The U.S. West Coast, including the Pacific Northwest and California Coastal Basins aquifer systems.
Groundwater response to interannual to multidecadal climate variability has important implications for security within the water–energy–food nexus. Here we use Singular Spectrum Analysis to quantify the teleconnections between AMO, PDO, ENSO, and PNA and precipitation and groundwater level fluctuations. The computer program DAMP was used to provide insight on the influence of soil texture, depth to water, and mean and period of a surface infiltration flux on the damping of climate signals in the vadose zone.
We find that PDO, ENSO, and PNA have significant influence on precipitation and groundwater fluctuations across a north-south gradient of the West Coast, but the lower frequency climate modes (PDO) have a greater influence on hydrologic patterns than higher frequency climate modes (ENSO and PNA). Low frequency signals tend to be preserved better in groundwater fluctuations than high frequency signals, which is a function of the degree of damping of surface variable fluxes related to soil texture, depth to water, mean and period of the infiltration flux. The teleconnection patterns that exist in surface hydrologic processes are not necessarily the same as those preserved in subsurface processes, which are affected by damping of some climate variability signals within infiltrating water.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2015.11.018","usgsCitation":"Velasco, E.M., Gurdak, J., Dickinson, J.E., Ferre, T., and Corona, C., 2017, Interannual to multidecadal climate forcings on groundwater resources of the U.S. West Coast: Journal of Hydrology: Regional Studies, v. 11, p. 250-265, https://doi.org/10.1016/j.ejrh.2015.11.018.","productDescription":"16 p.","startPage":"250","endPage":"265","ipdsId":"IP-067083","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":470245,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2015.11.018","text":"Publisher Index Page"},{"id":314871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.892578125,\n 32.63937487360669\n ],\n [\n -124.892578125,\n 49.095452162534826\n ],\n [\n -116.34521484375001,\n 49.095452162534826\n ],\n [\n -116.34521484375001,\n 32.63937487360669\n ],\n [\n -124.892578125,\n 32.63937487360669\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56a8a6c6e4b0b28f1184dbff","contributors":{"authors":[{"text":"Velasco, Elzie M.","contributorId":152546,"corporation":false,"usgs":false,"family":"Velasco","given":"Elzie","email":"","middleInitial":"M.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":589716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gurdak, Jason J.","contributorId":65125,"corporation":false,"usgs":true,"family":"Gurdak","given":"Jason J.","affiliations":[],"preferred":false,"id":589717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":589715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferre, T.P.A.","contributorId":196167,"corporation":false,"usgs":false,"family":"Ferre","given":"T.P.A.","email":"","affiliations":[],"preferred":false,"id":589718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corona, Claudia R.","contributorId":152548,"corporation":false,"usgs":false,"family":"Corona","given":"Claudia","middleInitial":"R.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":589719,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190718,"text":"70190718 - 2017 - Surface slip during large Owens Valley earthquakes","interactions":[],"lastModifiedDate":"2019-03-27T10:08:47","indexId":"70190718","displayToPublicDate":"2016-01-08T10:08:29","publicationYear":"2017","noYear":false,"publicationType":{"id":4,"text":"Book"},"title":"Surface slip during large Owens Valley earthquakes","docAbstract":"The 1872 Owens Valley earthquake is the third largest known historical earthquake in California. Relatively sparse field data and a complex rupture trace, however, inhibited attempts to fully resolve the slip distribution and reconcile the total moment release. We present a new, comprehensive record of surface slip based on lidar and field investigation, documenting 162 new measurements of laterally and vertically displaced landforms for 1872 and prehistoric Owens Valley earthquakes. Our lidar analysis uses a newly developed analytical tool to measure fault slip based on cross‐correlation of sublinear topographic features and to produce a uniquely shaped probability density function (PDF) for each measurement. Stacking PDFs along strike to form cumulative offset probability distribution plots (COPDs) highlights common values corresponding to single and multiple‐event displacements. Lateral offsets for 1872 vary systematically from ∼1.0 to 6.0 m and average 3.3 ± 1.1 m (2σ). Vertical offsets are predominantly east‐down between ∼0.1 and 2.4 m, with a mean of 0.8 ± 0.5 m. The average lateral‐to‐vertical ratio compiled at specific sites is ∼6:1. Summing displacements across subparallel, overlapping rupture traces implies a maximum of 7–11 m and net average of 4.4 ± 1.5 m, corresponding to a geologic Mw ∼7.5 for the 1872 event. We attribute progressively higher‐offset lateral COPD peaks at 7.1 ± 2.0 m, 12.8 ± 1.5 m, and 16.6 ± 1.4 m to three earlier large surface ruptures. Evaluating cumulative displacements in context with previously dated landforms in Owens Valley suggests relatively modest rates of fault slip, averaging between ∼0.6 and 1.6 mm/yr (1σ) over the late Quaternary.
A new Arctic Ostracode Database-2015 (AOD-2015) provides census data for 96 species of benthic marine Ostracoda from 1340 modern surface sediments from the Arctic Ocean and subarctic seas. Ostracoda is a meiofaunal, Crustacea group that secretes a bivalved calcareous (CaCO3) shell commonly preserved in sediments. Arctic and subarctic ostracode species have ecological limits controlled by temperature, salinity, oxygen, sea ice, food, and other habitat-related factors. Unique species ecology, shell chemistry (Mg/Ca ratios, stable isotopes), and limited stratigraphic ranges make them a useful tool for paleoceanographic reconstructions and biostratigraphy. The database, described here, will facilitate the investigation of modern ostracode biogeography, regional community structure, and ecology. These data, when compared to downcore faunal data from sediment cores, will provide a better understanding of how the Arctic has been affected by climatic and oceanographic change during the Quaternary. Images of all species and biogeographic distribution maps for selected species are presented, with brief discussion of representative species’ biogeographic and ecological significance. Publication of AOD-2015 is open-sourced and will be available online at several public websites with latitude, longitude, water depth, and bottom water temperature for most samples. It includes material from Arctic abyssal plains and submarine ridges, continental slopes, and shelves of the Kara, Laptev, East Siberian, Chukchi, Beaufort Seas, and several subarctic regions.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10750-015-2587-4","usgsCitation":"Gemery, L., Cronin, T.M., Briggs, W.M., Brouwers, E.M., Schornikov, E.I., Stepanova, A., Wood, A.M., and Yasuhara, M., 2017, An Arctic and Subarctic ostracode database: Biogeographic and paleoceanographic applications: Hydrobiologia, v. 786, p. 59-95, https://doi.org/10.1007/s10750-015-2587-4.","productDescription":"37 p.","startPage":"59","endPage":"95","ipdsId":"IP-070287","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":396243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic, Subarctic","volume":"786","noUsgsAuthors":false,"publicationDate":"2015-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":835560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":835561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, William M.","contributorId":279853,"corporation":false,"usgs":false,"family":"Briggs","given":"William","email":"","middleInitial":"M.","affiliations":[{"id":57377,"text":"INSTAAR","active":true,"usgs":false}],"preferred":false,"id":835562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brouwers, Elisabeth M. brouwers@usgs.gov","contributorId":279854,"corporation":false,"usgs":true,"family":"Brouwers","given":"Elisabeth","email":"brouwers@usgs.gov","middleInitial":"M.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":835563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schornikov, Eugene I.","contributorId":279855,"corporation":false,"usgs":false,"family":"Schornikov","given":"Eugene","email":"","middleInitial":"I.","affiliations":[{"id":57378,"text":"Zhirmunsky Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":835564,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stepanova, Anna","contributorId":147368,"corporation":false,"usgs":false,"family":"Stepanova","given":"Anna","email":"","affiliations":[{"id":16831,"text":"Borissiak Paleontological Institute","active":true,"usgs":false}],"preferred":false,"id":835565,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, Adrian M.","contributorId":279856,"corporation":false,"usgs":false,"family":"Wood","given":"Adrian","email":"","middleInitial":"M.","affiliations":[{"id":57379,"text":"Coventry University","active":true,"usgs":false}],"preferred":false,"id":835566,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yasuhara, Moriaki","contributorId":178705,"corporation":false,"usgs":false,"family":"Yasuhara","given":"Moriaki","email":"","affiliations":[],"preferred":false,"id":835567,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70159196,"text":"70159196 - 2017 - Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example","interactions":[],"lastModifiedDate":"2017-01-03T16:21:01","indexId":"70159196","displayToPublicDate":"2015-10-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5011,"text":"Geological Society of London Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example","docAbstract":"We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere – ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, cli- mate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation and can account for spatio-temporal variability in the intervening stages. The goal is a framework to determine whether, given uncertainties in the climate models and the biological response, meaningful inference can still be made. The non-linear downscaling of climate information to the river scale requires that one realistically account for spatial and temporal variability across scale. Our down- scaling procedure includes the use of fixed/calibrated hydrological flow and temperature models coupled with a stochastically parameterized sturgeon bioenergetics model. We show that, although there is a large amount of uncertainty associated with both the climate model output and the fish growth process, one can establish significant differences in fish growth distributions between models, and between future and current climates for a given model.
