usgsCitation":"Clague, D., Moore, J.G., and Reynolds, J., 2000, Formation of submarine flat-topped volcanic cones in Hawai'i: Bulletin of Volcanology, v. 62, p. 214-233, https://doi.org/10.1007/s004450000088.","productDescription":"20 p.","startPage":"214","endPage":"233","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":371326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hawaii","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -161.6748046875,\n              17.8742034396575\n            ],\n            [\n              -154.27001953125,\n              17.8742034396575\n            ],\n            [\n              -154.27001953125,\n              23.160563309048314\n            ],\n            [\n              -161.6748046875,\n              23.160563309048314\n            ],\n            [\n              -161.6748046875,\n              17.8742034396575\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clague, D.","contributorId":9398,"corporation":false,"usgs":true,"family":"Clague","given":"D.","affiliations":[],"preferred":false,"id":779635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, James G. 0000-0002-7543-2401 jmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-7543-2401","contributorId":2892,"corporation":false,"usgs":true,"family":"Moore","given":"James","email":"jmoore@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":779636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, J.R.","contributorId":72942,"corporation":false,"usgs":true,"family":"Reynolds","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":779637,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207686,"text":"70207686 - 2000 - Effort explores 130 Million years of Antarctic paleoenvironment","interactions":[],"lastModifiedDate":"2020-06-08T20:47:40.223184","indexId":"70207686","displayToPublicDate":"2000-01-06T12:30:51","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1578,"text":"Eos, Transactions, American Geophysical Union","onlineIssn":"2324-9250","printIssn":"0096-394","active":true,"publicationSubtype":{"id":10}},"title":"Effort explores 130 Million years of Antarctic paleoenvironment","docAbstract":"<p>Antarctic climate history has been dominated by events and turning points with causes that are poorly understood. To fill the gaps in our knowledges new effort is underway in the international geologic community to acquire and coordinate the circum‐Antarctic geologic data needed to derive and model paleoenvironments of the past 130 m.y. The effort, which focuses principally on using shallow (&lt;100 m) stratigraphic drilling and coring to acquire the geologic data, is being led by the Antarctic Offshore Stratigraphy Project (ANTOSTRAT), a group that works under the aegis of the Scientific Committee on Antarctic Research (SCAR).</p><p>About 40 scientists from 12 countries met this past summer in Wellington, New Zealand, at an ANTOSTRAT meeting to discuss strategies for implementing the desired paleoenvironmental field and modeling studies. The meeting was held in conjunction with the 8th International Symposium on Antarctic Earth Sciences.</p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/00EO00024","usgsCitation":"Kristoffersen, Y., Goodwin, I., and Cooper, A.K., 2000, Effort explores 130 Million years of Antarctic paleoenvironment: Eos, Transactions, American Geophysical Union, v. 81, no. 4, p. 36-37, https://doi.org/10.1029/00EO00024.","productDescription":"2 p.","startPage":"36","endPage":"37","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":479147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/00eo00024","text":"Publisher Index Page"},{"id":371010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Kristoffersen, Yngve","contributorId":191863,"corporation":false,"usgs":false,"family":"Kristoffersen","given":"Yngve","email":"","affiliations":[],"preferred":false,"id":778942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodwin, I.D.","contributorId":81676,"corporation":false,"usgs":true,"family":"Goodwin","given":"I.D.","email":"","affiliations":[],"preferred":false,"id":778943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, Alan K. acooper@usgs.gov","contributorId":2854,"corporation":false,"usgs":true,"family":"Cooper","given":"Alan","email":"acooper@usgs.gov","middleInitial":"K.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":778944,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70073401,"text":"70073401 - 2000 - Changes in North Atlantic deep-sea temperature during climatic fluctuations of the last 25,000 years based on ostracode Mg/Ca ratios","interactions":[],"lastModifiedDate":"2014-01-16T16:02:56","indexId":"70073401","displayToPublicDate":"2000-01-01T15:58:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Changes in North Atlantic deep-sea temperature during climatic fluctuations of the last 25,000 years based on ostracode Mg/Ca ratios","docAbstract":"We reconstructed three time series of last glacial-to-present deep-sea temperature from deep and intermediate water sediment cores from the western North Atlantic using Mg/Ca ratios of benthic ostracode shells. Although the Mg/Ca data show considerable variability (“scatter”) that is common to single-shell chemical analyses, comparisons between cores, between core top shells and modern bottom water temperatures (BWT), and comparison to other paleo-BWT proxies, among other factors, suggest that multiple-shell average Mg/Ca ratios provide reliable estimates of BWT history at these sites. The BWT records show not only glacial-to-interglacial variations but also indicate BWT changes during the deglacial and within the Holocene interglacial stage. At the deeper sites (4500- and 3400-m water depth), BWT decreased during the last glacial maximum (LGM), the late Holocene, and