{"pageNumber":"1641","pageRowStart":"41000","pageSize":"25","recordCount":41014,"records":[{"id":70236057,"text":"70236057 - null - Characterizing the interface between wild ducks and poultry to evaluate the potential of transmission of avian pathogens","interactions":[],"lastModifiedDate":"2022-08-26T16:20:23.390723","indexId":"70236057","displayToPublicDate":"2011-11-15T11:12:57","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2050,"text":"International Journal of Health Geographics","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing the interface between wild ducks and poultry to evaluate the potential of transmission of avian pathogens","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Characterizing the interface between wild and domestic animal populations is increasingly recognized as essential in the context of emerging infectious diseases (EIDs) that are transmitted by wildlife. More specifically, the spatial and temporal distribution of contact rates between wild and domestic hosts is a key parameter for modeling EIDs transmission dynamics. We integrated satellite telemetry, remote sensing and ground-based surveys to evaluate the spatio-temporal dynamics of indirect contacts between wild and domestic birds to estimate the risk that avian pathogens such as avian influenza and Newcastle viruses will be transmitted between wildlife to poultry. We monitored comb ducks (<i>Sarkidiornis melanotos melanotos</i>) with satellite transmitters for seven months in an extensive Afro-tropical wetland (the Inner Niger Delta) in Mali and characterise the spatial distribution of backyard poultry in villages. We modelled the spatial distribution of wild ducks using 250-meter spatial resolution and 8-days temporal resolution remotely-sensed environmental indicators based on a Maxent niche modelling method.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Our results show a strong seasonal variation in potential contact rate between wild ducks and poultry. We found that the exposure of poultry to wild birds was greatest at the end of the dry season and the beginning of the rainy season, when comb ducks disperse from natural water bodies to irrigated areas near villages.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Our study provides at a local scale a quantitative evidence of the seasonal variability of contact rate between wild and domestic bird populations. It illustrates a GIS-based methodology for estimating epidemiological contact rates at the wildlife and livestock interface integrating high-resolution satellite telemetry and remote sensing data.</p>","language":"English","publisher":"Springer Nature","doi":"10.1186/1476-072X-10-60","usgsCitation":"Cappelle, J., Gaidet, N., Iverson, S.A., Takekawa, J.Y., Newman, S.H., Fofana, B., and Gilbert, M., Characterizing the interface between wild ducks and poultry to evaluate the potential of transmission of avian pathogens: International Journal of Health Geographics, v. 10, 60, 9 p., https://doi.org/10.1186/1476-072X-10-60.","productDescription":"60, 9 p.","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":480526,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/1476-072x-10-60","text":"Publisher Index Page"},{"id":405689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mali","otherGeospatial":"Inner Niger Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -4.55108642578125,\n              14.98193315445839\n            ],\n            [\n              -3.9166259765625,\n              14.98193315445839\n            ],\n            [\n              -3.9166259765625,\n              15.493385656382307\n            ],\n            [\n              -4.55108642578125,\n              15.493385656382307\n            ],\n            [\n              -4.55108642578125,\n              14.98193315445839\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cappelle, Julien","contributorId":71440,"corporation":false,"usgs":true,"family":"Cappelle","given":"Julien","email":"","affiliations":[],"preferred":false,"id":849877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaidet, Nicolas","contributorId":37601,"corporation":false,"usgs":true,"family":"Gaidet","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":849878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iverson, S. A.","contributorId":22556,"corporation":false,"usgs":true,"family":"Iverson","given":"S.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":849879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":196611,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":849880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newman, Scott H.","contributorId":199129,"corporation":false,"usgs":false,"family":"Newman","given":"Scott","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":849881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fofana, Bouba","contributorId":295743,"corporation":false,"usgs":false,"family":"Fofana","given":"Bouba","email":"","affiliations":[],"preferred":false,"id":849882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gilbert, Marius","contributorId":61148,"corporation":false,"usgs":true,"family":"Gilbert","given":"Marius","email":"","affiliations":[],"preferred":false,"id":849883,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70207642,"text":"70207642 - null - Using indirect methods to constrain symbiotic nitrogen fixation rates: A case study from an Amazonian rain forest","interactions":[],"lastModifiedDate":"2020-01-02T10:31:59","indexId":"70207642","displayToPublicDate":"2010-12-31T10:15:44","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Using indirect methods to constrain symbiotic nitrogen fixation rates: A case study from an Amazonian rain forest","docAbstract":"<p><span>Human activities have profoundly altered the global&nbsp;</span><span class=\"ScopusTermHighlight\">nitrogen</span><span>&nbsp;(N) cycle. Increases in anthropogenic N have had multiple effects on the atmosphere, on terrestrial, freshwater and marine ecosystems, and even on human health. Unfortunately, methodological limitations challenge our ability to directly measure natural N inputs via biological N&nbsp;</span><span class=\"ScopusTermHighlight\">fixation</span><span>&nbsp;(BNF)-the largest natural source of new N to ecosystems. This confounds efforts to quantify the extent of anthropogenic perturbation to the N cycle. To address this gap, we used a pair of&nbsp;</span><span class=\"ScopusTermHighlight\">indirect</span><span>&nbsp;</span><span class=\"ScopusTermHighlight\">methods</span><span>-analytical modeling and N balance-to generate independent estimates of BNF in a presumed hotspot of N&nbsp;</span><span class=\"ScopusTermHighlight\">fixation</span><span>, a