","largerWorkTitle":"Integrated Environmental Modelling to Solve Real World Problems: Methods, Vision and Challenges","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP408.11","usgsCitation":"Wildhaber, M.L., Wikle, C.K., Moran, E.H., Anderson, C.J., Franz, K.J., and Dey, R., 2017, Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example: Geological Society of London Special Publications, v. 408, p. 119-145, https://doi.org/10.1144/SP408.11.","productDescription":"27 p.","startPage":"119","endPage":"145","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042354","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":470249,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/ge_at_pubs/290","text":"External Repository"},{"id":311623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Missouri River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.3076171875,\n 38.94232097947902\n ],\n [\n -92.2412109375,\n 39.14710270770074\n ],\n [\n -94.06494140625,\n 40.34654412118006\n ],\n [\n -95.7568359375,\n 43.13306116240612\n ],\n [\n -95.80078125,\n 43.992814500489914\n ],\n [\n -96.3720703125,\n 44.15068115978091\n ],\n [\n -98.87695312499999,\n 45.96642454131025\n ],\n [\n -101.49169921875,\n 48.21003212234042\n ],\n [\n -102.74414062499999,\n 48.777912755501845\n ],\n [\n -106.171875,\n 48.922499263758255\n ],\n [\n -107.3583984375,\n 49.25346477497736\n ],\n [\n -112.9833984375,\n 49.396675075193976\n ],\n [\n -115.13671875,\n 49.05227025601607\n ],\n [\n -115.02685546875,\n 48.1367666796927\n ],\n [\n -113.6865234375,\n 47.17477833929903\n ],\n [\n -113.9501953125,\n 46.042735653846506\n ],\n [\n -113.5986328125,\n 45.521743896993634\n ],\n [\n -112.30224609374999,\n 44.653024159812\n ],\n [\n -110.28076171875,\n 44.29240108529005\n ],\n [\n -107.90771484375,\n 43.004647127794435\n ],\n [\n -106.98486328124999,\n 42.04929263868686\n ],\n [\n -105.53466796874999,\n 39.57182223734374\n ],\n [\n -102.83203125,\n 39.04478604850143\n ],\n [\n -97.36083984375,\n 38.238180119798635\n ],\n [\n -94.46044921875,\n 38.11727165830543\n ],\n [\n -92.21923828124999,\n 37.92686760148135\n ],\n [\n -90.37353515625,\n 38.839707613545144\n ],\n [\n -90.3076171875,\n 38.94232097947902\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"408","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-12","publicationStatus":"PW","scienceBaseUri":"5650524ee4b0f162148c5d11","contributors":{"authors":[{"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":577821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wikle, Christopher K.","contributorId":116632,"corporation":false,"usgs":false,"family":"Wikle","given":"Christopher","email":"","middleInitial":"K.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":577825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moran, Edward H. emoran@usgs.gov","contributorId":5445,"corporation":false,"usgs":true,"family":"Moran","given":"Edward","email":"emoran@usgs.gov","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":577820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Christopher J.","contributorId":11516,"corporation":false,"usgs":true,"family":"Anderson","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":577822,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Franz, Kristie J.","contributorId":36061,"corporation":false,"usgs":true,"family":"Franz","given":"Kristie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":577824,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dey, Rima","contributorId":81210,"corporation":false,"usgs":true,"family":"Dey","given":"Rima","email":"","affiliations":[],"preferred":false,"id":577823,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160437,"text":"70160437 - 2017 - A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example","interactions":[],"lastModifiedDate":"2017-08-09T17:02:58","indexId":"70160437","displayToPublicDate":"2015-08-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example","docAbstract":"We develop a fully-stochasticized, age-structured population model suitable for population viability analysis (PVA) of fish and demonstrate its use with the endangered pallid sturgeon (Scaphirhynchus albus) of the Lower Missouri River as an example. The model incorporates three levels of variance: parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level, temporal variance (uncertainty caused by random environmental fluctuations over time) applied at the time-step level, and implicit individual variance (uncertainty caused by differences between individuals) applied within the time-step level. We found that population dynamics were most sensitive to survival rates, particularly age-2+ survival, and to fecundity-at-length. The inclusion of variance (unpartitioned or partitioned), stocking, or both generally decreased the influence of individual parameters on population growth rate. The partitioning of variance into parameter and temporal components had a strong influence on the importance of individual parameters, uncertainty of model predictions, and quasiextinction risk (i.e., pallid sturgeon population size falling below 50 age-1+ individuals). Our findings show that appropriately applying variance in PVA is important when evaluating the relative importance of parameters, and reinforce the need for better and more precise estimates of crucial life-history parameters for pallid sturgeon.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.ecolmodel.2015.07.019","usgsCitation":"Wildhaber, M.L., Albers, J.L., Green, N.S., and Moran, E.H., 2017, A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example: Ecological Modelling, v. 359, p. 434-448, https://doi.org/10.1016/j.ecolmodel.2015.07.019.","productDescription":"15 p.","startPage":"434","endPage":"448","ipdsId":"IP-063152","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":470251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2015.07.019","text":"Publisher Index Page"},{"id":312542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lower Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.448974609375,\n 42.42345651793833\n ],\n [\n -96.35009765625,\n 42.58544425738491\n ],\n [\n -97.294921875,\n 42.94033923363183\n ],\n [\n -98.031005859375,\n 42.88401467044253\n ],\n [\n -99.151611328125,\n 43.65197548731187\n ],\n [\n -99.261474609375,\n 44.15856343854312\n ],\n [\n -100.360107421875,\n 44.59829048984011\n ],\n [\n -100.04150390625,\n 45.56021795715051\n ],\n [\n -100.34912109375,\n 46.164614496897094\n ],\n [\n -100.39306640625,\n 46.626806395355175\n ],\n [\n -101.173095703125,\n 47.78363463526376\n ],\n [\n -102.26074218749999,\n 47.613569753973955\n ],\n [\n -101.590576171875,\n 47.3834738721015\n ],\n [\n -100.821533203125,\n 46.44542749723387\n ],\n [\n -100.8544921875,\n 46.08847179577592\n ],\n [\n -100.65673828125,\n 45.79050946752472\n ],\n [\n -100.601806640625,\n 45.00365115687189\n ],\n [\n -101.31591796875,\n 44.74673324024678\n ],\n [\n -100.70068359374999,\n 44.3002644115815\n ],\n [\n -99.635009765625,\n 43.95328204198018\n ],\n [\n -99.41528320312499,\n 43.35713822211053\n ],\n [\n -98.23974609375,\n 42.65820178455667\n ],\n [\n -97.393798828125,\n 42.73087427928485\n ],\n [\n -96.448974609375,\n 42.42345651793833\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"359","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56753c38e4b0da412f4f8bc2","contributors":{"authors":[{"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":582890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, Nicholas S. 0000-0002-8538-4191 ngreen@usgs.gov","orcid":"https://orcid.org/0000-0002-8538-4191","contributorId":150743,"corporation":false,"usgs":true,"family":"Green","given":"Nicholas","email":"ngreen@usgs.gov","middleInitial":"S.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moran, Edward H. emoran@usgs.gov","contributorId":5445,"corporation":false,"usgs":true,"family":"Moran","given":"Edward","email":"emoran@usgs.gov","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582893,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155010,"text":"70155010 - 2017 - Salinity influences on aboveground and belowground net primary productivity in tidal wetlands","interactions":[],"lastModifiedDate":"2017-03-03T11:00:09","indexId":"70155010","displayToPublicDate":"2015-08-05T14:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Salinity influences on aboveground and belowground net primary productivity in tidal wetlands","docAbstract":"Tidal freshwater wetlands are one of the most vulnerable ecosystems to climate change and rising sea levels. However salinification within these systems is poorly understood, therefore, productivity (litterfall, woody biomass, and fine roots) were investigated on three forested tidal wetlands [(1) freshwater, (2) moderately saline, and (3) heavily salt-impacted] and a marsh along the Waccamaw and Turkey Creek in South Carolina. Mean aboveground (litterfall and woody biomass) production on the freshwater, moderately saline, heavily salt-impacted, and marsh, respectively, was 1,061, 492, 79, and 0 g m−2 year−1 versus belowground (fine roots) 860, 490, 620, and 2,128 g m−2 year−1. Litterfall and woody biomass displayed an inverse relationship with salinity. Shifts in productivity across saline sites is of concern because sea level is predicted to continue rising. Results from the research reported in this paper provide baseline data upon which coupled hydrologic/wetland models can be created to quantify future changes in tidal forest functions.
