{"pageNumber":"136","pageRowStart":"3375","pageSize":"25","recordCount":16501,"records":[{"id":70134478,"text":"70134478 - 2014 - An empirical approach to modeling methylmercury concentrations in an Adirondack stream watershed","interactions":[],"lastModifiedDate":"2020-12-31T18:30:54.598283","indexId":"70134478","displayToPublicDate":"2014-10-01T10:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"An empirical approach to modeling methylmercury concentrations in an Adirondack stream watershed","docAbstract":"<p>Inverse empirical models can inform and improve more complex process-based models by quantifying the principal factors that control water quality variation. Here we developed a multiple regression model that explains 81% of the variation in filtered methylmercury (FMeHg) concentrations in Fishing Brook, a fourth-order stream in the Adirondack Mountains, New York, a known &ldquo;hot spot&rdquo; of Hg bioaccumulation. This model builds on previous observations that wetland-dominated riparian areas are the principal source of MeHg to this stream and were based on 43 samples collected during a 33 month period in 2007&ndash;2009. Explanatory variables include those that represent the effects of water temperature, streamflow, and modeled riparian water table depth on seasonal and annual patterns of FMeHg concentrations. An additional variable represents the effects of an upstream pond on decreasing FMeHg concentrations. Model results suggest that temperature-driven effects on net Hg methylation rates are the principal control on annual FMeHg concentration patterns. Additionally, streamflow dilutes FMeHg concentrations during the cold dormant season. The model further indicates that depth and persistence of the riparian water table as simulated by TOPMODEL are dominant controls on FMeHg concentration patterns during the warm growing season, especially evident when concentrations during the dry summer of 2007 were less than half of those in the wetter summers of 2008 and 2009. This modeling approach may help identify the principal factors that control variation in surface water FMeHg concentrations in other settings, which can guide the appropriate application of process-based models.</p>","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","usgsCitation":"Burns, D.A., Nystrom, E.A., Wolock, D.M., Bradley, P.M., and Riva-Murray, K., 2014, An empirical approach to modeling methylmercury concentrations in an Adirondack stream watershed: Journal of Geophysical Research: Biogeosciences, v. 119, no. 10, p. 1970-1984.","productDescription":"15 p.","startPage":"1970","endPage":"1984","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050741","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":296361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":296324,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/enhanced/doi/10.1002/2013JG002481/"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Mountains, Fishing Brook","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.35375213623047,\n              43.89492363306683\n            ],\n            [\n              -74.18071746826172,\n              43.89492363306683\n            ],\n            [\n              -74.18071746826172,\n              44.02195282780904\n            ],\n            [\n              -74.35375213623047,\n              44.02195282780904\n            ],\n            [\n              -74.35375213623047,\n              43.89492363306683\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"119","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"547ee2bae4b09357f05f8a3d","contributors":{"authors":[{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nystrom, Elizabeth A. 0000-0002-0886-3439 nystrom@usgs.gov","orcid":"https://orcid.org/0000-0002-0886-3439","contributorId":1072,"corporation":false,"usgs":true,"family":"Nystrom","given":"Elizabeth","email":"nystrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":525994,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525995,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":2984,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525996,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70126736,"text":"sir20145138 - 2014 - Geologic and hydrogeologic frameworks of the Biscayne aquifer in central Miami-Dade County, Florida","interactions":[],"lastModifiedDate":"2014-10-01T09:35:53","indexId":"sir20145138","displayToPublicDate":"2014-10-01T09:42:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5138","title":"Geologic and hydrogeologic frameworks of the Biscayne aquifer in central Miami-Dade County, Florida","docAbstract":"<p>Evaluations of the lithostratigraphy, lithofacies, paleontology, ichnology, depositional environments, and cyclostratigraphy from 11 test coreholes were linked to geophysical interpretations, and to results of hydraulic slug tests of six test coreholes at the Snapper Creek Well Field (SCWF), to construct geologic and hydrogeologic frameworks for the study area in central Miami-Dade County, Florida. The resulting geologic and hydrogeologic frameworks are consistent with those recently described for the Biscayne aquifer in the nearby Lake Belt area in Miami-Dade County and link the Lake Belt area frameworks with those developed for the SCWF study area. The hydrogeologic framework is characterized by a triple-porosity pore system of (1) matrix porosity (mainly mesoporous interparticle porosity, moldic porosity, and mesoporous to megaporous separate vugs), which under dynamic conditions, produces limited flow; (2) megaporous, touching-vug porosity that commonly forms stratiform groundwater passageways; and (3) conduit porosity, including bedding-plane vugs, decimeter-scale diameter vertical solution pipes, and meter-scale cavernous vugs. The various pore types and associated permeabilities generally have a predictable vertical spatial distribution related to the cyclostratigraphy.</p>\n<br>\n<p>The Biscayne aquifer within the study area can be described as two major flow units separated by a single middle semiconfining unit. The upper Biscayne aquifer flow unit is present mainly within the Miami Limestone at the top of the aquifer and has the greatest hydraulic conductivity values, with a mean of 8,200 feet per day. The middle semiconfining unit, mainly within the upper Fort Thompson Formation, comprises continuous to discontinuous zones with (1) matrix porosity; (2) leaky, low permeability layers that may have up to centimeter-scale vuggy porosity with higher vertical permeability than horizontal permeability; and (3) stratiform flow zones composed of fossil moldic porosity, burrow related vugs, or irregular vugs. Flow zones with a mean hydraulic conductivity of 2,600 feet per day are present within the middle semiconfining unit, but none of the flow zones are continuous across the study area. The lower Biscayne aquifer flow unit comprises a group of flow zones in the lower part of the aquifer. These flow zones are present in the lower part of the Fort Thompson Formation and in some cases within the limestone or sandstone or both in the uppermost part of the Pinecrest Sand Member of the Tamiami Formation. The mean hydraulic conductivity of major flow zones within the lower Biscayne aquifer flow unit is 5,900 feet per day, and the mean value for minor flow zones is 2,900 feet per day. A semiconfining unit is present beneath the Biscayne aquifer. The boundary between the two hydrologic units is at the top or near the top of the Pinecrest Sand Member of the Tamiami Formation. The lower semiconfining unit has a hydraulic conductivity of less than 350 feet per day.</p>\n<br>\n<p>The most productive zones of groundwater flow within the two Biscayne aquifer flow units have a characteristic pore system dominated by stratiform megaporosity related to selective dissolution of an Ophiomorpha-dominated ichnofabric. In the upper flow unit, decimeter-scale vertical solution pipes that are common in some areas of the SCWF study area contribute to high vertical permeability compared to that in areas without the pipes. Cross-hole flowmeter data collected from the SCWF test coreholes show that the distribution of vuggy porosity, matrix porosity, and permeability within the Biscayne aquifer of the SCWF is highly heterogeneous and anisotropic.</p>\n<br>\n<p>Groundwater withdrawals from production well fields in southeastern Florida may be inducing recharge of the Biscayne aquifer from canals near the well fields that are used for water-management functions, such as flood control and well-field pumping. The SCWF was chosen as a location within Miami-Dade County to study the potential for such recharge to the Biscayne aquifer from the C–2 (Snapper Creek) canal that roughly divides the well field in half. Geologic, hydrogeologic, and hydraulic information on the aquifer collected during construction of monitoring wells within the SCWF could be used to evaluate the groundwater flow budget at the well-field scale.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145138","collaboration":"Prepared in cooperation with the Miami-Dade County Water and Sewer Department","usgsCitation":"Wacker, M.A., Cunningham, K.J., and Williams, J., 2014, Geologic and hydrogeologic frameworks of the Biscayne aquifer in central Miami-Dade County, Florida: U.S. Geological Survey Scientific Investigations Report 2014-5138, Report: viii, 66 p.; 4 Appendices; 3 Plates: 36 X 29.17 or smaller, https://doi.org/10.3133/sir20145138.","productDescription":"Report: viii, 66 p.; 4 Appendices; 3 Plates: 36 X 29.17 or smaller","numberOfPages":"77","onlineOnly":"Y","ipdsId":"IP-044408","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":294577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145138.jpg"},{"id":294680,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5138/plates/sir2014-5138_plate02.pdf"},{"id":294681,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5138/plates/sir2014-5138_plate03.pdf"},{"id":294677,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5138/appendix/sir2014-5138_appendix04"},{"id":294678,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5138/appendix/sir2014-5138_appendix06.pdf"},{"id":294679,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5138/plates/sir2014-5138_plate01.pdf"},{"id":294673,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5138/"},{"id":294674,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5138/pdf/sir2014-5138.pdf"},{"id":294675,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5138/appendix/sir2014-5138_appendix01.pdf"},{"id":294676,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5138/appendix/sir2014-5138_appendix02"}],"country":"United States","state":"Florida","county":"Miami-Dade County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.8736,25.1374 ], [ -80.8736,25.9794 ], [ -80.1179,25.9794 ], [ -80.1179,25.1374 ], [ -80.8736,25.1374 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542d098ee4b092f17defc535","contributors":{"authors":[{"text":"Wacker, Michael A. mwacker@usgs.gov","contributorId":2162,"corporation":false,"usgs":true,"family":"Wacker","given":"Michael","email":"mwacker@usgs.gov","middleInitial":"A.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":502139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cunningham, Kevin J. 0000-0002-2179-8686 kcunning@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-8686","contributorId":1689,"corporation":false,"usgs":true,"family":"Cunningham","given":"Kevin","email":"kcunning@usgs.gov","middleInitial":"J.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":502138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":502137,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70128281,"text":"70128281 - 2014 - An enhanced model of land water and energy for global hydrologic and earth-system studies","interactions":[],"lastModifiedDate":"2014-10-07T09:26:36","indexId":"70128281","displayToPublicDate":"2014-10-01T09:24:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"An enhanced model of land water and energy for global hydrologic and earth-system studies","docAbstract":"LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrometeorology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JHM-D-13-0162.1","usgsCitation":"Milly, P., Malyshev, S.L., Shevliakova, E., Dunne, K.A., Findell, K.L., Gleeson, T., Liang, Z., Phillips, P., Stouffer, R.J., and Swenson, S., 2014, An enhanced model of land water and energy for global hydrologic and earth-system studies: Journal of Hydrometeorology, v. 15, p. 1739-1761, https://doi.org/10.1175/JHM-D-13-0162.1.","productDescription":"23 p.","startPage":"1739","endPage":"1761","numberOfPages":"23","ipdsId":"IP-054670","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":472719,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-13-0162.1","text":"Publisher Index Page"},{"id":294977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294973,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1175/JHM-D-13-0162.1"},{"id":294974,"type":{"id":15,"text":"Index Page"},"url":"https://journals.ametsoc.org/doi/full/10.1175/JHM-D-13-0162.1"}],"volume":"15","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5435009ee4b0a4f4b46a2374","contributors":{"authors":[{"text":"Milly, Paul C.D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":2119,"corporation":false,"usgs":true,"family":"Milly","given":"Paul C.D.","email":"cmilly@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":502796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malyshev, Sergey L.","contributorId":27810,"corporation":false,"usgs":true,"family":"Malyshev","given":"Sergey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":502803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shevliakova, Elena","contributorId":9596,"corporation":false,"usgs":true,"family":"Shevliakova","given":"Elena","affiliations":[],"preferred":false,"id":502799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunne, Krista A. kadunne@usgs.gov","contributorId":3936,"corporation":false,"usgs":true,"family":"Dunne","given":"Krista","email":"kadunne@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":502797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Findell, Kirsten L.","contributorId":8404,"corporation":false,"usgs":true,"family":"Findell","given":"Kirsten","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":502798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gleeson, Tom","contributorId":81041,"corporation":false,"usgs":true,"family":"Gleeson","given":"Tom","email":"","affiliations":[],"preferred":false,"id":502805,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liang, Zhi","contributorId":12397,"corporation":false,"usgs":true,"family":"Liang","given":"Zhi","email":"","affiliations":[],"preferred":false,"id":502801,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Phillips, Peter","contributorId":10740,"corporation":false,"usgs":true,"family":"Phillips","given":"Peter","email":"","affiliations":[],"preferred":false,"id":502800,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stouffer, Ronald J.","contributorId":17172,"corporation":false,"usgs":true,"family":"Stouffer","given":"Ronald","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":502802,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Swenson, Sean","contributorId":58584,"corporation":false,"usgs":true,"family":"Swenson","given":"Sean","affiliations":[],"preferred":false,"id":502804,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70189179,"text":"70189179 - 2014 - A computer program for uncertainty analysis integrating regression and Bayesian methods","interactions":[],"lastModifiedDate":"2018-09-14T16:01:30","indexId":"70189179","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A computer program for uncertainty analysis integrating regression and Bayesian methods","docAbstract":"<p><span>This work develops a new functionality in UCODE_2014 to evaluate Bayesian credible intervals using the Markov Chain Monte Carlo (MCMC) method. The MCMC capability in UCODE_2014 is based on the FORTRAN version of the differential evolution adaptive Metropolis (DREAM) algorithm of Vrugt et&nbsp;al. (2009), which estimates the posterior probability density function of model parameters in high-dimensional and multimodal sampling problems. The UCODE MCMC capability provides eleven prior probability distributions and three ways to initialize the sampling process. It evaluates parametric and predictive uncertainties and it has parallel computing capability based on multiple chains to accelerate the sampling process. This paper tests and demonstrates the MCMC capability using a 10-dimensional multimodal mathematical function, a 100-dimensional Gaussian function, and a groundwater reactive transport model. The use of the MCMC capability is made straightforward and flexible by adopting the JUPITER API protocol. With the new MCMC capability, UCODE_2014 can be used to calculate three types of uncertainty intervals, which all can account for prior information: (1) linear confidence intervals which require linearity and Gaussian error assumptions and typically 10s–100s of highly parallelizable model runs after optimization, (2) nonlinear confidence intervals which require a smooth objective function surface and Gaussian observation error assumptions and typically 100s–1,000s of partially parallelizable model runs after optimization, and (3) MCMC Bayesian credible intervals which require few assumptions and commonly 10,000s–100,000s or more partially parallelizable model runs. Ready access allows users to select methods best suited to their work, and to compare methods in many circumstances.