possibly during the Younger Dryas. Maximum deep-sea warming occurred during the latest deglacial and early Holocene, when BWT exceeded modern values by as much as 2.5°C. This warming was apparently most intense around 3000 m, the depth of the modern-day core of North Atlantic deep water (NADW). The BWT variations at the deeper water sites are consistent with changes in thermohaline circulation: warmer BWT signifies enhanced NADW influence relative to Antarctic bottom water (AABW). Thus maximum NADW production and associated heat flux likely occurred during the early Holocene and decreased abruptly around 6500 years B.P., a finding that is largely consistent with paleonutrient studies in the deep North Atlantic. BWT changes in intermediate waters (1000-m water depth) of the subtropical gyre roughly parallel the deep BWT variations including dramatic mid-Holocene cooling of around 4°C. Joint consideration of the Mg/Ca-based BWT estimates and benthic oxygen isotopes suggests that the cooling was accompanied by a decrease in salinity at this site. Subsequently, intermediate waters warmed to modern values that match those of the early Holocene maximum of ∼7°C. Intermediate water BWT changes must also be driven by changes in ocean circulation. These results thus provide independent evidence that supports the hypothesis that deep-ocean circulation is closely linked to climate change over a range of timescales regardless of the mean climate state. More generally, the results further demonstrate the potential of benthic Mg/Ca ratios as a tool for reconstructing past ocean and climate conditions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochemistry, Geophysics, Geosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1029/2000GC000046","usgsCitation":"Dwyer, G., Cronin, T.M., Baker, P.A., and Rodriguez-Lazaro, J., 2000, Changes in North Atlantic deep-sea temperature during climatic fluctuations of the last 25,000 years based on ostracode Mg/Ca ratios: Geochemistry, Geophysics, Geosystems, v. 1, no. 12, 17 p., https://doi.org/10.1029/2000GC000046.","productDescription":"17 p.","numberOfPages":"17","costCenters":[],"links":[{"id":479148,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2000gc000046","text":"Publisher Index Page"},{"id":281215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281214,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2000GC000046"}],"volume":"1","issue":"12","noUsgsAuthors":false,"publicationDate":"2000-12-28","publicationStatus":"PW","scienceBaseUri":"53cd506be4b0b290850f3531","contributors":{"authors":[{"text":"Dwyer, Gary S.","contributorId":67642,"corporation":false,"usgs":true,"family":"Dwyer","given":"Gary S.","affiliations":[],"preferred":false,"id":488693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":488692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, Paul A.","contributorId":89446,"corporation":false,"usgs":true,"family":"Baker","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":488694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodriguez-Lazaro, Julio","contributorId":105227,"corporation":false,"usgs":true,"family":"Rodriguez-Lazaro","given":"Julio","affiliations":[],"preferred":false,"id":488695,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70073841,"text":"70073841 - 2000 - Self-ordering and complexity in epizonal mineral deposits","interactions":[],"lastModifiedDate":"2014-01-22T15:47:55","indexId":"70073841","displayToPublicDate":"2000-01-01T15:43:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":806,"text":"Annual Review of Earth and Planetary Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Self-ordering and complexity in epizonal mineral deposits","docAbstract":"Epizonal base and precious metal deposits makeup a range of familiar deposit styles including porphyry copper-gold, epithermal veins and stockworks, carbonate-replacement deposits, and polymetallic volcanic rock-hosted (VHMS) deposits. They occur along convergent plate margins and are invariably associated directly with active faults and volcanism. They are complex in form, variable in their characteristics at all scales, and highly localized in the earth’s crust.\nMore than a century of detailed research has provided an extensive base of observational data characterizing these deposits, from their regional setting to the fluid and isotope chemistry of mineral deposition. This has led to a broad understanding of the large-scale hydrothermal systems within which they form. Low salinity vapor, released by magma crystallization and dispersed into vigorously convecting groundwater systems, is recognized as a principal source of metals and the gases that control redox conditions within systems. The temperature and pressure of the ambient fluid anywhere within these systems is close to its vapor-liquid phase boundary, and mineral deposition is a consequence of short timescale perturbations generated by localized release of crustal stress.\nHowever, a review of occurrence data raises questions about ore formation that are not addressed by traditional genetic models. For example, what are the origins of banding in epithermal veins, and what controls the frequency of oscillatory lamination? What controls where the phenomenon of mineralization occurs, and why are some porphyry deposits, for example, so much larger than others?