At the fringe of Everglades National Park in southwest Florida, United States, the Ten Thousand Islands National Wildlife Refuge (TTINWR) habitat has been heavily affected by the disruption of natural freshwater flow across the Tamiami Trail (U.S. Highway 41). As the Comprehensive Everglades Restoration Plan (CERP) proposes to restore the natural sheet flow from the Picayune Strand Restoration Project area north of the highway, the impact of planned measures on the hydrology in the refuge needs to be taken into account. The objective of this study was to develop a simple, computationally efficient mass balance model to simulate the spatial and temporal patterns of water level and salinity within the area of interest. This model could be used to assess the effects of the proposed management decisions on the surface water hydrological characteristics of the refuge. Surface water variations are critical to the maintenance of wetland processes. The model domain is divided into 10 compartments on the basis of their shared topography, vegetation, and hydrologic characteristics. A diversion of +10% of the discharge recorded during the modeling period was simulated in the primary canal draining the Picayune Strand forest north of the Tamiami Trail (Faka Union Canal) and this discharge was distributed as overland flow through the refuge area. Water depths were affected only modestly. However, in the northern part of the refuge, the hydroperiod, i.e., the duration of seasonal flooding, was increased by 21 days (from 115 to 136 days) for the simulation during the 2008 wet season, with an average water level rise of 0.06 m. The average salinity over a two-year period in the model area just south of Tamiami Trail was reduced by approximately 8 practical salinity units (psu) (from 18 to 10 psu), whereas the peak dry season average was reduced from 35 to 29 psu (by 17%). These salinity reductions were even larger with greater flow diversions (+20%). Naturally, the reduction in salinity diminished toward the open water areas where the daily flood tides mix in saline bay water. Partially restoring hydrologic flows to TTINWR will affect hydroperiod and salinity regimes within downslope wetlands, and perhaps serve as a management tool to reduce the speed of future encroachment of mangroves into marsh as sea levels rise.
","language":"English","publisher":"American Society of Civil Engineers","publisherLocation":"New York, NY","doi":"10.1061/(ASCE)HE.1943-5584.0001260","usgsCitation":"Michot, B., Meselhe, E., Krauss, K.W., Shrestha, S., From, A.S., and Patino, E., 2017, Hydrologic modeling in a marsh-mangrove ecotone: Predicting wetland surface water and salinity response to restoration in the Ten Thousand Islands region of Florida, USA: Journal of Hydrologic Engineering, v. 22, no. 1, D4015002-1: 18 p., https://doi.org/10.1061/(ASCE)HE.1943-5584.0001260.","productDescription":"D4015002-1: 18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059510","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":306317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55c090b0e4b033ef521042a1","contributors":{"authors":[{"text":"Michot, B.D.","contributorId":145740,"corporation":false,"usgs":false,"family":"Michot","given":"B.D.","email":"","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":565124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meselhe, E.A.","contributorId":145741,"corporation":false,"usgs":false,"family":"Meselhe","given":"E.A.","email":"","affiliations":[{"id":16216,"text":"Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":565125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":565123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shrestha, Surendra","contributorId":145742,"corporation":false,"usgs":false,"family":"Shrestha","given":"Surendra","email":"","affiliations":[],"preferred":false,"id":565126,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"From, Andrew S. 0000-0002-6543-2627 froma@usgs.gov","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":5038,"corporation":false,"usgs":true,"family":"From","given":"Andrew","email":"froma@usgs.gov","middleInitial":"S.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":565127,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Patino, Eduardo 0000-0003-1016-3658 epatino@usgs.gov","orcid":"https://orcid.org/0000-0003-1016-3658","contributorId":1743,"corporation":false,"usgs":true,"family":"Patino","given":"Eduardo","email":"epatino@usgs.gov","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":true,"id":565128,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189927,"text":"70189927 - 2017 - Effect of sediment supply and flow rate on the initiation and topographic evolution of sandbars in laboratory and numerical channels","interactions":[],"lastModifiedDate":"2019-10-17T12:16:27","indexId":"70189927","displayToPublicDate":"2015-05-01T12:05:13","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Effect of sediment supply and flow rate on the initiation and topographic evolution of sandbars in laboratory and numerical channels","docAbstract":"The evolution of barforms from a bed of uniform sediment and changes in sediment storage were measured in a laboratory flume and simulated numerically. Flume experiments were conducted with several upstream sediment supplies and flow conditions. For the sediment supply rates (no upstream supply, equilibrium supply, and 133, 166, and 200 percent of the equilibrium supply) and flow rates examined, the plane bed tended to evolve into mid-channel bars early in the runs ~15 minutes. As the flume experiments progressed, the bed transitioned to a lower mode configuration of alternate bars or a single-thread meandering thalweg. Increasing the upstream sediment supply to 133 percent or more of the equilibrium rate, increased the height and volume of deposited sediment relative to experiments conducted at the equilibrium rate and those experiments without sediment supply. Experiments conducted at flow rates of 0.5 and 1.0 L/s without sediment supply demonstrated that an increase in flow corresponded to a greater volume of erosion. A coupled two-dimensional flow and sediment transport model, Nays2DH, was used to simulate the evolution of bed topography for three sediment supply rates. We compared the morphodynamics and sediment storage predicted by Nays2DH for two initial bed conditions: one set of calculations used a plane bed with a small upstream perturbation as the initial bed condition, and the other set used the bed topography measured 15 minutes after the start of the flume run. Whereas initializing the model with measured flume topography provided a somewhat better analog to the final evolved morphology, predictions of sedimentation were not substantially improved over simulations using the plane bed as the initial condition.