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2014.06.002","usgsCitation":"Lu, D., Ye, M., Hill, M.C., Poeter, E.P., and Curtis, G., 2014, A computer program for uncertainty analysis integrating regression and Bayesian methods: Environmental Modelling and Software, v. 60, p. 45-56, https://doi.org/10.1016/j.envsoft.2014.06.002.","productDescription":"12 p.","startPage":"45","endPage":"56","ipdsId":"IP-057730","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c42e4b0d1f9f057e35e","contributors":{"authors":[{"text":"Lu, Dan","contributorId":194172,"corporation":false,"usgs":false,"family":"Lu","given":"Dan","email":"","affiliations":[],"preferred":false,"id":703376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ye, Ming","contributorId":70276,"corporation":false,"usgs":true,"family":"Ye","given":"Ming","affiliations":[],"preferred":false,"id":703377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703375,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poeter, Eileen P.","contributorId":78805,"corporation":false,"usgs":true,"family":"Poeter","given":"Eileen","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":703378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curtis, Gary gpcurtis@usgs.gov","contributorId":194175,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","affiliations":[],"preferred":true,"id":703379,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70126002,"text":"ds870 - 2014 - Watershed Data Management (WDM) database for Salt Creek streamflow simulation, DuPage County, Illinois, water years 2005-11","interactions":[],"lastModifiedDate":"2014-09-25T09:16:43","indexId":"ds870","displayToPublicDate":"2014-09-25T09:13:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"870","title":"Watershed Data Management (WDM) database for Salt Creek streamflow simulation, DuPage County, Illinois, water years 2005-11","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with DuPage County Stormwater Management Division, maintains a USGS database of hourly meteorologic and hydrologic data for use in a near real-time streamflow simulation system, which assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek watershed in DuPage County, Illinois. Most of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorologic data (wind speed, solar radiation, air temperature, and dewpoint temperature) are collected at Argonne National Laboratory in Argonne, Ill. Potential evapotranspiration is computed from the meteorologic data. The hydrologic data (discharge and stage) are collected at USGS streamflow-gaging stations in DuPage County. These data are stored in a Watershed Data Management (WDM) database. An earlier report describes in detail the WDM database development including the processing of data from January 1, 1997, through September 30, 2004, in SEP04.WDM database. SEP04.WDM is updated with the appended data from October 1, 2004, through September 30, 2011, water years 2005–11 and renamed as SEP11.WDM. This report details the processing of meteorologic and hydrologic data in SEP11.WDM.</p>\n<br/>\n<p>This report provides a record of snow affected periods and the data used to fill missing-record periods for each precipitation site during water years 2005–11. The meteorologic data filling methods are described in detail in Over and others (2010), and an update is provided in this report.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds870","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Division","usgsCitation":"Bera, M., 2014, Watershed Data Management (WDM) database for Salt Creek streamflow simulation, DuPage County, Illinois, water years 2005-11: U.S. Geological Survey Data Series 870, iv, 18 p., https://doi.org/10.3133/ds870.","productDescription":"iv, 18 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-051634","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":294451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds870.jpg"},{"id":294449,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0870/"},{"id":294450,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0870/pdf/ds870.pdf"}],"scale":"100000","projection":"Albers Equal-Area Conic projection","country":"United States","state":"Illinois","county":"Dupage County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.25,41.758333 ], [ -88.25,42.126389 ], [ -87.875,42.126389 ], [ -87.875,41.758333 ], [ -88.25,41.758333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54252090e4b0e641df8a6de3","contributors":{"authors":[{"text":"Bera, Maitreyee 0000-0002-3968-1961 mbera@usgs.gov","orcid":"https://orcid.org/0000-0002-3968-1961","contributorId":5450,"corporation":false,"usgs":true,"family":"Bera","given":"Maitreyee","email":"mbera@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501863,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70114418,"text":"sir20145095 - 2014 - Groundwater and surface-water interaction and potential for underground water storage in the Buena Vista-Salida Basin, Chaffee County, Colorado, 2011","interactions":[],"lastModifiedDate":"2014-09-25T08:47:48","indexId":"sir20145095","displayToPublicDate":"2014-09-25T08:43:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5095","title":"Groundwater and surface-water interaction and potential for underground water storage in the Buena Vista-Salida Basin, Chaffee County, Colorado, 2011","docAbstract":"<p>By 2030, the population of the Arkansas Headwaters Region, which includes all of Chaffee and Lake Counties and parts of Custer, Fremont, and Park Counties, Colorado, is forecast to increase about 73 percent. As the region’s population increases, it is anticipated that groundwater will be used to meet much of the increased demand. In September 2009, the U.S. Geological Survey, in cooperation with the Upper Arkansas Water Conservancy District and with support from the Colorado Water Conservation Board; Chaffee, Custer, and Fremont Counties; Buena Vista, Cañon City, Poncha Springs, and Salida; and Round Mountain Water and Sanitation District, began a 3-year study of groundwater and surface-water conditions in the Buena Vista-Salida Basin. This report presents results from the study of the Buena Vista-Salida Basin including synoptic gain-loss measurements and water budgets of Cottonwood, Chalk, and Browns Creeks, changes in groundwater storage, estimates of specific yield, transmissivity and hydraulic conductivity from aquifer tests and slug tests, an evaluation of areas with potential for underground water storage, and estimates of stream-accretion response-time factors for hypothetical recharge and selected streams in the basin.</p>\n<br/>\n<p>The four synoptic measurements of flow of Cottonwood, Chalk, and Browns Creeks, suggest quantifiable groundwater gains and losses in selected segments in all three perennial streams. The synoptic measurements of flow of Cottonwood and Browns Creeks suggest a seasonal variability, where positive later-irrigation season values in these creeks suggest groundwater discharge, possibly as infiltrated irrigation water. The overall sum of gains and losses on Chalk Creek does not indicate a seasonal variability but indicates a gaining stream in April and August/September. Gains and losses in the measured upper segments of Chalk Creek likely are affected by the Chalk Cliffs Rearing Unit (fish hatchery).</p>\n<br/>\n<p>Monthly water budgets were estimated for selected segments of five perennial streams (Cottonwood, North Cottonwood, Chalk, and Browns Creeks, and South Arkansas River) in the Buena Vista-Salida Basin for calendar year 2011. Differences between reported diversions and estimated crop irrigation requirements were used to estimate groundwater recharge in the areas irrigated by water supplied from the diversions. The amount of groundwater recharge in all the basins varied monthly; however, the greatest amount of recharge was during June and July for Cottonwood, North Cottonwood, and Chalk Creeks and South Arkansas River. The greatest amount of recharge in 2011 in Browns Creek occurred in July and August. The large seasonal fluctuations of groundwater near irrigated areas in the Buena Vista-Salida Basin indicate that the increased groundwater storage resulting from infiltration of surface-water diversions has dissipated by the following spring.</p>\n<br/>\n<p>Areas within the Buena Vista-Salida Basin with the potential for underground storage were identified using geographic information system data, including topographic, geologic, and hydrologic data, excluding the mountainous areas that border the Buena Vista-Salida Basin and igneous and metamorphic rock outcrop areas. The areas that met the selection criteria for underground water storage are located on terrace deposits near the Arkansas River and adjacent to its major tributaries. The selected areas also contain much of the irrigated land within the basin; consequently, irrigation ditches and canals could provide a means of conveying water to potential recharge sites.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145095","collaboration":"Prepared in cooperation with the Upper Arkansas Water Conservancy District; Colorado Water Conservation Board; Chaffee, Custer, and Fremont Counties; Buena Vista, Cañon City, Poncha Springs, and Salida; and Round Mountain Water and Sanitation District","usgsCitation":"Watts, K.R., Ivahnenko, T.I., Stogner, and Bruce, J.F., 2014, Groundwater and surface-water interaction and potential for underground water storage in the Buena Vista-Salida Basin, Chaffee County, Colorado, 2011: U.S. Geological Survey Scientific Investigations Report 2014-5095, viii, 63 p., https://doi.org/10.3133/sir20145095.","productDescription":"viii, 63 p.","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-052836","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":294442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145095.jpg"},{"id":294439,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5095/"},{"id":294441,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5095/pdf/sir2014-5095.pdf"}],"projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Colorado","county":"Chaffee County","otherGeospatial":"Buena Vista-salida Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.50,38.25 ], [ -106.50,39.15 ], [ -105.25,39.15 ], [ -105.25,38.25 ], [ -106.50,38.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5425208ce4b0e641df8a6da3","contributors":{"authors":[{"text":"Watts, Kenneth R. krwatts@usgs.gov","contributorId":1647,"corporation":false,"usgs":true,"family":"Watts","given":"Kenneth","email":"krwatts@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivahnenko, Tamara I. 0000-0002-1124-7688 ivahnenk@usgs.gov","orcid":"https://orcid.org/0000-0002-1124-7688","contributorId":2050,"corporation":false,"usgs":true,"family":"Ivahnenko","given":"Tamara","email":"ivahnenk@usgs.gov","middleInitial":"I.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":495312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stogner 0000-0002-3185-1452 rstogner@usgs.gov","orcid":"https://orcid.org/0000-0002-3185-1452","contributorId":938,"corporation":false,"usgs":true,"family":"Stogner","email":"rstogner@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":495310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruce, James F. 0000-0003-3125-2932 jbruce@usgs.gov","orcid":"https://orcid.org/0000-0003-3125-2932","contributorId":916,"corporation":false,"usgs":true,"family":"Bruce","given":"James","email":"jbruce@usgs.gov","middleInitial":"F.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":495309,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70121906,"text":"sir20145162 - 2014 - Hydrologic conditions in urban Miami-Dade County, Florida, and the effect of groundwater pumpage and increased sea level on canal leakage and regional groundwater flow","interactions":[],"lastModifiedDate":"2016-08-03T12:15:25","indexId":"sir20145162","displayToPublicDate":"2014-09-23T08:41:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5162","title":"Hydrologic conditions in urban Miami-Dade County, Florida, and the effect of groundwater pumpage and increased sea level on canal leakage and regional groundwater flow","docAbstract":"<p>The extensive and highly managed surface-water system in southeastern Florida constructed during the 20th Century has allowed for the westward expansion of urban and agricultural activities in Miami-Dade County. In urban areas of the county, the surface-water system is used to (1) control urban flooding, (2) supply recharge to production well fields, and (3) control seawater intrusion. Previous studies in Miami-Dade County have determined that on a local scale, leakage from canals adjacent to well fields can supply a large percentage (46 to 78 percent) of the total groundwater pumpage from production well fields. Canals in the urban areas also receive seepage from the Biscayne aquifer that is derived from a combination of local rainfall and groundwater flow from Water Conservation Area 3 and Everglades National Park, which are west of urban areas of Miami-Dade County.</p>\n<p>To evaluate the effects of groundwater pumpage on canal leakage and regional groundwater flow, the U.S. Geological Survey (USGS) developed and calibrated a coupled surface-water/groundwater model of the urban areas of Miami-Dade County, Florida. The model was calibrated by using observation data collected from January 1997 through December 2004. The model calibration was verified using observation data collected from January 2005 through December 2010. A 1-year warmup period (January 1996 through December 1996) was added prior to the start of the calibration period to reduce the effects of inaccurate initial conditions on model calibration. The model is designed to simulate surface-water stage and discharge in the managed canal system and dynamic canal leakage to the Biscayne aquifer as well as seepage to the canal from the aquifer. The model was developed using USGS MODFLOW&ndash;NWT with the Surface-Water Routing (SWR1) Process to simulate surface-water stage, surface-water discharge, and surface-water/groundwater interaction and the Seawater Intrusion (SWI2) Package to simulate seawater intrusion, respectively.</p>\n<p>Automated parameter estimation software (PEST) and highly parameterized inversion techniques were used to calibrate the model to observed surface-water stage, surface-water discharge, net surface-water subbasin discharge, and groundwater level data from 1997 through 2004 by modifying hydraulic conductivity, specific storage coefficients, specific yield, evapotranspiration parameters, canal roughness coefficients (Manning&rsquo;s&nbsp;<i>n</i>&nbsp;values), and canal leakance coefficients. Tikhonov regularization was used to produce parameter distributions that provide an acceptable fit between model outputs and observation data, while simultaneously minimizing deviations from preferred values based on field measurements and expert knowledge.