{"pageNumber":"82","pageRowStart":"2025","pageSize":"25","recordCount":16446,"records":[{"id":70197258,"text":"70197258 - 2018 - Long-term changes in pond permanence, size, and salinity in Prairie Pothole Region wetlands: The role of groundwater-pond interaction","interactions":[],"lastModifiedDate":"2018-05-25T10:10:36","indexId":"70197258","displayToPublicDate":"2018-05-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Long-term changes in pond permanence, size, and salinity in Prairie Pothole Region wetlands: The role of groundwater-pond interaction","docAbstract":"<div id=\"abst0010\"><p id=\"sect0015\"><strong>Study Region</strong></p><p id=\"spar0090\">Cottonwood Lake area wetlands, North Dakota, U.S.A.</p></div><div id=\"abst0015\"><p id=\"sect0020\"><strong>Study Focus</strong></p><p id=\"spar0095\">Fluctuations in pond permanence, size, and salinity are key features of prairie-pothole wetlands that provide a variety of wetland habitats for waterfowl in the northern prairie of North America. Observation of water-level and salinity fluctuations in a semi-permanent wetland pond over a 20-year period, included periods when the wetland occasionally was dry, as well as wetter years when the pond depth and surface extent doubled while volume increased 10 times.</p></div><div id=\"abst0020\"><p id=\"sect0025\"><strong>New hydrological insights for the study region</strong></p><p id=\"spar0100\">Compared to all other measured budget components, groundwater flow into the pond often contributed the least water (8–28 percent) but the largest amount (&gt;90 percent) of specific solutes to the water and solute budgets of the pond. In drier years flow from the pond into groundwater represented &gt; 10 percent of water loss, and in 1992 was approximately equal to evapotranspiration loss. Also during the drier years, export of calcium, magnesium, sodium, potassium, chloride, and sulfate by flow from the pond to groundwater was substantial compared with previous or subsequent years, a process that would have been undetected if groundwater flux had been calculated as a net value. Independent quantification of water and solute gains and losses were essential to understand controls on water-level and salinity fluctuations in the pond in response to variable climate conditions.</p></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2018.03.003","usgsCitation":"LaBaugh, J.W., Rosenberry, D.O., Mushet, D.M., Neff, B., Nelson, R., and Euliss, N.H., 2018, Long-term changes in pond permanence, size, and salinity in Prairie Pothole Region wetlands: The role of groundwater-pond interaction: Journal of Hydrology: Regional Studies, v. 17, p. 1-23, https://doi.org/10.1016/j.ejrh.2018.03.003.","productDescription":"23 p.","startPage":"1","endPage":"23","ipdsId":"IP-086270","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":468730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2018.03.003","text":"Publisher Index Page"},{"id":354492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d77e4b092d9651e1b2c","contributors":{"authors":[{"text":"LaBaugh, James W. 0000-0002-4112-2536 jlabaugh@usgs.gov","orcid":"https://orcid.org/0000-0002-4112-2536","contributorId":1311,"corporation":false,"usgs":true,"family":"LaBaugh","given":"James","email":"jlabaugh@usgs.gov","middleInitial":"W.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":736521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":736522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":736523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neff, Brian 0000-0003-3718-7350 bneff@usgs.gov","orcid":"https://orcid.org/0000-0003-3718-7350","contributorId":198885,"corporation":false,"usgs":true,"family":"Neff","given":"Brian","email":"bneff@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736524,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Richard D.","contributorId":55338,"corporation":false,"usgs":true,"family":"Nelson","given":"Richard D.","affiliations":[],"preferred":false,"id":736525,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Euliss, Ned H. Jr. ceuliss@usgs.gov","contributorId":2916,"corporation":false,"usgs":true,"family":"Euliss","given":"Ned","suffix":"Jr.","email":"ceuliss@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":736526,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197250,"text":"70197250 - 2018 - Assessing the impacts of dams and levees on the hydrologic record of the Middle and Lower Mississippi River, USA","interactions":[],"lastModifiedDate":"2018-05-24T10:46:20","indexId":"70197250","displayToPublicDate":"2018-05-24T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the impacts of dams and levees on the hydrologic record of the Middle and Lower Mississippi River, USA","docAbstract":"The impacts of dams and levees on the long-term (>130 years) discharge record was assessed along a ~1200 km segment of the Mississippi River between St. Louis, Missouri, and Vicksburg, Mississippi. To aid in our evaluation of dam impacts, we used data from the U.S. National Inventory of Dams to calculate the rate of reservoir expansion at five long-term hydrologic monitoring stations along the study segment. We divided the hydrologic record at each station into three periods: (1) a pre-rapid reservoir expansion period; (2) a rapid reservoir expansion period; and (3) a post-rapid reservoir expansion period. We then used three approaches to assess changes in the hydrologic record at each station. Indicators of hydrologic alteration (IHA) and flow duration hydrographs were used to quantify changes in flow conditions between the pre- and post-rapid reservoir expansion periods. Auto-regressive interrupted time series analysis (ARITS) was used to assess trends in maximum annual discharge, mean annual discharge, minimum annual discharge, and standard deviation of daily discharges within a given water year. A one-dimensional HEC-RAS hydraulic model was used to assess the impact of levees on flood flows. Our results revealed that minimum annual discharges and low-flow IHA parameters showed the most significant changes. Additionally, increasing trends in minimum annual discharge during the rapid reservoir expansion period were found at three out of the five hydrologic monitoring stations. These IHA and ARITS results support previous findings consistent with the observation that reservoirs generally have the greatest impacts on low-flow conditions. River segment scale hydraulic modeling revealed levees can modestly increase peak flood discharges, while basin-scale hydrologic modeling assessments by the U.S. Army Corps of Engineers showed that tributary reservoirs reduced peak discharges by a similar magnitude (2 to 30%). This finding suggests that the effects of dams and levees on peak flood discharges are in part offsetting one another along the modeled river segments and likely other substantially leveed segments of the Mississippi River.","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2018.01.004","usgsCitation":"Remo, J.W., Ickes, B., Ryherd, J.K., Guida, R.J., and Therrell, M.D., 2018, Assessing the impacts of dams and levees on the hydrologic record of the Middle and Lower Mississippi River, USA: Geomorphology, v. 313, p. 88-100, https://doi.org/10.1016/j.geomorph.2018.01.004.","productDescription":"13 p.","startPage":"88","endPage":"100","ipdsId":"IP-088232","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468733,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2018.01.004","text":"Publisher Index