\nThe distinctive, self-organized characteristics of epizonal deposits are shown to be the result of repetitive coupling of fracture dilation consequent on brittle failure, phase separation (“boiling”), and heat transfer between fluid and host rock. Process coupling substantially increases solute concentrations and triggers fast, far-from-equilibrium depositional processes. Since these coupled processes lead to localized transient changes in fluid characteristics, paragenetic, isotope, and fluid inclusion data relate to conditions at the site of deposition and only indirectly to the characteristics of the larger-scale hydrothermal system and its longer-term behavior. The metal concentrations (i.e. grade) of deposits and their internal variation is directly related to the geometry of the fracture array at the deposit scale, whereas finer-scale oscillatory fabrics in ores may be a result of molecular scale processes.\nGiant deposits are relatively rare and develop where efficient metal deposition is spatially focused by repetitive brittle failure in active fault arrays. Some brief case histories are provided for epithermal, replacement, and porphyry mineralization. These highlight how rock competency contrasts and feedback between processes, rather than any single component of a hydrothermal system, govern the size of individual deposits. In turn, the recognition of the probabilistic nature of mineralization provides a firmer foundation through which exploration investment and risk management decisions can be made.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Annual Review of Earth and Planetary Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev.earth.28.1.669","usgsCitation":"Henley, R.W., and Berger, B.R., 2000, Self-ordering and complexity in epizonal mineral deposits: Annual Review of Earth and Planetary Sciences, v. 28, p. 669-719, https://doi.org/10.1146/annurev.earth.28.1.669.","productDescription":"54 p.","startPage":"669","endPage":"719","numberOfPages":"54","costCenters":[],"links":[{"id":281402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281401,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1146/annurev.earth.28.1.669"}],"volume":"28","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7267e4b0b2908510847d","contributors":{"authors":[{"text":"Henley, Richard W.","contributorId":107193,"corporation":false,"usgs":true,"family":"Henley","given":"Richard","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":489128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berger, Byron R. bberger@usgs.gov","contributorId":1490,"corporation":false,"usgs":true,"family":"Berger","given":"Byron","email":"bberger@usgs.gov","middleInitial":"R.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":489127,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70093771,"text":"70093771 - 2000 - Stable isotope evolution and paleolimnology of ancient Lake Creede","interactions":[],"lastModifiedDate":"2017-04-18T12:28:45","indexId":"70093771","displayToPublicDate":"2000-01-01T15:38:00","publicationYear":"2000","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}},"title":"Stable isotope evolution and paleolimnology of ancient Lake Creede","docAbstract":"<p>The lacustrine carbonate and travertine (tufa) deposits of ancient Lake Creede preserve a remarkable record of the isotopic evolution of the lake. That record indicates that the δ18O of the lake water, and by analogy its salinity, evolved through evaporation. Limited and less reliable data on hydrous minerals and fluid inclusions in early diagenetic carbonates indicate that the δD of the lake waters also evolved through evaporation. The isotope data place restrictions on models of the physical limnology of the lake and its evolution.</p><p>The closed-basin Lake Creede formed shortly after collapse of the 26.9 Ma Creede caldera. Throughout most of its history it occupied the northern three quarters of the moat between the resurgent dome and wall of the caldera. The Creede Formation was deposited in the basin, dominantly as lacustrine sediments. Travertine mounds interfinger with Creede Formation sediments along the inner and outer margins of the lake basin. An estimated one-half of the original thickness of the Creede Formation has been lost mainly to erosion although scattered remnants of the upper portion remain on the caldera walls. Two diamond core holes (CCM-1 and CCM-2) sampled the uneroded portion of the Creede Formation as part of the U.S. Continental Drilling Program. Volcaniclastic material, including tuff units deposited directly into the lake and ash washed in from the watershed, compose the main lithologies of the Creede Formation. These volcaniclastic strata were produced by episodic ring-fracture volcanism.</p><p>Lacustrine carbonates make up about 15% of the section sampled by drill core. They occur as 1 mm to 2 cm low-Mg calcite laminae alternating with siliciclastic laminae in scattered intervals throughout the preserved section. The carbonate laminae are accumulations of 5–20 µm crystallites (microsparites) and brine shrimp fecal pellets (peloids) composed mainly of microsparite particles. Low-Mg calcite also occurs as an early diagenetic replacement of gypsum or ikaite (CaCO3 ·6H2O) crystals grown displacively in the muds and silts near the water-sediment interface (rice grains). Other studies indicate that aragonite was the original CaCO3 precipitate forming the microsparite and peloidal laminae and that it converted to calcite during burial diagenesis. Samples from CCM-2 and nearby outcrop do not appear to have undergone significant isotope exchange during recrystallization. Samples from CCM-1 and nearby outcrop, however, appear to have undergone extensive oxygen isotope exchange with meteoric water-dominated fluids possibly during a local 17.6 Ma hydrothermal event.