</p>\n<p>Analytical and simulated water budgets for the period from 1996 through 2010 indicate that most of the water discharging through the salinity control structures is derived from within the urban parts of the study area and that, on average, the canals are draining the Biscayne aquifer. Simulated groundwater discharge from the urban areas to the coast is approximately 7 percent of the total surface-water inflow to Biscayne Bay and is consistent with previous estimates of fresh groundwater discharge to Biscayne Bay. Simulated groundwater budgets indicate that groundwater pumpage in some surface-water basins ranges from 13 to 27 percent of the sum of local sources of groundwater inflow. The largest percentage of groundwater pumpage to local sources of groundwater inflow occurs in the basins that have the highest pumping rates (C&ndash;2 and C&ndash;100 Basins). The ratio of groundwater pumpage to simulated local sources of groundwater inflow is less than values calculated in previous local-scale studies.</p>\n<p>The position of the freshwater-seawater interface at the base of the Biscayne aquifer did not change notably during the simulation period (1996&ndash;2010), consistent with the similar positions of the interface in 1984, 1995, and 2011 under similar hydrologic and groundwater pumping conditions. Landward movement of the freshwater-seawater interface above the base of the aquifer is more prone to occur during relatively dry years.</p>\n<p>The model was used to evaluate the effect of increased groundwater pumpage and (or) increased sea level on canal leakage, regional groundwater flow, and the position of the freshwater-seawater interface. Permitted groundwater pumping rates, which generally exceed historical groundwater pumping rates, were used for Miami-Dade County Water and Sewer Department groundwater pumping wells in the base-case future scenario. Base-case future and increased pumping scenario results suggest seawater intrusion may occur at the Miami-Springs well field if the Miami Springs, Hialeah, and Preston well fields are operated using current permitted groundwater pumping rates. Scenario simulations also show that, in general, the canal system limits the adverse effects of proposed groundwater pumpage increases on water-level changes and saltwater intrusion. Proposed increases (up to a 7 percent increase) in groundwater pumpage do not have a notable effect on movement of the freshwater-seawater interface. Increased groundwater pumpage increased lateral groundwater inflow into basins subject to additional groundwater pumpage; however, most (55 percent) of the additional groundwater extracted from pumping wells was supplied by changes in canal seepage and leakage in urban areas of the model. Increased sea level caused increased water-table elevations in urban areas and decreased hydraulic gradients across the system; the largest increases in water-table elevations occurred seaward of the salinity control structures. The extent of flood-prone areas and the percentage of time water-table elevations in flood-prone areas were less than 0.5 foot below land surface increased with increased sea level. Increased sea level also resulted in landward migration of the freshwater-seawater interface; the largest changes in the position of the interface occurred seaward of the salinity control structures except in parts of the model area that were inundated by increased sea level. Decreased water-table gradients reduced groundwater inflow, groundwater outflow, canal exchanges, surface-water inflow, and surface-water outflow through salinity control structures. Results for the scenario that evaluated the combination of increased groundwater pumpage and increased sea level did not differ substantially from the scenario that evaluated increased sea level alone. Groundwater inflow, groundwater outflow, and canal exchanges were reduced in urban areas of the study area as a result of decreased water-table gradients across the system, although reductions were less than those in the increased sea-level scenario. The decline in groundwater levels caused by increased groundwater pumpage was less under the increased sea-level scenario than under the increased groundwater-pumpage scenario. The largest reductions in surface-water outflow from the salinity control structures occurred with increased sea level and increased groundwater pumpage.</p>\n<p>The model was designed specifically to evaluate the effect of groundwater pumpage on canal leakage at the surface-water-basin scale and thus may not be appropriate for (1) predictions that are dependent on data not included in the calibration process (for example, subdaily simulation of high-intensity events and travel times) and (or) (2) hydrologic conditions that are substantially different from those during the calibration and verification periods. The reliability of the model is limited by the conceptual model of the surface-water and groundwater system, the spatial distribution of physical properties, the scale and discretization of the system, and specified boundary conditions. Some of the model limitations are manifested in model errors. Despite these limitations, however, the model represents the complexities of the interconnected surface-water and groundwater systems that affect how the systems respond to groundwater pumpage, sea-level rise, and other hydrologic stresses. The model also quantifies the relative effects of groundwater pumpage and sea-level rise on the surface-water and groundwater systems.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145162","collaboration":"Prepared in cooperation with the Miami-Dade Water and Sewer Department","usgsCitation":"Hughes, J.D., and White, J., 2014, Hydrologic conditions in urban Miami-Dade County, Florida, and the effect of groundwater pumpage and increased sea level on canal leakage and regional groundwater flow (Version 1.0: Originally posted September 23, 2014; Version 1.1: May 26, 2016; Version 1.2: August 1, 2016): U.S. Geological Survey Scientific Investigations Report 2014-5162, Report: xiii, 175 p.; Data Release, https://doi.org/10.3133/sir20145162.","productDescription":"Report: xiii, 175 p.; Data Release","numberOfPages":"194","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051842","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":321776,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F79P2ZRH","text":"Data Release"},{"id":321775,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5162/versionHist.txt"},{"id":294282,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5162/"},{"id":294283,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5162/pdf/sir2014-5162.pdf","text":"Report","size":"33.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":294284,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5162/images/coverthb.jpg"}],"scale":"2000000","country":"United States","state":"Florida","county":"Miami-Dade County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.11299133300781,\n              25.842539331357372\n            ],\n            [\n              -80.11917114257811,\n              25.961748853879143\n            ],\n            [\n              -80.85662841796875,\n              25.94075695601904\n            ],\n            [\n              -80.86898803710938,\n              25.17014505150313\n            ],\n            [\n              -80.76461791992188,\n              25.139068709030795\n            ],\n            [\n              -80.54901123046875,\n              25.187544344824484\n            ],\n            [\n              -80.36773681640625,\n              25.293129530136873\n            ],\n            [\n              -80.299072265625,\n              25.388697990350824\n            ],\n            [\n              -80.244140625,\n              25.332855459462515\n            ],\n            [\n              -80.16998291015625,\n              25.494107850705554\n            ],\n            [\n              -80.13290405273438,\n              25.728158254981707\n            ],\n            [\n              -80.11299133300781,\n              25.842539331357372\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: Originally posted September 23, 2014; Version 1.1: May 26, 2016; Version 1.2: August 1, 2016","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5422baf6e4b08312ac7cee62","contributors":{"authors":[{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":499318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Jeremy T. jwhite@usgs.gov","contributorId":3930,"corporation":false,"usgs":true,"family":"White","given":"Jeremy T.","email":"jwhite@usgs.gov","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":false,"id":499319,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70137853,"text":"70137853 - 2014 - Strong influence of El Niño Southern Oscillation on flood risk around the world","interactions":[],"lastModifiedDate":"2015-01-14T09:27:58","indexId":"70137853","displayToPublicDate":"2014-09-22T09:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Strong influence of El Niño Southern Oscillation on flood risk around the world","docAbstract":"<p>El Ni&ntilde;o Southern Oscillation (ENSO) is the most dominant interannual signal of climate variability and has a strong influence on climate over large parts of the world. In turn, it strongly influences many natural hazards (such as hurricanes and droughts) and their resulting socioeconomic impacts, including economic damage and loss of life. However, although ENSO is known to influence hydrology in many regions of the world, little is known about its influence on the socioeconomic impacts of floods (i.e., flood risk). To address this, we developed a modeling framework to assess ENSO&rsquo;s influence on flood risk at the global scale, expressed in terms of affected population and gross domestic product and economic damages. We show that ENSO exerts strong and widespread influences on both flood hazard and risk. Reliable anomalies of flood risk exist during El Ni&ntilde;o or La Ni&ntilde;a years, or both, in basins spanning almost half (44%) of Earth&rsquo;s land surface. Our results show that climate variability, especially from ENSO, should be incorporated into disaster-risk analyses and policies. Because ENSO has some predictive skill with lead times of several seasons, the findings suggest the possibility to develop probabilistic flood-risk projections, which could be used for improved disaster planning. The findings are also relevant in the context of climate change. If the frequency and/or magnitude of ENSO events were to change in the future, this finding could imply changes in flood-risk variations across almost half of the world&rsquo;s terrestrial regions.</p>","language":"English","publisher":"National Academy of Sciences","publisherLocation":"Washington, D.C.","doi":"10.1073/pnas.1409822111","usgsCitation":"Ward, P.J., Jongman, B., Kummu, M., Dettinger, M., Sperna Weiland, F., and Winsemius, H., 2014, Strong influence of El Niño Southern Oscillation on flood risk around the world: Proceedings of the National Academy of Sciences, v. 111, no. 44, p. 15659-15664, https://doi.org/10.1073/pnas.1409822111.","productDescription":"6 p.","startPage":"15659","endPage":"15664","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057122","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":472753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1409822111","text":"Publisher Index Page"},{"id":297220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297187,"type":{"id":15,"text":"Index Page"},"url":"https://www.pnas.org/content/111/44/15659.full.pdf+html"}],"volume":"111","issue":"44","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-20","publicationStatus":"PW","scienceBaseUri":"54dd2c64e4b08de9379b377b","contributors":{"authors":[{"text":"Ward, Philip J.","contributorId":67434,"corporation":false,"usgs":true,"family":"Ward","given":"Philip","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":538185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jongman, B","contributorId":138641,"corporation":false,"usgs":false,"family":"Jongman","given":"B","email":"","affiliations":[{"id":6715,"text":"VU University Amsterdam","active":true,"usgs":false}],"preferred":false,"id":538186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kummu, M.","contributorId":39711,"corporation":false,"usgs":true,"family":"Kummu","given":"M.","email":"","affiliations":[],"preferred":false,"id":538187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dettinger, Mike 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":859,"corporation":false,"usgs":true,"family":"Dettinger","given":"Mike","email":"mddettin@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":538184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sperna Weiland, F.C","contributorId":138642,"corporation":false,"usgs":false,"family":"Sperna Weiland","given":"F.C","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":538188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winsemius, H.C","contributorId":138643,"corporation":false,"usgs":false,"family":"Winsemius","given":"H.C","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":538189,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70133425,"text":"70133425 - 2014 - Development and use of a basin-scale hydrologic model for the Onondaga Lake basin","interactions":[],"lastModifiedDate":"2017-06-05T15:32:36","indexId":"70133425","displayToPublicDate":"2014-09-22T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5049,"text":"Clear Waters","active":true,"publicationSubtype":{"id":10}},"title":"Development and use of a basin-scale hydrologic model for the Onondaga Lake basin","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"New York Water Environmental Association Inc.","usgsCitation":"Coon, W.F., 2014, Development and use of a basin-scale hydrologic model for the Onondaga Lake basin: Clear Waters, v. 44, p. 31-33.","productDescription":"3 p.","startPage":"31","endPage":"33","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057007","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":342124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Onondaga Lake basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.24340057373047,\n              43.11514450539713\n            ],\n            [\n              -76.23653411865233,\n              43.11514450539713\n            ],\n            [\n              -76.21988296508789,\n              43.105745559619855\n            ],\n            [\n              -76.20923995971678,\n              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,{"id":70123760,"text":"ofr20141138 - 2014 - Magnetic resonance sounding survey data collected in the North Platte, Twin Platte, and South Platte Natural Resource Districts, Western Nebraska, Fall 2012","interactions":[],"lastModifiedDate":"2014-09-19T12:14:52","indexId":"ofr20141138","displayToPublicDate":"2014-09-19T12:11:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1138","title":"Magnetic resonance sounding survey data collected in the North Platte, Twin Platte, and South Platte Natural Resource Districts, Western Nebraska, Fall 2012","docAbstract":"This report is a release of digital data and associated survey descriptions from a series of magnetic resonance soundings (MRS, also known as surface nuclear magnetic resonance) that was conducted during October and November of 2012 in areas of western Nebraska as part of a cooperative hydrologic study by the North Platte Natural Resource District (NRD), South Platte NRD, Twin Platte NRD, the Nebraska Environmental Trust, and the U.S. Geological Survey (USGS).  The objective of the study was to delineate the base-of-aquifer and refine the understanding of the hydrologic properties in the aquifer system.  The MRS technique non-invasively measures water content in the subsurface, which makes it a useful tool for hydrologic investigations in the near surface (up to depths of approximately 150 meters).  