Page"},{"id":354450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River","volume":"313","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d78e4b092d9651e1b38","contributors":{"authors":[{"text":"Remo, Jonathan W.F. 0000-0002-8208-2091","orcid":"https://orcid.org/0000-0002-8208-2091","contributorId":205201,"corporation":false,"usgs":false,"family":"Remo","given":"Jonathan","email":"","middleInitial":"W.F.","affiliations":[{"id":32417,"text":"Southern Illinois University-Carbondale","active":true,"usgs":false}],"preferred":false,"id":736404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ickes, Brian 0000-0001-5622-3842 bickes@usgs.gov","orcid":"https://orcid.org/0000-0001-5622-3842","contributorId":2925,"corporation":false,"usgs":true,"family":"Ickes","given":"Brian","email":"bickes@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":736403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryherd, Julia K.","contributorId":205202,"corporation":false,"usgs":false,"family":"Ryherd","given":"Julia","email":"","middleInitial":"K.","affiliations":[{"id":32417,"text":"Southern Illinois University-Carbondale","active":true,"usgs":false}],"preferred":false,"id":736405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guida, Ross J.","contributorId":205203,"corporation":false,"usgs":false,"family":"Guida","given":"Ross","email":"","middleInitial":"J.","affiliations":[{"id":37056,"text":"Sam Houston State University","active":true,"usgs":false}],"preferred":false,"id":736406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Therrell, Matthew D.","contributorId":172810,"corporation":false,"usgs":false,"family":"Therrell","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":736407,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70197221,"text":"70197221 - 2018 - Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed","interactions":[],"lastModifiedDate":"2018-10-11T15:00:36","indexId":"70197221","displayToPublicDate":"2018-05-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed","docAbstract":"<p><span>The U.S. Geological Survey monthly water balance model (MWBM) was enhanced with the capability to simulate glaciers in order to make it more suitable for simulating cold region hydrology. The new model, MWBMglacier, is demonstrated in the heavily glacierized and ecologically important Copper River watershed in Southcentral Alaska. Simulated water budget components compared well to satellite‐based observations and ground measurements of streamflow, evapotranspiration, snow extent, and total water storage, with differences ranging from 0.2% to 7% of the precipitation flux. Nash Sutcliffe efficiency for simulated and observed streamflow was greater than 0.8 for six of eight stream gages. Snow extent matched satellite‐based observations with Nash Sutcliffe efficiency values of greater than 0.89 in the four Copper River ecoregions represented. During the simulation period 1949 to 2009, glacier ice melt contributed 25% of total runoff, ranging from 12% to 45% in different tributaries, and glacierized area was reduced by 6%. Statistically significant (</span><i>p</i><span>&nbsp;&lt;&nbsp;0.05) decreasing and increasing trends in annual glacier mass balance occurred during the multidecade cool and warm phases of the Pacific Decadal Oscillation, respectively, reinforcing the link between climate perturbations and glacier mass balance change. The simulations of glaciers and total runoff for a large, remote region of Alaska provide useful data to evaluate hydrologic, cryospheric, ecologic, and climatic trends. MWBM glacier is a valuable tool to understand when, and to what extent, streamflow may increase or decrease as glaciers respond to a changing climate.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2017JF004482","usgsCitation":"Valentin, M.M., Viger, R.J., Van Beusekom, A.E., Hay, L.E., Hogue, T.S., and Foks, N.L., 2018, Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed: Journal of Geophysical Research F: Earth Surface, v. 123, no. 5, p. 1116-1132, https://doi.org/10.1029/2017JF004482.","productDescription":"17 p.","startPage":"1116","endPage":"1132","ipdsId":"IP-094374","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":468839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jf004482","text":"Publisher Index Page"},{"id":354424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-23","publicationStatus":"PW","scienceBaseUri":"5b155d78e4b092d9651e1b3c","contributors":{"authors":[{"text":"Valentin, Melissa M.","contributorId":205172,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","email":"","middleInitial":"M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":736281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":147818,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":736280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Beusekom, Ashley E. 0000-0002-6996-978X beusekom@usgs.gov","orcid":"https://orcid.org/0000-0002-6996-978X","contributorId":3992,"corporation":false,"usgs":true,"family":"Van Beusekom","given":"Ashley","email":"beusekom@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":736284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foks, Nathan Leon","contributorId":194012,"corporation":false,"usgs":false,"family":"Foks","given":"Nathan","email":"","middleInitial":"Leon","affiliations":[],"preferred":false,"id":736285,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70200455,"text":"70200455 - 2018 - Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios","interactions":[],"lastModifiedDate":"2018-10-18T13:45:55","indexId":"70200455","displayToPublicDate":"2018-05-22T13:45:44","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios","docAbstract":"<p><span>Climatically driven changes in snow characteristics (snowfall, snowpack, and snowmelt) will affect hydrologic and ecological systems in Alaska over the coming century, yet there exist no projections of downscaled future snow pack metrics for the state of Alaska. We updated historical and projected snow day fraction (PSF, the fraction of days with precipitation falling as snow) from McAfee et al. We developed modeled snowfall equivalent (SFE) derived from the product of snow-day fraction (PSF) and existing gridded precipitation for Alaska from Scenarios Network for Alaska and Arctic Planning (SNAP). We validated the assumption that modeled SFE approximates historical decadally averaged snow water equivalent (SWE) observations from snowcourse and Snow Telemetry (SNOTEL) sites. We present analyses of future downscaled PSF and two new products, October–March SFE and ratio of snow fall equivalent to precipitation (SFE:P) based on bias-corrected statistically downscaled projections of Coupled Model Intercomparison Project 5 (CMIP5) Global Climate Model (GCM) temperature and precipitation for the state of Alaska. We analyzed mid-century (2040–2069) and late-century (2070–2099) changes in PSF, SFE, and SFE:P relative to historical (1970–1999) mean temperature and present results for Alaska climate divisions and 12-digit Hydrologic Unit Code (HUC12) watersheds. Overall, estimated historical the SFE is reasonably well related to the observed SWE, with correlations over 0.75 in all decades, and correlations exceeding 0.9 in the 1960s and 1970s. In absolute terms, SFE is generally biased low compared to the observed SWE. PSF and SFE:P decrease universally across Alaska under both Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 emissions scenarios, with the smallest changes for RCP 4.5 in 2040–2069 and the largest for RCP 8.5 in 2070–2099. The timing and magnitude of maximum decreases in PSF vary considerably with regional average temperature, with the largest changes in months at the beginning and end of the snow season. Mean SFE changes vary widely among climate divisions, ranging from decreases between −17 and −58% for late twenty-first century in southeast, southcentral, west coast and southwest Alaska to increases up to 21% on the North Slope. SFE increases most at highest elevations and latitudes and decreases most in coastal southern Alaska. SFE:P ratios indicate a broad switch from snow-dominated to transitional annual hydrology across most of southern Alaska by mid-century, and from transitional to rain-dominated watersheds in low elevation parts of southeast Alaska by the late twenty-first century.