</p><p>The δ18O-δ13C data set produced by microsampling of individual carbonate lamellae and rice grains is exceptional in several aspects and provides important clues concerning the evolution of limnologic structure of the lake and its chemical and isotopic composition. Travertine and ikaite pseudomorphs in travertine deposits extend the record an additional 330 m above the collar of CCM-2. The δ18O values on CCM-2 samples range from 10.4‰ to 37.3‰ and δ13C values range from –10.8‰ to 9.6‰. The data fall into two distinct groups, a covariant group and an invariant group. The covariant group shows a strong negative covariance and a large range of δ18O and δ13C values. The negative covariance is opposite that normally reported for lacustrine carbonates. The large range of δ18O and δ13C values requires that the carbonates precipitated from waters have a large range of temperature and carbon and oxygen isotopic composition. The invariant group has a narrow range of large δ18O values (35‰ ± 2‰) and a wide range of δ13C values (–10.8‰ to 9.6‰), indicating precipitation from waters with a narrow range of temperature and δ18O but a wide range in δ13C of aqueous carbon. The ranges of isotope values for microsparite and peloid samples are virtually identical; two-thirds are in the covariant group. By contrast, the values for almost all rice grain samples are in the invariant group. The range in δ18O for all samples reflects precipitation from waters having varying proportions of deep, cold evaporated lake water and shallow, warmer meteoric water. The range for δ13C reflects varying proportions of organic carbon and carbon of volcanic or atmospheric origin, probably dominantly volcanic, in the aqueous carbon.</p><p>Changes in the detailed carbon-oxygen isotope systematics with stratigraphic position define three periods of isotopic evolution of Lake Creede. Period I is represented by the lowest ~200 m of Creede Formation core in CCM-2. Analyses of individual microsparite and peloidal carbonate laminae within single thin sections of samples from that interval are tightly grouped. The data set as a whole shows a negative covariance. Rice grains are not found in this interval. Period II is represented by the succeeding 120 m of core in CCM-2. In that interval, δ13C-δ18O values for individual microsparite and peloidal carbonate laminae within single thin sections show strong negative covariance, and the set of values for the entire interval also shows strong negative covariance. Rice grains occur near the top of the interval. Period III is represented by the upper 225 m of CCM-2 core. In this interval, rice grains are abundant and δ13C-δ18O values for microsparite and peloidal laminae as well as rice grains fall in the invariant group.</p><p>During Period I the lake was well mixed and the oxygen isotopic composition of the lake in the productive zone was only slightly influenced by short-term (e.g., annual) variations in the water budget of the lake. In Period II the lake was stratified, possibly with annual overturn. The productive zone included the mixolimnion and the isotopic composition of the microsparites and peloids reflected mixtures of shallow surface (meteoric) water containing volcanic or atmospheric CO2 (epilimnion) and cold underlying waters, the oxygen isotopic compositions of which had evolved through evaporation and were dominated by CO2 produced by the oxidation of organic matter (hypolimnion). During Period III the lake remained stratified. The productive zone was in the hypolimnion, probably due to a thinning of the epilimnion resulting from an increase in the surface area of the lake or a decrease in input waters reflecting a climate change. An upsection increase in values of δ18O for the heaviest samples during Periods I and II indicates evaporative concentration of 18O and, by analogy, salinity in the hypolimnion.</p><p>The δD-δ18O evolution of the lake is inferred on theoretical evaporation trends, comparison to Mono Lake, and measurement of the δD in fluid inclusions in a calcite pseudomorph after ikaite. The δD-δ18O composition of the lake water followed a curved path that eventually hooked over at a nearly constant δ18O value for the lake of 2‰ ± 2‰</p><p>Travertine (tufa) mounds formed along the inner and outer margins of the lake in a zone of mixing of warm, volcanic CO2-bearing, meteoric waters and lake water. Ikaite crystals formed on the mounds from unmixed saline lake water, probably below the thermocline. As the position of the thermocline deepened, likely following the spring runoff, the ikaite was replaced by calcite and the resulting “pearls” were covered with travertine deposited from mixed meteoric and lake waters.</p><p>The upsection increase in δ18O values of the carbonates, the long period of invariance of large δ18OH2O values, the presence of brine shrimp fecal pellets, and the inferred hooked δD-δ18O path are consistent with evidence from other studies that Lake Creede obtained significant salinity rather early in its history and certainly by the time the lake became permanently stratified.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"GSA Special Papers","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/0-8137-2346-9.233","usgsCitation":"Rye, R.O., Bethke, P., and Finkelstein, D., 2000, Stable isotope evolution and paleolimnology of ancient Lake Creede: GSA Special Papers, v. 346, p. 233-265, https://doi.org/10.1130/0-8137-2346-9.233.","productDescription":"33 p.","startPage":"233","endPage":"265","numberOfPages":"33","costCenters":[],"links":[{"id":282376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282335,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/0-8137-2346-9.233"}],"country":"United States","state":"Colorado","city":"Creede","otherGeospatial":"Lake Creede","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.934323,37.841685 ], [ -106.934323,37.869147 ], [ -106.919627,37.869147 ], [ -106.919627,37.841685 ], [ -106.934323,37.841685 ] ] ] } } ] }","volume":"346","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd73e1e4b0b29085109352","contributors":{"authors":[{"text":"Rye, Robert O. rrye@usgs.gov","contributorId":1486,"corporation":false,"usgs":true,"family":"Rye","given":"Robert","email":"rrye@usgs.gov","middleInitial":"O.