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 3rd Joint Federal Interagency Conference (10th Federal Interagency Sedimentation Conference and 5th Federal Interagency Hydrologic Modeling Conference),","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"5th Federal Interagency Hydrologic Modeling Conference and the 10th Federal Interagency Sedimentation Conference","conferenceDate":"April 19 – 23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Advisory Committee on Water Information","usgsCitation":"Kinzel, P.J., Logan, B., and Nelson, J.M., 2017, Effect of sediment supply and flow rate on the initiation and topographic evolution of sandbars in laboratory and numerical channels, in Proceedings of the 3rd Joint Federal Interagency Conference (10th Federal Interagency Sedimentation Conference and 5th Federal Interagency Hydrologic Modeling Conference),, Reno, NV, April 19 – 23, 2015, p. 1132-1143.","productDescription":"12 p.","startPage":"1132","endPage":"1143","ipdsId":"IP-061617","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":368390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368389,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/3rdJFIC/index.html"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":706787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Logan, Brandy blogan@usgs.gov","contributorId":195338,"corporation":false,"usgs":false,"family":"Logan","given":"Brandy","email":"blogan@usgs.gov","affiliations":[],"preferred":false,"id":706788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":706789,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70138831,"text":"sir20155010 - 2017 - Spatially distributed groundwater recharge for 2010 land cover estimated using a water-budget model for the Island of O‘ahu, Hawai‘i","interactions":[],"lastModifiedDate":"2020-02-06T13:53:49","indexId":"sir20155010","displayToPublicDate":"2015-02-26T10:00:00","publicationYear":"2017","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":"2015-5010","title":"Spatially distributed groundwater recharge for 2010 land cover estimated using a water-budget model for the Island of O‘ahu, Hawai‘i","docAbstract":"Owing mainly to projected population growth, demand for freshwater on the Island of Oʻahu is expected to increase by about 26 percent between 2010 and 2030, according to the City and County of Honolulu. Estimates of groundwater recharge are needed to evaluate the availability of fresh groundwater. For this study, a water-budget model with a daily computation interval was developed and used to estimate the spatial distribution of recharge on Oʻahu for average climate conditions (1978–2007 rainfall and 2010 land cover) and for drought conditions (1998–2002 rainfall and 2010 land cover). For average climate conditions, mean annual recharge for Oʻahu is about 660 million gallons per day, or about 36 percent of precipitation (rainfall and fog interception). Recharge for average climate conditions is about 34 percent of total water inflow, which consists of precipitation, irrigation, septic leachate, water-main leakage, and seepage from reservoirs and cesspools. Recharge is high along the crest of the Koʻolau Range, reaching as much as about 180 inches per year in the north-central part of the range. Recharge is much lower outside of the mountainous areas of the island, commonly less than 5 inches per year in unirrigated areas. The island-wide estimate of groundwater recharge for average climate conditions from this study is within 1 percent of the recharge estimate used in the 2008 State of Hawaiʻi Water Resource Protection Plan, which divides the Island of Oʻahu into 23 aquifer systems for groundwater management purposes. To facilitate direct comparisons with this study, these 23 aquifer systems were consolidated into 21 aquifer systems. Recharge estimates from this study are higher for 12 of the aquifer-system areas and lower for 9. Differences in mean rainfall distribution and the inclusion of irrigation in this study are the primary reasons for discrepancies in recharge estimates between this study and the 2008 Hawaiʻi Water Resources Protection Plan. For drought conditions, mean annual recharge for Oʻahu is about 417 million gallons per day, which is about 37 percent less than recharge for average climate conditions. For individual aquifer-system areas, recharge for drought conditions is about 25 to 70 percent less than recharge for average climate conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155010","collaboration":"Prepared in cooperation with the State of Hawai‘i Commission on Water Resource Management and the City and County of Honolulu Board of Water Supply","usgsCitation":"Engott, J.A., Johnson, A.G., Bassiouni, Maoya, Izuka, S.K., and Rotzoll, Kolja, 2017, Spatially distributed groundwater recharge for 2010 land cover estimated using a water-budget model for the Island of O‘ahu, Hawai‘i (ver. 2.0, December 2017): U.S. Geological Survey Scientific Investigations Report 2015–5010, 49 p., https://doi.org/10.3133/sir20155010.","productDescription":"Report: v, 49 p.; 2 Datasets","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-036376","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":349857,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5010/downloads/sir20155010_v2_versionhist.txt","text":"Version History","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5010"},{"id":349860,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7SX6B7M","text":"Dataset","linkHelpText":" - Mean annual water-budget components for the Island of Oahu, Hawaii, for drought conditions, 1998-2002 rainfall and 2010 land cover (version 2.0)"},{"id":298156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5010/images/coverthb.jpg"},{"id":349859,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7XP72ZX","text":"Dataset","linkHelpText":" - Mean annual water-budget components for the Island of Oahu, Hawaii, for average climate conditions, 1978-2007 rainfall and 2010 land cover (version 2.0)"},{"id":349856,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5010/downloads/sir20155010_v2.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5010"}],"country":"United States","state":"Hawai'i","otherGeospatial":"O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.39263916015625,\n 21.212579790630603\n ],\n [\n -158.39263916015625,\n 21.733988636412214\n ],\n [\n -157.57965087890625,\n 21.733988636412214\n ],\n [\n -157.57965087890625,\n 21.212579790630603\n ],\n [\n -158.39263916015625,\n 21.212579790630603\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted February 2015; Version 2.0: December 2017","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI
All living whooping cranes (Grus americana) are descended from 16 or fewer birds that remained alive in the early 1940s, a bottleneck that puts the species at potential risk for inbreeding depression. Although AI is commonly used in the management of the captive population of this species, little is known about seminal traits or factors affecting sperm quality in the whooping crane. In the present study, semen samples were collected from 29 adult males (age 3–27 years) during the early (March), mid (April) and late (May) breeding season over 2 consecutive years. The effects of donor age, time within reproductive season and level of inbreeding on seminal characteristics were analysed using regression and information–theoretic model selection. Only time within reproductive season significantly affected seminal traits, with total numbers of spermatozoa and proportions of pleiomorphisms increasing across the season. We conclude that, even with a highly restricted number of founders, there is no discernible influence of inbreeding (at the levels described) on sperm output or quality. Furthermore, although there is variance in seminal quality, the whooping crane produces significant numbers of motile spermatozoa throughout the breeding season, similar to values reported for the greater sandhill crane (Grus canadensis tabida).
