The U.S. Geological Survey, in cooperation with the Puerto Rico Electric Power Authority, completed hydrologic and hydraulic analyses to assess the potential hazard to human life and property associated with the hypothetical failure of the Lago El Guineo Dam. The Lago El Guineo Dam is within the headwaters of the Río Grande de Manatí and impounds a drainage area of about 4.25 square kilometers.
The hydrologic assessment was designed to determine the outflow hydrographs and peak discharges for Lago El Guineo and other subbasins in the Río Grande de Manatí hydrographic basin for three extreme rainfall events: (1) a 6-hour probable maximum precipitation event, (2) a 24-hour probable maximum precipitation event, and (3) a 24-hour, 100-year recurrence rainfall event. The hydraulic study simulated a dam failure of Lago El Guineo Dam using flood hydrographs generated from the hydrologic study. The simulated dam failure generated a hydrograph that was routed downstream from Lago El Guineo Dam through the lower reaches of the Río Toro Negro and the Río Grande de Manatí to determine water-surface profiles developed from the event-based hydrologic scenarios and “sunny day” conditions. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC–HMS) and Hydrologic Engineering Center’s River Analysis System (HEC–RAS) computer programs, developed by the U.S. Army Corps of Engineers, were used for the hydrologic and hydraulic modeling, respectively. The flow routing in the hydraulic analyses was completed using the unsteady flow module available in the HEC–RAS model.
Above the Lago El Guineo Dam, the simulated inflow peak discharges from HEC–HMS resulted in about 550 and 414 cubic meters per second for the 6- and 24-hour probable maximum precipitation events, respectively. The 24-hour, 100-year recurrence storm simulation resulted in a peak discharge of about 216 cubic meters per second. For the hydrologic analysis, no dam failure conditions are considered within the model. The results of the hydrologic simulations indicated that for all hydrologic conditions scenarios, the Lago El Guineo Dam would not experience overtopping. For the dam breach hydraulic analysis, failure by piping was the selected hypothetical failure mode for the Lago El Guineo Dam.
Results from the simulated dam failure of the Lago El Guineo Dam using the HEC–RAS model for the 6- and 24-hour probable maximum precipitation events indicated peak discharges below the dam of 1,342.43 and 1,434.69 cubic meters per second, respectively. Dam failure during the 24-hour, 100-year recurrence rainfall event resulted in a peak discharge directly downstream from Lago El Guineo Dam of 1,183.12 cubic meters per second. Dam failure during sunny-day conditions (no precipitation) produced a peak discharge at Lago El Guineo Dam of 1,015.31 cubic meters per second assuming the initial water-surface elevation was at the morning-glory spillway invert elevation.
The results of the hydraulic analysis indicate that the flood would extend to many inhabited areas along the stream banks from the Lago El Guineo Dam to the mouth of the Río Grande as a result of the simulated failure of the Lago El Guineo Dam. Low-lying regions in the vicinity of Ciales, Manatí, and Barceloneta, Puerto Rico, are among the regions that would be most affected by failure of the Lago El Guineo Dam. Effects of the flood control (levee) structure constructed in 2000 to provide protection to the low-lying populated areas of Barceloneta, Puerto Rico, were considered in the hydraulic analysis of dam failure. The results indicate that overtopping can be expected in the aforementioned levee during 6- and 24-hour probable maximum precipitation events. The levee was not overtopped during dam failure scenarios under the 24-hour, 100-year recurrence rainfall event or sunny-day conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165070","collaboration":"Prepared in cooperation with the Puerto Rico Electric Power Authority","usgsCitation":"Gómez-Fragoso, Julieta, and Torres-Sierra, Heriberto, 2016, Dam failure analysis for the Lago El Guineo Dam, Orocovis, Puerto Rico: U.S. Geological Survey Scientific Investigations Report 2016–5070, 49 p., 4 pls., https://dx.doi.org/10.3133/sir20165070.","productDescription":"Report: vi, 49 p.; 4 Plates: 29 x 35 inches; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062802","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":438575,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72V2D7Q","text":"USGS data release","linkHelpText":"Dam Failure Analysis for the Lago de Guineo dam, Orocovis, Puerto Rico"},{"id":326029,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070_plate02.pdf","text":"Plate 2 - Flood-Inundation Map of the Predicted 24-Hour Probable Maximum Precipitation Event, Northern Part of Rio Grande de Manati Basin","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326026,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5070/coverthb.jpg"},{"id":326028,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070_plate01.pdf","text":"Plate 1 - Flood-Inundation Map of the Predicted 6-Hour Probable Maximum Precipitation Event, Northern Part of Rio Grande de Manati Basin","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326027,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326030,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070_plate03.pdf","text":"Plate 3 - Flood-Inundation Map of the Predicted 100-Year Recurrence, 24-Hour Precipitation Event, Northern Part of Rio Grande de Manati Basin","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326031,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070_plate04.pdf","text":"Plate 4 - Flood-Inundation Map During Sunny Day Conditions, Northern Part of Rio Grande de Manati Basin ","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326032,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F72V2D7Q","text":"USGS data release - Spatial Data for Dam failure analysis for the Lago El Guineo Dam, Orocovis, Puerto Rico","description":"SIR 2016-5070"},{"id":326195,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F72J690R","text":"USGS data release - HEC-HMS and HEC-RAS models used to analyze dam failure for the Lago El Guineo Dam, Orocovis, Puerto Rico","description":"SIR 2016-5070"}],"country":"Puerto Rico","city":"Orocovis","otherGeospatial":"Lago El Guineo Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.583333,\n 18.49\n ],\n [\n -66.583333,\n 18.291667\n ],\n [\n -66.394444,\n 18.291667\n ],\n [\n -66.394444,\n 18.49\n ],\n [\n -66.583333,\n 18.49\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
813-498-5000
http://pr.water.usgs.gov/
Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most post-wildfire debris flows are generated from water runoff. The majority of existing debris-flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's $n$) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR018176","usgsCitation":"Rengers, F.K., McGuire, L., Kean, J.W., Staley, D.M., and Hobley, D., 2016, Model simulations of flood and debris flow timing in steep catchments after wildfire: Water Resources Research, v. 52, no. 8, p. 6041-6061, https://doi.org/10.1002/2015WR018176.","productDescription":"21 p.","startPage":"6041","endPage":"6061","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073271","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470675,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018176","text":"Publisher Index Page"},{"id":326243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-11","publicationStatus":"PW","scienceBaseUri":"57a99f25e4b05e859bdf4859","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":620765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke lmcguire@usgs.gov","contributorId":167018,"corporation":false,"usgs":true,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":620766,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":620767,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":620768,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hobley, D.E.J","contributorId":167019,"corporation":false,"usgs":false,"family":"Hobley","given":"D.E.J","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":620769,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188567,"text":"70188567 - 2016 - Modeling streamflow from coupled airborne laser scanning and acoustic Doppler current profiler data","interactions":[],"lastModifiedDate":"2017-08-03T08:41:16","indexId":"70188567","displayToPublicDate":"2016-08-08T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5426,"text":"Hydrology Research","active":true,"publicationSubtype":{"id":10}},"title":"Modeling streamflow from coupled airborne laser scanning and acoustic Doppler current profiler data","docAbstract":"The rating curve enables the translation of water depth into stream discharge through a reference cross-section. This study investigates coupling national scale airborne laser scanning (ALS) and acoustic Doppler current profiler (ADCP) bathymetric survey data for generating stream rating curves. A digital terrain model was defined from these data and applied in a physically based 1-D hydraulic model to generate rating curves for a regularly monitored location in northern Sweden. Analysis of the ALS data showed that overestimation of the streambank elevation could be adjusted with a root mean square error (RMSE) block adjustment using a higher accuracy manual topographic survey. The results of our study demonstrate that the rating curve generated from the vertically corrected ALS data combined with ADCP data had lower errors (RMSE = 0.79 m3/s) than the empirical rating curve (RMSE = 1.13 m3/s) when compared to streamflow measurements. We consider these findings encouraging as hydrometric agencies can potentially leverage national-scale ALS and ADCP instrumentation to reduce the cost and effort required for maintaining and establishing rating curves at gauging station sites similar to the Röån River.