tropical rain forest site in central Rondônia in the Brazilian Amazon Basin. Our objectives were to attempt to&nbsp;</span><span class=\"ScopusTermHighlight\">constrain</span><span>&nbsp;</span><span class=\"ScopusTermHighlight\">symbiotic</span><span>&nbsp;N&nbsp;</span><span class=\"ScopusTermHighlight\">fixation</span><span>&nbsp;</span><span class=\"ScopusTermHighlight\">rates</span><span>&nbsp;in this site using&nbsp;</span><span class=\"ScopusTermHighlight\">indirect</span><span>&nbsp;</span><span class=\"ScopusTermHighlight\">methods</span><span>, and to assess strengths and weaknesses of this approach by looking for areas of convergence and disagreement between the estimates. This approach yielded two remarkably similar estimates of N&nbsp;</span><span class=\"ScopusTermHighlight\">fixation</span><span>. However, when compared to a previously published bottom-up estimate, our analysis indicated much lower N inputs via&nbsp;</span><span class=\"ScopusTermHighlight\">symbiotic</span><span>&nbsp;BNF in the Rondônia site than has been suggested for the tropics as a whole. This discrepancy may reflect errors associated with extrapolating bottom-up fluxes from plot-scale measures, those resulting from the&nbsp;</span><span class=\"ScopusTermHighlight\">indirect</span><span>&nbsp;analyses, and/or the relatively low abundance of legumes at the Rondônia site. While&nbsp;</span><span class=\"ScopusTermHighlight\">indirect</span><span>&nbsp;</span><span class=\"ScopusTermHighlight\">methods</span><span>&nbsp;have some limitations, we suggest that until the technological challenges of directly measuring N&nbsp;</span><span class=\"ScopusTermHighlight\">fixation</span><span>&nbsp;are overcome, integrated approaches that employ a combination of model-generated and empirically-derived data offer a promising way of constraining N inputs via BNF in natural ecosystems.&nbsp;</span></p>","language":"English","doi":"10.1007/s10533-009-9392-y","issn":"01682563","usgsCitation":"Cleveland, C., Houlton , B., Neill, C., Reed, S.C., Wang, Y., and Townsend, A., Using indirect methods to constrain symbiotic nitrogen fixation rates: A case study from an Amazonian rain forest: Biogeochemistry, v. 99, no. 1, p. 1-13, https://doi.org/10.1007/s10533-009-9392-y.","productDescription":"13 p. ","startPage":"1","endPage":"13","costCenters":[],"links":[{"id":480528,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10533-009-9392-y","text":"Publisher Index Page"},{"id":370927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Amazonian rain forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -60.8642578125,\n              8.624472107633936\n            ],\n            [\n              -63.06152343750001,\n              7.013667927566642\n            ],\n            [\n              -64.3359375,\n              7.36246686553575\n            ],\n            [\n              -66.4453125,\n              7.449624260197816\n            ],\n            [\n              -68.291015625,\n              5.090944175033399\n            ],\n            [\n              -72.8173828125,\n              3.425691524418062\n            ],\n            [\n              -76.201171875,\n              2.3723687086440504\n            ],\n            [\n              -78.2666015625,\n              -1.7575368113083125\n            ],\n            [\n              -79.0576171875,\n              -5.266007882805485\n            ],\n            [\n              -76.552734375,\n              -9.622414142924805\n            ],\n            [\n              -73.6962890625,\n              -13.025965926333539\n            ],\n            [\n              -71.2353515625,\n              -12.983147716796566\n            ],\n            [\n              -68.3349609375,\n              -16.003575733881313\n            ],\n            [\n              -59.9853515625,\n              -16.13026201203474\n            ],\n            [\n              -55.06347656249999,\n              -16.214674588248542\n            ],\n            [\n              -50.625,\n              -8.971897294083014\n            ],\n            [\n              -48.8671875,\n              -2.5040852618529215\n            ],\n            [\n              -48.3837890625,\n              -0.21972602392080884\n            ],\n            [\n              -51.591796875,\n              4.477856485570586\n            ],\n            [\n              -56.99707031249999,\n              6.053161295714067\n            ],\n            [\n              -60.8642578125,\n              8.624472107633936\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"99","issue":"1","noUsgsAuthors":false,"publicationDate":"2009-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Cleveland, C.C.","contributorId":62387,"corporation":false,"usgs":true,"family":"Cleveland","given":"C.C.","email":"","affiliations":[],"preferred":false,"id":778715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houlton , B.Z. ","contributorId":221564,"corporation":false,"usgs":false,"family":"Houlton ","given":"B.Z. ","affiliations":[],"preferred":false,"id":778716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neill, C","contributorId":221565,"corporation":false,"usgs":false,"family":"Neill","given":"C","email":"","affiliations":[],"preferred":false,"id":778717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":778718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Y","contributorId":221568,"corporation":false,"usgs":false,"family":"Wang","given":"Y","affiliations":[],"preferred":false,"id":778719,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Townsend, A.R.","contributorId":16631,"corporation":false,"usgs":true,"family":"Townsend","given":"A.R.","email":"","affiliations":[],"preferred":false,"id":778720,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256005,"text":"70256005 - null - Simulation of the long term radiometric responses of the Terra MODIS and EO-1 ALI using Hyperion spectral responses over Railroad Valley Playa in Nevada (RVPN)","interactions":[],"lastModifiedDate":"2024-07-12T14:32:29.122156","indexId":"70256005","displayToPublicDate":"2010-11-04T09:23:35","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Simulation of the long term radiometric responses of the Terra MODIS and EO-1 ALI using Hyperion spectral responses over Railroad Valley Playa in Nevada (RVPN)","docAbstract":"<p><span>The Earth Observing-1 (EO-1) Hyperion instrument provides 220 spectral bands with wavelengths between 400 and 2500 nm at 30 m spatial resolution, which covers a 7.5 km by 100 km area on the ground. The EO-1 spacecraft has another multispectral sensor called the Advanced Land Imager (ALI), which has 10 spectral bands with wavelengths between 400 and 2350 nm