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bethke, Philip M.","contributorId":52829,"corporation":false,"usgs":true,"family":"Bethke","given":"Philip M.","affiliations":[],"preferred":false,"id":490214,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finkelstein, David B.","contributorId":64687,"corporation":false,"usgs":true,"family":"Finkelstein","given":"David B.","affiliations":[],"preferred":false,"id":490215,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70073840,"text":"70073840 - 2000 - Trace metal-rich Quaternary hydrothermal manganese oxide and barite deposit, Milos Island, Greece","interactions":[],"lastModifiedDate":"2014-01-22T15:12:15","indexId":"70073840","displayToPublicDate":"2000-01-01T15:08:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":829,"text":"Applied Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Trace metal-rich Quaternary hydrothermal manganese oxide and barite deposit, Milos Island, Greece","docAbstract":"The Cape Vani Mn oxide and barite deposit on Milos Island offers an excellent opportunity to study the three-dimensional characteristics of a shallow-water hydrothermal system. Milos Island is part of the active Aegean volcanic arc. A 1 km long basin located between two dacitic domes in northwest Milos is filled with a 35-50 m thick section of Quaternary volcaniclastic and pyroclastic rocks capped by reef limestone that were hydrothermally mineralized by Mn oxides and barite. Manganese occurs as thin layers, as cement of sandstone and as metasomatic replacement of the limestone, including abundant fossil shells. Manganese minerals include chiefly δ-MnO2, pyrolusite and ramsdellite. The MnO contents for single beds range up to 60%. The Mn oxide deposits are rich in Pb (to 3.4%), BaO (to 3.1%), Zn (to 0.8%), As (to 0.3%), Sb (to 0.2%) and Ag (to 10 ppm). Strontium isotopic compositions of the Mn oxide deposits and sulphur isotopic compositions of the associated barite show that the mineralizing fluids were predominantly sea water. The Mn oxide deposit formed in close geographical proximity to sulphide-sulphate-Au-Ag deposits and the two deposit types probably formed from the same hydrothermal system. Precipitation of Mn oxide took place at shallow burial depths and was promoted by the mixing of modified sea water (hydrothermal fluid) from which the sulphides precipitated at depth and sea water that penetrated along faults and fractures in the Cape Vani volcaniclastic and tuff deposits. The hydrothermal fluid was formed from predominantly sea water that was enriched in metals leached from the basement and overlying volcanogenic rocks. The hydrothermal fluids were driven by convection sustained by heat from cooling magma chambers. Barite was deposited throughout the time of Mn oxide mineralization, which occurred in at least two episodes. Manganese mineralization occurred by both focused and diffuse flow, the fluids mineralizing the beds of greatest porosity and filling dilatational fractures along with barite.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Earth Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Institute of Mining and Metallurgy","doi":"10.1179/aes.2000.109.2.67","usgsCitation":"Hein, J., Stamatakis, G., and Dowling, J., 2000, Trace metal-rich Quaternary hydrothermal manganese oxide and barite deposit, Milos Island, Greece: Applied Earth Sciences, v. 109, no. 2, p. 67-76, https://doi.org/10.1179/aes.2000.109.2.67.","productDescription":"10 p.","startPage":"67","endPage":"76","numberOfPages":"10","costCenters":[],"links":[{"id":281400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281399,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1179/aes.2000.109.2.67"}],"country":"Greece","otherGeospatial":"Milos Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 24.317285,36.644784 ], [ 24.317285,36.774206 ], [ 24.547792,36.774206 ], [ 24.547792,36.644784 ], [ 24.317285,36.644784 ] ] ] } } ] }","volume":"109","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-07-18","publicationStatus":"PW","scienceBaseUri":"53cd7972e4b0b2908510cd19","contributors":{"authors":[{"text":"Hein, J.R. 0000-0002-5321-899X","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":61429,"corporation":false,"usgs":true,"family":"Hein","given":"J.R.","affiliations":[],"preferred":false,"id":489125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stamatakis, G.","contributorId":9959,"corporation":false,"usgs":true,"family":"Stamatakis","given":"G.","email":"","affiliations":[],"preferred":false,"id":489124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dowling, J.S.","contributorId":72443,"corporation":false,"usgs":true,"family":"Dowling","given":"J.S.","email":"","affiliations":[],"preferred":false,"id":489126,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70093982,"text":"70093982 - 2000 - Streamflow changes in the Sierra Nevada, California, simulated using a statistically downscaled general circulation model scenario of climate change","interactions":[],"lastModifiedDate":"2016-07-27T12:54:27","indexId":"70093982","displayToPublicDate":"2000-01-01T15:01:00","publicationYear":"2000","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Streamflow changes in the Sierra Nevada, California, simulated using a statistically downscaled general circulation model scenario of climate change","docAbstract":"<p>Simulations of future climate using general circulation models (GCMs) suggest that rising concentrations of greenhouse gases may have significant consequences for the global climate. Of less certainty is the extent to which regional scale (i.e., sub-GCM grid) environmental processes will be