","language":"English","publisher":"IWA","doi":"10.2166/nh.2016.257","usgsCitation":"Norris, L., Kean, J.W., and Lyon, S., 2016, Modeling streamflow from coupled airborne laser scanning and acoustic Doppler current profiler data: Hydrology Research, v. 48, no. 4, p. 981-996, https://doi.org/10.2166/nh.2016.257.","productDescription":"16 p.","startPage":"981","endPage":"996","ipdsId":"IP-075690","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470677,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-135572","text":"External Repository"},{"id":342555,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-08","publicationStatus":"PW","scienceBaseUri":"59439c94e4b062508e31a9b8","contributors":{"authors":[{"text":"Norris, Lam","contributorId":192981,"corporation":false,"usgs":false,"family":"Norris","given":"Lam","email":"","affiliations":[],"preferred":false,"id":698369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyon, Steve","contributorId":192971,"corporation":false,"usgs":false,"family":"Lyon","given":"Steve","affiliations":[],"preferred":false,"id":698371,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175387,"text":"70175387 - 2016 - Inter-annual variability of area-scaled gaseous carbon emissions from wetland soils in the Liaohe Delta, China","interactions":[],"lastModifiedDate":"2018-03-21T13:30:05","indexId":"70175387","displayToPublicDate":"2016-08-08T00:00:00","publicationYear":"2016","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":"Inter-annual variability of area-scaled gaseous carbon emissions from wetland soils in the Liaohe Delta, China","docAbstract":"Global management of wetlands to suppress greenhouse gas (GHG) emissions, facilitate carbon (C) sequestration, and reduce atmospheric CO2 concentrations while simultaneously promoting agricultural gains is paramount. However, studies that relate variability in CO2 and CH4 emissions at large spatial scales are limited. We investigated three-year emissions of soil CO2 and CH4 from the primary wetland types of the Liaohe Delta, China, by focusing on a total wetland area of 3287 km2. One percent is Suaeda salsa, 24% is Phragmites australis, and 75% is rice. While S. salsa wetlands are under somewhat natural tidal influence, P. australis and rice are managed hydrologically for paper and food, respectively. Total C emissions from CO2 and CH4 from these wetland soils were 2.9 Tg C/year, ranging from 2.5 to 3.3 Tg C/year depending on the year assessed. Primary emissions were from CO2 (~98%). Photosynthetic uptake of CO2 would mitigate most of the soil CO2 emissions, but CH4 emissions would persist. Overall, CH4 fluxes were high when soil temperatures were >18°C and pore water salinity <18 PSU. CH4 emissions from rice habitat alone in the Liaohe Delta represent 0.2% of CH4 carbon emissions globally from rice. With such a large area and interannual sensitivity in soil GHG fluxes, management practices in the Delta and similar wetlands around the world have the potential not only to influence local C budgeting, but also to influence global biogeochemical cycling.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0160612","usgsCitation":"Ye, S., Krauss, K.W., Brix, H., Wei, M., Olsson, L., Yu, X., Ma, Y., Wang, J., Yuan, H., Zhao, G., Ding, X., and Moss, R., 2016, Inter-annual variability of area-scaled gaseous carbon emissions from wetland soils in the Liaohe Delta, China: PLoS ONE, v. 11, no. 8, Article e0160612; 20 p., https://doi.org/10.1371/journal.pone.0160612.","productDescription":"Article e0160612; 20 p.","ipdsId":"IP-072645","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0160612","text":"Publisher Index Page"},{"id":338190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Liaohe Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 121.17,\n 40.33\n ],\n [\n 122.5,\n 40.33\n ],\n [\n 122.5,\n 41.33\n ],\n [\n 121.17,\n 41.33\n ],\n [\n 121.17,\n 40.33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-08","publicationStatus":"PW","scienceBaseUri":"58d4df03e4b05ec79911d1a6","contributors":{"authors":[{"text":"Ye, Siyuan","contributorId":146732,"corporation":false,"usgs":false,"family":"Ye","given":"Siyuan","email":"","affiliations":[{"id":16739,"text":"Qingdao Institute of Marine Geology, Shandong Province, China","active":true,"usgs":false}],"preferred":false,"id":645010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken W. 0000-0003-2195-0729 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China","active":true,"usgs":false}],"preferred":false,"id":645015,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wang, Jin","contributorId":189743,"corporation":false,"usgs":false,"family":"Wang","given":"Jin","email":"","affiliations":[],"preferred":false,"id":645016,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yuan, Hongming","contributorId":173534,"corporation":false,"usgs":false,"family":"Yuan","given":"Hongming","email":"","affiliations":[{"id":27244,"text":"Qingdao Institute of Marine Geology, China","active":true,"usgs":false}],"preferred":false,"id":645017,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhao, Guangming","contributorId":173535,"corporation":false,"usgs":false,"family":"Zhao","given":"Guangming","email":"","affiliations":[{"id":27244,"text":"Qingdao Institute of Marine Geology, China","active":true,"usgs":false}],"preferred":false,"id":645018,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ding, Xigui","contributorId":173536,"corporation":false,"usgs":false,"family":"Ding","given":"Xigui","email":"","affiliations":[{"id":27244,"text":"Qingdao Institute of Marine Geology, China","active":true,"usgs":false}],"preferred":false,"id":645019,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moss, Rebecca 0000-0002-7599-9758 mossr@usgs.gov","orcid":"https://orcid.org/0000-0002-7599-9758","contributorId":169722,"corporation":false,"usgs":true,"family":"Moss","given":"Rebecca","email":"mossr@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":645020,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70175734,"text":"70175734 - 2016 - Analysis of hydrologic and geochemical time-series data at James Cave, Virginia: Implications for epikarst influence on recharge in Appalachian karst aquifers","interactions":[],"lastModifiedDate":"2016-08-31T11:05:08","indexId":"70175734","displayToPublicDate":"2016-08-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5198,"text":"Geological Society of America Special Papers ","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of hydrologic and geochemical time-series data at James Cave, Virginia: Implications for epikarst influence on recharge in Appalachian karst aquifers","docAbstract":"The epikarst, which consists of highly weathered rock in the upper vadose zone of exposed karst systems, plays a critical role in determining the hydrologic and geochemical characteristics of recharge to an underlying karst aquifer. This study utilized time series (2007–2014) of hydrologic and geochemical data of drip water collected within James Cave, Virginia, to examine the influence of epikarst on the quantity and quality of recharge in a mature, doline-dominated karst terrain. Results show a strong seasonality of both hydrology and geochemistry of recharge, which has implications for management of karst aquifers in temperate climatic zones. First, recharge (discharge from the epikarst to the underlying aquifer) reaches a maximum between late winter and early spring, with the onset of the recharge season ranging from as early as December to as late as March during the study period. The timing and duration of the recharge season were found to be a function of precipitation in excess of evapotranspiration on a seasonal time scale. Secondly, seasonally variable residence times for water in the epikarst influence rock-water interaction and, hence, the geochemical characteristics of recharge. Overall, results highlight the strong and complex influence that the epikarst has on karst recharge, which requires long-term and high-resolution data sets to accurately understand and quantify.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2015.2516(15)","usgsCitation":"Eagle, S.D., Orndorff, W., Schwartz, B.F., Doctor, D.H., Gerst, J.D., and Schreiber, M.E., 2016, Analysis of hydrologic and geochemical time-series data at James Cave, Virginia: Implications for epikarst influence on recharge in Appalachian karst aquifers: Geological Society of America Special Papers , v. 516, p. 181-196, https://doi.org/10.1130/2015.2516(15).","productDescription":"16 p.","startPage":"181","endPage":"196","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061917","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":328105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":326851,"type":{"id":15,"text":"Index Page"},"url":"https://specialpapers.gsapubs.org/content/516/181"}],"country":"United States","state":"Virginia","otherGeospatial":"James Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.87654113769531,\n 37.11707372086296\n ],\n [\n -80.67260742187499,\n 37.2133783531779\n ],\n [\n -80.61698913574219,\n 37.228141500433615\n ],\n [\n -80.59776306152344,\n 37.18821967018367\n ],\n [\n -80.58609008789062,\n 37.18110808791507\n ],\n [\n -80.56755065917969,\n 37.19533058280065\n ],\n [\n -80.52291870117188,\n 37.209003532428646\n ],\n [\n -80.51673889160155,\n 37.19423663983283\n ],\n [\n -80.55450439453125,\n 37.1893137003281\n ],\n [\n -80.56480407714844,\n 37.17563718436526\n ],\n [\n -80.53047180175781,\n 37.14937133266766\n ],\n [\n -80.50575256347656,\n 37.073258333985585\n ],\n [\n -80.72067260742188,\n 36.95318415967938\n ],\n [\n -80.87654113769531,\n 37.11707372086296\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"516","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7ffaee4b0f2f0cebfc21c","contributors":{"authors":[{"text":"Eagle, Sarah D.","contributorId":150746,"corporation":false,"usgs":false,"family":"Eagle","given":"Sarah","email":"","middleInitial":"D.","affiliations":[{"id":18089,"text":"Virginia Tech, Dept. of Geosciences","active":true,"usgs":false}],"preferred":false,"id":646235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, William","contributorId":150745,"corporation":false,"usgs":false,"family":"Orndorff","given":"William","email":"","affiliations":[{"id":18088,"text":"Virginia Dept. of Conservation and Recreation","active":true,"usgs":false}],"preferred":false,"id":646236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwartz, Benjamin F.","contributorId":150744,"corporation":false,"usgs":false,"family":"Schwartz","given":"Benjamin","email":"","middleInitial":"F.","affiliations":[{"id":18087,"text":"Texas State University, San Marcos","active":true,"usgs":false}],"preferred":false,"id":646237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":646234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gerst, Jonathan D.","contributorId":150747,"corporation":false,"usgs":false,"family":"Gerst","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[{"id":18089,"text":"Virginia Tech, Dept. of Geosciences","active":true,"usgs":false}],"preferred":false,"id":646238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schreiber, Madeline E.","contributorId":138959,"corporation":false,"usgs":false,"family":"Schreiber","given":"Madeline","email":"","middleInitial":"E.","affiliations":[{"id":12594,"text":"Department of Geosciences, Virginia Tech, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":646239,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175476,"text":"70175476 - 2016 - Reconstructions of Columbia River streamflow from tree-ring chronologies in the Pacific Northwest, USA","interactions":[],"lastModifiedDate":"2018-04-24T13:42:14","indexId":"70175476","displayToPublicDate":"2016-08-04T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2126,"text":"JAWRA","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructions of Columbia River streamflow from tree-ring chronologies in the Pacific Northwest, USA","docAbstract":"We developed Columbia River streamflow reconstructions using a network of existing, new, and updated tree-ring records sensitive to the main climatic factors governing discharge. Reconstruction quality is enhanced by incorporating tree-ring chronologies where high snowpack limits growth, which better represent the contribution of cool-season precipitation to flow than chronologies from trees positively sensitive to hydroclimate alone. The best performing reconstruction (back to 1609 CE) explains 59% of the historical variability and the longest reconstruction (back to 1502 CE) explains 52% of the variability. Droughts similar to the high-intensity, long-duration low flows observed during the 1920s and 1940s are rare, but occurred in the early 1500s and 1630s-1640s. The lowest Columbia flow events appear to be reflected in chronologies both positively and negatively related to streamflow, implying low snowpack and possibly low warm-season precipitation. High flows of magnitudes observed in the instrumental record appear to have been relatively common, and high flows from the 1680s to 1740s exceeded the magnitude and duration of observed wet periods in the late-19th and 20th Century. Comparisons between the Columbia River reconstructions and future projections of streamflow derived from global climate and hydrologic models show the potential for increased hydrologic variability, which could present challenges for managing water in the face of competing demands