at 30 m spatial resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra spacecraft was launched in Dec., 1999, and flies approximately 30 minutes behind EO-1. Nearsimultaneous observations from Terra MODIS, EO-1 ALI and Hyperion over a well characterized Railroad Valley Playa in Nevada (RVPN) target are chosen for this study. A uniform region of interest (ROI) within the playa within latitudes and longitudes of 38.48 and -115.71 to 38.53 and -115.66 was chosen for this analysis. A representation of the ground spectra during every near-simultaneous acquisition of MODIS and ALI is obtained using EO-1 Hyperion data. Using the EO-1 Hyperion derived top-of-atmosphere (TOA) reflectance profile along with the ALI and MODIS relative spectral responses (RSR), simulated reflectance for the matching band pairs is calculated. The Hyperion simulated TOA reflectance results are compared to the measured TOA reflectance trends of ALI and MODIS. The long-term measured versus simulated reflectance results are used to examine the relationships and calibration differences between the ALI and MODIS sensors.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SPIE 7862, Earth observing missions and sensors: Development, implementation, and characterization","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Earth Observing Missions and Sensors: Development, Implementation, and Characterization","conferenceDate":"October 11-14, 2010","conferenceLocation":"Incheon, Republic of Korea","language":"English","publisher":"Society of Photo-Optical Instrumentation Engineers (SPIE)","doi":"10.1117/12.868963","usgsCitation":"Choi, T., Xiong, X., Angal, A., and Chander, G., Simulation of the long term radiometric responses of the Terra MODIS and EO-1 ALI using Hyperion spectral responses over Railroad Valley Playa in Nevada (RVPN), <i>in</i> Proceedings of SPIE 7862, Earth observing missions and sensors: Development, implementation, and characterization, v. 7862, Incheon, Republic of Korea, October 11-14, 2010, 78620H, 11 p., https://doi.org/10.1117/12.868963.","productDescription":"78620H, 11 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":431006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7862","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Choi, Taeyoung","contributorId":146955,"corporation":false,"usgs":false,"family":"Choi","given":"Taeyoung","email":"","affiliations":[],"preferred":false,"id":906334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":906335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angal, Amit","contributorId":67394,"corporation":false,"usgs":true,"family":"Angal","given":"Amit","email":"","affiliations":[],"preferred":false,"id":906336,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":906337,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273254,"text":"70273254 - null - An empirical algorithm for estimating agricultural and riparian evapotranspiration using MODIS Enhanced Vegetation Index and ground measurements of ET. II. Application to the lower Colorado River, U.S.","interactions":[],"lastModifiedDate":"2025-12-23T16:00:36.737075","indexId":"70273254","displayToPublicDate":"2009-11-20T09:55:13","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An empirical algorithm for estimating agricultural and riparian evapotranspiration using MODIS Enhanced Vegetation Index and ground measurements of ET. II. Application to the lower Colorado River, U.S.","docAbstract":"<p><span>Large quantities of water are consumed by irrigated crops and riparian vegetation in western U.S. irrigation districts. Remote sensing methods for estimating evaporative water losses by soil and vegetation (evapotranspiration, ET) over wide river stretches are needed to allocate water for agricultural and environmental needs. We used the Enhanced Vegetation Index (EVI) from MODIS sensors on the Terra satellite to scale ET over agricultural and riparian areas along the Lower Colorado River in the southwestern U.S., using a linear regression equation between ET of riparian plants and alfalfa measured on the ground, and meteorological and remote sensing data, with an error or uncertainty of about 20%. The algorithm was applied to irrigation districts and riparian areas from Lake Mead to the U.S./Mexico border. The results for agricultural crops were similar to results produced by crop coefficients developed for the irrigation districts along the river. However, riparian ET was only half as great as crop coefficient estimates set by expert opinion, equal to about 40% of reference crop evapotranspiration. Based on reported acreages in 2007, agricultural crops (146,473 ha) consumed 2.2 × 10</span><sup>9</sup><span>&nbsp;m</span><sup>3</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;of water. All riparian shrubs and trees (47,014 ha) consumed 3.8 × 10</span><sup>8</sup><span>&nbsp;m</span><sup>3</sup><span>&nbsp;yr</span><sup>−1</sup><span>, of which saltcedar, the dominant riparian shrub (25,044 ha), consumed 1.8 × 10</span><sup>8</sup><span>&nbsp;m</span><sup>3</sup><span>&nbsp;yr</span><sup>−1</sup><span>, about 1% of the annual flow of the river. This method could supplement existing protocols for estimating ET by providing an estimate based on the actual state of the canopy as determined by frequent-return satellite data.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs1041125","usgsCitation":"Murray, R.S., Nagler, P.L., Morino, K., and Glenn, E., An empirical algorithm for estimating agricultural and riparian evapotranspiration using MODIS Enhanced Vegetation Index and ground measurements of ET. II. Application to the lower Colorado River, U.S.: Remote Sensing, v. 1, no. 4, p. 1125-1138, https://doi.org/10.3390/rs1041125.","productDescription":"14 p.","startPage":"1125","endPage":"1138","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498057,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs1041125","text":"Publisher Index Page"},{"id":497940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"lower Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.8813192791255,\n              36.97080066185404\n            ],\n            [\n              -116.96456312629869,\n              36.97080066185404\n            ],\n            [\n              -116.96456312629869,\n              32.699643980926254\n            ],\n            [\n              -110.8813192791255,\n              32.699643980926254\n            ],\n            [\n              -110.8813192791255,\n              