&nbsp;</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w10050668","usgsCitation":"Littell, J., McAfee, S., and Hayward, G.D., 2018, Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios: Water, v. 10, no. 5, p. 1-16, https://doi.org/10.3390/w10050668.","productDescription":"Article 668; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-097141","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":468739,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10050668","text":"Publisher Index 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D.","contributorId":209846,"corporation":false,"usgs":false,"family":"Hayward","given":"Gregory","email":"","middleInitial":"D.","affiliations":[{"id":38010,"text":"US Forest Service, Alaska Region","active":true,"usgs":false}],"preferred":false,"id":748950,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196405,"text":"sir20185055 - 2018 - Effects of surface-water and groundwater inflows and outflows on the hydrology of the Tsala Apopka Lake Basin in Citrus County, Florida","interactions":[],"lastModifiedDate":"2018-09-25T06:21:32","indexId":"sir20185055","displayToPublicDate":"2018-05-21T00:00:00","publicationYear":"2018","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":"2018-5055","title":"Effects of surface-water and groundwater inflows and outflows on the hydrology of the Tsala Apopka Lake Basin in Citrus County, Florida","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Southwest Florida Water Management District, initiated a study to quantify the inflows and outflows in the Floral City, Inverness, and Hernando pools of the Tsala Apopka Lake Basin in Citrus County, Florida. This study assesses hydrologic changes in pool stages, groundwater levels, spring flows, and streamflows caused by the diversion of streamflow from the Withlacoochee River to the Tsala Apopka Lake Basin through water-control structures. A surface-water/groundwater flow model was developed using hydraulic parameters for lakes, streams, the unsaturated zone, and the underlying surficial and Upper Floridan aquifers estimated using an inverse modeling calibration technique. After calibration, the model was used to assess the relation between inflows and outflows in the Tsala Apopka Lake Basin and changes in pool stages.</p><p>Simulation results using the calibrated surface-water/groundwater flow model showed that leakage rates from the pools to the Upper Floridan aquifer were largest at the deep lake cells and that these leakage rates to the Upper Floridan aquifer were the highest in the model area. Downward leakage to the Upper Floridan aquifer occurred beneath most of the extent of the Floral City, Inverness, and Hernando pools. These leakage rates depended on the lakebed leakance and the difference between lake stages and heads in the Upper Floridan aquifer. Leakage rates were higher for the Floral City pool than for the Inverness pool, and higher for the Inverness pool than for the Hernando pool. Lakebed leakance was higher for the Floral City pool than for the Hernando pool, and higher for the Hernando pool than for the Inverness pool.</p><p>Simulation results showed that the average recharge rate to the surficial aquifer was 10.3 inches per year for the 2004 to 2012 simulation period. Areas that recharge the surficial aquifer covered about 86 percent of the model area. Simulations identified areas along segments of the Withlacoochee River and within land-surface depressions that receive water from the surficial aquifer. Recharge rates were largest in physiographic regions having a deep water table. Simulated heads in the Upper Floridan aquifer indicated the general flow directions in the active flow model area were from the northeast toward the southwest and then westward toward the coast, and from the southeast toward the northwest and then westward toward the coast, consistent with flow directions inferred from the estimated potentiometric surface map for May 2010. The largest inflow in the water budget of the Upper Floridan aquifer was downward leakage from the overlying hydrogeologic unit. The largest outflow in the water budget of the Upper Floridan aquifer was spring flow.</p><p>The calibrated surface-water and groundwater flow model was used to simulate hydrologic scenarios that included changes in rainfall rates, projected increases in groundwater pumping rates for 2025 and 2035, no flow for the 2004–12 period through the eight water-control structures in the Tsala Apopka Lake Basin, and the removal of the Inglis Dam and the Inglis Bypass Spillway on Lake Rousseau. Scenario simulation results were compared to annual average calibrated water levels and flows from 2004 to 2012. Simulated declines in the Tsala Apopka Lake pool stages under the 10-percent lower rainfall scenario were about 0.8, 0.3, and 1.3 feet (ft) for the Floral City, Inverness, and Hernando pools, respectively. Simulated groundwater levels under the same scenario declined up to 5.4 ft in the surficial aquifer and up to 2.9 ft in the Upper Floridan aquifer. Under the projected increases in groundwater pumping rates for 2035 that represented an increase of 36 percent from average 2004 to 2012 pumping rates, the simulated declines in the Floral City, Inverness, and Hernando pool stages were, in downstream order, 0.02, 0.06, and 0.04 ft. The largest drawdown under the projected increases in groundwater pumping rates for 2035 was 2.1 ft in the surficial aquifer and about 1.8 ft in the Upper Floridan aquifer. A scenario of decreased rainfall by 10 percent caused&nbsp;greater declines in water levels and pool stages than projected increases in groundwater pumping rates. The simulation with no flow through the eight Tsala Apopka Lake water-control structures resulted in simulated declines in average pool stage of 1.8, 1.9, and 0.5 ft in the Floral City, Inverness, and Hernando pools, respectively. The simulated removal of the two water-control structures in Lake Rousseau caused flow to increase at Rainbow Springs by 28 cubic feet per second, an increase of 4.7 percent from the average calibrated flow for 2004 to 2012.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185055","collaboration":"Prepared in cooperation with the Southwest Florida Water Management District","usgsCitation":"Sepúlveda, N., Fulkerson, M., Basso, R., and Ryan, P.J., 2018, Effects of surface-water and groundwater inflows and outflows on the hydrology of the Tsala Apopka Lake Basin in Citrus County, Florida: U.S. Geological Survey Scientific Investigations Report 2018–5055, 137 p., https://doi.org/10.3133/sir20185055.","productDescription":"Report: vii, 137 p.; Data Release","numberOfPages":"150","onlineOnly":"Y","ipdsId":"IP-066230","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":354255,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QF8RS2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data sets for simulation of effects of surface-water and groundwater inflows and outflows on the hydrology of the Tsala Apopka Lake Basin in Citrus County, Florida"},{"id":354253,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5055/coverthb2.jpg"},{"id":354254,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5055/sir20185055.pdf","text":"Report","size":"41.