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12442","usgsCitation":"Littell, J.S., Pederson, G.T., Gray, S., Tjoelker, M., Hamlet, A.F., and Woodhouse, C.A., 2016, Reconstructions of Columbia River streamflow from tree-ring chronologies in the Pacific Northwest, USA: JAWRA, v. 52, no. 5, p. 1121-1141, https://doi.org/10.1111/1752-1688.12442.","productDescription":"21 p.","startPage":"1121","endPage":"1141","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063792","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":470681,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/1752-1688.12442","text":"External Repository"},{"id":326463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Pacific Northwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.25634765624999,\n 53.370220573956786\n ],\n [\n -120.43212890625,\n 51.6180165487737\n ],\n [\n -120.87158203125,\n 49.35375571830993\n ],\n [\n -122.08007812499999,\n 46.6795944656402\n ],\n [\n -122.958984375,\n 44.55916341529184\n ],\n [\n -123.74999999999999,\n 42.48830197960227\n ],\n [\n -121.904296875,\n 41.820455096140314\n ],\n [\n -119.77294921874999,\n 39.402244340292775\n ],\n [\n -117.48779296875,\n 39.7240885773337\n ],\n [\n -113.818359375,\n 41.32732632036622\n ],\n [\n -111.90673828125,\n 41.80407814427237\n ],\n [\n -110.0390625,\n 42.342305278572816\n ],\n [\n -108.34716796875,\n 43.14909399920127\n ],\n [\n -108.87451171875,\n 45.058001435398296\n ],\n [\n -110.32470703125,\n 46.81509864599243\n ],\n [\n -113.466796875,\n 49.42526716083716\n ],\n [\n -114.32373046875,\n 50.24720490139267\n ],\n [\n -120.25634765624999,\n 53.370220573956786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-04","publicationStatus":"PW","scienceBaseUri":"57aef346e4b0fc09faae03ed","contributors":{"authors":[{"text":"Littell, Jeremy S. 0000-0002-5302-8280 jlittell@usgs.gov","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":4428,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"jlittell@usgs.gov","middleInitial":"S.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":645378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":645379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Stephen T. sgray@usgs.gov","contributorId":221,"corporation":false,"usgs":true,"family":"Gray","given":"Stephen T.","email":"sgray@usgs.gov","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":645380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tjoelker, Michael","contributorId":173658,"corporation":false,"usgs":false,"family":"Tjoelker","given":"Michael","email":"","affiliations":[{"id":13194,"text":"School of Environmental and Forest Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":645381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hamlet, Alan F.","contributorId":15529,"corporation":false,"usgs":true,"family":"Hamlet","given":"Alan","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":645382,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":645383,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70185009,"text":"70185009 - 2016 - Microbial pathogens in source and treated waters from drinking water treatment plants in the United States and implications for human health","interactions":[],"lastModifiedDate":"2018-08-07T12:11:38","indexId":"70185009","displayToPublicDate":"2016-08-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Microbial pathogens in source and treated waters from drinking water treatment plants in the United States and implications for human health","docAbstract":"An occurrence survey was conducted on selected pathogens in source and treated drinking water collected from 25 drinking water treatment plants (DWTPs) in the United States. Water samples were analyzed for the protozoa Giardia and Cryptosporidium (EPA Method 1623); the fungi Aspergillus fumigatus, Aspergillus niger and Aspergillus terreus (quantitative PCR [qPCR]); and the bacteria Legionella pneumophila (qPCR), Mycobacterium avium, M. avium subspecies paratuberculosis, and Mycobacterium intracellulare (qPCR and culture). Cryptosporidium and Giardia were detected in 25% and in 46% of the source water samples, respectively (treated waters were not tested). Aspergillus fumigatus was the most commonly detected fungus in source waters (48%) but none of the three fungi were detected in treated water. Legionella pneumophila was detected in 25% of the source water samples but in only 4% of treated water samples. M. avium and M. intracellulare were both detected in 25% of source water, while all three mycobacteria were detected in 36% of treated water samples. Five species of mycobacteria, Mycobacterium mucogenicum, Mycobacterium phocaicum, Mycobacterium triplex, Mycobacterium fortuitum, and Mycobacterium lentiflavum were cultured from treated water samples. Although these DWTPs represent a fraction of those in the U.S., the results suggest that many of these pathogens are widespread in source waters but that treatment is generally effective in reducing them to below detection limits. The one exception is the mycobacteria, which were commonly detected in treated water, even when not detected in source waters.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.214","usgsCitation":"King, D.N., Donohue, M.J., Vesper, S.J., Villegas, E.N., Ware, M.W., Vogel, M.E., Furlong, E., Kolpin, D.W., Glassmeyer, S., and Pfaller, S., 2016, Microbial pathogens in source and treated waters from drinking water treatment plants in the United States and implications for human health: Science of the Total Environment, v. 562, p. 987-995, https://doi.org/10.1016/j.scitotenv.2016.03.214.","productDescription":"9 p.","startPage":"987","endPage":"995","ipdsId":"IP-061631","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.214","text":"Publisher Index Page"},{"id":337446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"562","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7afa1e4b0849ce9795ea8","chorus":{"doi":"10.1016/j.scitotenv.2016.03.214","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.03.214","publisher":"Elsevier BV","authors":"King Dawn N., Donohue Maura J., Vesper Stephen J., Villegas Eric N., Ware Michael W., Vogel Megan E., Furlong Edward F., Kolpin Dana W., Glassmeyer Susan T., Pfaller Stacy","journalName":"Science of The Total Environment","publicationDate":"8/2016"},"contributors":{"authors":[{"text":"King, Dawn N.","contributorId":189145,"corporation":false,"usgs":false,"family":"King","given":"Dawn","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":683968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donohue, Maura J.","contributorId":189146,"corporation":false,"usgs":false,"family":"Donohue","given":"Maura","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":683969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vesper, Stephen J.","contributorId":78296,"corporation":false,"usgs":true,"family":"Vesper","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":683970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villegas, Eric N.","contributorId":56947,"corporation":false,"usgs":true,"family":"Villegas","given":"Eric","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":683971,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ware, Michael W.","contributorId":65357,"corporation":false,"usgs":true,"family":"Ware","given":"Michael","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":683972,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vogel, Megan E.","contributorId":189147,"corporation":false,"usgs":false,"family":"Vogel","given":"Megan","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":683973,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward","contributorId":62689,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","affiliations":[],"preferred":false,"id":683974,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683947,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Glassmeyer, Susan T.","contributorId":72924,"corporation":false,"usgs":true,"family":"Glassmeyer","given":"Susan T.","affiliations":[],"preferred":false,"id":683975,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pfaller, Stacy","contributorId":189148,"corporation":false,"usgs":false,"family":"Pfaller","given":"Stacy","email":"","affiliations":[],"preferred":false,"id":683976,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70195836,"text":"70195836 - 2016 - Urban base flow with low impact development","interactions":[],"lastModifiedDate":"2018-03-06T11:39:52","indexId":"70195836","displayToPublicDate":"2016-08-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Urban base flow with low impact development","docAbstract":"A novel form of urbanization, low impact development (LID), aims to engineer systems that replicate natural hydrologic functioning, in part by infiltrating stormwater close to the impervious surfaces that generate it. We sought to statistically evaluate changes in a base flow regime because of urbanization with LID, specifically changes in base flow magnitude, seasonality, and rate of change. We used a case study watershed in Clarksburg, Maryland, in which streamflow was monitored during whole-watershed urbanization from forest and agricultural to suburban residential development using LID. The 1.11-km2 watershed contains 73 infiltration-focused stormwater facilities, including bioretention facilities, dry wells, and dry swales. We examined annual and monthly flow during and after urbanization (2004–2014) and compared alterations to nearby forested and urban control watersheds. We show that total streamflow and base flow increased in the LID watershed during urbanization as compared with control watersheds. The LID watershed had more gradual storm recessions after urbanization and attenuated seasonality in base flow. These flow regime changes may be because of a reduction in evapotranspiration because of the overall decrease in vegetative cover with urbanization and the increase in point sources of recharge. Precipitation that may once have infiltrated soil, been stored in soil moisture to be eventually transpired in a forested landscape, may now be recharged and become base flow. The transfer of evapotranspiration to base flow is an unintended consequence to the water balance of LID.