36.97080066185404\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"1","issue":"4","noUsgsAuthors":false,"publicationDate":"2009-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Murray, R. Scott","contributorId":64468,"corporation":false,"usgs":true,"family":"Murray","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":952887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":952888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morino, Kiyomi","contributorId":78210,"corporation":false,"usgs":true,"family":"Morino","given":"Kiyomi","email":"","affiliations":[],"preferred":false,"id":952889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":952890,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236409,"text":"70236409 - null - New approaches to stability analysis of steep coastal bluffs","interactions":[],"lastModifiedDate":"2022-09-06T15:28:14.694506","indexId":"70236409","displayToPublicDate":"2008-12-31T10:19:44","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"New approaches to stability analysis of steep coastal bluffs","docAbstract":"<p><span>We present a discussion on the limitations and needed improvements for existing slope stability analysis methods to accurately model steep coastal bluff failures resulting from both direct wave action at the toe in weakly cemented sands and precipitation-induced seepage failures in moderately cemented sands. Using a case-study detailing over 5 years of observations of coastal bluff erosion and landsliding in northern California, we show that existing analysis methods over-predict the observed crest retreat and mis-predict the field-measured failure geometry. In response, we propose new analysis methods for evaluating stability in these settings.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of geocongress 2008","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"GeoCongress 2008","conferenceDate":"Mar 9-12, 2008","conferenceLocation":"New Orleans, LA","language":"English","publisher":"ASCE","doi":"10.1061/40971(310)63","usgsCitation":"Collins, B.D., and Sitar, N., New approaches to stability analysis of steep coastal bluffs, <i>in</i> Proceedings of geocongress 2008, New Orleans, LA, Mar 9-12, 2008, p. 507-513, https://doi.org/10.1061/40971(310)63.","productDescription":"7 p.","startPage":"507","endPage":"513","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":406233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2012-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":850914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sitar, Nicholas","contributorId":42253,"corporation":false,"usgs":true,"family":"Sitar","given":"Nicholas","email":"","affiliations":[],"preferred":false,"id":850915,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70236406,"text":"70236406 - null - Modeling of wave driven circulation and water quality in nearshore environments","interactions":[],"lastModifiedDate":"2022-09-06T15:07:20.521719","indexId":"70236406","displayToPublicDate":"2008-12-31T10:02:21","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Modeling of wave driven circulation and water quality in nearshore environments","docAbstract":"<p><span>In order to investigate the effects of nearshore discharges of water quality degrading substances and bacteria in coastal environments, models capable of predicting nearshore circulation due to local wave and tide conditions are required. One of the larger challenges to nearshore coastal modeling is accurately reproducing nearshore circulation due to wave action. Local wave action not only drives circulation through processes such as longshore transport and rip currents, but also contributes significantly to the mixing of water quality constituents. In the present work, a wave model was used to calculate radiation shear stresses and dissipation due to wave action. The shear stresses and dissipation were incorporated into a hydrodynamic model to force circulation in the nearshore environment. The model was applied to a site in Santa Cruz, CA where site specific current data was available. The model reproduces the nearshore current structure observed in the region and was used to study the transport of dredge disposal plumes in the region which could have deleterious effects on local beaches. This presentation will outline the nearshore circulation model development and application.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2008 world environmental and water resources congress","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2008","conferenceDate":"May 12-16, 2008","conferenceLocation":"Honolulu, HI","language":"English","publisher":"ASCE","doi":"10.1061/9780784409763","usgsCitation":"Jones, C., and Angster, S.J., Modeling of wave driven circulation and water quality in nearshore environments, <i>in</i> Proceedings of the 2008 world environmental and water resources congress, Honolulu, HI, May 12-16, 2008, 10 p., https://doi.org/10.1061/9780784409763.","productDescription":"10 p.","costCenters":[],"links":[{"id":406231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2012-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Craig","contributorId":208632,"corporation":false,"usgs":false,"family":"Jones","given":"Craig","affiliations":[{"id":37853,"text":"Integral Constulting Inc., Santa Cruz, California, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":850908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angster, Stephen J. 0000-0001-9250-8415 sangster@usgs.gov","orcid":"https://orcid.org/0000-0001-9250-8415","contributorId":3885,"corporation":false,"usgs":true,"family":"Angster","given":"Stephen","email":"sangster@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":850909,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70273251,"text":"70273251 - null - Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: What vegetation indices can and cannot tell us about the landscape","interactions":[],"lastModifiedDate":"2025-12-23T15:33:23.073849","indexId":"70273251","displayToPublicDate":"2008-03-28T09:13:57","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: What vegetation indices can and cannot tell us about the landscape","docAbstract":"<p><span>Vegetation indices (VIs) are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT), Surface Energy Balance (SEB), and Global Climate Models (GCM). These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with “Big Leaf” SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/s8042136","usgsCitation":"Glenn, E.P., Huete, A.R., Nagler, P.L., and Nelson, S.G., Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: What vegetation indices can and cannot tell us about the landscape: Sensors, v. 8, no. 4, p. 2136-2160, https://doi.org/10.3390/s8042136.","productDescription":"25 p.","startPage":"2136","endPage":"2160","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s8042136","text":"Publisher Index Page"},{"id":497937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Havasu