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/RD15251","usgsCitation":"Brown, M., Converse, S.J., Chandler, J.N., Crosier, A.L., Lynch, W., Wildt, D., Keefer, C.L., and Songsasen, N., 2017, Time within reproductive season, but not age or inbreeding coefficient, influences seminal and sperm quality in the whooping crane (Grus americana): Reproduction, Fertility and Development, v. 29, no. 2, p. 294-306, https://doi.org/10.1071/RD15251.","productDescription":"13 p.","startPage":"294","endPage":"306","ipdsId":"IP-065075","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":333802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"588876dbe4b05ccb964baad5","contributors":{"authors":[{"text":"Brown, M.E.","contributorId":99680,"corporation":false,"usgs":true,"family":"Brown","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":660228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":660227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Jane N. 0000-0002-6131-2396 jchandler@usgs.gov","orcid":"https://orcid.org/0000-0002-6131-2396","contributorId":3512,"corporation":false,"usgs":true,"family":"Chandler","given":"Jane","email":"jchandler@usgs.gov","middleInitial":"N.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":660229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crosier, A. L.","contributorId":178636,"corporation":false,"usgs":false,"family":"Crosier","given":"A.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":660230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lynch, W.","contributorId":178637,"corporation":false,"usgs":false,"family":"Lynch","given":"W.","email":"","affiliations":[],"preferred":false,"id":660231,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wildt, D.E.","contributorId":106610,"corporation":false,"usgs":true,"family":"Wildt","given":"D.E.","affiliations":[],"preferred":false,"id":660232,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keefer, C. L.","contributorId":178639,"corporation":false,"usgs":false,"family":"Keefer","given":"C.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":660233,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Songsasen, Nucharin","contributorId":146371,"corporation":false,"usgs":false,"family":"Songsasen","given":"Nucharin","email":"","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":660234,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187379,"text":"70187379 - 2017 - Considerations in representing human individuals in social ecological models","interactions":[],"lastModifiedDate":"2017-05-02T09:41:14","indexId":"70187379","displayToPublicDate":"2014-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Considerations in representing human individuals in social ecological models","docAbstract":"In this chapter we focus on how to integrate the human individual into social-ecological systems analysis, and how to improve research on individual thought and action regarding the environment by locating it within the broader social-ecological context. We discuss three key questions as considerations for future research: (1) is human thought conceptualized as a dynamic and adaptive process, (2) is the individual placed in a multi-level context (including within-person levels, person-group interactions, and institutional and structural factors), and (3) is human thought seen as mutually constructed with the social and natural environment. Increased emphasis on the individual will be essential if we are to understand agency, innovation, and adaptation in social-ecological systems.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Understanding society and natural resources","language":"English","publisher":"Springer","doi":"10.1007/978-94-017-8959-2_7","usgsCitation":"Manfredo, M.J., Teel, T.L., Gavin, M.C., and Fulton, D.C., 2017, Considerations in representing human individuals in social ecological models, chap. of Understanding society and natural resources, p. 137-158, https://doi.org/10.1007/978-94-017-8959-2_7.","productDescription":"22 p.","startPage":"137","endPage":"158","ipdsId":"IP-050963","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":490024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-94-017-8959-2_7","text":"Publisher Index Page"},{"id":340716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-25","publicationStatus":"PW","scienceBaseUri":"59099aaee4b0fc4e449157ea","contributors":{"authors":[{"text":"Manfredo, Michael J.","contributorId":127326,"corporation":false,"usgs":false,"family":"Manfredo","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":693875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teel, Tara L.","contributorId":80169,"corporation":false,"usgs":false,"family":"Teel","given":"Tara","email":"","middleInitial":"L.","affiliations":[{"id":35701,"text":"CO State University, Fort Collins","active":true,"usgs":false}],"preferred":false,"id":693876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gavin, Michael C.","contributorId":191696,"corporation":false,"usgs":false,"family":"Gavin","given":"Michael","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":693877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693662,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70072607,"text":"ds817 - 2017 - Onshore industrial wind turbine locations for the United States","interactions":[],"lastModifiedDate":"2017-02-06T09:48:58","indexId":"ds817","displayToPublicDate":"2014-02-11T11:39:00","publicationYear":"2017","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":"817","title":" Onshore industrial wind turbine locations for the United States","docAbstract":"This dataset provides industrial-scale onshore wind turbine locations in the United States, corresponding facility information, and turbine technical specifications. The database has wind turbine records that have been collected, digitized, locationally verified, and internally quality controlled. Turbines from the Federal Aviation Administration Digital Obstacles File, through product release date July 22, 2013, were used as the primary source of turbine data points. The dataset was subsequently revised and reposted as described in the revision histories for the report. Verification of the turbine positions was done by visual interpretation using high-resolution aerial imagery in Environmental Systems Research Institute (Esri) ArcGIS Desktop. Turbines without Federal Aviation Administration Obstacles Repository System numbers were visually identified and point locations were added to the collection. We estimated a locational error of plus or minus 10 meters for turbine locations. Wind farm facility names were identified from publicly available facility datasets. Facility names were then used in a Web search of additional industry publications and press releases to attribute additional turbine information (such as manufacturer, model, and technical specifications of wind turbines). Wind farm facility location data from various wind and energy industry sources were used to search for and digitize turbines not in existing databases. Technical specifications for turbines were assigned based on the wind turbine make and model as described in literature, specifications listed in the Federal Aviation Administration Digital Obstacles File, and information on the turbine manufacturer’s Web site. Some facility and turbine information on make and model did not exist or was difficult to obtain. Thus, uncertainty may exist for certain turbine specifications. That uncertainty was rated and a confidence was recorded for both location and attribution data quality.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds817","usgsCitation":"Diffendorfer, J.E., Compton, R., Kramer, L., Ancona, Z., and Norton, D., 2017, Onshore industrial wind turbine locations for the United States (Version 1.0: Originally posted February 11, 2014; Version 1.1: May 4, 2015; Version 1.2: January 19, 2017): U.S. Geological Survey Data Series 817, Report: iii, 2 p.; Downloads Directory, https://doi.org/10.3133/ds817.","productDescription":"Report: iii, 2 p.; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalEnd":"2014-03-01","ipdsId":"IP-053290","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":282262,"type":{"id":15,"text":"Index 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jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":55137,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"Jay","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":488525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Compton, Roger","contributorId":9961,"corporation":false,"usgs":true,"family":"Compton","given":"Roger","affiliations":[],"preferred":false,"id":488523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kramer, Louisa lkramer@usgs.gov","contributorId":5579,"corporation":false,"usgs":true,"family":"Kramer","given":"Louisa","email":"lkramer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":488521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ancona, Zach","contributorId":53292,"corporation":false,"usgs":true,"family":"Ancona","given":"Zach","affiliations":[],"preferred":false,"id":488524,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Norton, Donna dnorton@usgs.gov","contributorId":5580,"corporation":false,"usgs":true,"family":"Norton","given":"Donna","email":"dnorton@usgs.gov","affiliations":[],"preferred":true,"id":488522,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191533,"text":"70191533 - 2017 - Micro-seismicity within the Coso Geothermal field, California, from 1996-2012","interactions":[],"lastModifiedDate":"2018-01-05T14:56:42","indexId":"70191533","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Micro-seismicity within the Coso Geothermal field, California, from 1996-2012","docAbstract":"We extend our previous catalog of seismicity within the Coso Geothermal field by adding over two and a half years of additional data to prior results. In total, we locate over 16 years of seismicity spanning from April 1996 to May of 2012 using a refined velocity model, apply it to all events and utilize differential travel times in relocations to improve the accuracy of event locations. The improved locations elucidate major structural features within the reservoir that we interpret to be faults that contribute to heat and fluid flow within the reservoir. Much of the relocated seismicity remains diffuse between these major structural features, suggesting that a large volume of accessible and distributed fracture porosity is maintained within the geothermal reservoir through ongoing brittle failure. We further track changes in b value and seismic moment release within the reservoir as a whole through time. We find that b values decrease significantly during 2009 and 2010, coincident with the occurrence of a greater number of moderate magnitude earthquakes (3.0 ≤ ML < 4.5). Analysis of spatial variations in seismic moment release between years reveals that localized seismicity tends to spread from regions of high moment release into regions with previously low moment release, akin to aftershock sequences. These results indicate that the Coso reservoir is comprised of a network of fractures at a variety of spatial scales that evolves dynamically over time, with progressive changes in characteristics of microseismicity and inferred fractures and faults that are only evident from a long period of seismic monitoring analyzed using self-consistent methods.