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5055"}],"country":"United States","state":"Florida","county":"Citrus County","otherGeospatial":"Tsala Apopka Lake Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.81494140625,\n              28.168875180063345\n            ],\n            [\n              -81.650390625,\n              28.168875180063345\n            ],\n            [\n              -81.650390625,\n              29.16895060109228\n            ],\n            [\n              -82.81494140625,\n              29.16895060109228\n            ],\n            [\n              -82.81494140625,\n              28.168875180063345\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\" data-mce-href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\">Caribbean-Florida Water Science Center</a>&nbsp;<br>U.S. Geological Survey<br>4446 Pet Lane, Suite 108<br>Lutz, FL 33559</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Summary of Model Results<br></li><li>Simulation of Hydrologic Changes Effected by Variations in the Hydrologic System<br></li><li>Model Limitations<br></li><li>Summary and Conclusions<br></li><li>References Cited<br></li><li>Appendix 1. Model Construction and Calibration<br></li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2018-05-21","noUsgsAuthors":false,"publicationDate":"2018-05-21","publicationStatus":"PW","scienceBaseUri":"5b155d7ae4b092d9651e1b58","contributors":{"authors":[{"text":"Sepulveda, Nicasio 0000-0002-6333-1865 nsepul@usgs.gov","orcid":"https://orcid.org/0000-0002-6333-1865","contributorId":1454,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Nicasio","email":"nsepul@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":732787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fulkerson, Mark","contributorId":203972,"corporation":false,"usgs":false,"family":"Fulkerson","given":"Mark","affiliations":[{"id":36777,"text":"SWFWMD","active":true,"usgs":false}],"preferred":false,"id":732788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Basso, Ron","contributorId":203973,"corporation":false,"usgs":false,"family":"Basso","given":"Ron","email":"","affiliations":[{"id":36777,"text":"SWFWMD","active":true,"usgs":false}],"preferred":false,"id":732789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Patrick J. 0000-0002-1490-4938 pryan@usgs.gov","orcid":"https://orcid.org/0000-0002-1490-4938","contributorId":203974,"corporation":false,"usgs":true,"family":"Ryan","given":"Patrick","email":"pryan@usgs.gov","middleInitial":"J.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":732790,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198551,"text":"70198551 - 2018 - Longevity and population age structure of the arroyo southwestern toad (Anaxyrus californicus) with drought implications","interactions":[],"lastModifiedDate":"2018-08-07T12:26:46","indexId":"70198551","displayToPublicDate":"2018-05-20T11:50:18","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Longevity and population age structure of the arroyo southwestern toad (<i> Anaxyrus californicus</i>) with drought implications","title":"Longevity and population age structure of the arroyo southwestern toad (Anaxyrus californicus) with drought implications","docAbstract":"<p><span>The arroyo southwestern toad is a specialized and federally endangered amphibian endemic to the coastal plains and mountains of central and southern California and northwestern Baja California. It is largely unknown how long these toads live in natural systems, how their population demographics vary across occupied drainages, and how hydrology affects age structure. We used skeletochronology to estimate the ages of adult arroyo toads in seven occupied drainages with varying surface water hydrology in southern California. We processed 179 adult toads with age estimates between 1 and 6&nbsp;years. Comparisons between skeletochronological ages and known ages of PIT tagged toads showed that skeletochronology likely underestimated toad age by up to 2&nbsp;years, indicating they may live to 7 or 8&nbsp;years, but nonetheless major patterns were evident. Arroyo toads showed sexual size dimorphism with adult females reaching a maximum size of 12&nbsp;mm greater than males. Population age structure varied among the sites. Age structure at sites with seasonally predictable surface water was biased toward younger individuals, which indicated stable recruitment for these populations. Age structures at the ephemeral sites were biased toward older individuals with cohorts roughly corresponding to higher rainfall years. These populations are driven by surface water availability, a stochastic process, and thus more unstable. Based on our estimates of toad ages, climate predictions of extreme and prolonged drought events could mean that the number of consecutive dry years could surpass the maximum life span of toads making them vulnerable to extirpation, especially in ephemeral freshwater systems. Understanding the relationship between population demographics and hydrology is essential for predicting species resilience to projected changes in weather and rainfall patterns. The arroyo toad serves as a model for understanding potential responses to climatic and hydrologic changes in Mediterranean stream systems. We recommend development of adaptive management strategies to address these threats.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4158","usgsCitation":"Fisher, R.N., Brehme, C.S., Hathaway, S.A., Hovey, T.E., Warburton, M.L., and Stokes, D.C., 2018, Longevity and population age structure of the arroyo southwestern toad (Anaxyrus californicus) with drought implications: Ecology and Evolution, v. 8, no. 12, p. 6124-6132, https://doi.org/10.1002/ece3.4158.","productDescription":"9 p.","startPage":"6124","endPage":"6132","ipdsId":"IP-095515","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468742,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4158","text":"Publisher Index Page"},{"id":356281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.01239013671874,\n              32.579220642875676\n            ],\n            [\n              -116.68853759765626,\n              32.579220642875676\n            ],\n            [\n              -116.68853759765626,\n              34.04583232505719\n            ],\n            [\n              -118.01239013671874,\n              34.04583232505719\n            ],\n            [\n              -118.01239013671874,\n              32.579220642875676\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"12","noUsgsAuthors":false,"publicationDate":"2018-05-20","publicationStatus":"PW","scienceBaseUri":"5b6fc450e4b0f5d57878ea4d","contributors":{"authors":[{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brehme, Cheryl S. 0000-0001-8904-3354 cbrehme@usgs.gov","orcid":"https://orcid.org/0000-0001-8904-3354","contributorId":3419,"corporation":false,"usgs":true,"family":"Brehme","given":"Cheryl","email":"cbrehme@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hathaway, Stacie A. 0000-0002-4167-8059 