In total, 14 MRS production-level soundings were acquired by the USGS over an area of approximately 10,600 square kilometers.  The data are presented here in digital format, along with acquisition information, survey and site descriptions, and metadata.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141138","collaboration":"Prepared in cooperation with the North Platte Natural Resources District, the South Platte Natural Resources District, the Twin Platte Natural Resources District, the Nebraska Environmental Trust, and the University of Nebraska Conservation and Survey Division","usgsCitation":"Kass, M.A., Bloss, B., Irons, T.P., Cannia, J.C., and Abraham, J., 2014, Magnetic resonance sounding survey data collected in the North Platte, Twin Platte, and South Platte Natural Resource Districts, Western Nebraska, Fall 2012: U.S. Geological Survey Open-File Report 2014-1138, Report: viii, 18 p.; Downloads Directory, https://doi.org/10.3133/ofr20141138.","productDescription":"Report: viii, 18 p.; Downloads Directory","numberOfPages":"29","ipdsId":"IP-050655","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":294224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141138.jpg"},{"id":294223,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1138/pdf/ofr2014-1138.pdf"},{"id":294221,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1138/"},{"id":294222,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1138/GIS_data"}],"country":"United States","state":"Nebraska","otherGeospatial":"North Platte;Twin Platte;South Platte Natural Resource Districts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.14,40.74 ], [ -104.14,41.96 ], [ -99.44,41.96 ], [ -99.44,40.74 ], [ -104.14,40.74 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d378de4b0f68901ebd9ac","contributors":{"authors":[{"text":"Kass, Mason A. 0000-0001-6119-2593 mkass@usgs.gov","orcid":"https://orcid.org/0000-0001-6119-2593","contributorId":613,"corporation":false,"usgs":true,"family":"Kass","given":"Mason","email":"mkass@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":500224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bloss, Benjamin R.","contributorId":19446,"corporation":false,"usgs":true,"family":"Bloss","given":"Benjamin R.","affiliations":[],"preferred":false,"id":500226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irons, Trevor P. tirons@usgs.gov","contributorId":4851,"corporation":false,"usgs":true,"family":"Irons","given":"Trevor","email":"tirons@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":500225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cannia, James C.","contributorId":94356,"corporation":false,"usgs":true,"family":"Cannia","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":500228,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Abraham, Jared D.","contributorId":42630,"corporation":false,"usgs":true,"family":"Abraham","given":"Jared D.","affiliations":[],"preferred":false,"id":500227,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70123759,"text":"sim3310 - 2014 - Base of principal aquifer for parts of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska","interactions":[],"lastModifiedDate":"2014-09-19T08:47:58","indexId":"sim3310","displayToPublicDate":"2014-09-19T08:36:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3310","title":"Base of principal aquifer for parts of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska","docAbstract":"<p>Water resources in the North and South Platte River valleys of Nebraska, including the valley of Lodgepole Creek, are critical to the social and economic health of the area, and for the recovery of threatened and endangered species in the Platte River Basin. Groundwater and surface water are heavily used resources, and uses are regulated in the study area. Irrigation is the dominant water use and, in most instances, is supplied by both groundwater and surface-water sources. The U.S. Geological Survey and its partners have collaborated to use airborne geophysical surveys for areas of the North and South Platte River valleys including the valley of Lodgepole Creek in western Nebraska. The objective of the surveys was to map the aquifers and underlying bedrock topography of selected areas to help improve the understanding of groundwater–surface-water relations to guide water-management decisions. This project was a cooperative study involving the North Platte Natural Resources District, the South Platte Natural Resources District, the Twin Platte Natural Resources District, the Conservation and Survey Division of the University of Nebraska-Lincoln, and the Nebraska Environmental Trust.</p>\n<br/>\n<p>This report presents the interpreted base-of-aquifer surface for part of the area consisting of the North Platte Natural Resources District, the South Platte Natural Resources District, and the Twin Platte Natural Resources District. The interpretations presented herein build on work done by previous researchers from 2008 to 2009 by incorporating additional airborne electromagnetic survey data collected in 2010 and additional test holes from separate, related studies. To make the airborne electromagnetic data useful, numerical inversion was used to convert the measured data into a depth-dependent subsurface resistivity model. An interpretation of the elevation and configuration of the base of aquifer was completed in a geographic information system that provided x, y, and z coordinates. The process of interpretation involved manually picking locations (base-of-aquifer elevations) on the displayed airborne electromagnetic-derived resistivity profile by the project geophysicist, hydrologist, and geologist. These locations, or picks, of the base-of-aquifer elevation (typically the top of the Brule Formation of the White River Group) were then stored in a georeferenced database. The pick was made by comparing the inverted airborne electromagnetic-derived resistivity profile to the lithologic descriptions and borehole geophysical logs from nearby test holes. The database of interpretive picks of the base-of-aquifer elevation was used to create primary input for interpolating the new base-of-aquifer contours.</p>\n<br/>\n<p>The automatically generated contours were manually adjusted based on the interpreted location of paleovalleys eroded into the base-of-aquifer surface and associated bedrock highs, many of which were unmapped before this study. When contours are overlain by the water-table surface, the saturated thickness of the aquifer can be computed, which allows an estimate of total water in storage. The contours of the base-of-aquifer surface presented in this report may be used as the lower boundary layer in existing and future groundwater-flow models. The integration of geophysical data into the contouring process facilitated a more continuous and spatially comprehensive view of the hydrogeologic framework.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3310","collaboration":"Prepared in cooperation with the North Platte Natural Resources District, South Platte Natural Resources District, Twin Platte Natural Resources District, Conservation and Survey Division of the University of Nebraska-Lincoln, and the Nebraska Environmental Trust","usgsCitation":"Hobza, C.M., Abraham, J., Cannia, J.C., Johnson, M., and Sibray, S.S., 2014, Base of principal aquifer for parts of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska: U.S. Geological Survey Scientific Investigations Map 3310, 2 Sheets: 53.0 x 36.0 inches and 36.5 x 36.0 inches; Downloads Directory, https://doi.org/10.3133/sim3310.","productDescription":"2 Sheets: 53.0 x 36.0 inches and 36.5 x 36.0 inches; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-054502","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":294201,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3310/GIS_files"},{"id":294199,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3310/pdf/sim3310_sheet1.pdf"},{"id":294200,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3310/pdf/sim3310_sheet2.pdf"},{"id":294194,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3310/"},{"id":294202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3310.jpg"}],"projection":"Universal Transverse Mercator projection, zone 13 north","datum":"North American Datum of 1983","country":"United States","state":"Nebraska","otherGeospatial":"Lodgepole Creek;North Platte River Valley;Platte River Basin;South Platte River Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.25,41.0 ], [ -104.25,42.25 ], [ -101.875,42.25 ], [ -101.875,41.0 ], [ -104.25,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541d3786e4b0f68901ebd97e","contributors":{"authors":[{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":500220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abraham, Jared D.","contributorId":42630,"corporation":false,"usgs":true,"family":"Abraham","given":"Jared D.","affiliations":[],"preferred":false,"id":500221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannia, James C.","contributorId":94356,"corporation":false,"usgs":true,"family":"Cannia","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":500223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":500219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sibray, Steven S.","contributorId":88589,"corporation":false,"usgs":true,"family":"Sibray","given":"Steven","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":500222,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70126013,"text":"tm6A51 - 2014 - One-Water Hydrologic Flow Model (MODFLOW-OWHM)","interactions":[],"lastModifiedDate":"2014-09-19T08:13:45","indexId":"tm6A51","displayToPublicDate":"2014-09-18T16:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A51","title":"One-Water Hydrologic Flow Model (MODFLOW-OWHM)","docAbstract":"<p>The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, MF-OWHM has the unique set of capabilities to simulate and analyze historical, present, and future conjunctive-use conditions. MF-OWHM is especially useful for the analysis of agricultural water use where few data are available for pumpage, land use, or agricultural information. The features presented in this IHM include additional linkages with SFR, SWR, Drain-Return (DRT), Multi-Node Wells (MNW1 and MNW2), and Unsaturated-Zone Flow (UZF). Thus, MF-OWHM helps to reduce the loss of water during simulation of the hydrosphere and helps to account for “all of the water everywhere and all of the time.”</p>\n<br/>\n<p>In addition to groundwater, surface-water, and landscape budgets, MF-OWHM provides more options for observations of land subsidence, hydraulic properties, and evapotranspiration (ET) than previous models. Detailed landscape budgets combined with output of estimates of actual evapotranspiration facilitates linkage to remotely sensed observations as input or as additional observations for parameter estimation or water-use analysis. The features of FMP have been extended to allow for temporally variable water-accounting units (farms) that can be linked to land-use models and the specification of both surface-water and groundwater allotments to facilitate sustainability analysis and connectivity to the Groundwater Management Process (GWM).</p>\n<br/>\n<p>An example model described in this report demonstrates the application of MF-OWHM with the addition of land subsidence and a vertically deforming mesh, delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in demand caused by deficiency in supply, and changes in multi-aquifer pumpage caused by constraints imposed through the Farm Process and the MNW2 Package, and changes in surface water such as runoff, streamflow, and canal flows through SFR and SWR linkages.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Groundwater in Book 6 <i>Modeling Techniques</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A51","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation. This report is Chapter 51 of Section A: Groundwater in Book 6 <i>Modeling Techniques</i>.","usgsCitation":"Hanson, R.T., Boyce, S.E., Schmid, W., Hughes, J.D., Mehl, S.W., Leake, S.A., Maddock, T., and Niswonger, R., 2014, One-Water Hydrologic Flow Model (MODFLOW-OWHM): U.S. Geological Survey Techniques and Methods 6-A51, x, 120 p., https://doi.org/10.3133/tm6A51.","productDescription":"x, 120 p.","numberOfPages":"134","onlineOnly":"Y","ipdsId":"IP-040669","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438744,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C6F6C5","text":"USGS data release","linkHelpText":"MODFLOW One-Water Hydrologic Flow Model (MF-OWHM) Conjunctive Use and Integrated Hydrologic Flow Modeling Software with compiled windows executable, version 2.0.1"},{"id":294191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6A51.jpg"},{"id":294189,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/06/a51/"},{"id":294190,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a51/pdf/tm6-a51.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541be60de4b0e96537dda07d","contributors":{"authors":[{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Scott 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":501871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":501867,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mehl, Steffen W. swmehl@usgs.gov","contributorId":975,"corporation":false,"usgs":true,"family":"Mehl","given":"Steffen","email":"swmehl@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":501865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leake, Stanley A. 0000-0003-3568-2542 saleake@usgs.gov","orcid":"https://orcid.org/0000-0003-3568-2542","contributorId":1846,"corporation":false,"usgs":true,"family":"Leake","given":"Stanley","email":"saleake@usgs.gov","middleInitial":"A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":501866,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maddock, Thomas III","contributorId":32983,"corporation":false,"usgs":true,"family":"Maddock","given":"Thomas","suffix":"III","affiliations":[],"preferred":false,"id":501869,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Niswonger, Richard G.","contributorId":45402,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","affiliations":[],"preferred":false,"id":501870,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70103642,"text":"sir20145080 - 2014 - Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change","interactions":[],"lastModifiedDate":"2017-05-22T14:49:07","indexId":"sir20145080","displayToPublicDate":"2014-09-18T14:44:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5080","title":"Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change","docAbstract":"<p>A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia.</p>\n<br/>\n<p>The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling.</p>\n<br/>\n<p>The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the benefit of hydrological, soil erosion, and coarser ecological modeling. Reach attributes are summarized for each segment. In six subbasins segments are assigned additional attributes about barriers (usually impoundments) to fish migration and stream isolation. Segments in the six sub-basins are also attributed with percent urban area for the watershed upstream from the stream segment for each decade from 2010–2100 from models of urban growth.</p>\n<br/>\n<p>On a broader scale, for application in a coarse-scale species-response model, the stream-network information is aggregated and summarized by 256 drainage subbasins (Hydrologic Response Units) used for watershed hydrologic and stream-temperature models. A model of soil erodibility based on the Revised Universal Soil Loss Equation also was developed at this scale to parameterize a model to evaluate stream condition.</p>\n<br/>\n<p>The reach-scale network was classified using multivariate clustering based on modeled channel width, valley width, and mean reach gradient as variables. The resulting classification consists of a 6-cluster and a 12-cluster classification for every reach in the Apalachicola-Chattahoochee-Flint Basin. We present an example of the utility of the classification that was tested using the occurrence of two species of darters and two species of minnows in the Apalachicola-Chattahoochee-Flint River Basin, the blackbanded darter and Halloween darter, and the bluestripe shiner and blacktail shiner.