","largerWorkTitle":"Proceedings, Thirty-Eighth Workshop on Geothermal Reservoir Engineering","conferenceTitle":"Thirty-Eighth Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 11-13, 2013","conferenceLocation":"Stanford, California","language":"English","publisher":"Stanford University","usgsCitation":"Kaven, J., Hickman, S.H., and Weber, L.C., 2017, Micro-seismicity within the Coso Geothermal field, California, from 1996-2012, in Proceedings, Thirty-Eighth Workshop on Geothermal Reservoir Engineering, Stanford, California, February 11-13, 2013, 10 p.","productDescription":"10 p.","ipdsId":"IP-043946","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":350339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coso Geothermal Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.84,\n 35.95\n ],\n [\n -117.76,\n 35.95\n ],\n [\n -117.76,\n 36.1\n ],\n [\n -117.84,\n 36.1\n ],\n [\n -117.84,\n 35.95\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc5ae4b06e28e9c23da0","contributors":{"authors":[{"text":"Kaven, J. Ole 0000-0003-2625-2786 okaven@usgs.gov","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":3993,"corporation":false,"usgs":true,"family":"Kaven","given":"J. Ole","email":"okaven@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hickman, Stephen H. 0000-0003-2075-9615 hickman@usgs.gov","orcid":"https://orcid.org/0000-0003-2075-9615","contributorId":2705,"corporation":false,"usgs":true,"family":"Hickman","given":"Stephen","email":"hickman@usgs.gov","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":712665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weber, Lisa C.","contributorId":124586,"corporation":false,"usgs":true,"family":"Weber","given":"Lisa","email":"","middleInitial":"C.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":712664,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190114,"text":"70190114 - 2017 - Chemical tracer methods","interactions":[],"lastModifiedDate":"2021-04-26T17:27:03.084879","indexId":"70190114","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"Chemical tracer methods","docAbstract":"Tracers have a wide variety of uses in hydrologic studies: providing quantitative or qualitative estimates of recharge, identifying sources of recharge, providing information on velocities and travel times of water movement, assessing the importance of preferential flow paths, providing information on hydrodynamic dispersion, and providing data for calibration of water flow and solute-transport models (Walker, 1998; Cook and Herczeg, 2000; Scanlon et al., 2002b). Tracers generally are ions, isotopes, or gases that move with water and that can be detected in the atmosphere, in surface waters, and in the subsurface. Heat also is transported by water; therefore, temperatures can be used to trace water movement. This chapter focuses on the use of chemical and isotopic tracers in the subsurface to estimate recharge. Tracer use in surface-water studies to determine groundwater discharge to streams is addressed in Chapter 4; the use of temperature as a tracer is described in Chapter 8.
Following the nomenclature of Scanlon et al. (2002b), tracers are grouped into three categories: natural environmental tracers, historical tracers, and applied tracers. Natural environmental tracers are those that are transported to or created within the atmosphere under natural processes; these tracers are carried to the Earth’s surface as wet or dry atmospheric deposition. The most commonly used natural environmental tracer is chloride (Cl) (Allison and Hughes, 1978). Ocean water, through the process of evaporation, is the primary source of atmospheric Cl. Other tracers in this category include chlorine-36 (36Cl) and tritium (3H); these two isotopes are produced naturally in the Earth’s atmosphere; however, there are additional anthropogenic sources of them.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Estimating groundwater recharge","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Cambridge University Press","publisherLocation":"Cambridge, UK","doi":"10.1017/CBO9780511780745.008","usgsCitation":"Healy, R.W., 2017, Chemical tracer methods, chap. 7 of Estimating groundwater recharge, p. 136-165, https://doi.org/10.1017/CBO9780511780745.008.","productDescription":"30 p.","startPage":"136","endPage":"165","ipdsId":"IP-014174","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b76f73e4b08b1644ddfb03","contributors":{"authors":[{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":707545,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70190201,"text":"70190201 - 2017 - Use of modflow drain package for simulating inter-basin transfer in abandoned coal mines","interactions":[],"lastModifiedDate":"2017-08-23T09:44:34","indexId":"70190201","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Use of modflow drain package for simulating inter-basin transfer in abandoned coal mines","docAbstract":"Simulation of groundwater flow in abandoned mines is difficult, especially where flux to and from mines is unknown or poorly quantified, and inter-basin transfer of groundwater occurs. A 3-year study was conducted in the Elkhorn area, West Virginia to better understand groundwater-flow processes and inter-basin transfer in above drainage abandoned coal mines. The study area was specifically selected, as all mines are located above the elevation of tributary receiving streams, to allow accurate measurements of discharge from mine portals and tributaries for groundwater model calibration.\r\nAbandoned mine workings were simulated in several ways, initially as a layer of high hydraulic conductivity bounded by lower permeability rock in adjacent strata, and secondly as rows of higher hydraulic conductivity embedded within a lower hydraulic conductivity coal aquifer matrix. Regardless of the hydraulic conductivity assigned to mine workings, neither approach to simulate mine workings could accurately reproduce the inter-basin transfer of groundwater from adjacent watersheds. \r\nTo resolve the problem, a third approach was developed. The MODFLOW DRAIN package was used to simulate seepage into and through mine workings discharging water under unconfined conditions to Elkhorn Creek, North Fork, and tributaries of the Bluestone River. Drain nodes were embedded in a matrix of uniform hydraulic conductivity cells that represented the coal mine aquifer. Drain heads were empirically defined from well observations, and elevations were based on structure contours for the Pocahontas No. 3 mine workings. Use of the DRAIN package to simulate mine workings as an internal boundary condition resolved the inter-basin transfer problem, and effectively simulated a shift from a topographic- dominated to a dip-dominated flow system, by dewatering overlying unmined strata and shifting the groundwater drainage divide up dip within the Pocahontas No. 3 coal seam several kilometers into the adjacent Bluestone River Watershed. Model simulations prior to use of the DRAIN package for simulating mine workings produced estimated flows of 0.32 to 0.34 m3/s in each of the similar sized Elkhorn Creek and North Fork Watersheds, but failed to estimate inter-basin transfer of groundwater from the adjacent Bluestone River Watershed. The simulation of mine entries and discharge using the MODFLOW DRAIN package produced estimated flows of 0.46 and 0.26 m3/s for the Elkhorn Creek and North Fork watersheds respectively, which matched well measured flows for the respective watersheds of 0.47 and 0.26 m3/s.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings America Society of Mining and Reclamation","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Sustainable Reclamation: 2012 National Meeting of the American Society of Mining and Reclamation","conferenceDate":"June 8-15, 2012","conferenceLocation":"Tupelo, MS","language":"English","publisher":"ASMR","doi":"10.21000/JASMR12010304","usgsCitation":"Kozar, M.D., and McCoy, K.J., 2017, Use of modflow drain package for simulating inter-basin transfer in abandoned coal mines, in Proceedings America Society of Mining and Reclamation, Tupelo, MS, June 8-15, 2012, p. 304-320, 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PSC"},"noUsgsAuthors":false,"publicationDate":"2012-06-30","publicationStatus":"PW","scienceBaseUri":"599e9447e4b04935557fe9c1","contributors":{"authors":[{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":707946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Kurt J. 0000-0002-9756-8238 kjmccoy@usgs.gov","orcid":"https://orcid.org/0000-0002-9756-8238","contributorId":1391,"corporation":false,"usgs":true,"family":"McCoy","given":"Kurt","email":"kjmccoy@usgs.gov","middleInitial":"J.