National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.46320466185165,\n              34.705992498069406\n            ],\n            [\n              -114.398916590966,\n              34.73603912838132\n            ],\n            [\n              -114.53190465917093,\n              34.97188700395952\n            ],\n            [\n              -114.64409364561838,\n              34.905752361774034\n            ],\n            [\n              -114.54892208969932,\n              34.76089704626571\n            ],\n            [\n              -114.46320466185165,\n              34.705992498069406\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2008-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":952873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huete, Alfredo R","contributorId":243589,"corporation":false,"usgs":false,"family":"Huete","given":"Alfredo","email":"","middleInitial":"R","affiliations":[{"id":48742,"text":"School of Life Sciences, Faculty of Science, University of Technology Sydney, Sydney, NSW 2007, Australia","active":true,"usgs":false}],"preferred":false,"id":952874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":952875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Stephen G.","contributorId":174719,"corporation":false,"usgs":false,"family":"Nelson","given":"Stephen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":952876,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70259123,"text":"70259123 - null - Comparative analysis of GPP products estimated from an empirical model and MODIS","interactions":[],"lastModifiedDate":"2024-09-27T15:19:00.857652","indexId":"70259123","displayToPublicDate":"2006-12-01T10:12:44","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Comparative analysis of GPP products estimated from an empirical model and MODIS","docAbstract":"<p>Carbon-cycle models have uncertainties associated with data inputs, parameters, and model algorithms. The prerequisite for an applicable model is that it should perform at an acceptable level of accuracy and uncertainties should be documented. In this study, we validated the gross primary productivity (GPP) data from a piecewise regression (PWR) model and the MODIS GPP model at five grassland flux towers in the Northern Great Plains. The results showed a good agreement of GPP values (agreement coefficient <i>d</i> = 0.88–0.98) among PWR, MODIS, and tower measurements at Fort Peck, Mandan, and Cheyenne sites; but MODIS GPP did not agree well (<i>d</i> = 0.62–0.79) with tower measurements at Miles City and Lethbridge sites. Additionally, we compared PWR GPP and MODIS GPP for grasslands in the entire study area. We found that the PWR GPP was lower than or similar to the MODIS GPP in the east and higher in the west and south. We explored possible factors that may cause the GPP difference in spatial distribution between the two models. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Global priorities in land remote sensing","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"William T. Pecora Memorial Symposium on Remote Sensing, 16th","conferenceDate":"October 23-27, 2005","conferenceLocation":"Sioux Falls, SD","language":"English","publisher":"ASPRS","usgsCitation":"Zhang, L., Wylie, B.K., Loveland, T., and Ji, L., Comparative analysis of GPP products estimated from an empirical model and MODIS, <i>in</i> Global priorities in land remote sensing, Sioux Falls, SD, October 23-27, 2005, 12 p.","productDescription":"12 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":462337,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.asprs.org/Conference-Proceedings.html","linkFileType":{"id":5,"text":"html"}},{"id":462338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Li","contributorId":222540,"corporation":false,"usgs":false,"family":"Zhang","given":"Li","email":"","affiliations":[],"preferred":false,"id":914249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":914250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":914251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":139587,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":914252,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70205983,"text":"70205983 - null - Characterizing the two-dimensional thermal conductivity distribution in a sand and gravel aquifer","interactions":[],"lastModifiedDate":"2019-10-14T14:38:34","indexId":"70205983","displayToPublicDate":"2006-10-14T14:38:13","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing the two-dimensional thermal conductivity distribution in a sand and gravel aquifer","docAbstract":"<p><span>Both hydrologic and thermal transport properties play a significant role in the movement of heat through permeable sedimentary material; however, the thermal conductivity is rarely characterized in detailed spatial resolution. As part of a study of the movement of thermal plumes through a sand and gravel aquifer, we have constructed a two-dimensional profile of thermal conductivity. This work consisted of: (i) measuring the thermal conductivity of the soil solids, λ</span><sub>s</sub><span>, for the main stratigraphic units using the steady-state divided-bar apparatus and estimating conductivity from mineral composition; (ii) measuring the volumetric water content and porosity using crosshole ground-penetrating radar; (iii) evaluating four models used to predict the apparent thermal conductivity, λ, of variably saturated soils and selecting the best model using the information-theoretic approach, (iv) calculating the λ field on a 0.25-m square cell grid using measured data and the selected model, and (v) simulating thermal transport within the two-dimensional domain using a finite element numerical model. The apparent thermal conductivity in the saturated aquifer ranges from 2.14 to 2.69 W m</span><sup>−1</sup><span>&nbsp;K</span><sup>−1</sup><span>&nbsp;with a mean of 2.42 W m</span><sup>−1</sup><span>&nbsp;K</span><sup>−1</sup><span>&nbsp;Numerical simulations show that the heterogeneous thermal conductivity field results in increased thermal dispersion that is most pronounced at the plume front. Our values for λ and λ</span><sub>s</sub><span>&nbsp;may be used for glacial soils with similar mineralogy and texture. Our methods may also be used at other sites to construct the thermal conductivity distribution.