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145080","collaboration":"Prepared in cooperation with the National Climate Change and Wildlife Science Center","usgsCitation":"Elliott, C.M., Jacobson, R.B., and Freeman, M., 2014, Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change: U.S. Geological Survey Scientific Investigations Report 2014-5080, ix, 79 p., https://doi.org/10.3133/sir20145080.","productDescription":"ix, 79 p.","numberOfPages":"94","onlineOnly":"Y","ipdsId":"IP-043137","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":294188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145080.jpg"},{"id":294187,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5080/pdf/sir2014-5080.pdf"},{"id":294186,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5080/"}],"country":"United States","state":"Alabama, Florida, Georgia, Virginia","otherGeospatial":"Apalachicola-Chattahoochee-Flint River System","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.333333,29.0 ], [ -85.333333,38.333333 ], [ -75.866667,38.333333 ], [ -75.866667,29.0 ], [ -85.333333,29.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541be610e4b0e96537dda095","contributors":{"authors":[{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":493431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":493430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":493432,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70112327,"text":"sir20145111 - 2014 - Integrated hydrologic model of Pajaro Valley, Santa Cruz and Monterey Counties, California","interactions":[],"lastModifiedDate":"2015-05-08T11:47:10","indexId":"sir20145111","displayToPublicDate":"2014-09-18T08:44:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5111","title":"Integrated hydrologic model of Pajaro Valley, Santa Cruz and Monterey Counties, California","docAbstract":"<p>Increasing population, agricultural development (including shifts to more water-intensive crops), and climate variability are placing increasingly larger demands on available groundwater resources in the Pajaro Valley, one of the most productive agricultural regions in the world. This study provided a refined conceptual model, geohydrologic framework, and integrated hydrologic model of the Pajaro Valley. The goal of this study was to produce a model capable of being accurate at scales relevant to water management decisions that are being considered in the revision and updates to the Basin Management Plan (BMP). The Pajaro Valley Hydrologic Model (PVHM) was designed to reproduce the most important natural and human components of the hydrologic system and related climatic factors, permitting an accurate assessment of groundwater conditions and processes that can inform the new BMP and help to improve planning for long-term sustainability of water resources. Model development included a revision of the conceptual model of the flow system, reevaluation of the previous model transformed into MODFLOW, implementation of the new geohydrologic model and conceptual model, and calibration of the transient hydrologic model.</p>\n<p>&nbsp;</p>\n<p>The PVHM model, using MODFLOW with the Farm Process (MF-FMP2), is capable of being accurate at seasonal to interannual time frames and subregional to valley-wide spatial scales for the assessment of the groundwater hydrologic budget for water years 1964&ndash;2009, as well as potential assessment of the BMP components and sustainability analysis of conjunctive use. The model provides a good representation of the regional flow system and the use and movement of water throughout the valley.</p>\n<p>&nbsp;</p>\n<p>Simulated changes in storage over time show that, prior to the 1984&ndash;92 dry period, significant withdrawals from storage occurred only during drought years. Since about 1993, growers in the Pajaro Valley have shifted to more water intensive crops, such as strawberries, bushberries, and vegetable row crops, as well as making additional rotational plantings, which have increased demand on limited groundwater resources. Simulated groundwater flow indicates that vertical hydraulic gradients between horizontal layers fluctuate and even reverse in several parts of the basin as recharge and pumpage rates change seasonally and annually. The majority of recharge predominantly enters the Alluvial aquifer system, and along with pumpage and the largest fractions of storage depletion, occurs in the inland regions. Coastal inflow as seawater intrusion replaces much of the potential storage depletion in the coastal regions. The simulated long-term imbalance between inflows and outflows indicates overdraft of the groundwater basin averaging about 12,950 acre-feet per year (acre-ft/yr) over the 46-year period of water years (1964&ndash;2009). Annual overdraft varies considerably from year to year, depending on land use, pumpage, and climate conditions. Climatically driven factors can affect inflows, outflows, and water use by as much as a factor of two between wet and dry years. Coastal inflows and outflows vary by year and by aquifer; the net coastal inflow, or seawater intrusion, ranges from about 1,000 to more than 6,000 acre-ft/yr. Maps of simulated and measured water-level elevations indicate regions with water levels below sea level in the alluvium and Aromas layers.</p>\n<p><br />Ongoing expansion of local hydrologic monitoring networks indicates the importance of these networks to the understanding of changes in groundwater flow, streamflow, and streamflow infiltration. In particular, the monitoring of streamflow, groundwater pumpage, and groundwater levels throughout the valley not only indicates the state of the resources, but also provides valuable information for model calibration and for model-based evaluation of management actions.</p>\n<p>The HS-ASR was simulated for the years 2002&ndash;09, and replaced about about 1,290 acre-ft of coastal pumpage. This was combined with the simulation of additional 6,200 acre-ft of deliveries from supplemental wells, recycled water, and city connection deliveries through the CDS that also supplanted some coastal pumpage. Total simulated deliveries were 7,350 acre-ft of the 7,500 acre-ft of reported deliveries for the period 2002-09. The completed CDS should be capable of delivering about 8.8 million cubic meters (7,150 acre-ft) of water per year to coastal farms within the Pajaro Valley, if all the local supply components were fully available for this purpose. This would represent about 15 percent of the 48,300 acre-ft (59.6 million cubic meters) average agricultural pumpage for the period 2005 to 2009. Combined with the potential capture and reuse of some of the return flows and tile-drain flows, this could represent an almost 70 percent reduction of average overdraft for the entire valley and a large part of the coastal pumpage that induces seawater intrusion.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145111","collaboration":"Prepared in cooperation with Pajaro Valley Water Management Agency","usgsCitation":"Hanson, R.T., Schmid, W., Faunt, C., Lear, J., and Lockwood, B., 2014, Integrated hydrologic model of Pajaro Valley, Santa Cruz and Monterey Counties, California: U.S. Geological Survey Scientific Investigations Report 2014-5111, x, 166 p., https://doi.org/10.3133/sir20145111.","productDescription":"x, 166 p.","numberOfPages":"180","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-003917","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":294084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145111.jpg"},{"id":294082,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5111"},{"id":294083,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5111/pdf/sir2014-5111.pdf"}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"California","county":"Monterey County;Santa Cruz County","otherGeospatial":"Pajaro Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.00,36.866667 ], [ -122.00,37.5 ], [ -121.616667,37.5 ], [ -121.616667,36.866667 ], [ -122.00,36.866667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541be60ce4b0e96537dda06b","contributors":{"authors":[{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":494674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":1491,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":494671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lear, Jonathan","contributorId":72303,"corporation":false,"usgs":true,"family":"Lear","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":494672,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lockwood, Brian","contributorId":80202,"corporation":false,"usgs":true,"family":"Lockwood","given":"Brian","email":"","affiliations":[],"preferred":false,"id":494673,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70125660,"text":"ofr20141188 - 2014 - Legacy data for a northern prairie grassland: Woodworth Study Area, North Dakota, 1963-89","interactions":[],"lastModifiedDate":"2014-09-17T12:47:10","indexId":"ofr20141188","displayToPublicDate":"2014-09-17T12:36:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1188","title":"Legacy data for a northern prairie grassland: Woodworth Study Area, North Dakota, 1963-89","docAbstract":"Ecological data commonly become more valuable through time. Such legacy data provide baseline records of past biological, physical, and social information that provide historical perspective and are necessary for assessment of stasis or change. Legacy data collected at the Woodworth Study Area (WSA), a contiguous block of grasslands, croplands, and wetlands covering more than 1,000 hectares of the Prairie Pothole Region of North Dakota, are cataloged and summarized in this study. The WSA is one of the longest researched grassland sites in the Upper Midwest. It has an extensive history of settlement, land use, and management that provides a deeper context for future research. The WSA data include long-term vegetation transect records, land use history, habitat management records, geologic information, wetland hydrology and chemistry information, and spatial images. Substantial parts of these data have not been previously reported. The WSA is representative of many other lands purchased by the U.S. Fish and Wildlife Service in the Prairie Pothole Region from the 1930s to the 1970s; therefore, synthesized data from the WSA are broadly applicable to topics of concern in northern grasslands, such as increases in non-native plants, managing for biodiversity, and long-term effects of habitat management. New techniques are also described that were used to preserve these data for future analyses. The data preservation techniques are applicable to any project with data that should be preserved for 100 years or more.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141188","usgsCitation":"Williams, S.H., and Austin, J., 2014, Legacy data for a northern prairie grassland: Woodworth Study Area, North Dakota, 1963-89: U.S. Geological Survey Open-File Report 2014-1188, viii, 85 p., https://doi.org/10.3133/ofr20141188.","productDescription":"viii, 85 p.","numberOfPages":"94","onlineOnly":"Y","temporalStart":"1963-01-01","temporalEnd":"1989-12-31","ipdsId":"IP-056719","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":294050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141188.jpg"},{"id":294047,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1188/"},{"id":294049,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1188/pdf/ofr2014-1188.pdf"}],"country":"United States","state":"North Dakota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.05,45.9351 ], [ -104.05,49.0007 ], [ -96.5545,49.0007 ], [ -96.5545,45.9351 ], [ -104.05,45.9351 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541a9491e4b01571b3d4cc50","contributors":{"authors":[{"text":"Williams, Shelby H. shwilliams@usgs.gov","contributorId":5944,"corporation":false,"usgs":true,"family":"Williams","given":"Shelby","email":"shwilliams@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":501566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Austin, Jane E.","contributorId":43094,"corporation":false,"usgs":true,"family":"Austin","given":"Jane E.","affiliations":[],"preferred":false,"id":501567,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70121118,"text":"sir20105070L - 2014 - Deposit model for heavy-mineral sands in coastal environments","interactions":[],"lastModifiedDate":"2020-07-01T19:49:29.216529","indexId":"sir20105070L","displayToPublicDate":"2014-09-17T11:33:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5070","chapter":"L","title":"Deposit model for heavy-mineral sands in coastal environments","docAbstract":"<p>This report provides a descriptive model of heavy-mineral sands, which are sedimentary deposits of dense minerals that accumulate with sand, silt, and clay in coastal environments, locally forming economic concentrations of the heavy minerals. This deposit type is the main source of titanium feedstock for the titanium dioxide (TiO<sub>2</sub>) pigments industry, through recovery of the minerals ilmenite (Fe<sup>2+</sup>TiO<sub>3</sub>), rutile (TiO<sub>2</sub>), and leucoxene (an alteration product of ilmenite). Heavy-mineral sands are also the principal source of zircon (ZrSiO<sub>4</sub>) and its zirconium oxide; zircon is often recovered as a coproduct. Other heavy minerals produced as coproducts from some deposits are sillimanite/kyanite, staurolite, monazite, and garnet. Monazite [(Ce,La,Nd,Th)PO<sub>4</sub>] is a source of rare earth elements as well as thorium, which is used in thorium-based nuclear power under development in India and elsewhere.</p>\n<p>The processes that form coastal deposits of heavy-mineral sands begin inland. High-grade metamorphic and igneous rocks that contain heavy minerals weather and erode, contributing detritus composed of sand, silt, clay, and heavy minerals to fluvial systems. Streams and rivers carry the detritus to the coast, where they are deposited in a variety of coastal environments, such as deltas, the beach face (foreshore), the nearshore, barrier islands or dunes, and tidal lagoons, as well as the channels and floodplains of streams and rivers in the coastal plain. The sediments are reworked by waves, tides, longshore currents, and wind, which are effective mechanisms for sorting the mineral grains on the basis of differences in their size and density. The finest-grained, most dense heavy minerals are the most effectively sorted. The result is that heavy minerals accumulate together, forming laminated or lens-shaped, heavy-mineral-rich sedimentary packages that can be several meters and even as much as tens of meters thick. Most economic deposits of heavy-mineral sands are Paleogene, Neogene, and Quaternary in age; some are modern coastal deposits.</p>\n<p>Superimposed on these basic processes of ore formation are a multitude of contributing and modifying factors, such as the following:</p>\n<ul>\n<li>Strong, sustained wave action moves sand from offshore to the shore, where the sand and heavy minerals are sorted by size and density. Mineral sorting occurs mainly on the upper part of the hightide swash (wave) zone.</li>\n<li>Fine-grained sands and heavy minerals on the foreshore can be remobilized by winds, forming heavy mineral-rich sand dunes behind the beach.</li>\n<li>Longshore drift combined with the geomorphology of the coast exert strong influence on the location of the heavy-mineral sands deposits.</li>\n<li>Sea level changes are a function of climatic changes, such as ice ages. Rises in regional sea level (transgression) and lowering of sea level (regression) strongly influence the deposition and preservation of heavy-mineral sands. The majority of heavy-mineral sands accumulation appears related to seaward progradation of the shore during regression events.</li>\n<li>Local faulting may affect the geomorphology of the coast, which controls the distribution of heavy mineral deposition in a coastal basin.