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10808","usgsCitation":"Bhaskar, A., Hogan, D.M., and Archfield, S.A., 2016, Urban base flow with low impact development: Hydrological Processes, v. 30, no. 18, p. 3156-3171, https://doi.org/10.1002/hyp.10808.","productDescription":"16 p.","startPage":"3156","endPage":"3171","ipdsId":"IP-069104","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.10808","text":"Publisher Index Page"},{"id":352262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"18","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-26","publicationStatus":"PW","scienceBaseUri":"5afee9ade4b0da30c1bfc57e","contributors":{"authors":[{"text":"Bhaskar, Aditi abhaskar@usgs.gov","contributorId":146249,"corporation":false,"usgs":true,"family":"Bhaskar","given":"Aditi","email":"abhaskar@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":730226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":2299,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":730227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":730228,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195837,"text":"70195837 - 2016 - Insights into plant water uptake from xylem-water isotope measurements in two tropical catchments with contrasting moisture conditions","interactions":[],"lastModifiedDate":"2018-03-06T11:36:31","indexId":"70195837","displayToPublicDate":"2016-08-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Insights into plant water uptake from xylem-water isotope measurements in two tropical catchments with contrasting moisture conditions","docAbstract":"Water transpired by trees has long been assumed to be sourced from the same subsurface water stocks that contribute to groundwater recharge and streamflow. However, recent investigations using dual water stable isotopes have shown an apparent ecohydrological separation between tree-transpired water and stream water. Here we present evidence for such ecohydrological separation in two tropical environments in Puerto Rico where precipitation seasonality is relatively low and where precipitation is positively correlated with primary productivity. We determined the stable isotope signature of xylem water of 30 mahogany (Swietenia spp.) trees sampled during two periods with contrasting moisture status. Our results suggest that the separation between transpiration water and groundwater recharge/streamflow water might be related less to the temporal phasing of hydrologic inputs and primary productivity, and more to the fundamental processes that drive evaporative isotopic enrichment of residual soil water within the soil matrix. The lack of an evaporative signature of both groundwater and streams in the study area suggests that these water balance components have a water source that is transported quickly to deeper subsurface storage compared to waters that trees use. A Bayesian mixing model used to partition source water proportions of xylem water showed that groundwater contribution was greater for valley-bottom, riparian trees than for ridge-top trees. Groundwater contribution was also greater at the xeric site than at the mesic–hydric site. These model results (1) underline the utility of a simple linear mixing model, implemented in a Bayesian inference framework, in quantifying source water contributions at sites with contrasting physiographic characteristics, and (2) highlight the informed judgement that should be made in interpreting mixing model results, of import particularly in surveying groundwater use patterns by vegetation from regional to global scales.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10841","usgsCitation":"Evaristo, J., McDonnell, J.J., Scholl, M.A., Bruijnzeel, L., and Chun, K.P., 2016, Insights into plant water uptake from xylem-water isotope measurements in two tropical catchments with contrasting moisture conditions: Hydrological Processes, v. 30, no. 18, p. 3210-3227, https://doi.org/10.1002/hyp.10841.","productDescription":"18 p.","startPage":"3210","endPage":"3227","ipdsId":"IP-069760","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":352261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"18","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"5afee9ade4b0da30c1bfc57c","contributors":{"authors":[{"text":"Evaristo, Jaivime","contributorId":202933,"corporation":false,"usgs":false,"family":"Evaristo","given":"Jaivime","email":"","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":730230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonnell, Jeffrey J.","contributorId":202934,"corporation":false,"usgs":false,"family":"McDonnell","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[{"id":36551,"text":"University of Saskatchewan, Canada, and University of Aberdeen, Scotland","active":true,"usgs":false}],"preferred":false,"id":730231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":730229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruijnzeel, L. Adrian","contributorId":202935,"corporation":false,"usgs":false,"family":"Bruijnzeel","given":"L. Adrian","affiliations":[{"id":36552,"text":"King's College London","active":true,"usgs":false}],"preferred":false,"id":730232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chun, Kwok P.","contributorId":202936,"corporation":false,"usgs":false,"family":"Chun","given":"Kwok","email":"","middleInitial":"P.","affiliations":[{"id":36553,"text":"Hong Kong Baptist University","active":true,"usgs":false}],"preferred":false,"id":730233,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192565,"text":"70192565 - 2016 - The road to NHDPlus — Advancements in digital stream networks and associated catchments","interactions":[],"lastModifiedDate":"2017-11-17T11:34:42","indexId":"70192565","displayToPublicDate":"2016-08-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"The road to NHDPlus — Advancements in digital stream networks and associated catchments","docAbstract":"A progression of advancements in Geographic Information Systems techniques for hydrologic network and associated catchment delineation has led to the production of the National Hydrography Dataset Plus (NHDPlus). NHDPlus is a digital stream network for hydrologic modeling with catchments and a suite of related geospatial data. Digital stream networks with associated catchments provide a geospatial framework for linking and integrating water-related data. Advancements in the development of NHDPlus are expected to continue to improve the capabilities of this national geospatial hydrologic framework. NHDPlus is built upon the medium-resolution NHD and, like NHD, was developed by the U.S. Environmental Protection Agency and U.S. Geological Survey to support the estimation of streamflow and stream velocity used in fate-and-transport modeling. Catchments included with NHDPlus were created by integrating vector information from the NHD and from the Watershed Boundary Dataset with the gridded land surface elevation as represented by the National Elevation Dataset. NHDPlus is an actively used and continually improved dataset. Users recognize the importance of a reliable stream network and associated catchments. The NHDPlus spatial features and associated data tables will continue to be improved to support regional water quality and streamflow models and other user-defined applications.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12389","usgsCitation":"Moore, R.B., and Dewald, T.A., 2016, The road to NHDPlus — Advancements in digital stream networks and associated catchments: Journal of the American Water Resources Association, v. 52, no. 4, p. 890-900, https://doi.org/10.1111/1752-1688.12389.","productDescription":"11 p.","startPage":"890","endPage":"900","ipdsId":"IP-067213","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":482073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12389","text":"Publisher Index Page"},{"id":349062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-11","publicationStatus":"PW","scienceBaseUri":"5a60fd04e4b06e28e9c24672","contributors":{"authors":[{"text":"Moore, Richard B. rmoore@usgs.gov","contributorId":1464,"corporation":false,"usgs":true,"family":"Moore","given":"Richard","email":"rmoore@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dewald, Thomas A.","contributorId":198480,"corporation":false,"usgs":false,"family":"Dewald","given":"Thomas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716214,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175369,"text":"70175369 - 2016 - On the deterministic and stochastic use of hydrologic models","interactions":[],"lastModifiedDate":"2018-04-03T11:39:16","indexId":"70175369","displayToPublicDate":"2016-07-31T08:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"On the deterministic and stochastic use of hydrologic models","docAbstract":"Environmental simulation models, such as precipitation-runoff watershed models, are increasingly used in a deterministic manner for environmental and water resources design, planning, and management. In operational hydrology, simulated responses are now routinely used to plan, design, and manage a very wide class of water resource systems. However, all such models are calibrated to existing data sets and retain some residual error. This residual, typically unknown in practice, is often ignored, implicitly trusting simulated responses as if they are deterministic quantities. In general, ignoring the residuals will result in simulated responses with distributional properties that do not mimic those of the observed responses. This discrepancy has major implications for the operational use of environmental simulation models as is shown here. Both a simple linear model and a distributed-parameter precipitation-runoff model are used to document the expected bias in the distributional properties of simulated responses when the residuals are ignored. The systematic reintroduction of residuals into simulated responses in a manner that produces stochastic output is shown to improve the distributional properties of the simulated responses. Every effort should be made to understand the distributional behavior of simulation residuals and to use environmental simulation models in a stochastic manner.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016WR019129","usgsCitation":"Farmer, W.H., and Vogel, R.M., 2016, On the deterministic and stochastic use of hydrologic models: Water Resources Research, v. 52, no. 7, p. 5619-5633, https://doi.org/10.1002/2016WR019129.","productDescription":"15 p.","startPage":"5619","endPage":"5633","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075481","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470712,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr019129","text":"Publisher Index Page"},{"id":438579,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7W37TF4","text":"USGS data release","linkHelpText":"Data release in support of &quot;One the Deterministic and Stochastic Use of Hydrologic Models&quot;"},{"id":326189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-31","publicationStatus":"PW","scienceBaseUri":"57a9ad6ae4b05e859bdfba82","contributors":{"authors":[{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"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}],"preferred":true,"id":644942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vogel, Richard M.","contributorId":66811,"corporation":false,"usgs":true,"family":"Vogel","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":644943,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170574,"text":"sir20165055 - 2016 - Budgets and chemical characterization of groundwater for the Diamond Valley flow system, central Nevada, 2011–12","interactions":[],"lastModifiedDate":"2019-08-16T08:36:22","indexId":"sir20165055","displayToPublicDate":"2016-07-29T15:00:00","publicationYear":"2016","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":"2016-5055","title":"Budgets and chemical characterization of groundwater for the Diamond Valley flow system, central Nevada, 2011–12","docAbstract":"The Diamond Valley flow system consists of six hydraulically connected hydrographic areas in central Nevada. The general down-gradient order of the areas are southern and northern Monitor Valleys, Antelope Valley, Kobeh Valley, Stevens Basin, and Diamond Valley. Groundwater flow in the Diamond Valley flow system terminates at a large playa in the northern part of Diamond Valley. Concerns relating to continued water-resources development of the flow system resulted in a phased hydrologic investigation that began in 2005 by the U.S. Geological Survey in cooperation with Eureka County. This report presents the culmination of the phased investigation to increase understanding of the groundwater resources of the basin-fill aquifers in the Diamond Valley flow system through evaluations of groundwater chemistry and budgets. Groundwater chemistry was characterized using major ions and stable isotopes from groundwater and precipitation samples. Groundwater budgets accounted for all inflows, outflows, and changes in storage, and were developed for pre-development (pre-1950) and recent (average annual 2011–12) conditions. Major budget components include groundwater discharge by evapotranspiration and groundwater withdrawals; groundwater recharge by precipitation, and interbasin flow; and storage change.