affected. In this chapter, a range of downscaling techniques are critiqued. Then a relatively simple (yet robust) statistical downscaling technique and its use in the modelling of future runoff scenarios for three river basins in the Sierra Nevada, California, is described. This region was selected because GCM experiments driven by combined greenhouse-gas and sulphate-aerosol forcings consistently show major changes in the hydro-climate of the southwest United States by the end of the 21st century. The regression-based downscaling method was used to simulate daily rainfall and temperature series for streamflow modelling in three Californian river basins under current-and future-climate conditions. The downscaling involved just three predictor variables (specific humidity, zonal velocity component of airflow, and 500 hPa geopotential heights) supplied by the U.K. Meteorological Office couple ocean-atmosphere model (HadCM2) for the grid point nearest the target basins. When evaluated using independent data, the model showed reasonable skill at reproducing observed area-average precipitation, temperature, and concomitant streamflow variations. Overall, the downscaled data resulted in slight underestimates of mean annual streamflow due to underestimates of precipitation in spring and positive temperature biases in winter. Differences in the skill of simulated streamflows amongst the three basins were attributed to the smoothing effects of snowpack on streamflow responses to climate forcing. The Merced and American River basins drain the western, windward slope of the Sierra Nevada and are snowmelt dominated, whereas the Carson River drains the eastern, leeward slope and is a mix of rainfall runoff and snowmelt runoff. Simulated streamflow in the American River responds rapidly and sensitively to daily-scale temperature and precipitation fluctuations and errors; in the Merced and Carson Rivers, the response to the same short-term influences is much less. Consequently, the skill of simulated flows was significantly lower in the American River model than in the Carson and Merced. The physiography of the three basins also accounts for differences in their sensitivities to future climate change. Increases in winter precipitation exceeding +100% coupled with mean temperature rises greater than +2&deg;C result in increased winter streamflows in all three basins. In the Merced and Carson basins, these streamflow increases reflect large changes in winter snowpack, whereas the streamflow changes in the lower elevation American basin are driven primarily by rainfall runoff. Furthermore, reductions in winter snowpack in the American River basin, owing to less precipitation falling as snow and earlier melting of snow at middle elevations, lead to less spring and summer streamflow. Taken collectively, the downscaling results suggest significant changes to both the timing and magnitude of streamflows in the Sierra Nevada by the end of the 21st Century. In the higher elevation basins, the HadCM2 scenario implies more annual streamflow and more streamflow during the spring and summer months that are critical for water-resources management in California. Depending on the relative significance of rainfall runoff and snowmelt, each basin responds in its own way to regional climate forcing. Generally, then, climate scenarios need to be specified &mdash; by whatever means &mdash; with sufficient temporal and spatial resolution to capture subtle orographic influences if projections of climate-change responses are to be useful and reproducible.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Linking climate change to land surface change","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","doi":"10.1007/0-306-48086-7_6","isbn":"978-0-306-48086-7","usgsCitation":"Wilby, R.L., and Dettinger, M., 2000, Streamflow changes in the Sierra Nevada, California, simulated using a statistically downscaled general circulation model scenario of climate change, chap. <i>of</i> Linking climate change to land surface change, v. 6, p. 99-121, https://doi.org/10.1007/0-306-48086-7_6.","productDescription":"23 p.","startPage":"99","endPage":"121","numberOfPages":"23","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":5079,"text":"Pacific Regional Director's Office","active":true,"usgs":true}],"links":[{"id":282436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282435,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/0-306-48086-7_6"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.886496,37.494762 ], [ -119.886496,38.185228 ], [ -119.195416,38.185228 ], [ -119.195416,37.494762 ], [ -119.886496,37.494762 ] ] ] } } ] }","volume":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7493e4b0b290851099eb","contributors":{"authors":[{"text":"Wilby, Robert L.","contributorId":101561,"corporation":false,"usgs":true,"family":"Wilby","given":"Robert","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":490412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dettinger, Michael D. 0000-0002-7509-7332","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":31743,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael D.","affiliations":[],"preferred":false,"id":490411,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70073541,"text":"70073541 - 2000 - Hydrologic and geologic characteristics of the Yucca Mountain site relevant to the performance of a potential repository","interactions":[],"lastModifiedDate":"2021-04-09T13:14:53.172784","indexId":"70073541","displayToPublicDate":"2000-01-01T14:46:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1724,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic and geologic characteristics of the Yucca Mountain site relevant to the performance of a potential