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":707945,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190183,"text":"70190183 - 2017 - Hydrogeology, groundwater flow, and groundwater quality of an abandoned underground coal-mine aquifer, Elkhorn Area, West Virginia","interactions":[],"lastModifiedDate":"2017-08-23T10:18:01","indexId":"70190183","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Hydrogeology, groundwater flow, and groundwater quality of an abandoned underground coal-mine aquifer, Elkhorn Area, West Virginia","docAbstract":"The Pocahontas No. 3 coal seam in southern West Virginia has been extensively mined by underground methods since the 1880’s. An extensive network of abandoned mine entries in the Pocahontas No. 3 has since filled with good-quality water, which is pumped from wells or springs discharging from mine portals (adits), and used as a source of water for public supplies. This report presents results of a three-year investigation of the geology, hydrology, geochemistry, and groundwater flow processes within abandoned underground coal mines used as a source of water for public supply in the Elkhorn area, McDowell County, West Virginia. This study focused on large (> 500 gallon per minute) discharges from the abandoned mines used as public supplies near Elkhorn, West Virginia. Median recharge calculated from base-flow recession of streamflow at Johns Knob Branch and 12 other streamflow gaging stations in McDowell County was 9.1 inches per year. Using drainage area versus mean streamflow relationships from mined and unmined watersheds in McDowell County, the subsurface area along dip of the Pocahontas No. 3 coal-mine aquifer contributing flow to the Turkey Gap mine discharge was determined to be 7.62 square miles (mi2), almost 10 times larger than the 0.81 mi2 surface watershed. Results of this \r\ninvestigation indicate that groundwater flows down dip beneath surface drainage divides from areas up to six miles east in the adjacent Bluestone River watershed. A conceptual model was developed that consisted of a \r\nstacked sequence of perched aquifers, controlled by stress-relief and subsidence fractures, overlying a highly permeable abandoned underground coal-mine aquifer, capable of substantial interbasin transfer of water. Groundwater-flow directions are controlled by the dip of the Pocahontas No. 3 coal seam, the geometry of abandoned mine workings, and location of unmined barriers within that seam, rather than surface topography. Seven boreholes were drilled to intersect abandoned mine workings in the Pocahontas No. 3 coal seam and underlying strata in various structural settings of the Turkey Gap and adjacent down-dip mines. Geophysical logging and aquifer testing were conducted on the boreholes to locate the coal- mine aquifers, characterize fracture geometry, and define permeable zones within strata overlying and underlying the Pocahontas No. 3 coal-mine aquifer. Water levels were measured monthly in the wells and showed a relatively static phreatic zone within subsided strata a few feet above the top of or within the Pocahontas No. 3 coal-mine aquifer (PC3MA). A groundwater-flow model was developed to verify and refine the conceptual understanding of groundwater flow and to develop groundwater budgets for the study area. The model consisted of four layers to represent overburden strata, the Pocahontas No. 3 coal-mine aquifer, underlying fractured rock, and fractured rock below regional drainage. Simulation of flow in the flooded abandoned mine entries using highly conductive layers or zones within the model, was unable to realistically simulate interbasin transfer of water. Therefore it was necessary to represent the coal-mine aquifer as an internal boundary condition rather than a contrast in aquifer properties. By \r\nrepresenting the coal-mine aquifer with a series of drain nodes and optimizing input parameters with parameter estimation software, model \r\nerrors were reduced dramatically and discharges for Elkhorn Creek, Johns Knob Branch, and other tributaries were more accurately simulated. Flow in the Elkhorn Creek and Johns Knob Branch watersheds is dependent on interbasin transfer of water, primarily from up dip areas of abandoned mine workings in the Pocahontas No. 3 coal-mine aquifer within the Bluestone River watershed to the east. For the 38th, 70th, and 87th percentile flow duration of streams in the region, mean measured groundwater discharge was estimated to be 1.30, 0.47, and 0.39 cubic feet per square mile (ft3/s/mi2","language":"English","publisher":"West Virginia Geological and Economic Survey","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection, the West Virginia Department of Health and Human Resources, and the West Virginia Geological and Economic Survey","usgsCitation":"Kozar, M.D., McCoy, K.J., Britton, J.Q., and Blake, B., 2017, Hydrogeology, groundwater flow, and groundwater quality of an abandoned underground coal-mine aquifer, Elkhorn Area, West Virginia, x, 103 p.","productDescription":"x, 103 p.","ipdsId":"IP-037003","costCenters":[{"id":642,"text":"West Virginia Water Science 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Aerial survey data, collected during range-wide breeding population surveys for Eastern Prairie Population (EPP) Canada Geese (Branta canadensis interior), 1987–2008, were evaluated to assess factors influencing their nesting distribution. Specifically, associations between nesting Lesser Snow Geese (Chen caerulescens caerulescens) and EPP Canada Geese were quantified; and changes in the spatial distribution of EPP Canada Geese were identified. Mixed-effects Poisson regression models of EPP Canada Goose nest counts were evaluated within a cross-validation framework. The total count of EPP Canada Goose nests varied moderately among years between 1987 and 2008 with no long-term trend; however, the total count of nesting Lesser Snow Geese generally increased. Three models containing factors related to previous EPP Canada Goose nest density (representing recruitment), distance to Hudson Bay (representing brood-habitat), nesting habitat type, and Lesser Snow Goose nest density (inter-specific associations) were the most accurate, improving prediction accuracy by 45% when compared to intercept-only models. EPP Canada Goose nest density varied by habitat type, was negatively associated with distance to coastal brood-rearing areas, and suggested density-dependent intra-specific effects on recruitment. However, a non-linear relationship between Lesser Snow and EPP Canada Goose nest density suggests that as nesting Lesser Snow Geese increase, EPP Canada Geese locally decline and subsequently the spatial distribution of EPP Canada Geese on western Hudson Bay has changed.
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In the next phase of research, \nadditional field investigations will be conducted in key locations of \ninterest and additional analysis will be undertaken. Simultaneously, \nthe MOST tsunami generation and propagation model used by NOAA will \nfirst be enhanced to include landslide-based initiation mechanisms and \nthen will be used to investigate the impact of the tsunamigenic sources \nidentified and characterized by the USGS. 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2016 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","interactions":[{"subject":{"id":70176667,"text":"sim3366 - 2016 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","indexId":"sim3366","publicationYear":"2016","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas"},"predicate":"SUPERSEDED_BY","object":{"id":70250060,"text":"sim3510 - 2023 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","indexId":"sim3510","publicationYear":"2023","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas"},"id":1}],"supersededBy":{"id":70250060,"text":"sim3510 - 2023 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","indexId":"sim3510","publicationYear":"2023","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas"},"lastModifiedDate":"2023-11-17T18:48:11.349185","indexId":"sim3366","displayToPublicDate":"2023-11-17T00:00:00","publicationYear":"2016","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":"3366","title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","docAbstract":"During 2014–16, the U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, documented the geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas. The Edwards and Trinity aquifers are major sources of water for agriculture, industry, and urban and rural communities in south-central Texas. Both the Edwards and Trinity are classified as major aquifers by the State of Texas.
The purpose of this report is to present the geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Tex. The report includes a detailed 1:24,000-scale hydrostratigraphic map, names, and descriptions of the geology and hydrostratigraphic units (HSUs) in the study area.
The scope of the report is focused on geologic framework and hydrostratigraphy of the outcrops and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Tex. In addition, parts of the adjacent upper confining unit to the Edwards aquifer are included.
The study area, approximately 866 square miles, is within the outcrops of the Edwards and Trinity aquifers and overlying confining units (Washita, Eagle Ford, Austin, and Taylor Groups) in northern Bexar and Comal Counties, Tex. The rocks within the study area are sedimentary and range in age from Early to Late Cretaceous. The Miocene-age Balcones fault zone is the primary structural feature within the study area. The fault zone is an extensional system of faults that generally trends southwest to northeast in south-central Texas. The faults have normal throw, are en echelon, and are mostly downthrown to the southeast.