\nGroundwater in the basin-fill aquifer of the Diamond Valley flow system was mostly a calcium or sodium bicarbonate water type and generally within acceptable drinking-water standards. The general water type was similar among the individual hydrographic areas. Stable isotopes of oxygen-18 and deuterium from precipitation varied seasonally, such that enrichment from evaporation was greater during warmer months than cooler months. The isotopic signature of shallow groundwater was similar to cool season precipitation, indicating recharge was relatively recent (similar to recent climatic conditions) and was derived from cool season precipitation.
\nSite-scale groundwater evapotranspiration was estimated from eddy-covariance and micrometeorological measurements collected at four sites and ranged from 0.15 feet per year in sparse, undisturbed shrubland to 1.13 feet per year in a grassland meadow. Vegetation indices calculated from satellite imagery and field mapping were used to define three evapotranspiration units (shrubland, grassland, and playa) and to extrapolate site-scale groundwater evapotranspiration rates to basin-scale estimates. Annual pre-development groundwater evapotranspiration for individual hydrographic areas ranged from 2,900 acre-feet per year (acre-ft/yr) in northern Monitor Valley to 35,000 acre-ft/yr in Diamond Valley. Total groundwater evapotranspiration from the Diamond Valley flow system under pre-development conditions was about 70,000 acre-ft/yr.
\nAreas of irrigated land in the Diamond Valley flow system increased from less than 5,000 acres in the early 1960s to more than 25,000 acres in 2012 and are mostly for growing alfalfa in southern Diamond Valley. Annual (2011–12) net groundwater withdrawals for irrigation, assumed to be the volume of groundwater consumed by crops and pastureland, ranged from about 420 acre-ft/yr in Antelope Valley to 67,000 acre-ft/yr in Diamond Valley. Total net groundwater withdrawals for irrigation in the Diamond Valley flow system were about 69,000 acre-ft/yr (2011–12).
\nGroundwater recharge, the largest inflow component to the Diamond Valley flow system, was determined as the sum of groundwater evapotranspiration and net subsurface outflow (subsurface outflow minus subsurface inflow). Annual groundwater recharge estimates ranged from 200 acre-ft/yr in Stevens Basin to 35,000 acre-ft/yr in Diamond Valley.
\nSubsurface flow between hydrographic basins was evaluated using estimated transmissivity, groundwater-flow sections derived from remotely sensed imagery, and hydraulic gradients determined from 2012 water-level data. Subsurface outflow ranged from 0 acre-ft/yr for Diamond Valley to 3,400 acre-ft/yr for northern Monitor Valley into western Kobeh Valley. Subsurface inflow ranged from 0 acre-ft/yr for southern Monitor Valley to 4,200 acre-ft/yr for Kobeh Valley from northern Monitor and Antelope Valleys.
\nThe pre-development, steady state, groundwater budget for the Diamond Valley flow system was estimated at about 70,000 acre-ft/yr of inflow and outflow. During years 2011–12, inflow components of groundwater recharge from precipitation and subsurface inflow from adjacent basins totaled 70,000 acre-ft/yr for the DVFS, whereas outflow components included 64,000 acre-ft/yr of groundwater evapotranspiration and 69,000 acre-ft/yr of net groundwater withdrawals, or net pumpage. Spring discharge in northern Diamond Valley declined about 6,000 acre-ft/yr between pre-development time and years 2011–12. Assuming net groundwater withdrawals minus spring flow decline is equivalent to the storage change, the 2011–12 summation of inflow and storage change was balanced with outflow at about 133,000 acre-ft/yr.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165055","collaboration":"Prepared in cooperation with Eureka County, Nevada","usgsCitation":"Berger, D.L., Mayers, C.J., Garcia, C.A., Buto, S.G., and Huntington, J.M., 2016, Budgets and chemical characterization of groundwater for the Diamond Valley flow system, central Nevada, 2011–12: U.S. Geological Survey Scientific Investigations Report 2016–5055, 83 p., https://dx.doi.org/10.3133/sir20165055.","productDescription":"Report: x, 84 p.; Plate: 22 x 33 inches; 5 Datasets","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042275","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":325830,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7JM27QV","text":"Irrigated Agricultural Lands and Associated Land Disturbance in the Diamond Valley Flow System, Central Nevada, 2011"},{"id":325831,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F75B00K7","text":"Groundwater Discharge Area for the Diamond Valley Flow System, Central Nevada"},{"id":325832,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7930R9K","text":"Summer Mean Enhanced Vegetation Index for the Diamond Valley Flow System Groundwater Discharge Area, 2010"},{"id":325833,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7DV1H0J","text":"Evapotranspiration Units for the Diamond Valley Flow System, Central Nevada, 2010"},{"id":325829,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F71J97VZ","text":"Water-Level Altitude Contours for the Diamond Valley Flow System, Central Nevada, 2012"},{"id":325825,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5055/coverthb.jpg"},{"id":325826,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5055/sir20165055.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5055 Report PDF"},{"id":325827,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5055/sir20165055_high-res.pdf","text":"Report - Print Resolution","size":"47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5055 Report Print PDF"},{"id":325828,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5055/sir20165055_plate.pdf","text":"Plate 1","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5055 Plate 1","linkHelpText":"Groundwater Levels in Basin-Fill Deposits, Groundwater-Discharge Areas, and Agricultural Areas of the Diamond Valley Flow System, Central Nevada"},{"id":366584,"rank":10,"type":{"id":28,"text":"Dataset"},"url":" https://doi.org/10.5066/P9NZ9XSP","text":"Evapotranspiration data, Kobeh Valley, Nevada, 2010–12"}],"country":"United States","state":"Nevada","county":"Elko County, Eureka County, Lander County, Nye County","otherGeospatial":"Diamond Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.33333,\n 38.33333\n ],\n [\n -117.33333,\n 40.33333\n ],\n [\n -115.33333,\n 40.33333\n ],\n [\n -115.33333,\n 38.33333\n ],\n [\n -117.33333,\n 38.33333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/
","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2016-07-29","noUsgsAuthors":false,"publicationDate":"2016-07-29","publicationStatus":"PW","scienceBaseUri":"579c7020e4b0589fa1c98a08","contributors":{"authors":[{"text":"Berger, David L. dlberger@usgs.gov","contributorId":1861,"corporation":false,"usgs":true,"family":"Berger","given":"David","email":"dlberger@usgs.gov","middleInitial":"L.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":627724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayers, C. Justin cjmayers@usgs.gov","contributorId":2306,"corporation":false,"usgs":true,"family":"Mayers","given":"C. Justin","email":"cjmayers@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":627725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garcia, C. Amanda 0000-0003-3776-3565 cgarcia@usgs.gov","orcid":"https://orcid.org/0000-0003-3776-3565","contributorId":1899,"corporation":false,"usgs":true,"family":"Garcia","given":"C.","email":"cgarcia@usgs.gov","middleInitial":"Amanda","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buto, Susan G. 0000-0002-1107-9549 sbuto@usgs.gov","orcid":"https://orcid.org/0000-0002-1107-9549","contributorId":1057,"corporation":false,"usgs":true,"family":"Buto","given":"Susan","email":"sbuto@usgs.gov","middleInitial":"G.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huntington, Jena M. 0000-0002-9291-1404 jmhunt@usgs.gov","orcid":"https://orcid.org/0000-0002-9291-1404","contributorId":2294,"corporation":false,"usgs":true,"family":"Huntington","given":"Jena","email":"jmhunt@usgs.gov","middleInitial":"M.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627728,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175057,"text":"70175057 - 2016 - Ordinary kriging as a tool to estimate historical daily streamflow records","interactions":[],"lastModifiedDate":"2016-07-28T10:06:14","indexId":"70175057","displayToPublicDate":"2016-07-28T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Ordinary kriging as a tool to estimate historical daily streamflow records","docAbstract":"