sahathaway@usgs.gov","orcid":"https://orcid.org/0000-0002-4167-8059","contributorId":3420,"corporation":false,"usgs":true,"family":"Hathaway","given":"Stacie","email":"sahathaway@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hovey, Tim E.","contributorId":206822,"corporation":false,"usgs":false,"family":"Hovey","given":"Tim","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":741874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warburton, Manna L.","contributorId":174875,"corporation":false,"usgs":false,"family":"Warburton","given":"Manna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":741875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stokes, Drew C.","contributorId":33836,"corporation":false,"usgs":true,"family":"Stokes","given":"Drew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":741876,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197124,"text":"70197124 - 2018 - Do downscaled general circulation models reliably simulate historical climatic conditions?","interactions":[],"lastModifiedDate":"2018-05-18T09:43:34","indexId":"70197124","displayToPublicDate":"2018-05-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Do downscaled general circulation models reliably simulate historical climatic conditions?","docAbstract":"The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.","language":"English","publisher":"American Meteorological Society","doi":"10.1175/EI-D-17-0018.1","usgsCitation":"Bock, A.R., Hay, L.E., McCabe, G., Markstrom, S.L., and Atkinson, R.D., 2018, Do downscaled general circulation models reliably simulate historical climatic conditions?: Earth Interactions, v. 22, p. 1-22, https://doi.org/10.1175/EI-D-17-0018.1.","productDescription":"Paper 10; 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-090110","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":468746,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/ei-d-17-0018.1","text":"Publisher Index Page"},{"id":354299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","scienceBaseUri":"5afee6b2e4b0da30c1bfbd46","contributors":{"authors":[{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":735759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":735770,"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":735771,"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":735772,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, R. Dwight","contributorId":195660,"corporation":false,"usgs":false,"family":"Atkinson","given":"R.","email":"","middleInitial":"Dwight","affiliations":[],"preferred":false,"id":735773,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70197075,"text":"70197075 - 2018 - A mechanistic assessment of seasonal microhabitat selection by drift-feeding rainbow trout Oncorhynchus mykiss in a southwestern headwater stream","interactions":[],"lastModifiedDate":"2018-05-18T09:56:20","indexId":"70197075","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A mechanistic assessment of seasonal microhabitat selection by drift-feeding rainbow trout <i>Oncorhynchus mykiss</i> in a southwestern headwater stream","title":"A mechanistic assessment of seasonal microhabitat selection by drift-feeding rainbow trout Oncorhynchus mykiss in a southwestern headwater stream","docAbstract":"<p><span>The positioning of fishes within a riverscape is dependent on the proximity of complementary habitats. In this study, foraging and non-foraging habitat were quantified monthly over an entire year for a rainbow trout (</span><i class=\"EmphasisTypeItalic \">Oncorhynchus mykiss</i><span>) population in an isolated, headwater stream in southcentral New Mexico. The stream follows a seasonal thermal and hydrologic pattern typical for a Southwestern stream and was deemed suitable for re-introduction of the native and close relative, Rio Grande cutthroat trout (</span><i class=\"EmphasisTypeItalic \">O. clarkii virginalis</i><span>). However, uncertainty associated with limited habitat needed to be resolved if repatriation of the native fish was to be successful. Habitat was evaluated using resource selection functions with a mechanistic drift-foraging model to explain trout distributions. Macroinvertebrate drift was strongly season- and temperature-dependent (lower in winter and spring, higher in summer and fall). Models identified stream depth as the most limiting factor for habitat selection across seasons and size-classes. Additionally, positions closer to cover were selected during the winter by smaller size-classes (0, 1, 2), while net energy intake was important during the spring for most size-classes (0, 1, 2, 3). Drift-foraging models identified that 81% of observed trout selected positions that could meet maintenance levels throughout the year. Moreover, 40% of selected habitats could sustain maximum growth. Stream positions occupied by rainbow trout were more energetically profitable than random sites regardless of season or size-class. Larger size-classes (3, 4+) were energetically more limited throughout the year than were smaller size-classes. This research suggests that habitat in the form of deep pools is of paramount importance for rainbow trout or native cutthroat trout.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10641-017-0696-9","usgsCitation":"Kalb, B.W., Huntsman, B.M., Caldwell, C.A., and Bozek, M.A., 2018, A mechanistic assessment of seasonal microhabitat selection by drift-feeding rainbow trout Oncorhynchus mykiss in a southwestern headwater stream: Environmental Biology of Fishes, v. 202, no. 2, p. 257-273, https://doi.org/10.1007/s10641-017-0696-9.","productDescription":"16 p.","startPage":"257","endPage":"273","ipdsId":"IP-085358","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.314453125,\n              31.89621446335144\n            ],\n            [\n              -104.0185546875,\n              31.89621446335144\n            ],\n            [\n              -104.0185546875,\n              34.57895241036948\n            ],\n            [\n              -107.314453125,\n              34.57895241036948\n            ],\n            [\n              -107.314453125,\n              31.89621446335144\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"202","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-30","publicationStatus":"PW","scienceBaseUri":"5afee6b9e4b0da30c1bfbd62","contributors":{"authors":[{"text":"Kalb, Bradley W.","contributorId":201490,"corporation":false,"usgs":false,"family":"Kalb","given":"Bradley","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":735680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntsman, Brock M. 