</li>\n<li>Heavy mineral grains appear to weather primarily after their deposition in the coastal plain; this weathering is caused by groundwaters, humic acids, and other intrabasinal fluids. This weathering can enhance the TiO<sub>2</sub> content of ilmenite. Iron is leached from ilmenite during weathering, which thereby upgrades the TiO<sub>2</sub> content of the ilmenite, forming leucoxene.</li>\n</ul>\n<p>The resulting deposits of heavy-mineral sands can be voluminous. Individual bodies of heavy mineral-rich sands are typically about 1 kilometer wide and more than 5 kilometers long. Many heavy-mineral sands districts extend for more than 10 kilometers and contain several individual deposits that are spread along an ancient or modern strandline. Reported thicknesses of economic deposits range from 3 to 45 meters. Individual ore deposits typically comprise at least 10 megatonnes of ore (the total size of the individual sand-silt body), whose overall heavy-mineral content is 2 to greater than 10 percent.</p>\n<p>Heavy-mineral sands deposits are relatively easy to mine because they are weakly to poorly consolidated, and they are relatively easy to process. From a geoenvironmental standpoint, mining of heavy mineral-sands generates little or no acid or solubilized metals. However, environmental and human health concerns related to such mining include potential effects on indigenous flora and fauna, effects on local hydrology, and issues related to processing and storing thorium-bearing monazite, owing to its radioactivity.</p>\n<p>Regional exploration for deposits of heavy-mineral sands can utilize the analyses of stream sediment samples for Ti, Hf, the rare earth elements, Th, and U, and geophysical surveys, particularly radiometric (gamma-ray spectrometry for K, U, and Th) and magnetic methods. Geophysical anomalies may be small, and surveys are generally more successful when conducted close to sources of interest.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit models for resource assessment","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070L","issn":"2328-0328","usgsCitation":"Van Gosen, B.S., Fey, D.L., Shah, A.K., Verplanck, P.L., and Hoefen, T.M., 2014, Deposit model for heavy-mineral sands in coastal environments: U.S. Geological Survey Scientific Investigations Report 2010-5070, viii, 51 p., https://doi.org/10.3133/sir20105070L.","productDescription":"viii, 51 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053206","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":294045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105070L.jpg"},{"id":294044,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5070/l/"},{"id":294046,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/l/pdf/sir2010-5070l.pdf","text":"Report","size":"15.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541a948be4b01571b3d4cc21","contributors":{"authors":[{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":498806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":498804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":498807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":498805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":498803,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70121300,"text":"ofr20141158 - 2014 - Two decision-support tools for assessing the potential effects of energy development on hydrologic resources as part of the Energy and Environment in the Rocky Mountain Area interactive energy atlas","interactions":[],"lastModifiedDate":"2018-08-10T16:13:29","indexId":"ofr20141158","displayToPublicDate":"2014-09-16T12:44:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1158","title":"Two decision-support tools for assessing the potential effects of energy development on hydrologic resources as part of the Energy and Environment in the Rocky Mountain Area interactive energy atlas","docAbstract":"The U.S. Geological Survey project—Energy and Environment in the Rocky Mountain Area (EERMA)—has developed a set of virtual tools in the form of an online interactive energy atlas for Colorado and New Mexico to facilitate access to geospatial data related to energy resources, energy infrastructure, and natural resources that may be affected by energy development. The interactive energy atlas currently (2014) consists of three components: (1) a series of interactive maps; (2) downloadable geospatial datasets; and (3) decison-support tools, including two maps related to hydrologic resources discussed in this report. The hydrologic-resource maps can be used to examine the potential effects of energy development on hydrologic resources with respect to (1) groundwater vulnerability, by using the depth to water, recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity of the aquifer (DRASTIC) model, and (2) landscape erosion potential, by using the revised universal soil loss equation (RUSLE). The DRASTIC aquifer vulnerability index value for the two-State area ranges from 48 to 199. Higher values, indicating greater relative aquifer vulnerability, are centered in south-central Colorado, areas in southeastern New Mexico, and along riparian corridors in both States—all areas where the water table is relatively close to the land surface and the aquifer is more susceptible to surface influences. As calculated by the RUSLE model, potential mean annual erosion, as soil loss in units of tons per acre per year, ranges from 0 to 12,576 over the two-State area. The RUSLE model calculated low erosion potential over most of Colorado and New Mexico, with predictions of highest erosion potential largely confined to areas of mountains or escarpments. An example is presented of how a fully interactive RUSLE model could be further used as a decision-support tool to evaluate the potential hydrologic effects of energy development on a site-specific basis and to explore the effectiveness of various mitigation practices.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141158","usgsCitation":"Linard, J.I., Matherne, A.M., Leib, K.J., Carr, N.B., Diffendorfer, J., Hawkins, S.J., Latysh, N., Ignizio, D., and Babel, N.C., 2014, Two decision-support tools for assessing the potential effects of energy development on hydrologic resources as part of the Energy and Environment in the Rocky Mountain Area interactive energy atlas: U.S. Geological Survey Open-File Report 2014-1158, iv, 16 p., https://doi.org/10.3133/ofr20141158.","productDescription":"iv, 16 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-057229","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":293955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141158.jpg"},{"id":293953,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1158/"},{"id":293954,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1158/pdf/ofr2014-1158.pdf"}],"scale":"2000000","projection":"Albers Equal-Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Colorado;New Mexico","otherGeospatial":"Rocky Mountain Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.00,31.00 ], [ -111.00,41.00 ], [ -102.00,41.00 ], [ -102.00,31.00 ], [ -111.00,31.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5419430de4b091c7ffc8e524","contributors":{"authors":[{"text":"Linard, Joshua I. jilinard@usgs.gov","contributorId":1465,"corporation":false,"usgs":true,"family":"Linard","given":"Joshua","email":"jilinard@usgs.gov","middleInitial":"I.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matherne, Anne Marie 0000-0002-5873-2226 matherne@usgs.gov","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":303,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne","email":"matherne@usgs.gov","middleInitial":"Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leib, Kenneth J. 0000-0002-0373-0768 kjleib@usgs.gov","orcid":"https://orcid.org/0000-0002-0373-0768","contributorId":701,"corporation":false,"usgs":true,"family":"Leib","given":"Kenneth","email":"kjleib@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":498939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carr, Natasha B. 0000-0002-4842-0632 carrn@usgs.gov","orcid":"https://orcid.org/0000-0002-4842-0632","contributorId":1918,"corporation":false,"usgs":true,"family":"Carr","given":"Natasha","email":"carrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":498942,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":498943,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hawkins, Sarah J. 0000-0002-1878-9121 shawkins@usgs.gov","orcid":"https://orcid.org/0000-0002-1878-9121","contributorId":4818,"corporation":false,"usgs":true,"family":"Hawkins","given":"Sarah","email":"shawkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":498944,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Latysh, Natalie 0000-0003-0149-3962 nlatysh@usgs.gov","orcid":"https://orcid.org/0000-0003-0149-3962","contributorId":1356,"corporation":false,"usgs":true,"family":"Latysh","given":"Natalie","email":"nlatysh@usgs.gov","affiliations":[{"id":5060,"text":"Data Preservation Program","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":498940,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ignizio, Drew A. 0000-0001-8054-5139 dignizio@usgs.gov","orcid":"https://orcid.org/0000-0001-8054-5139","contributorId":4822,"corporation":false,"usgs":true,"family":"Ignizio","given":"Drew A.","email":"dignizio@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":498945,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Babel, Nils C.","contributorId":42862,"corporation":false,"usgs":true,"family":"Babel","given":"Nils","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":498946,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70112900,"text":"ofr20141106 - 2014 - Ecological requirements for pallid sturgeon reproduction and recruitment in the Missouri River: annual report 2011","interactions":[],"lastModifiedDate":"2014-09-11T15:06:23","indexId":"ofr20141106","displayToPublicDate":"2014-09-11T12:36:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1106","title":"Ecological requirements for pallid sturgeon reproduction and recruitment in the Missouri River: annual report 2011","docAbstract":"<p>The Comprehensive Sturgeon Research Project is a multiyear, multiagency collaborative research framework developed to provide information to support pallid sturgeon recovery and Missouri River management decisions. The project strategy integrates field and laboratory studies of sturgeon reproductive ecology, early life history, habitat requirements, and physiology. The project scope of work is developed annually with cooperating research partners and in collaboration with the U.S. Army Corps of Engineers, Missouri River Recovery—Integrated Science Program. The research consists of several interdependent and complementary tasks that engage multiple disciplines.</p>\n<br/>\n<p>The research tasks in the 2011 scope of work emphasized understanding of reproductive migrations and spawning of adult sturgeon, and hatch and drift of larvae. These tasks were addressed in three hydrologically and geomorphologically distinct parts of the Missouri River Basin: the Lower Missouri River downstream from Gavins Point Dam, the Upper Missouri River downstream from Fort Peck Dam and including downstream reaches of the Milk River, and the Lower Yellowstone River. The research is designed to inform management decisions related to channel re-engineering, flow modification, and pallid sturgeon population augmentation on the Missouri River, and throughout the range of the species. Research and progress made through this project are reported to the U.S. Army Corps of Engineers annually. This annual report details the research effort and progress made by the Comprehensive Sturgeon Research Project during 2011.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141106","collaboration":"Prepared in cooperation with the Missouri River Recovery–Integrated Science Program, U.S. Army Corps of Engineers, Yankton, South Dakota","usgsCitation":"DeLonay, A.J., Jacobson, R.B., Chojnacki, K.A., Annis, M., Braaten, P., Elliott, C.M., Fuller, D.B., Haas, J.D., Haddix, T.M., Ladd, H.L., McElroy, B.J., Mestl, G.E., Papoulias, D.M., Rhoten, J.C., and Wildhaber, M.L., 2014, Ecological requirements for pallid sturgeon reproduction and recruitment in the Missouri River: annual report 2011: U.S. Geological Survey Open-File Report 2014-1106, xi, 96 p., https://doi.org/10.3133/ofr20141106.","productDescription":"xi, 96 p.","numberOfPages":"112","onlineOnly":"Y","ipdsId":"IP-043483","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":293715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141106.jpg"},{"id":293714,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1106/pdf/ofr14-1106.pdf"},{"id":293713,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1106/"}],"scale":"2000000","projection":"Albers Equal Area projection","country":"United States","otherGeospatial":"Missouri River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.00,35.00 ], [ -115.00,49.00 ], [ -90.00,49.00 ], [ -90.00,35.00 ], [ -115.00,35.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5412ab8ce4b0239f1986b9e1","contributors":{"authors":[{"text":"DeLonay, Aaron J.","contributorId":53360,"corporation":false,"usgs":true,"family":"DeLonay","given":"Aaron","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":494891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":494882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chojnacki, Kimberly A. kchojnacki@usgs.gov","contributorId":1978,"corporation":false,"usgs":true,"family":"Chojnacki","given":"Kimberly","email":"kchojnacki@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":494884,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Annis, Mandy L.","contributorId":41575,"corporation":false,"usgs":true,"family":"Annis","given":"Mandy L.","affiliations":[],"preferred":false,"id":494889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Braaten, P. J. pbraaten@usgs.gov","contributorId":2724,"corporation":false,"usgs":true,"family":"Braaten","given":"P. J.","email":"pbraaten@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":494886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":494885,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fuller, D. B.","contributorId":58196,"corporation":false,"usgs":true,"family":"Fuller","given":"D.