Efficient and responsible management of water resources relies on accurate streamflow records. However, many watersheds are ungaged, limiting the ability to assess and understand local hydrology. Several tools have been developed to alleviate this data scarcity, but few provide continuous daily streamflow records at individual streamgages within an entire region. Building on the history of hydrologic mapping, ordinary kriging was extended to predict daily streamflow time series on a regional basis. Pooling parameters to estimate a single, time-invariant characterization of spatial semivariance structure is shown to produce accurate reproduction of streamflow. This approach is contrasted with a time-varying series of variograms, representing the temporal evolution and behavior of the spatial semivariance structure. Furthermore, the ordinary kriging approach is shown to produce more accurate time series than more common, single-index hydrologic transfers. A comparison between topological kriging and ordinary kriging is less definitive, showing the ordinary kriging approach to be significantly inferior in terms of Nash–Sutcliffe model efficiencies while maintaining significantly superior performance measured by root mean squared errors. Given the similarity of performance and the computational efficiency of ordinary kriging, it is concluded that ordinary kriging is useful for first-order approximation of daily streamflow time series in ungaged watersheds.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-20-2721-2016","usgsCitation":"Farmer, W.H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records: Hydrology and Earth System Sciences, v. 20, no. 7, p. 2721-2735, https://doi.org/10.5194/hess-20-2721-2016.","productDescription":"15 p.","startPage":"2721","endPage":"2735","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070177","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-2721-2016","text":"Publisher Index Page"},{"id":325769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"579b1e9fe4b0589fa1c951cc","contributors":{"authors":[{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"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":643738,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70173914,"text":"70173914 - 2016 - Characterization of mean transit time at large springs in the Upper Colorado River Basin, USA: A tool for assessing groundwater discharge vulnerability","interactions":[],"lastModifiedDate":"2016-12-09T16:26:20","indexId":"70173914","displayToPublicDate":"2016-07-20T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of mean transit time at large springs in the Upper Colorado River Basin, USA: A tool for assessing groundwater discharge vulnerability","docAbstract":"Environmental tracers (noble gases, tritium, industrial gases, stable isotopes, and radio-carbon) and hydrogeology were interpreted to determine groundwater transit-time distribution and calculate mean transit time (MTT) with lumped parameter modeling at 19 large springs distributed throughout the Upper Colorado River Basin (UCRB), USA. The predictive value of the MTT to evaluate the pattern and timing of groundwater response to hydraulic stress (i.e., vulnerability) is examined by a statistical analysis of MTT, historical spring discharge records, and the Palmer Hydrological Drought Index. MTTs of the springs range from 10 to 15,000 years and 90 % of the cumulative discharge-weighted travel-time distribution falls within the range of 2−10,000 years. Historical variability in discharge was assessed as the ratio of 10–90 % flow-exceedance (R 10/90%) and ranged from 2.8 to 1.1 for select springs with available discharge data. The lag-time (i.e., delay in discharge response to drought conditions) was determined by cross-correlation analysis and ranged from 0.5 to 6 years for the same select springs. Springs with shorter MTTs (<80 years) statistically correlate with larger discharge variations and faster responses to drought, indicating MTT can be used for estimating the relative magnitude and timing of groundwater response. Results indicate that groundwater discharge to streams in the UCRB will likely respond on the order of years to climate variation and increasing groundwater withdrawals.
","language":"English","publisher":"International Association of Hydrogeologists","doi":"10.1007/s10040-016-1440-9","usgsCitation":"Solder, J.E., Stolp, B.J., Heilweil, V.M., and Susong, D.D., 2016, Characterization of mean transit time at large springs in the Upper Colorado River Basin, USA: A tool for assessing groundwater discharge vulnerability: Hydrogeology Journal, v. 24, no. 8, p. 2017-2033, https://doi.org/10.1007/s10040-016-1440-9.","productDescription":"17 p.","startPage":"2017","endPage":"2033","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075897","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":325907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","volume":"24","issue":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-20","publicationStatus":"PW","scienceBaseUri":"57a1c42de4b006cb45552bfb","contributors":{"authors":[{"text":"Solder, John E. 0000-0002-0660-3326 jsolder@usgs.gov","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":171916,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"jsolder@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stolp, Bernard J. 0000-0003-3803-1497 bjstolp@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-1497","contributorId":963,"corporation":false,"usgs":true,"family":"Stolp","given":"Bernard","email":"bjstolp@usgs.gov","middleInitial":"J.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heilweil, Victor M. heilweil@usgs.gov","contributorId":837,"corporation":false,"usgs":true,"family":"Heilweil","given":"Victor","email":"heilweil@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Susong, David D. ddsusong@usgs.gov","contributorId":1040,"corporation":false,"usgs":true,"family":"Susong","given":"David","email":"ddsusong@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639089,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70175240,"text":"70175240 - 2016 - Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska","interactions":[],"lastModifiedDate":"2016-08-03T09:43:31","indexId":"70175240","displayToPublicDate":"2016-07-18T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska","docAbstract":"Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake ice growth, causing a shift from bedfast to floating ice conditions. September sea ice concentrations in the Arctic Ocean since 1991 correlate well (r = +0.69,p < 0.001) to this lake regime shift. To understand how and to what extent sea ice affects lakes, we conducted model experiments to simulate winters with years of high (1991/92) and low (2007/08) sea ice extent for which we also had field measurements and satellite imagery characterizing lake ice conditions. A lake ice growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake ice growth when 2007/08 sea ice was imposed on 1991/92 climatology and a 9% increase in lake ice growth for the opposing experiment. Here, we clearly link early winter 'ocean-effect' snowfall and warming to reduced lake ice growth. Future reductions in sea ice extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.
","language":"English","publisher":"Institute of Physics","publisherLocation":"London","doi":"10.1088/1748-9326/11/7/074022","usgsCitation":"Alexeev, V., Arp, C.D., Jones, B.M., and Cai, L., 2016, Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska: Environmental Research Letters, v. 11, no. 7, https://doi.org/10.1088/1748-9326/11/7/074022.","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071294","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":470745,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/11/7/074022","text":"Publisher Index Page"},{"id":326013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"11","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-18","publicationStatus":"PW","scienceBaseUri":"57a315bbe4b006cb45558a2d","contributors":{"authors":[{"text":"Alexeev, Vladimir","contributorId":173393,"corporation":false,"usgs":false,"family":"Alexeev","given":"Vladimir","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":644494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":644495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":644493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cai, Lei","contributorId":173394,"corporation":false,"usgs":false,"family":"Cai","given":"Lei","email":"","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":644496,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176581,"text":"70176581 - 2016 - Parameter regionalization of a monthly water balance model for the conterminous United States","interactions":[],"lastModifiedDate":"2018-07-09T12:13:29","indexId":"70176581","displayToPublicDate":"2016-07-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Parameter regionalization of a monthly water balance model for the conterminous United States","docAbstract":"A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash–Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-20-2861-2016","usgsCitation":"Bock, A.R., Hay, L.E., McCabe, G., Markstrom, S.L., and Atkinson, R., 2016, Parameter regionalization of a monthly water balance model for the conterminous United States: Hydrology and Earth System Sciences, v. 20, p. 2861-2876, https://doi.org/10.5194/hess-20-2861-2016.","productDescription":"16 p.","startPage":"2861","endPage":"2876","ipdsId":"IP-067200","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":470749,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-2861-2016","text":"Publisher Index Page"},{"id":328838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328857,"rank":2,"type":{"id":30,"text":"Data 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Branch","active":true,"usgs":true}],"preferred":true,"id":649267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":649268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":140378,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":649269,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, R. Dwight","contributorId":174777,"corporation":false,"usgs":false,"family":"Atkinson","given":"R. Dwight","affiliations":[{"id":27513,"text":"U.S. Environmental Protection Agency, Office of Water","active":true,"usgs":false}],"preferred":false,"id":649270,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173928,"text":"ofr20161101 - 2016 - Low-flow frequency and flow duration of selected South Carolina streams in the Savannah and Salkehatchie River Basins through March 2014","interactions":[],"lastModifiedDate":"2016-11-15T09:31:00","indexId":"ofr20161101","displayToPublicDate":"2016-07-14T14:00:00","publicationYear":"2016","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":"2016-1101","title":"Low-flow frequency and flow duration of selected South Carolina streams in the Savannah and Salkehatchie River Basins through March 2014","docAbstract":"An ongoing understanding of streamflow characteristics of the rivers and streams in South Carolina is important for the protection and preservation of the State’s water resources. Information concerning the low-flow characteristics of streams is especially important during critical flow periods, such as during the historic droughts that South Carolina has experienced in the past few decades.
