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.
","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, in 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":"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.
","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":"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 d = 0.88–0.98) among PWR, MODIS, and tower measurements at Fort Peck, Mandan, and Cheyenne sites; but MODIS GPP did not agree well (d = 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.
","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, in 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":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":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":"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, λs, 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−1 K−1 with a mean of 2.42 W m−1 K−1 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 λs 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.
","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":"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.
","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 of 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":"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.
","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":"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.
","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":"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
","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":"Acoustic mapping of the EEZ sea floor using GLORIA 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).
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