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":166748,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock","email":"","middleInitial":"M.","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":735681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Colleen A. 0000-0002-4730-4867 ccaldwel@usgs.gov","orcid":"https://orcid.org/0000-0002-4730-4867","contributorId":3050,"corporation":false,"usgs":true,"family":"Caldwell","given":"Colleen","email":"ccaldwel@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735488,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bozek, Michael A.","contributorId":51030,"corporation":false,"usgs":true,"family":"Bozek","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":735682,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196934,"text":"70196934 - 2018 - Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning","interactions":[],"lastModifiedDate":"2018-09-10T11:32:27","indexId":"70196934","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning","docAbstract":"<p><span>Early warning for rainfall-induced shallow landsliding can help reduce fatalities and economic losses. Although these commonly occurring landslides are typically triggered by subsurface hydrological processes, most early warning criteria rely exclusively on empirical rainfall thresholds and other indirect proxies for subsurface wetness. We explore the utility of explicitly accounting for antecedent wetness by integrating real-time subsurface hydrologic measurements into landslide early warning criteria. Our efforts build on previous progress with rainfall thresholds, monitoring, and numerical modeling along the landslide-prone railway corridor between Everett and Seattle, Washington, USA. We propose a modification to a previously established recent versus antecedent (RA) cumulative rainfall thresholds by replacing the antecedent 15-day rainfall component with an average saturation observed over the same timeframe. We calculate this antecedent saturation with real-time telemetered measurements from five volumetric water content probes installed in the shallow subsurface within a steep vegetated hillslope. Our hybrid rainfall versus saturation (RS) threshold still relies on the same recent 3-day rainfall component as the existing RA thresholds, to facilitate ready integration with quantitative precipitation forecasts. During the 2015–2017 monitoring period, this RS hybrid approach has an increase of true positives and a decrease of false positives and false negatives relative to the previous RA rainfall-only thresholds. We also demonstrate that alternative hybrid threshold formats could be even more accurate, which suggests that further development and testing during future landslide seasons is needed. The positive results confirm that accounting for antecedent wetness conditions with direct subsurface hydrologic measurements can improve thresholds for alert systems and early warning of rainfall-induced shallow landsliding.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10346-018-0995-z","usgsCitation":"Mirus, B.B., Becker, R.E., Baum, R.L., and Smith, J.B., 2018, Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning: Landslides, v. 15, no. 10, p. 1909-1919, https://doi.org/10.1007/s10346-018-0995-z.","productDescription":"11 p.","startPage":"1909","endPage":"1919","ipdsId":"IP-093501","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":354283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-15","publicationStatus":"PW","scienceBaseUri":"5afee6bae4b0da30c1bfbd6e","contributors":{"authors":[{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":735057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Becker, Rachel E. 0000-0002-2546-1706","orcid":"https://orcid.org/0000-0002-2546-1706","contributorId":204809,"corporation":false,"usgs":false,"family":"Becker","given":"Rachel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":735058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":735059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":735060,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70190581,"text":"sir20175100 - 2018 - Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona","interactions":[],"lastModifiedDate":"2019-05-15T09:24:27","indexId":"sir20175100","displayToPublicDate":"2018-05-15T00:00:00","publicationYear":"2018","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":"2017-5100","title":"Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona","docAbstract":"<p>A 3-year study was undertaken to evaluate the suitability of the available modeling tools for characterizing environmental flows in the middle Verde River watershed of central Arizona, describe riparian vegetation throughout the watershed, and estimate sediment mobilization in the river. Existing data on fish and macroinvertebrates were analyzed in relation to basin characteristics, flow regimes, and microhabitat, and a pilot study was conducted that sampled fish and macroinvertebrates and the microhabitats in which they were found. The sampling for the pilot study took place at five different locations in the middle Verde River watershed. This report presents the results of this 3-year study.&nbsp;</p><p>The Northern Arizona Groundwater Flow Model (NARGFM) was found to be capable of predicting long-term changes caused by alteration of regional recharge (such as may result from climate variability) and groundwater pumping in gaining, losing, and dry reaches of the major streams in the middle Verde River watershed. Over the period 1910 to 2006, the model simulated an increase in dry reaches, a small increase in reaches losing discharge to the groundwater aquifer, and a concurrent decrease in reaches gaining discharge from groundwater. Although evaluations of the suitability of using the NARGFM and Basin Characteristic Model to characterize various streamflow intervals showed that smallerscale basin monthly runoff could be estimated adequately at locations of interest, monthly stream-flow estimates were found unsatisfactory for determining environmental flows.</p><p>Orthoimagery and Moderate Resolution Imaging Spectroradiometer data were used to quantify stream and riparian vegetation properties related to biotic habitat. The relative abundance of riparian vegetation varied along the main channel of the Verde River. As would be expected, more upland plant species and fewer lowland species were found in the upper-middle section compared to the lower-middle section, and vice-versa. Vegetation changes within the upper-middle and lower-middle reaches are related to differences in climate and hydrology. In general, the riparian vegetation of the middle Verde River watershed is that of a healthy ecosystem’s mixed age, mixed patch structure, likely a result of the mostly unaltered disturbance regime.</p><p>The frequency of in-river hydrogeomorphic features (pool, riffle, run) varied along the middle Verde River channel. There was a greater abundance of riffle habitat in the upper-middle reach; the lower-middle reach included more pool habitat. The Oak Creek tributary was more homogenous in geomorphic stream habitat composition than West Clear Creek, where runs dominated the upper reaches and pools dominated many of the lower reaches.</p><p>On the basis of the period of record and discharges recorded at 15-minute intervals, five flows were found to reach the gravel-transport threshold. Sediment mobilization computed with flows averaged over daily time steps yielded just three flows that reached the gravel-transport threshold, and monthly averaged flows yielded none. In the middle Verde River watershed, 15-minute data should be used when possible to evaluate sediment transport in the river system.</p><p>Data from more than 300 fish surveys conducted from 1992 to 2011 were analyzed using two schemes, one that divided the river into five reaches based on basin characteristics, and a second that divided the river into five reaches based on degree of flow alteration (specifically, diversions). Fish community metrics and assemblage data were used to analyze patterns of species composition and abundance in the two approaches. Overall, native and non-native species were regularly interacting and probably competing for similar resources. Fish abundances were also analyzed in response to floods and other flow metrics. Although the data are limited, native fish abundances increased more rapidly than non-native fish abundances in response to large floods. The basin-characteristic reach analysis showed native fish in greater abundance in the upper-middle reaches of the Verde River watershed and generally decreasing with downstream distance. The median relative abundance of native fish decreased by 50 percent from reach 1 to reach 5. Using the reach scheme based on degree of flow alteration, nondiverted reaches were found to have a greater abundance of native fish than diverted reaches. In heavily diverted reaches, non-native species outnumbered native species.