In 2008, the U.S. Geological Survey, in cooperation with the South Carolina Department of Health and Environmental Control, initiated a study to update low-flow statistics at continuous-record streamgaging stations operated by the U.S. Geological Survey in South Carolina. This report presents the low-flow statistics for 28 selected streamgaging stations in the Savannah and Salkehatchie River Basins in South Carolina. The low-flow statistics include daily mean flow durations for the 5-, 10-, 25-, 50-, 75-, 90-, and 95-percent probability of exceedance and the annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day mean flows with recurrence intervals of 2, 5, 10, 20, 30, and 50 years, depending on the length of record available at the streamgaging station. The low-flow statistics were computed from records available through March 31, 2014.
Low-flow statistics are influenced by length of record, hydrologic regime under which the data were collected, analytical techniques used, and other factors, such as urbanization, diversions, and droughts that may have occurred in the basin. To assess changes in the low-flow statistics from the previously published values, a comparison of the low-flow statistics for the annual minimum 7-day average streamflow with a 10-year recurrence interval (7Q10) from this study was made with the most recently published values. Of the 28 streamgaging stations for which recurrence interval computations were made, 14 streamgaging stations were suitable for comparing to low-flow statistics that were previously published in U.S. Geological Survey reports. These comparisons indicated that seven of the streamgaging stations had values lower than the previous values, two streamgaging stations had values higher than the previous values, and two streamgaging stations had values that were unchanged from previous values. The remaining three stations for which previous 7Q10 values were computed, which are located on the main stem of the Savannah River, were not compared with current estimates because of differences in the way the pre-regulation and regulated flow data were analyzed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161101","collaboration":"Prepared in cooperation with the South Carolina Department of Health and Environmental Control","usgsCitation":"Feaster, T.D., and Guimaraes, W.B., 2016, Low-flow frequency and flow duration of selected South Carolina streams in the Savannah and Salkehatchie River Basins through March 2014 (ver. 1.1, November 2016): U.S. Geological Survey Open-File Report 2016–1101, 62 p., https://dx.doi.org/10.3133/ofr20161101.","productDescription":"vi, 62 p.","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074376","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":325181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1101/ofr20161101.pdf","text":"Report","size":"2.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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720 Gracern Road
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Mangrove ecosystems protect vulnerable coastlines from storm effects, recycle nutrients, stabilize shorelines, improve water quality, and provide habitat for commercial and recreational fish species as well as for threatened and endangered wildlife. U.S. Geological Survey scientists conduct research on mangrove ecosystems to provide reliable scientific information about their ecology, productivity, hydrological processes, carbon storage stress response, and restoration success. The Mangrove Science Network is a collaboration of USGS scientists focused on working with natural resource managers to develop and conduct research to inform decisions on mangrove management and restoration. Information about the Mangrove Science Network can be found at: http://www.usgs.gov/ecosystems/environments/mangroves.html.
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Potential health effects from hexavalent chromium in groundwater have recently become a concern to regulators at the Tucson International Airport Area Superfund site. In 2016, the U.S. Geological Survey sampled 46 wells in the area to characterize the nature and extent of chromium in groundwater, to understand what proportion of total chromium is in the hexavalent state, and to determine if substantial differences are present between filtered and unfiltered chromium concentrations. Results indicate detectable chromium concentrations in all wells, over 75 % of total chromium is in the hexavalent state in a majority of wells, and filtered and unfiltered results differ substantially in only a few high-turbidity total chromium samples.
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Charles","contributorId":193562,"corporation":false,"usgs":false,"family":"Visser","given":"Charles","email":"","affiliations":[],"preferred":false,"id":700820,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Liberty, Lee M.","contributorId":89631,"corporation":false,"usgs":true,"family":"Liberty","given":"Lee","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":700817,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Siler, Drew","contributorId":193559,"corporation":false,"usgs":false,"family":"Siler","given":"Drew","affiliations":[],"preferred":false,"id":700816,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Evans, James P.","contributorId":53760,"corporation":false,"usgs":true,"family":"Evans","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":700823,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Santellanes, Sean","contributorId":193566,"corporation":false,"usgs":false,"family":"Santellanes","given":"Sean","email":"","affiliations":[],"preferred":false,"id":700824,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70170126,"text":"70170126 - 2016 - Using Cape Sable seaside sparrow distribution data for water management decision support","interactions":[],"lastModifiedDate":"2016-07-11T15:35:32","indexId":"70170126","displayToPublicDate":"2016-07-08T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Using Cape Sable seaside sparrow distribution data for water management decision support","docAbstract":"The Cape Sable Seaside Sparrow (Ammodramus maritimus mirabilis; hereafter sparrow) is endemic to south Florida and a key indicator species of marl prairie, the most diverse freshwater community in the Florida Everglades. Marl prairie habitat is shaped by intermediate levels of disturbances such as flooding, drying, and fire, which maintain periphyton production (Gaiser et al. 2011), vegetation composition (Sah et al. 2011), and habitat structure for wildlife (Lockwood et al. 2003). Historically, patches of marl prairie shifted in response to changing climatic conditions,; however, habitat loss and hydrologic alteration have restricted the sparrow’s range and increased their sensitivity to changing hydropatterns. As a result, sparrow numbers have declined as much as 60% range-wide since 1992 (Curnutt et al. 1998, Nott et al. 1998). Currently, the sparrow is restricted to the freshwater prairies of the Everglades National Park (ENP) and Big Cypress Preserve (Lockwood et al. 1997). Because this non-migratory bird is restricted in its range it was among the first species to be listed as endangered by the US Fish and Wildlife Service on March 11, 1967 (Pimm et al. 2000). Now protected by the Endangered Species Act of 1973, the sparrow is listed as an endangered species, and the marl prairies that it resides in are listed as critical habitat. Since its designation as an endangered species, federal agencies have a statutory obligation to not jeopardize the survival of the species or modify its critical habitat. However, there are still uncertainties in how to increase suitable habitat within and surrounding the six existing sparrow subpopulations (Fig. 1) which are vulnerable to environmental stochasticity because of their small population size and restricted range. Since Because maintenance and creation of suitable habitat is seen as the most important pathway to the persistence of sparrow subpopulations (Sustainable Ecosystems Institute 2007), emphasis should be on identifying factors affecting sparrow habitat suitability and expanding the total area of suitable habitat over a gradient of environmental conditions. Our objective is to improve the definition of suitable sparrow habitat based on the relationship between daily sparrow distributions from 1992-present and hydrologic and habitat variables. Further, these models can provide an estimate of habitat quality when linked with estimates of reproductive responses.
","largerWorkTitle":"Report to the U.S. Fish and Wildlife Service","language":"English","usgsCitation":"Beerens, J.M., and Romanach, S.S., 2016, Using Cape Sable seaside sparrow distribution data for water management decision support, 20 p.","productDescription":"20 p.","startPage":"1","endPage":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073857","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":325061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5784c347e4b0e02680be59fa","contributors":{"authors":[{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":626225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":626226,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174978,"text":"70174978 - 2016 - Biogeochemical controls of uranium bioavailability from the dissolved phase in natural freshwaters","interactions":[],"lastModifiedDate":"2018-08-09T12:01:50","indexId":"70174978","displayToPublicDate":"2016-07-06T14:30:00","publicationYear":"2016","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":"Biogeochemical controls of uranium bioavailability from the dissolved phase in natural freshwaters","docAbstract":"To gain insights into the risks associated with uranium (U) mining and processing, we investigated the biogeochemical controls of U bioavailability in the model freshwater speciesLymnaea stagnalis (Gastropoda). Bioavailability of dissolved U(VI) was characterized in controlled laboratory experiments over a range of water hardness, pH, and in the presence of complexing ligands in the form of dissolved natural organic matter (DOM). Results show that dissolved U is bioavailable under all the geochemical conditions tested. Uranium uptake rates follow first order kinetics over a range encompassing most environmental concentrations. Uranium uptake rates in L. stagnalis ultimately demonstrate saturation uptake kinetics when exposure concentrations exceed 100 nM, suggesting uptake via a finite number of carriers or ion channels. The lack of a relationship between U uptake rate constants and Ca uptake rates suggest that U does not exclusively use Ca membrane transporters. In general, U bioavailability decreases with increasing pH, increasing Ca and Mg concentrations, and when DOM is present. Competing ions did not affect U uptake rates. Speciation modeling that includes formation constants for U ternary complexes reveals that the aqueous concentration of dicarbonato U species (UO2(CO3)2–2) best predicts U bioavailability to L. stagnalis, challenging the free-ion activity model postulate.