repository","docAbstract":"Yucca Mountain, located ~100 mi northwest of Las Vegas, Nevada, has been designated by Congress as a site to be characterized for a potential mined geologic repository for high-level radioactive waste. This field trip will examine the regional geologic and hydrologic setting for Yucca Mountain, as well as specific results of the site characterization program. The first day focuses on the regional setting with emphasis on current and paleo hydrology, which are both of critical concern for predicting future performance of a potential repository. Morning stops will be southern Nevada and afternoon stops will be in Death Valley. The second day will be spent at Yucca Mountain. The field trip will visit the underground testing sites in the \"Exploratory Studies Facility\" and the \"Busted Butte Unsaturated Zone Transport Field Test\" plus several surface-based testing sites. Much of the work at the site has concentrated on studies of the unsaturated zone, an element of the hydrologic system that historically has received little attention. Discussions during the second day will compromise selected topics of Yucca Mountain geology, hydrology and geochemistry and will include the probabilistic volcanic hazard analysis and the seismicity and seismic hazard in the Yucca Mountain area. Evening discussions will address modeling of regional groundwater flow, the results of recent hydrologic studies by the Nye County Nuclear Waste Program Office, and the relationship of the geology and hydrology of Yucca Mountain to the performance of a potential repository. Day 3 will examine the geologic framework and hydrology of the Pahute Mesa-Oasis Valley Groundwater Basin and then will continue to Reno via Hawthorne, Nevada and the Walker Lake area.","language":"English","publisher":"Geological Society of America","doi":"10.1130/0-8137-0002-7.383","usgsCitation":"Levich, R., Linden, R., Patterson, R., and Stuckless, J., 2000, Hydrologic and geologic characteristics of the Yucca Mountain site relevant to the performance of a potential repository: GSA Field Guides, v. 2, p. 383-414, https://doi.org/10.1130/0-8137-0002-7.383.","productDescription":"32 p.","startPage":"383","endPage":"414","numberOfPages":"32","costCenters":[],"links":[{"id":281259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Yucca Mountain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.0,36.0 ], [ -117.0,37.0 ], [ -115.0,37.0 ], [ -115.0,36.0 ], [ -117.0,36.0 ] ] ] } } ] }","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd615ee4b0b290850fd7c7","contributors":{"authors":[{"text":"Levich, R.A.","contributorId":68553,"corporation":false,"usgs":true,"family":"Levich","given":"R.A.","affiliations":[],"preferred":false,"id":488909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linden, R.M.","contributorId":66007,"corporation":false,"usgs":true,"family":"Linden","given":"R.M.","email":"","affiliations":[],"preferred":false,"id":488908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, R.L.","contributorId":24272,"corporation":false,"usgs":true,"family":"Patterson","given":"R.L.","email":"","affiliations":[],"preferred":false,"id":488907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stuckless, J. S.","contributorId":6060,"corporation":false,"usgs":true,"family":"Stuckless","given":"J. S.","affiliations":[],"preferred":false,"id":488906,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70074108,"text":"70074108 - 2000 - Can contaminant transport models predict breakthrough?","interactions":[],"lastModifiedDate":"2018-12-14T06:42:02","indexId":"70074108","displayToPublicDate":"2000-01-01T14:15:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1866,"text":"Groundwater Monitoring & Remediation","active":true,"publicationSubtype":{"id":10}},"title":"Can contaminant transport models predict breakthrough?","docAbstract":"A solute breakthrough curve measured during a two-well tracer test was successfully predicted in 1986 using specialized contaminant transport models. Water was injected into a confined, unconsolidated sand aquifer and pumped out 125 feet (38.3 m) away at the same steady rate. The injected water was spiked with bromide for over three days; the outflow concentration was monitored for a month. Based on previous tests, the horizontal hydraulic conductivity of the thick aquifer varied by a factor of seven among 12 layers. Assuming stratified flow with small dispersivities, two research groups accurately predicted breakthrough with three-dimensional (12-layer) models using curvilinear elements following the arc-shaped flowlines in this test.\n\nCan contaminant transport models commonly used in industry, that use rectangular blocks, also reproduce this breakthrough curve? The two-well test was simulated with four MODFLOW-based models, MT3D (FD and HMOC options), MODFLOWT, MOC3D, and MODFLOW-SURFACT.\n\nUsing the same 12 layers and small dispersivity used in the successful 1986 simulations, these models fit almost as accurately as the models using curvilinear blocks. Subtle variations in the curves illustrate differences among the codes. Sensitivities of the results to number and size of grid blocks, number of layers, boundary conditions, and values of dispersivity and porosity are briefly presented. The fit between calculated and measured breakthrough curves degenerated as the number of layers and/or grid blocks decreased, reflecting a loss of model predictive power as the level of characterization lessened. Therefore, the breakthrough curve for most field sites can be predicted only qualitatively due to limited characterization of the hydrogeology and contaminant source strength.","language":"English","publisher":"Wiley","doi":"10.1111/j.1745-6592.2000.tb00295.x","usgsCitation":"Peng, W., Hampton, D.R., Konikow, L.F., Kambham, K., and