The Early Cretaceous Edwards Group rocks were deposited in an open marine to supratidal flats environment during two marine transgressions. The Edwards Group is composed of the Kainer and Person Formations. Following tectonic uplift, subaerial exposure, and erosion near the end of Early Cretaceous time, the area of present-day south-central Texas was again submerged during the Late Cretaceous by a marine transgression resulting in deposition of the Georgetown Formation of the Washita Group.
The Early Cretaceous Edwards Group, which overlies the Trinity Group, is composed of mudstone to boundstone, dolomitic limestone, argillaceous limestone, evaporite, shale, and chert. The Kainer Formation is subdivided into (bottom to top) the basal nodular, dolomitic, Kirschberg Evaporite, and grainstone members. The Person Formation is subdivided into (bottom to top) the regional dense, leached and collapsed (undivided), and cyclic and marine (undivided) members.
Hydrostratigraphically the rocks exposed in the study area represent a section of the upper confining unit to the Edwards aquifer, the Edwards aquifer, the upper zone of the Trinity aquifer, and the middle zone of the Trinity aquifer. The Pecan Gap Formation (Taylor Group), Austin Group, Eagle Ford Group, Buda Limestone, and Del Rio Clay are generally considered to be the upper confining unit to the Edwards aquifer.
The Edwards aquifer was subdivided into HSUs I to VIII. The Georgetown Formation of the Washita Group contains HSU I. The Person Formation of the Edwards Group contains HSUs II (cyclic and marine members [Kpcm], undivided), III (leached and collapsed members [Kplc,] undivided), and IV (regional dense member [Kprd]), and the Kainer Formation of the Edwards Group contains HSUs V (grainstone member [Kkg]), VI (Kirschberg Evaporite Member [Kkke]), VII (dolomitic member [Kkd]), and VIII (basal nodular member [Kkbn]).
The Trinity aquifer is separated into upper, middle, and lower aquifer units (hereinafter referred to as “zones”). The upper zone of the Trinity aquifer is in the upper member of the Glen Rose Limestone. The middle zone of the Trinity aquifer is formed in the lower member of the Glen Rose Limestone, Hensell Sand, and Cow Creek Limestone. The regionally extensive Hammett Shale forms a confining unit between the middle and lower zones of the Trinity aquifer. The lower zone of the Trinity aquifer consists of the Sligo and Hosston Formations, which do not crop out in the study area.
The upper zone of the Trinity aquifer is subdivided into five informal HSUs (top to bottom): cavernous, Camp Bullis, upper evaporite, fossiliferous, and lower evaporite. The middle zone of the Trinity aquifer is composed of the (top to bottom) Bulverde, Little Blanco, Twin Sisters, Doeppenschmidt, Rust, Honey Creek, Hensell, and Cow Creek HSUs. The underlying Hammett HSU is a regional confining unit between the middle and lower zones of the Trinity aquifer. The lower zone of the Trinity aquifer is not exposed in the study area.
Groundwater recharge and flow paths in the study area are influenced not only by the hydrostratigraphic characteristics of the individual HSUs but also by faults and fractures and geologic structure. Faulting associated with the Balcones fault zone (1) might affect groundwater flow paths by forming a barrier to flow that results in water moving parallel to the fault plane, (2) might affect groundwater flow paths by increasing flow across the fault because of fracturing and juxtaposing porous and permeable units, or (3) might have no effect on the groundwater flow paths.
The hydrologic connection between the Edwards and Trinity aquifers and the various HSUs is complex. The complexity of the aquifer system is a combination of the original depositional history, bioturbation, primary and secondary porosity, diagenesis, and fracturing of the area from faulting. All of these factors have resulted in development of modified porosity, permeability, and transmissivity within and between the aquifers. Faulting produced highly fractured areas that have allowed for rapid infiltration of water and subsequently formed solutionally enhanced fractures, bedding planes, channels, and caves that are highly permeable and transmissive. The juxtaposition resulting from faulting has resulted in areas of interconnectedness between the Edwards and Trinity aquifers and the various HSUs that form the aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3366","collaboration":"Prepared in cooperation with the Edwards Aquifer Authority","usgsCitation":"Clark, A.K., Golab, J.A., and Morris, R.R., 2016, Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas: U.S. Geological Survey Scientific Investigations Map 3366, 1 sheet, scale 1:24,000, pamphlet, https://doi.org/10.3133/sim3366.","productDescription":"Pamphlet: vi, 20 p.; Sheet: 48.00 x 36.00 inches; Appendix 1","numberOfPages":"29","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-073371","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":331194,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3366/sim3366_pamphlet.pdf","text":"Pamphlet","size":"805 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3366 Pamphlet"},{"id":331192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3366/coverthb1.jpg"},{"id":331195,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3366/sim3366_BexarComalGIS.zip","text":"Appendix 1","size":"19.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3366 Appendix 1"},{"id":331193,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3366/sim3366.pdf","text":"Map","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3366"}],"country":"United States","state":"Texas","county":"Comal County, Bexar County","otherGeospatial":"Edwards Aquifer, Trinity Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.30017089843749,\n 30.0405664305846\n ],\n [\n -98.65447998046875,\n 29.75364773335698\n ],\n [\n -98.78494262695312,\n 29.72025928058346\n ],\n [\n -98.80691528320311,\n 29.699982298744377\n ],\n [\n -98.80691528320311,\n 29.489815619374962\n ],\n [\n -98.60916137695312,\n 29.48383858387499\n ],\n [\n -98.316650390625,\n 29.597341920567366\n ],\n [\n -98.09280395507812,\n 29.685666670118724\n ],\n [\n -97.99942016601562,\n 29.757224408272663\n ],\n [\n -98.0364990234375,\n 29.852555290064018\n ],\n [\n -98.30017089843749,\n 30.0405664305846\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
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Digital geospatial datasets of the extents and top elevations of the regional hydrogeologic units of the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to northeastern North Carolina were developed to provide an updated hydrogeologic framework to support analysis of groundwater resources. The 19 regional hydrogeologic units were delineated by elevation grids and extent polygons for 20 layers: the land and bathymetric surface at the top of the unconfined surficial aquifer, the upper surfaces of 9 confined aquifers and 9 confining units, and the bedrock surface that defines the base of all Northern Atlantic Coastal Plain sediments. The delineation of the regional hydrogeologic units relied on the interpretive work from source reports for New York, New Jersey, Delaware and Maryland, Virginia, and North Carolina rather than from re-analysis of fundamental hydrogeologic data. This model of regional hydrogeologic unit geometries represents interpolation, extrapolation, and generalization of the earlier interpretive work. Regional units were constructed from available digital data layers from the source studies in order to extend units consistently across political boundaries and approximate units in offshore areas.
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These changes occur over distances of tens of meters (m) implying rapid removal kinetics of the chromophoric DOM that imparts color to groundwater. A one-compartment input-output model was used to derive a differential equation describing the removal of DOM from the dissolved phase due to the combined effects of biodegradation and sorption. The general solution to the equation was parameterized using a 2-year record of dissolved organic carbon (DOC) concentration changes in groundwater at a long-term observation well. Estimated rates of DOC loss were rapid and ranged from 0.093 to 0.21 micromoles per liter per day (μM d−1), and rate constants for DOC removal ranged from 0.0021 to 0.011 per day (d−1). Applying these removal rate constants to an advective-dispersion model illustrates substantial depletion of DOC over flow-path distances of 200 m or less and in timeframes of 2 years or less. These results explain the low to moderate DOC concentrations (20–75 μM; 0.26–1 mg L−1) and ultraviolet absorption coefficient values (a254 < 5 m−1) observed in groundwater produced from 59 wells tapping eight different aquifer systems of the United States. The nearly uniform optical clarity of groundwater, therefore, results from similarly rapid DOM-removal kinetics exhibited by geologically and hydrologically dissimilar aquifers.
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