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b02406","usgsCitation":"Croteau, M.N., Fuller, C.C., Cain, D.J., Campbell, K.M., and Aiken, G.R., 2016, Biogeochemical controls of uranium bioavailability from the dissolved phase in natural freshwaters: Environmental Science & Technology, v. 50, no. 15, p. 8120-8127, https://doi.org/10.1021/acs.est.6b02406.","productDescription":"8 p.","startPage":"8120","endPage":"8127","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075146","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"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":325712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-21","publicationStatus":"PW","scienceBaseUri":"5799db3be4b0589fa1c7e732","chorus":{"doi":"10.1021/acs.est.6b02406","url":"http://dx.doi.org/10.1021/acs.est.6b02406","publisher":"American Chemical Society (ACS)","authors":"Croteau Marie-Noële, Fuller Christopher C., Cain Daniel J., Campbell Kate M., Aiken George","journalName":"Environmental Science & Technology","publicationDate":"8/2/2016"},"contributors":{"authors":[{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":643486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":643487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":643488,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":643489,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"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":643490,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188881,"text":"70188881 - 2016 - The Pilot Valley shoreline: An early record of Lake Bonneville dynamics","interactions":[],"lastModifiedDate":"2020-08-25T18:25:05.606281","indexId":"70188881","displayToPublicDate":"2016-07-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"The Pilot Valley shoreline: An early record of Lake Bonneville dynamics","docAbstract":"The Pilot Valley shoreline is named for distinctive gravel beaches on the eastern, northern, and western sides of Pilot Valley playa, Utah. The shoreline has been identified across the Bonneville basin where it is characterized by one to three beach crests between ~ 1305 and 1309 m elevation, all overlain by deep-water marl of Lake Bonneville. It thus represents the lowest and earliest recognized shoreline of Lake Bonneville. Features of the shoreline indicate that both high wave energy and high stream sediment discharge contributed to shoreline development. Basin hypsometry did not play a role in the development of the shoreline, which must have been caused by a combination of climatically driven hydrologic and storm factors, such as reduced precipitation that stabilized lake level and increase in storm-driven wave energy. The Pilot Valley shoreline is poorly dated at about 30 ka. If it is somewhat older, correlation with Greenland Interstadial 5.1 at 30.8–30.6 ka could explain the stabilization of lake level.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Developments in Earth Surface Processes 20","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/B978-0-444-63590-7.00003-2","usgsCitation":"Miller, D., and Phelps, G., 2016, The Pilot Valley shoreline: An early record of Lake Bonneville dynamics, chap. 3 of Developments in Earth Surface Processes 20, v. 20, p. 60-74, https://doi.org/10.1016/B978-0-444-63590-7.00003-2.","productDescription":"15 p.","startPage":"60","endPage":"74","ipdsId":"IP-068696","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":342958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Nevada, Utah","otherGeospatial":"Lake Bonneville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.141667,\n 42.041667\n ],\n [\n -111,\n 42.041667\n ],\n [\n -111,\n 37\n ],\n [\n -114.141667,\n 37\n ],\n [\n -114.141667,\n 42.041667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536ea8e4b062508e3c7a7b","contributors":{"authors":[{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phelps, Geoffrey 0000-0003-1958-2736 gphelps@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-2736","contributorId":127489,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey","email":"gphelps@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700806,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175393,"text":"70175393 - 2016 - Implications of climate change for wetland-dependent birds in the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2017-01-03T16:15:45","indexId":"70175393","displayToPublicDate":"2016-07-04T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Implications of climate change for wetland-dependent birds in the Prairie Pothole Region","docAbstract":"The habitats and food resources required to support breeding and migrant birds dependent on North American prairie wetlands are threatened by impending climate change. The North American Prairie Pothole Region (PPR) hosts nearly 120 species of wetland-dependent birds representing 21 families. Strategic management requires knowledge of avian habitat requirements and assessment of species most vulnerable to future threats. We applied bioclimatic species distribution models (SDMs) to project range changes of 29 wetland-dependent bird species using ensemble modeling techniques, a large number of General Circulation Models (GCMs), and hydrological climate covariates. For the U.S. PPR, mean projected range change, expressed as a proportion of currently occupied range, was −0.31 (± 0.22 SD; range − 0.75 to 0.16), and all but two species were projected to lose habitat. Species associated with deeper water were expected to experience smaller negative impacts of climate change. The magnitude of climate change impacts was somewhat lower in this study than earlier efforts most likely due to use of different focal species, varying methodologies, different modeling decisions, or alternative GCMs. Quantification of the projected species-specific impacts of climate change using species distribution modeling offers valuable information for vulnerability assessments within the conservation planning process.
","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-016-0791-2","usgsCitation":"Steen, V., Skagen, S., and Melcher, C.P., 2016, Implications of climate change for wetland-dependent birds in the Prairie Pothole Region: Wetlands, v. 36, no. s2, p. 445-459, https://doi.org/10.1007/s13157-016-0791-2.","productDescription":"15 p.","startPage":"445","endPage":"459","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073432","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":326285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.73046875,\n 48.83579746243093\n ],\n [\n -112.3681640625,\n 48.40003249610685\n ],\n [\n -108.984375,\n 48.63290858589532\n ],\n [\n -105.6884765625,\n 48.574789910928864\n ],\n [\n -104.150390625,\n 48.45835188280866\n ],\n [\n -103.0517578125,\n 48.22467264956519\n ],\n [\n -102.48046875,\n 47.84265762816538\n ],\n [\n -101.953125,\n 47.54687159892238\n ],\n [\n -100.5029296875,\n 47.100044694025215\n ],\n [\n -100.32714843749999,\n 46.46813299215554\n ],\n [\n -100.2392578125,\n 45.82879925192134\n ],\n [\n -99.97558593749999,\n 45.02695045318546\n ],\n [\n -99.5361328125,\n 44.11914151643737\n ],\n [\n -98.26171875,\n 43.929549935614595\n ],\n [\n -97.03125,\n 43.89789239125797\n ],\n [\n -96.45996093749999,\n 44.276671273775186\n ],\n [\n -95.712890625,\n 43.866218006556394\n ],\n [\n -95.4052734375,\n 43.229195113965005\n ],\n [\n -94.921875,\n 42.68243539838623\n ],\n [\n -94.1748046875,\n 42.00032514831621\n ],\n [\n -93.6474609375,\n 41.77131167976407\n ],\n [\n -93.0322265625,\n 42.032974332441405\n ],\n [\n -92.6806640625,\n 42.94033923363181\n ],\n [\n -93.251953125,\n 43.89789239125797\n ],\n [\n -94.2626953125,\n 44.77793589631623\n ],\n [\n -95.2294921875,\n 45.521743896993634\n ],\n [\n -95.625,\n 45.67548217560647\n ],\n [\n -96.15234375,\n 47.100044694025215\n ],\n [\n -96.94335937499999,\n 48.45835188280866\n ],\n [\n -97.3828125,\n 49.095452162534826\n ],\n [\n -99.404296875,\n 50.875311142200765\n ],\n [\n -100.7666015625,\n 52.214338608258224\n ],\n [\n -102.4365234375,\n 53.35710874569601\n ],\n [\n -105.46875,\n 54.80068486732233\n ],\n [\n -108.3251953125,\n 56.24334992410525\n ],\n [\n -110.61035156249999,\n 57.16007826737998\n ],\n [\n -111.97265625,\n 57.77451753559619\n ],\n [\n -115.400390625,\n 57.088515327886505\n ],\n [\n -114.6533203125,\n 54.316523240258284\n ],\n [\n -114.5654296875,\n 51.37178037591739\n ],\n [\n -113.73046875,\n 48.83579746243093\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"s2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-04","publicationStatus":"PW","scienceBaseUri":"57aaff4ce4b05e859be0f5bf","contributors":{"authors":[{"text":"Steen, Valerie vsteen@usgs.gov","contributorId":5598,"corporation":false,"usgs":true,"family":"Steen","given":"Valerie","email":"vsteen@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":645033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":167829,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan K.","email":"skagens@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":645032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Melcher, Cynthia P. 0000-0002-8044-9689 melcherc@usgs.gov","orcid":"https://orcid.org/0000-0002-8044-9689","contributorId":5094,"corporation":false,"usgs":true,"family":"Melcher","given":"Cynthia","email":"melcherc@usgs.gov","middleInitial":"P.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":645034,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199855,"text":"70199855 - 2016 - A framework for effective use of hydroclimate models in climate-change adaptation planning for managed habitats with limited hydrologic response data","interactions":[],"lastModifiedDate":"2018-10-01T15:34:04","indexId":"70199855","displayToPublicDate":"2016-07-01T15:33:56","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"A framework for effective use of hydroclimate models in climate-change adaptation planning for managed habitats with limited hydrologic response data","docAbstract":"Climate-change adaptation planning for managed wetlands is challenging under uncertain futures when the impact of historic climate variability on wetland response is unquantified. We assessed vulnerability of Modoc National Wildlife Refuge (MNWR) through use of the Basin Characterization Model (BCM) landscape hydrology model, and six global climate models, representing projected wetter and drier conditions. We further developed a conceptual model that provides greater value for water managers by incorporating the BCM outputs into a conceptual framework that links modeled parameters to refuge management outcomes. This framework was used to identify landscape hydrology parameters that reflect refuge sensitivity to changes in (1) climatic water deficit (CWD) and recharge, and (2) the magnitude, timing, and frequency of water inputs. BCM outputs were developed for 1981–2100 to assess changes and forecast the probability of experiencing wet and dry water year types that have historically resulted in challenging conditions for refuge habitat management. We used a Yule’s Q skill score to estimate the probability of modeled discharge that best represents historic water year types. CWD increased in all models across 72.3–100 % of the water supply basin by 2100. Earlier timing in discharge, greater cool season discharge, and lesser irrigation season water supply were predicted by most models. Under the worst-case scenario, moderately dry years increased from 10–20 to 40–60 % by 2100. MNWR could adapt by storing additional water during the cool season for later use and prioritizing irrigation of habitats during dry years.
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