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":494892,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haas, Justin D.","contributorId":92123,"corporation":false,"usgs":true,"family":"Haas","given":"Justin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":494896,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Haddix, Tyler M.","contributorId":72315,"corporation":false,"usgs":true,"family":"Haddix","given":"Tyler","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":494894,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ladd, Hallie L.A.","contributorId":81817,"corporation":false,"usgs":true,"family":"Ladd","given":"Hallie","email":"","middleInitial":"L.A.","affiliations":[],"preferred":false,"id":494895,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McElroy, Brandon J.","contributorId":58197,"corporation":false,"usgs":true,"family":"McElroy","given":"Brandon","email":"","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":494893,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mestl, Gerald E.","contributorId":49336,"corporation":false,"usgs":true,"family":"Mestl","given":"Gerald","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":494890,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Papoulias, Diana M. 0000-0002-5106-2469 dpapoulias@usgs.gov","orcid":"https://orcid.org/0000-0002-5106-2469","contributorId":2726,"corporation":false,"usgs":true,"family":"Papoulias","given":"Diana","email":"dpapoulias@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":494887,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Rhoten, Jason C.","contributorId":7633,"corporation":false,"usgs":false,"family":"Rhoten","given":"Jason","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":494888,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":494883,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70123972,"text":"70123972 - 2014 - Lacustrine responses to decreasing wet mercury deposition rates: results from a case study in northern Minnesota","interactions":[],"lastModifiedDate":"2018-09-18T16:27:34","indexId":"70123972","displayToPublicDate":"2014-09-10T10:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Lacustrine responses to decreasing wet mercury deposition rates: results from a case study in northern Minnesota","docAbstract":"We present a case study comparing metrics of methylmercury (MeHg) contamination for four undeveloped lakes in Voyageurs National Park to wet atmospheric deposition of mercury (Hg), sulfate (SO<sub>4</sub><sup>–2</sup>), and hydrogen ion (H<sup>+</sup>) in northern Minnesota. Annual wet Hg, SO<sub>4</sub><sup>–2</sup>, and H<sup>+</sup> deposition rates at two nearby precipitation monitoring sites indicate considerable decreases from 1998 to 2012 (mean decreases of 32, 48, and 66%, respectively). Consistent with decreases in the atmospheric pollutants, epilimnetic aqueous methylmercury (MeHg<sub>aq</sub>) and mercury in small yellow perch (Hg<sub>fish</sub>) decreased in two of four lakes (mean decreases of 46.5% and 34.5%, respectively, between 2001 and 2012). Counter to decreases in the atmospheric pollutants, MeHg<sub>aq</sub> increased by 85% in a third lake, whereas Hg<sub>fish</sub> increased by 80%. The fourth lake had two disturbances in its watershed during the study period (forest fire; changes in shoreline inundation due to beaver activity); this lake lacked overall trends in MeHg<sub>aq</sub> and Hg<sub>fish</sub>. The diverging responses among the study lakes exemplify the complexity of ecosystem responses to decreased loads of atmospheric pollutants.","language":"English","publisher":"American Chemical Society","doi":"10.1021/es500301a","usgsCitation":"Brigham, M.E., Sandheinrich, M.B., Gay, D., Maki, R., Krabbenhoft, D.P., and Wiener, J.G., 2014, Lacustrine responses to decreasing wet mercury deposition rates: results from a case study in northern Minnesota: Environmental Science & Technology, v. 48, no. 11, p. 6115-6123, https://doi.org/10.1021/es500301a.","productDescription":"9 p.","startPage":"6115","endPage":"6123","ipdsId":"IP-051280","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472769,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/es500301a","text":"Publisher Index Page"},{"id":293591,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es500301a"},{"id":293596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Voyageurs National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.203689,48.299689 ], [ -93.203689,48.631628 ], [ -92.453285,48.631628 ], [ -92.453285,48.299689 ], [ -93.203689,48.299689 ] ] ] } } ] }","volume":"48","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-05-16","publicationStatus":"PW","scienceBaseUri":"541157b4e4b0fe7e184a553d","chorus":{"doi":"10.1021/es500301a","url":"http://dx.doi.org/10.1021/es500301a","publisher":"American Chemical Society (ACS)","authors":"Brigham Mark E., Sandheinrich Mark B., Gay David A., Maki Ryan P., Krabbenhoft David P., Wiener James G.","journalName":"Environmental Science & Technology","publicationDate":"6/3/2014","auditedOn":"3/4/2016","publiclyAccessibleDate":"6/3/2014"},"contributors":{"authors":[{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":500484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandheinrich, Mark B.","contributorId":86736,"corporation":false,"usgs":true,"family":"Sandheinrich","given":"Mark","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":500486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gay, David A.","contributorId":68022,"corporation":false,"usgs":true,"family":"Gay","given":"David A.","affiliations":[],"preferred":false,"id":500485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maki, Ryan P.","contributorId":100111,"corporation":false,"usgs":true,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":500488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":500483,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wiener, James G.","contributorId":93853,"corporation":false,"usgs":false,"family":"Wiener","given":"James","email":"","middleInitial":"G.","affiliations":[{"id":17913,"text":"River Studies Center, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":500487,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70126398,"text":"70126398 - 2014 - Size-dependent reactivity of magnetite nanoparticles: a field-laboratory comparison","interactions":[],"lastModifiedDate":"2018-09-04T16:35:18","indexId":"70126398","displayToPublicDate":"2014-09-09T10:04:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Size-dependent reactivity of magnetite nanoparticles: a field-laboratory comparison","docAbstract":"Logistic challenges make direct comparisons between laboratory- and field-based investigations into the size-dependent reactivity of nanomaterials difficult. This investigation sought to compare the size-dependent reactivity of nanoparticles in a field setting to a laboratory analog using the specific example of magnetite dissolution. Synthetic magnetite nanoparticles of three size intervals, ∼6 nm, ∼44 nm, and ∼90 nm were emplaced in the subsurface of the USGS research site at the Norman Landfill for up to 30 days using custom-made subsurface nanoparticle holders. Laboratory analog dissolution experiments were conducted using synthetic groundwater. Reaction products were analyzed via TEM and SEM and compared to initial particle characterizations. Field results indicated that an organic coating developed on the particle surfaces largely inhibiting reactivity. Limited dissolution occurred, with the amount of dissolution decreasing as particle size decreased. Conversely, the laboratory analogs without organics revealed greater dissolution of the smaller particles. These results showed that the presence of dissolved organics led to a nearly complete reversal in the size-dependent reactivity trends displayed between the field and laboratory experiments indicating that size-dependent trends observed in laboratory investigations may not be relevant in organic-rich natural systems.","language":"English","publisher":"American Chemical Society","doi":"10.1021/es500172p","usgsCitation":"Swindle, A.L., Elwood Madden, A.S., Cozzarelli, I.M., and Benamara, M., 2014, Size-dependent reactivity of magnetite nanoparticles: a field-laboratory comparison: Environmental Science & Technology, v. 48, no. 19, p. 11413-11420, https://doi.org/10.1021/es500172p.","productDescription":"8 p.","startPage":"11413","endPage":"11420","numberOfPages":"8","ipdsId":"IP-058257","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":294296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294261,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es500172p"}],"volume":"48","issue":"19","noUsgsAuthors":false,"publicationDate":"2014-09-22","publicationStatus":"PW","scienceBaseUri":"5422bb32e4b08312ac7cf0d9","chorus":{"doi":"10.1021/es500172p","url":"http://dx.doi.org/10.1021/es500172p","publisher":"American Chemical Society (ACS)","authors":"Swindle Andrew L., Madden Andrew S. Elwood, Cozzarelli Isabelle M., Benamara Mourad","journalName":"Environmental Science & Technology","publicationDate":"10/7/2014","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Swindle, Andrew L.","contributorId":41759,"corporation":false,"usgs":true,"family":"Swindle","given":"Andrew","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":501992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elwood Madden, Andrew S.","contributorId":42150,"corporation":false,"usgs":true,"family":"Elwood Madden","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":501993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":501991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benamara, Mourad","contributorId":52506,"corporation":false,"usgs":true,"family":"Benamara","given":"Mourad","email":"","affiliations":[],"preferred":false,"id":501994,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70120245,"text":"ofr20141173 - 2014 - Water-chemistry data collected in and near Kaloko-Honokohau National Historical Park, Hawaii, 2012–2014","interactions":[],"lastModifiedDate":"2014-09-09T16:13:46","indexId":"ofr20141173","displayToPublicDate":"2014-09-09T08:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1173","title":"Water-chemistry data collected in and near Kaloko-Honokohau National Historical Park, Hawaii, 2012–2014","docAbstract":"Kaloko-Honokōhau National Historical Park (KAHO) on western Hawaiʻi was established in 1978 to preserve, interpret, and perpetuate traditional Native Hawaiian culture and activities, including the preservation of a variety of culturally and ecologically significant water resources that are vital to this mission. KAHO water bodies provide habitat for 1 threatened, 11 endangered, and 3 candidate threatened or endangered species. These habitats are sustained by, and in the case of ʻAimakapā Fishpond and the anchialine pools, entirely dependent on, groundwater from the Keauhou aquifer system. Development of inland impounded groundwater in the Keauhou aquifer system may affect the coastal freshwater-lens system on which KAHO depends, if the inland impounded-groundwater and coastal freshwater-lens systems are hydrologically connected. This report documents water-chemistry results from a U.S. Geological Survey study that collected and analyzed water samples from 2012 to 2014 from 25 sites in and near KAHO to investigate potential geochemical indicators in water that might indicate the presence or absence of a hydrologic connection between the inland impounded-groundwater and coastal freshwater-lens systems in the area. Samples were collected under high-tide and low-tide conditions for KAHO sites, and in dry-season and wet-season conditions for all sites. Samples were collected from two ocean sites, two fishponds, three anchialine pools, and three monitoring wells within KAHO. Two additional nearshore wells were sampled on property adjacent to and north of KAHO. Additional samples from the freshwater-lens system were collected from six inland wells located upslope from KAHO, including three production wells. Seven production wells in the inland impounded-groundwater system also were sampled. Water samples were analyzed for major ions, selected trace elements, rare-earth elements, strontium-isotope ratio, and stable isotopes of water. Precipitation samples from five sites were collected roughly along a transect upslope from KAHO. All precipitation samples were analyzed for stable isotopes of water and some precipitation samples were analyzed for rare-earth and selected trace elements.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141173","collaboration":"Prepared in cooperation with the Hawaiʻi Commission on Water Resource Management and the National Park Service","usgsCitation":"Tillman, F., Oki, D.S., and Johnson, A.G., 2014, Water-chemistry data collected in and near Kaloko-Honokohau National Historical Park, Hawaii, 2012–2014: U.S. Geological Survey Open-File Report 2014-1173, Report: v, 14 p.; Tables, https://doi.org/10.3133/ofr20141173.","productDescription":"Report: v, 14 p.; Tables","numberOfPages":"24","onlineOnly":"Y","temporalStart":"2012-01-01","temporalEnd":"2014-09-01","ipdsId":"IP-057290","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":293481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141173.jpg"},{"id":293477,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1173/pdf/ofr2014-1173.pdf"},{"id":293478,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1173/downloads/ofr2014-1173_tables.xlsx"},{"id":293469,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1173/"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kaloko-honokohau National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.045925,19.665068 ], [ -156.045925,19.693891 ], [ -156.016629,19.693891 ], [ -156.016629,19.665068 ], [ -156.045925,19.665068 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54100634e4b07ab1cd980825","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":1629,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred D.","email":"ftillman@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":498048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oki, Delwyn S. 0000-0002-6913-8804 dsoki@usgs.gov","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":1901,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn","email":"dsoki@usgs.gov","middleInitial":"S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498050,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70101015,"text":"sir20145065 - 2014 - Status and understanding of groundwater quality in the Klamath Mountains study unit, 2010: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2018-06-08T13:31:38","indexId":"sir20145065","displayToPublicDate":"2014-09-05T12:18:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5065","title":"Status and understanding of groundwater quality in the Klamath Mountains study unit, 2010: California GAMA Priority Basin Project","docAbstract":"<p>Groundwater quality in the Klamath Mountains (KLAM) study unit was investigated as part of the Priority Basin Project of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in Del Norte, Humboldt, Shasta, Siskiyou, Tehama, and Trinity Counties. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory.</p>\n<br/>\n<p>The GAMA Priority Basin Project was designed to provide a spatially unbiased, statistically robust assessment of the quality of untreated (raw) groundwater in the primary aquifer system. The assessment is based on water-quality data and explanatory factors for groundwater samples collected in 2010 by the USGS from 39 sites and on water-quality data from the California Department of Public Health (CDPH) water-quality database. The primary aquifer system was defined by the depth intervals of the wells listed in the CDPH water-quality database for the KLAM study unit. The quality of groundwater in the primary aquifer system may be different from that in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination.</p>\n<br/>\n<p>This study included two types of assessments: (1) a <i>status assessment</i>, which characterized the status of the current quality of the groundwater resource by using data from samples analyzed for volatile organic compounds, pesticides, and naturally occurring inorganic constituents, such as major ions and trace elements, and (2) an <i>understanding assessment</i>, which evaluated the natural and human factors potentially affecting the groundwater quality. The assessments were intended to characterize the quality of groundwater resources in the primary aquifer system of the KLAM study unit, not the quality of treated drinking water delivered to consumers by water purveyors.</p>\n<br/>\n<p>Relative-concentrations (sample concentrations divided by the health- or aesthetic-based benchmark concentrations) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration greater than (>) 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to (≤) 1.0 indicates a concentration less than or equal to a benchmark. Relative-concentrations of organic constituents were classified as “high” (relative-concentration > 1.0), “moderate” (0.1 < relative-concentration ≤ 1.0), or “low” (relative-concentration ≤ 0.1). For inorganic constituents, the boundary between low and moderate relative-concentration was set at 0.5.</p>\n<br/>\n<p>Aquifer-scale proportion was used in the status assessment as the primary metric for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifer system with a relative-concentration greater than 1.0 for a particular constituent or class of constituents; percentage is based on an areal rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the percentages of the primary aquifer system with moderate and low relative-concentrations, respectively.</p>\n<br/>\n<p>The KLAM study unit includes more than 8,800 square miles (mi<sup>2</sup>), but only those areas near the sampling sites, about 920 mi<sup>2</sup>, are included in the areal assessment of the study unit. Two statistical approaches—grid-based and spatially weighted—were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. To confirm this methodology, 90 percent confidence intervals were calculated for the grid-based high aquifer-scale proportions and were compared to the spatially weighted results, which were found to be within these confidence intervals in all cases. Grid-based results were selected for use in the status assessment unless, as was observed in a few cases, a grid-based result was zero and the spatially weighted result was not zero, in which case, the spatially weighted result was used.