</span></p>","doi":"10.2136/sssaj2005.0293","usgsCitation":"Markle, J.M., Schincariol, R.A., Sass, J., and Molson, J.W., Characterizing the two-dimensional thermal conductivity distribution in a sand and gravel aquifer: Soil Science Society of America Journal, v. 70, no. 4, p. 1281-1294, https://doi.org/10.2136/sssaj2005.0293.","productDescription":"14 p.","startPage":"1281","endPage":"1294","costCenters":[],"links":[{"id":368310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Ontario","otherGeospatial":"Tricks Creek Watershed ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.0458984375,\n              43.52266348752663\n            ],\n            [\n              -81.6998291015625,\n              43.52266348752663\n            ],\n            [\n              -81.6998291015625,\n              43.94537239244209\n            ],\n            [\n              -82.0458984375,\n              43.94537239244209\n            ],\n            [\n              -82.0458984375,\n              43.52266348752663\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"70","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Markle, Jeff M.","contributorId":219782,"corporation":false,"usgs":false,"family":"Markle","given":"Jeff","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":773164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schincariol, Robert A.","contributorId":219783,"corporation":false,"usgs":false,"family":"Schincariol","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":773165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sass, J.H.","contributorId":70749,"corporation":false,"usgs":true,"family":"Sass","given":"J.H.","email":"","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":773166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molson, John W.","contributorId":219784,"corporation":false,"usgs":false,"family":"Molson","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":773167,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70248281,"text":"70248281 - null - Scouting craton’s edge in Paleo-Pacific Gondwana","interactions":[],"lastModifiedDate":"2023-09-06T20:12:30.474783","indexId":"70248281","displayToPublicDate":"2006-01-01T14:47:51","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4.1","title":"Scouting craton’s edge in Paleo-Pacific Gondwana","docAbstract":"<p><span>The geology of the ice-covered interior of the East Antarctic shield is completely unknown; inferences about its composition and history are based on extrapolating scant outcrops from the coast inland. Although the shield is clearly composite in nature, a large part of its interior has been represented by a single Precambrian block, termed the Mawson block, that includes the Archean-Mesoproterozoic Gawler and Curnamona cratons of Australia. In Australia, the Mawson block is bounded on the east by Neoproterozoic sedimentary rocks and the superimposed early Paleozoic Delamerian Orogen, marked by curvilinear belts of arc plutons, and on the west by the unexposed Coompana block and Mesoproterozoic Albany-Fraser mobile belt. In Antarctica, these crustal elements are inferred to extend across Wilkes Land and south to the Miller Range region. Aero- and satellite magnetic data provide a means to see through the ice, helping to elucidate the broad composition of the shield. Rocks of the Mawson block in Australia produce distinctive magnetic anomalies; Paleoproterozoic granites and Meso- to Neoproterozoic mafic igneous rocks are associated with high-amplitude, broad-wavelength positive aero- and satellite-magnetic anomalies. The same types of magnetic anomalies can be traced to ice-covered Wilkes Land, Antarctica, and are interpreted to signify similar rocks. However, the diagnostic satellite magnetic high ends ∼800 km south of the Antarctic coast, suggesting that the Mawson block is smaller than first proposed and that the remaining East Antarctic shield is composed of several Precambrian crustal blocks of largely undetermined composition and age. Nonetheless, the coincident eastern borders of these magnetic highs and high seismic-velocity anomalies characteristic of the Precambrian shield, together define the edge of thick cratonic lithosphere. East of this boundary, magnetic lows are explained by magnetite-poor upper Neoproterozoic and lower Paleozoic sedimentary rocks, and their metamorphic equivalents, which crop out discontinuously along the Ross margin of Antarctica and in eastern Australia. These rocks are inferred to overlie a Neoproterozoic rift margin, which transects older basement provinces. The coincidence of this cratonic rift boundary with the western limit of Paleozoic and Jurassic magmatism suggests that, although tectonically modified by younger events, the composite Antarctic-Australian shield comprised thick lithosphere that was not penetrated by Paleozoic and younger convergent-margin magmas.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Antarctica: Contributions to global earth sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/3-540-32934-X_20","usgsCitation":"Finn, C.A., Goodge, J.W., Damaske, D., and Fanning, C.M., Scouting craton’s edge in Paleo-Pacific Gondwana, chap. 4.1 <i>of</i> Antarctica: Contributions to global earth sciences, p. 165-173, https://doi.org/10.1007/3-540-32934-X_20.","productDescription":"9 p.","startPage":"165","endPage":"173","costCenters":[],"links":[{"id":420584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Gondwana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              106.88469524334846,\n              -57.49514229065598\n            ],\n            [\n              106.88469524334846,\n              -78.93509637484914\n            ],\n            [\n              164.3416785133088,\n              -78.93509637484914\n            ],\n            [\n              164.3416785133088,\n              -57.49514229065598\n            ],\n            [\n              106.88469524334846,\n              -57.49514229065598\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Futterer, Dieter Karl","contributorId":279857,"corporation":false,"usgs":false,"family":"Futterer","given":"Dieter","email":"","middleInitial":"Karl","affiliations":[],"preferred":false,"id":882257,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Kleinschmidt, Georg","contributorId":26968,"corporation":false,"usgs":true,"family":"Kleinschmidt","given":"Georg","email":"","affiliations":[],"preferred":false,"id":882258,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Miller, Hubert","contributorId":328909,"corporation":false,"usgs":false,"family":"Miller","given":"Hubert","email":"","affiliations":[],"preferred":false,"id":882259,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Tessensohn, Franz","contributorId":27196,"corporation":false,"usgs":true,"family":"Tessensohn","given":"Franz","email":"","affiliations":[],"preferred":false,"id":882260,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Finn, Carol A. 0000-0002-6178-0405 