</p><p>Fish metrics and stream-flow metrics for the 30, 90, and 365-day periods before collection were computed and the results analyzed statistically. Only abundance of all fish species was associated with the 30-day flow metrics. The 90-day&nbsp;flow metrics were generally positively associated with fish metrics, whereas the 365-day flow metrics had more negative correlations. In particular, significant relations were found between fish metrics and the magnitude and frequency of high flows, including maximum monthly flow, median annual number of high-flow events, and median annual maximum streamflow. Native sucker (Catostomidae) populations tended to decrease in periods of extended base flow, and fish in the non-native sunfish family (Centrarchidae) decreased in periods of flashy, high magnitude flows.</p><p>A pilot study surveyed fish at five locations in the upper part of the middle Verde River watershed as a means to measure microhabitat availability and quantify native and non-native fish use of that available microhabitat. Results indicated that native and non-native species exhibit some clear differences in microhabitat use. Although at least some native and non-native fish were found in each velocity, depth, and substrate category, preferential microhabitat use was common. On a percentage basis, non-native species had a strong preference for slow-moving and deeper water with silt and sand substrate, with a secondary preference for faster moving and very shallow water and a coarse gravel substrate. Native species showed a general preference for somewhat faster, moderate depth water over coarse gravel and had no clear secondary preference.</p><p>Macroinvertebrate-variables index period, high-flow year, and collection location (upper-middle Verde River, lowermiddle Verde River, or Verde River tributaries) were found to be important explanatory variables in differentiating among community metrics. Overall richness (number of unique taxa), Shannon’s diversity index, and the percent of the most dominant taxa were all highly correlated, but their response to each macroinvertebrate variable was different. The percentage of mayfly (order Ephemeroptera) taxa was significantly higher in Oak Creek and the upper-middle and lower-middle Verde River reaches, locations which have higher flows and more urbanization than other reaches. When community metrics were related to hydrologic metrics, caddisfly (order Trichoptera) populations appeared to increase and mayfly populations to decrease in response to less flashy and more stable streamflows. Conversely, caddisfly populations appeared to decrease and mayfly populations to increase in response to greater flow variability.</p><p>Six locations along the Verde River were sampled for macroinvertebrates as part of a pilot study associated with this report—(1) below Granite Creek, (2) near Campbell Ranch, (3) at the U.S. Geological Survey Paulden gage, (4) at the Perkinsville Bridge, (5) at the USGS Clarkdale gage, and (6) near the Reitz Ranch property. A nonmetric multidimensional scaling ordination of macroinvertebrate assemblages showed that the Verde River below Granite Creek site was different from the five other sites and that the Perkinsville Bridge and near Reitz Ranch samples had similar community structure. The near Campbell Ranch and Paulden gage locations had similar microhabitat characteristics, with the exception of riparian cover, yet the assemblage structure was very different. The different community composition at Verde River below Granite Creek was likely due to it having the smallest substrate sizes, lowest velocities, shallowest depths, and most riparian cover of the six sites.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175100","collaboration":"Prepared in cooperation with The Nature Conservancy and Salt River Project","usgsCitation":"Paretti, N.V., Brasher, A.M.D., Pearlstein, S.L., Skow, D.M., Gungle, Bruce, and Garner, B.D., 2018, Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona: U.S. Geological Survey Scientific Investigations Report 2017–5100, 104 p., https://doi.org/10.3133/sir20175100.","productDescription":"Report: xii; 104 p.; 3 Tables","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084364","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":354141,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_table14.csv","text":"Table 14","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"Scientific Investigation Report 2017-5100 Table 12"},{"id":354142,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_tables12_14.xlsx","text":"Table 12 and 14","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Scientific Investigation Report 2017-5100 Table 12 and 14 Excel file"},{"id":354139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigation Report 2017-5100"},{"id":354138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5100/coverthb.jpg"},{"id":354140,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_table12.csv","text":"Table 12","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"Scientific Investigation Report 2017-5100 Table 12"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River Watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.5,\n              34.5\n            ],\n            [\n              -112.5,\n              34.5\n            ],\n            [\n              -112.5,\n              35.5\n            ],\n            [\n              -111.5,\n              35.5\n            ],\n            [\n              -111.5,\n              34.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p class=\"m_-6831585728661646797m_-183912103513208559gmail-m_8963803729901694701gmail-p1\"><span class=\"m_-6831585728661646797m_-183912103513208559gmail-m_8963803729901694701gmail-s1\"><a href=\"mailto:dc_az@usgs.gov\" target=\"_blank\" data-mce-href=\"mailto:dc_az@usgs.gov\">Director</a></span><span class=\"m_-6831585728661646797m_-183912103513208559gmail-m_8963803729901694701gmail-s2\">,<span class=\"m_-6831585728661646797m_-183912103513208559gmail-m_8963803729901694701gmail-Apple-converted-space\">&nbsp;<br></span></span><span class=\"m_-6831585728661646797m_-183912103513208559gmail-m_8963803729901694701gmail-s1\"><a href=\"https://az.water.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://az.water.usgs.gov/\">Arizona Water Science Center<br></a></span><span class=\"m_-6831585728661646797m_-183912103513208559gmail-m_8963803729901694701gmail-s1\"><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey<br></a></span><span class=\"m_-6831585728661646797m_-183912103513208559gmail-m_8963803729901694701gmail-s1\">520 N. Park Avenue<br></span><span class=\"m_-6831585728661646797m_-183912103513208559gmail-m_8963803729901694701gmail-s1\">Tucson, AZ 85719</span></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Purpose and Scope<br></li><li>Physical Setting<br></li><li>Surface Water and Groundwater<br></li><li>Riparian Vegetation<br></li><li>Geomorphology<br></li><li>Fish and Macroinvertebrates<br></li><li>Fish<br></li><li>Macroinvertebrates<br></li><li>Conclusion and Future Directions<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-05-15","noUsgsAuthors":false,"publicationDate":"2018-05-15","publicationStatus":"PW","scienceBaseUri":"5afee6bde4b0da30c1bfbd8c","contributors":{"authors":[{"text":"Paretti, Nicholas V. 0000-0003-2178-4820 nparetti@usgs.gov","orcid":"https://orcid.org/0000-0003-2178-4820","contributorId":173412,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas","email":"nparetti@usgs.gov","middleInitial":"V.