Benegar, J.J., 2000, Can contaminant transport models predict breakthrough?: Groundwater Monitoring & Remediation, v. 20, no. 4, p. 104-113, https://doi.org/10.1111/j.1745-6592.2000.tb00295.x.","productDescription":"10 p.","startPage":"104","endPage":"113","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":281587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281586,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6592.2000.tb00295.x"}],"country":"United States","state":"Alabama","city":"Mobile","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.221253,30.560374 ], [ -88.221253,30.843458 ], [ -87.956616,30.843458 ], [ -87.956616,30.560374 ], [ -88.221253,30.560374 ] ] ] } } ] }","volume":"20","issue":"4","noUsgsAuthors":false,"publicationDate":"2007-02-22","publicationStatus":"PW","scienceBaseUri":"53cd501de4b0b290850f3217","contributors":{"authors":[{"text":"Peng, Wei-Shyuan","contributorId":108389,"corporation":false,"usgs":true,"family":"Peng","given":"Wei-Shyuan","email":"","affiliations":[],"preferred":false,"id":489415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hampton, Duane R.","contributorId":65377,"corporation":false,"usgs":true,"family":"Hampton","given":"Duane","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":489413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Konikow, Leonard F. 0000-0002-0940-3856 lkonikow@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-3856","contributorId":158,"corporation":false,"usgs":true,"family":"Konikow","given":"Leonard","email":"lkonikow@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":489411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kambham, Kiran","contributorId":100284,"corporation":false,"usgs":true,"family":"Kambham","given":"Kiran","email":"","affiliations":[],"preferred":false,"id":489414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Benegar, Jeffery J.","contributorId":8760,"corporation":false,"usgs":true,"family":"Benegar","given":"Jeffery","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":489412,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70073370,"text":"70073370 - 2000 - Late Cenozoic crustal extension and magmatism, southern Death Valley region, California","interactions":[],"lastModifiedDate":"2014-01-16T14:20:19","indexId":"70073370","displayToPublicDate":"2000-01-01T14:02:00","publicationYear":"2000","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1724,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":10}},"title":"Late Cenozoic crustal extension and magmatism, southern Death Valley region, California","docAbstract":"The late Cenozoic geologic history of the southern Death Valley region is characterized by coeval crustal extension and magamatism. Crustal extension is accommodated by numerous listric and planar normal faults as well as right- and left-lateral strike slip faults. The normal faults sip 30&deg;-50&deg; near the surface and flatten and merge leozoic miogeoclinal rocks; the strike-slip faults act as tear faults between crustal blocks that have extended at different times and at different rates. Crustal extension began 13.4-13.1 Ma and migrated northwestward with time; undeformed basalt flows and lacustrine deposits suggest that extension stopped in this region (but continued north of the Death Valley graben) between 5 and 7 Ma. Estimates of crustal extension in this region vary from 30-50 percent to more than 100 percent. Magmatic rocks syntectonic with crustal extension in the southern Death Valley region include 12.4-6.4 Ma granitic rocks as well as bimodal 14.0-4.0 Ma volcanic rocks. Geochemical and isotopic evidence suggest that the granitic rocks get younger and less alkalic from south to north; the volcanic rocks become more mafic with less evidence of crustal interaction as they get younger. The close spatial and temporal relation between crustal extension and magmatism suggest a genetic and probably a dynamic relation between these geologic processes. We propose a rectonic-magmatic model that requires heat to be transported into the crust by mantle-derived mafic magmas. These magmas pond at lithologic or rheologic boundaries, begin the crystallize, and partially melt the surrounding crustal rocks. With time, the thermally weakened crust is extended (given a regional extensional stress field) concurrent with granitic magmatism and bimodal volcanism.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"GSA Field Guides","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/0-8137-0002-7.135","usgsCitation":"Calzia, J., and Ramo, O., 2000, Late Cenozoic crustal extension and magmatism, southern Death Valley region, California: GSA Field Guides, v. 2, p. 135-164, https://doi.org/10.1130/0-8137-0002-7.135.","productDescription":"30 p.","startPage":"135","endPage":"164","numberOfPages":"30","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":281198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281197,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/0-8137-0002-7.135"}],"country":"United States","state":"California","otherGeospatial":"Death Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.0,35.0 ], [ -117.0,36.5 ], [ -115.0,36.5 ], [ -115.0,35.0 ], [ -117.0,35.0 ] ] ] } } ] }","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd6422e4b0b290850ff430","contributors":{"authors":[{"text":"Calzia, J.P.","contributorId":58614,"corporation":false,"usgs":true,"family":"Calzia","given":"J.P.","affiliations":[],"preferred":false,"id":488658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramo, O.T.","contributorId":15520,"corporation":false,"usgs":true,"family":"Ramo","given":"O.T.","email":"","affiliations":[],"preferred":false,"id":488657,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}