cfinn@usgs.gov","orcid":"https://orcid.org/0000-0002-6178-0405","contributorId":1326,"corporation":false,"usgs":true,"family":"Finn","given":"Carol","email":"cfinn@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":882253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodge, John W.","contributorId":20414,"corporation":false,"usgs":true,"family":"Goodge","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":882254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Damaske, Detlef","contributorId":77384,"corporation":false,"usgs":true,"family":"Damaske","given":"Detlef","email":"","affiliations":[],"preferred":false,"id":882255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fanning, C. Mark","contributorId":193462,"corporation":false,"usgs":false,"family":"Fanning","given":"C.","email":"","middleInitial":"Mark","affiliations":[],"preferred":false,"id":882256,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70263458,"text":"70263458 - null - Development of stochastic modeling systems using deterministic models and GIS: Principles and a case study in the Atlantic Zone of Costa Rica","interactions":[],"lastModifiedDate":"2025-02-11T16:55:21.741843","indexId":"70263458","displayToPublicDate":"2003-12-01T10:49:02","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development of stochastic modeling systems using deterministic models and GIS: Principles and a case study in the Atlantic Zone of Costa Rica","docAbstract":"<p>The most important requirements for large-area environmental modeling are a tight integration between models and data, and a close match of the spatial scale at which the model is developed with the scale at which the model is to be applied. To better match the scale of data with that of the model, we propose a set of principles for the development of stochastic modeling systems based on linkage of deterministic models with GIS data. For modeling purposes, a region is usually rasterized into cells and the environmental conditions of those cells are specified by ranges or classes using GIS data layers. It is not necessary to simulate each and every GIS cell in the study area because many cells may have similar environmental conditions and can be grouped together to form cohorts. We define a cohort as the assembly of the cells sharing a unique combination of environmental conditions within the study region. Multiple model simulations can be performed for any given cohort. For each simulation, some of the parameter values can be randomly generated within the specified environmental conditions of the cohort according to a certain statistical distribution which, in turn, can be specified by GIS data layers. By this method the variance and covariance of environmental variables in space and time are integrated into the simulation processes with these modeling systems to make full use of the available data and to assess the uncertainties of the simulated results. An integrated simulation system between CENTURY model and GIS was developed to demonstrate the value of the concepts imbedded in stochastic simulation systems for large area studies.</p>","conferenceTitle":"4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4)","conferenceDate":"September 2-8, 2000","conferenceLocation":"Banff, Alberta, Canada","language":"English","publisher":"University of Colorado, Cooperative Institute for Research in Environmental Sciences","usgsCitation":"Liu, S., Reiners, W.A., Gerow, K.G., Schimel, D.S., and Keller, M., Development of stochastic modeling systems using deterministic models and GIS: Principles and a case study in the Atlantic Zone of Costa Rica, 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), Banff, Alberta, Canada, September 2-8, 2000, 9 p.","productDescription":"9 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":481935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.6133520275848,\n              9.499325548625436\n            ],\n            [\n              -82.44230009071387,\n              9.73121764978167\n            ],\n            [\n              -83.54701051633626,\n              11.16801392273345\n            ],\n            [\n              -83.68242663302513,\n              10.951175271798036\n            ],\n            [\n              -83.66104514091643,\n              10.78319089811086\n            ],\n            [\n              -84.16707378749192,\n              10.566072375621317\n            ],\n            [\n              -83.7038081251345,\n              9.604750752776496\n            ],\n            [\n              -82.88418426096321,\n              9.506354909569495\n            ],\n            [\n              -82.6133520275848,\n              9.499325548625436\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":927046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reiners, William A.","contributorId":147117,"corporation":false,"usgs":false,"family":"Reiners","given":"William","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":927047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerow, Kenneth G.","contributorId":49672,"corporation":false,"usgs":true,"family":"Gerow","given":"Kenneth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":927048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schimel, David S","contributorId":267312,"corporation":false,"usgs":false,"family":"Schimel","given":"David","email":"","middleInitial":"S","affiliations":[{"id":55473,"text":"Jep Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":927049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keller, Michael","contributorId":42681,"corporation":false,"usgs":true,"family":"Keller","given":"Michael","email":"","affiliations":[],"preferred":false,"id":927050,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209260,"text":"70209260 - null - Storm‐dominated bottom boundary layer dynamics on the Northern California Continental Shelf: Measurements and predictions","interactions":[],"lastModifiedDate":"2020-03-25T14:50:41","indexId":"70209260","displayToPublicDate":"1987-03-25T14:36:27","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Storm‐dominated bottom boundary layer dynamics on the Northern California Continental Shelf: Measurements and predictions","docAbstract":"<p><span>Measurements of near‐bottom velocity profiles in 85 m water depth during a storm on the continental shelf off northern California using the GEOPROBE tripod in December 1979 provided estimates of shear velocities, , and roughness lengths, , when the near‐bottom velocity profiles were logarithmic. These estimates agree within 90% confidence intervals with values computed from a simple near‐bottom combined wave‐current model that includes movable bed effects. The reasonably good comparison between model and profile estimates of suggests that such models can be used to predict bed shear stresses (or shear velocities) under combined flows of waves and currents typical of stormy conditions on continental shelves if stratification corrections to the velocity profile resulting from suspended sediment are small. The repeated occurrences of storms of similar intensities and wind velocities during the winter months off northern California suggest that the resultant high bottom stresses due to the combined effects of waves and currents are major factors in controlling the distribution of surficial sediment on the central portion of the northern California shelf.