</p>\n<br/>\n<p>The <i>status assessment</i> showed that inorganic constituents with human-health benchmarks were detected at high relative-concentrations in 2.6 percent of the primary aquifer system and at moderate relative-concentrations in 10 percent of the system. The high aquifer-scale proportion for inorganic constituents mainly reflected the high aquifer-scale proportions of boron. Inorganic constituents with secondary maximum contaminant levels were detected at high relative-concentrations in 13 percent of the primary aquifer system and at moderate relative-concentrations in 10 percent of the system. The constituents present at high relative-concentrations included iron and manganese.</p>\n<br/>\n<p>Organic constituents with human-health benchmarks were not detected at high relative-concentrations, but were detected at moderate relative-concentrations in 1.9 percent of the primary aquifer system. The 1.9 percent reflected a spatially weighted moderate aquifer-scale proportion for the gasoline additive methyl tert-butyl ether. Of the 148 organic constituents analyzed, 14 constituents were detected. Only one organic constituent had a detection frequency of greater than 10 percent—the trihalomethane, chloroform.</p>\n<br/>\n<p>The second component of this study, the <i>understanding assessment</i>, identified the natural and human factors that may have affected the groundwater quality in the KLAM study unit by evaluating statistical correlations between water-quality constituents and potential explanatory factors. The potential explanatory factors evaluated were aquifer lithology, land use, hydrologic conditions, depth, groundwater age, and geochemical conditions. Results of the statistical evaluations were used to explain the occurrence and distribution of constituents in the KLAM study unit.</p>\n<br/>\n<p>Groundwater age distribution (modern, mixed, or pre-modern), redox class (oxic, mixed, or anoxic), and dissolved oxygen concentration were the explanatory factors that best explained occurrence patterns of the inorganic constituents. High concentrations of boron were found to be associated with groundwater classified as mixed or pre-modern with respect to groundwater age. Boron was also negatively correlated to dissolved oxygen and positively correlated to specific conductance. Iron and manganese concentrations were strongly associated with low dissolved oxygen concentrations, anoxic and mixed redox classifications, and pre-modern groundwater. Specific conductance concentrations were found to be related to pre-modern groundwater, low dissolved oxygen concentrations, and high pH.</p>\n<br/>\n<p>Chloroform was selected for additional evaluation in the <i>understanding assessment</i> because it was detected in more than 10 percent of wells sampled in the KLAM study unit. Septic tank density was the only explanatory factor that was found to relate to chloroform concentrations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145065","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Bennett, G.L., Fram, M.S., and Belitz, K., 2014, Status and understanding of groundwater quality in the Klamath Mountains study unit, 2010: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5065, viii, 58 p., https://doi.org/10.3133/sir20145065.","productDescription":"viii, 58 p.","numberOfPages":"70","ipdsId":"IP-043179","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":293462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145065.jpg"},{"id":293460,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5065/"},{"id":293461,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5065/pdf/sir2014-5065.pdf"}],"projection":"Albers Equal Area Conic Projection","datum":"North American Datum of 1983","country":"United States","state":"California","otherGeospatial":"Klamath Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.00,32.00 ], [ -125.00,42.00 ], [ -114.00,42.00 ], [ -114.00,32.00 ], [ -125.00,32.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"540ac032e4b023c1f29d587d","contributors":{"authors":[{"text":"Bennett, George L. V 0000-0002-6239-1604 georbenn@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-1604","contributorId":1373,"corporation":false,"usgs":true,"family":"Bennett","given":"George","suffix":"V","email":"georbenn@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":492541,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70123324,"text":"70123324 - 2014 - Physiological condition of juvenile wading birds in relation to multiple landscape stressors in the Florida Everglades: effects of hydrology, prey availability, and mercury bioaccumulation","interactions":[],"lastModifiedDate":"2018-09-14T16:48:36","indexId":"70123324","displayToPublicDate":"2014-09-04T15:57:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Physiological condition of juvenile wading birds in relation to multiple landscape stressors in the Florida Everglades: effects of hydrology, prey availability, and mercury bioaccumulation","docAbstract":"The physiological condition of juvenile birds can be influenced by multiple ecological stressors, and few studies have concurrently considered the effects of environmental contaminants in combination with ecological attributes that can influence foraging conditions and prey availability. Using three temporally distinct indices of physiological condition, we compared the physiological response of nestling great egrets (<i>Ardea alba</i>) and white ibises (<i>Eudocimus albus</i>) to changing prey availability, hydrology (water depth, recession rate), and mercury exposure in the Florida Everglades. We found that the physiological response of chicks varied between species and among environmental variables. Chick body condition (short-term index) and fecal corticosterone levels (medium-term) were influenced by wetland water depth, prey availability, region, and age, but not by mercury contamination. However, mercury exposure did influence heat shock protein 70 (HSP70) in egret chicks, indicating a longer-term physiological response to contamination. Our results indicate that the physiological condition of egret and ibis chicks were influenced by several environmental stressors, and the time frame of the effect may depend on the specialized foraging behavior of the adults provisioning the chicks.","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0106447","usgsCitation":"Herring, G., Eagles-Smith, C.A., Gawlik, D.E., Beerens, J., and Ackerman, J., 2014, Physiological condition of juvenile wading birds in relation to multiple landscape stressors in the Florida Everglades: effects of hydrology, prey availability, and mercury bioaccumulation: PLoS ONE, v. 9, no. 9, 10 p., https://doi.org/10.1371/journal.pone.0106447.","productDescription":"10 p.","ipdsId":"IP-056103","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":472778,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0106447","text":"Publisher Index Page"},{"id":293428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293341,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0106447"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.46309,26.471496 ], [ -80.46309,26.527636 ], [ -80.208971,26.527636 ], [ -80.208971,26.471496 ], [ -80.46309,26.471496 ] ] ] } } ] }","volume":"9","issue":"9","noUsgsAuthors":false,"publicationDate":"2014-09-03","publicationStatus":"PW","scienceBaseUri":"542a66b5e4b01535cb427298","contributors":{"authors":[{"text":"Herring, Garth 0000-0003-1106-4731 gherring@usgs.gov","orcid":"https://orcid.org/0000-0003-1106-4731","contributorId":4403,"corporation":false,"usgs":true,"family":"Herring","given":"Garth","email":"gherring@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":500016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":500015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gawlik, Dale E.","contributorId":88055,"corporation":false,"usgs":true,"family":"Gawlik","given":"Dale","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":500018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beerens, James M. 0000-0001-8143-916X","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":25440,"corporation":false,"usgs":false,"family":"Beerens","given":"James M.","affiliations":[],"preferred":false,"id":500017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":500019,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70118930,"text":"fs20143067 - 2014 - Science for the stewardship of the groundwater resources of Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2019-05-13T15:53:00","indexId":"fs20143067","displayToPublicDate":"2014-09-04T09:38:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3067","title":"Science for the stewardship of the groundwater resources of Cape Cod, Massachusetts","docAbstract":"<p>Groundwater is the sole source of drinking water and a major source of freshwater for domestic, industrial, and agricultural uses on Cape Cod, Massachusetts. Groundwater discharged from aquifers also supports freshwater pond and stream ecosystems and coastal wetlands. Six hydraulically distinct groundwater-flow systems (lenses) have been delineated on Cape Cod. Of the approximately 450 million gallons per day of water that enters these lenses as recharge from precipitation, about 69 percent discharges directly to the coast, about 24 percent discharges to streams, and almost 7 percent is withdrawn by public-supply wells. In most areas, groundwater in the sand and gravel aquifers is shallow and susceptible to contamination from anthropogenic sources and saltwater intrusion. Continued land development and population growth on Cape Cod have created concerns that potable water will become less available and that the quantity and quality of water flowing to natural discharge areas such as ponds, streams, and coastal waters will continue to decline.</p>\n<br/>\n<p>The U.S. Geological Survey (USGS) has been investigating groundwater and surface-water resources on Cape Cod for more than 50 years. Recent studies highlighted in this fact sheet have focused on the sources of water to public-supply wells, ponds, streams, and coastal areas; the transport and discharge of nitrogen derived from domestic and municipal disposal of wastewater; and the effects of climate change on groundwater and surface-water resources. Other USGS activities include long-term monitoring of groundwater and pond levels and field research on groundwater contamination at the USGS Cape Cod Toxic Substances Hydrology Research Site (<a href=\"http://ma.water.usgs.gov/MMRCape/\" target=\"_blank\">http://ma.water.usgs.gov/MMRCape/</a>) near the Joint Base Cape Cod (JBCC), formerly the Massachusetts Military Reservation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143067","collaboration":"This fact sheet was prepared with support  from the Toxic Substances Hydrology and  Groundwater Resources Programs of the  U.S. Geological Survey.","usgsCitation":"Barbaro, J.R., Masterson, J., and LeBlanc, D.R., 2014, Science for the stewardship of the groundwater resources of Cape Cod, Massachusetts: U.S. Geological Survey Fact Sheet 2014-3067, 6 p., https://doi.org/10.3133/fs20143067.","productDescription":"6 p.","numberOfPages":"6","ipdsId":"IP-057579","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":293356,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3067/"},{"id":293358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143067.jpg"},{"id":293357,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3067/pdf/fs2014-3067.pdf"}],"country":"United States","state":"Massachusetts","city":"Cape Cod","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.25,41.50 ], [ -70.25,42.15 ], [ -70.00,42.15 ], [ -70.00,41.50 ], [ -70.25,41.50 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542a66b8e4b01535cb4272b5","contributors":{"authors":[{"text":"Barbaro, Jeffrey R. 0000-0002-6107-2142 jrbarbar@usgs.gov","orcid":"https://orcid.org/0000-0002-6107-2142","contributorId":1626,"corporation":false,"usgs":true,"family":"Barbaro","given":"Jeffrey","email":"jrbarbar@usgs.gov","middleInitial":"R.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":497519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masterson, John P. 0000-0003-3202-4413 jpmaster@usgs.gov","orcid":"https://orcid.org/0000-0003-3202-4413","contributorId":1865,"corporation":false,"usgs":true,"family":"Masterson","given":"John P.","email":"jpmaster@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":497521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628 dleblanc@usgs.gov","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":1696,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"dleblanc@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":497520,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70124278,"text":"70124278 - 2014 - Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors","interactions":[],"lastModifiedDate":"2014-09-11T13:13:11","indexId":"70124278","displayToPublicDate":"2014-09-01T13:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors","docAbstract":"Downscaling Global Climate Model (GCM) projections of future climate is critical for impact studies. Downscaling enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical Downscaling Model (SDSM) to downscale 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in downscaling the precipitation. Downscaling was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the downscaled precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change. Precipitation during and after the monsoon is likely to increase in both basins under the A1B and A2 emission scenarios; whereas, the pre-monsoon precipitation is likely to decrease. Peak monsoon precipitation is likely to shift from July to August, and may impact the livelihoods of large rural populations linked to subsistence agriculture in the basins. Uncertainty analysis of the downscaled precipitation indicated that the uncertainty in the downscaled precipitation was less than the uncertainty in the original CGCM3.1 precipitation; hence, the CGCM3.1 downscaled precipitation was a better input for the regional hydrological impact studies. However, downscaled precipitation from multiple GCMs is suggested for comprehensive impact studies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.05.016","usgsCitation":"Pervez, M., and Henebry, G., 2014, Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors: Journal of Hydrology, v. 517, p. 120-134, https://doi.org/10.1016/j.jhydrol.2014.05.016.","productDescription":"15 p.","startPage":"120","endPage":"134","numberOfPages":"15","ipdsId":"IP-049180","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472786,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2014.05.016","text":"Publisher Index Page"},{"id":293736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293735,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2014.05.016"}],"country":"Bangladesh;China;India","otherGeospatial":"Brahmaputra;Ganges","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 75.0,25.0 ], [ 75.0,30.0 ], [ 95.0,30.0 ], [ 95.0,25.0 ], [ 75.0,25.0 ] ] ] } } ] }","volume":"517","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5412b9b7e4b0239f1986bad5","contributors":{"authors":[{"text":"Pervez, Md Shahriar 0000-0003-3417-1871 shahriar.pervez.ctr@usgs.gov","orcid":"https://orcid.org/0000-0003-3417-1871","contributorId":74230,"corporation":false,"usgs":true,"family":"Pervez","given":"Md Shahriar","email":"shahriar.pervez.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":500642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henebry, Geoffrey M.","contributorId":48114,"corporation":false,"usgs":true,"family":"Henebry","given":"Geoffrey M.","affiliations":[],"preferred":false,"id":500641,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}