</span></p>","doi":"10.1029/JC092iC02p01817","usgsCitation":"Cacchione, D., Grant, W., Drake, D., and Glenn, S., Storm‐dominated bottom boundary layer dynamics on the Northern California Continental Shelf: Measurements and predictions: Journal of Geophysical Research C: Oceans, v. 92, no. C2, p. 1817-1827, https://doi.org/10.1029/JC092iC02p01817.","productDescription":"11 p.","startPage":"1817","endPage":"1827","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":373529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Northern California Continental Shelf","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.2718505859375,\n              37.99183365313853\n            ],\n            [\n              -122.7008056640625,\n              37.99183365313853\n            ],\n            [\n              -122.7008056640625,\n              39.00211029922515\n            ],\n            [\n              -124.2718505859375,\n              39.00211029922515\n            ],\n            [\n              -124.2718505859375,\n              37.99183365313853\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"92","issue":"C2","noUsgsAuthors":false,"publicationDate":"2012-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Cacchione, D.A.","contributorId":65448,"corporation":false,"usgs":true,"family":"Cacchione","given":"D.A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":785618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, W.D.","contributorId":11764,"corporation":false,"usgs":true,"family":"Grant","given":"W.D.","email":"","affiliations":[],"preferred":false,"id":785619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drake, D.E.","contributorId":48150,"corporation":false,"usgs":true,"family":"Drake","given":"D.E.","email":"","affiliations":[],"preferred":false,"id":785620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glenn, S.M.","contributorId":223608,"corporation":false,"usgs":false,"family":"Glenn","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":785621,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70207209,"text":"70207209 - null -  PIERRE PERRAULT: THE MAN AND HIS CONTRIBUTION TO MODERN HYDROLOGY","interactions":[],"lastModifiedDate":"2019-12-12T09:50:36","indexId":"70207209","displayToPublicDate":"1974-08-31T09:48:13","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2126,"text":"JAWRA","active":true,"publicationSubtype":{"id":10}},"title":" PIERRE PERRAULT: THE MAN AND HIS CONTRIBUTION TO MODERN HYDROLOGY","docAbstract":"<p><span>ABSTRACT: Pierre Perrault, member of a bourgeois provincial family whose roots were in the Touraine region of France, grew up in Paris. One of six illustrious Brothers, all characterized by brilliance and diversity, he was educated as a lawyer but turned to finance and rose to a high position under King Louis XIV. Owing to political naivete and financial imprudence, he fell into disgrace and went bankrupt. He then became an amateur scientist and wrote a book on the origin of springs. This book broke almost wholly with the traditional authoritarianism of 2, 000 years'standing, and set hydrology on the modern path of observation and direct experiment, He developed the concept of the hydrological cycle, correctly accounting for the disposition of rainfall by evaporation, transpiration, ground‐water recharge and runoff. Some of his ideas about specific processes were erroneous, but where he was wrong his errors were logically based. Much of his contribution to the foundation of scientific hydrology has been overlooked or distorted by historians and hydrologists alike. Copyright © 1974, Wiley Blackwell. All rights reserved</span></p>","language":"English","publisher":"Wiley Blackwell ","doi":"10.1111/j.1752-1688.1974.tb05623.x","issn":"1093474X","usgsCitation":"Nace, R.L.,  PIERRE PERRAULT: THE MAN AND HIS CONTRIBUTION TO MODERN HYDROLOGY: JAWRA, v. 10, no. 4, p. 633-647, https://doi.org/10.1111/j.1752-1688.1974.tb05623.x.","productDescription":"15 p. ","startPage":"633","endPage":"647","costCenters":[],"links":[{"id":370202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"4","noUsgsAuthors":false,"publicationDate":"2007-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Nace, R. L.","contributorId":11332,"corporation":false,"usgs":true,"family":"Nace","given":"R.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":777276,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70182006,"text":"70182006 - No Year - Seafloor images refine petroleum exploration models","interactions":[],"lastModifiedDate":"2017-03-29T10:04:21","indexId":"70182006","displayToPublicDate":"2003-12-31T00:00:00","noYear":true,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Seafloor images refine petroleum exploration models","docAbstract":"<p><span>Acoustic mapping of the </span><abbr title=\"Exclusive Economic Zone\">EEZ</abbr><span> sea floor using </span><abbr title=\"Geological Long-Range Inclined Asdic\">GLORIA</abbr><span> side-scan sonar tool includes the margins of the continental United States, Alaska, Hawaii, and Johnston Island. This decade-long program was undertaken in cooperation with the United Kingdom's Institute of Oceanographic Sciences at the Deacon Laboratory (now the Southampton Oceanography Centre).</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70182006","usgsCitation":"Twichell, D., Seafloor images refine petroleum exploration models, HTML Document, https://doi.org/10.3133/70182006.","productDescription":"HTML Document","onlineOnly":"Y","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":335465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":335452,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/seafloor-images/","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","publicComments":"Published between 2000 and 2003","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58a57710e4b057081a24eee5","contributors":{"authors":[{"text":"Twichell, David","contributorId":15871,"corporation":false,"usgs":true,"family":"Twichell","given":"David","affiliations":[],"preferred":false,"id":669243,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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