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709893,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brasher, Anne M. D. abrasher@usgs.gov","contributorId":1715,"corporation":false,"usgs":true,"family":"Brasher","given":"Anne","email":"abrasher@usgs.gov","middleInitial":"M. D.","affiliations":[],"preferred":true,"id":709894,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearlstein, Susanna L.","contributorId":196282,"corporation":false,"usgs":false,"family":"Pearlstein","given":"Susanna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":709895,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skow, Dena M.","contributorId":196283,"corporation":false,"usgs":false,"family":"Skow","given":"Dena","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":709896,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gungle, Bruce 0000-0001-6406-1206 bgungle@usgs.gov","orcid":"https://orcid.org/0000-0001-6406-1206","contributorId":2237,"corporation":false,"usgs":true,"family":"Gungle","given":"Bruce","email":"bgungle@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709897,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garner, Bradley D. 0000-0002-6912-5093 bdgarner@usgs.gov","orcid":"https://orcid.org/0000-0002-6912-5093","contributorId":2133,"corporation":false,"usgs":true,"family":"Garner","given":"Bradley","email":"bdgarner@usgs.gov","middleInitial":"D.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":709898,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196889,"text":"70196889 - 2018 - Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows","interactions":[],"lastModifiedDate":"2018-05-21T13:03:19","indexId":"70196889","displayToPublicDate":"2018-05-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows","docAbstract":"<p><span>The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel (</span><i>Parvaspina steinstansana</i><span>) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).</span></p>","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/697947","usgsCitation":"Drew, C.A., Eddy, M., Kwak, T.J., Cope, W., and Augspurger, T., 2018, Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows: Freshwater Science, v. 37, no. 2, p. 343-356, https://doi.org/10.1086/697947.","productDescription":"14 p.","startPage":"343","endPage":"356","ipdsId":"IP-095471","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","volume":"37","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6bee4b0da30c1bfbd94","contributors":{"authors":[{"text":"Drew, C. Ashton","contributorId":140953,"corporation":false,"usgs":false,"family":"Drew","given":"C.","email":"","middleInitial":"Ashton","affiliations":[],"preferred":false,"id":735242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eddy, Michele","contributorId":198941,"corporation":false,"usgs":false,"family":"Eddy","given":"Michele","email":"","affiliations":[],"preferred":false,"id":735243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":735244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Augspurger, Tom","contributorId":189894,"corporation":false,"usgs":false,"family":"Augspurger","given":"Tom","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":735245,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196459,"text":"sir20185017 - 2018 - Flood-inundation maps for the Wabash River at Lafayette, Indiana","interactions":[],"lastModifiedDate":"2018-05-14T10:39:38","indexId":"sir20185017","displayToPublicDate":"2018-05-10T11:15:00","publicationYear":"2018","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":"2018-5017","title":"Flood-inundation maps for the Wabash River at Lafayette, Indiana","docAbstract":"<p>Digital flood-inundation maps for an approximately 4.8-mile reach of the Wabash River at Lafayette, Indiana (Ind.) were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science web site at <a href=\"https://water.usgs.gov/osw/flood_inundation/\" data-mce-href=\"https://water.usgs.gov/osw/flood_inundation/\">https://water.usgs.gov/osw/flood_inundation/</a>, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 03335500, Wabash River at Lafayette, Ind. Current streamflow conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the internet at <a href=\"https://waterdata.usgs.gov/in/nwis/uv?site_no=03335500\" data-mce-href=\"https://waterdata.usgs.gov/in/nwis/uv?site_no=03335500\">https://waterdata.usgs.gov/in/nwis/uv?site_no=03335500</a>. In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood-warning system (<a href=\"https://water.weather.gov/ahps/\" data-mce-href=\"https://water.weather.gov/ahps/\">https://water.weather.gov/ahps/</a>). The NWS AHPS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the Wabash River at Lafayette, Ind. NWS AHPS-forecast peak-stage information may be used with the maps developed in this study to show predicted areas of flood inundation.</p><p>For this study, flood profiles were computed for the Wabash River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 03335500, Wabash River at Lafayette, Ind., and high-water marks from the flood of July 2003 (U.S. Army Corps of Engineers [USACE], 2007). The calibrated hydraulic model was then used to determine 23 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging to delineate the area flooded at each water level. The availability of these maps, along with internet information regarding current stage from the USGS streamgage 03335500, Wabash River at Lafayette, Ind., and forecasted high-flow stages from the NWS AHPS, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, and for postflood recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185017","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Kim, M.H., 2018, Flood-inundation maps for the Wabash River at Lafayette, Indiana: U.S. Geological Survey Scientific Investigations Report 2018–5017, <br>10 p., https://doi.org/10.3133/sir20185017.\n\n","productDescription":"Report: vi, 10 p.; Data release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-085085","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":353948,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PC31BN","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data and surface-water model archive for a flood-inundation mapping study of the Wabash River at Lafayette, Indiana"},{"id":353947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5017/sir20185017.pdf","text":"Report","size":"1.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR  2018-5017"},{"id":353946,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5017/coverthb2.jpg"}],"country":"United States","state":"Indiana","city":"Lafayette","otherGeospatial":"Wabash River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.95,\n              40.3833\n            ],\n            [\n              -86.85430526733398,\n              40.3833\n            ],\n            [\n              -86.85430526733398,\n              40.475\n            ],\n            [\n              -86.95,\n              40.475\n            ],\n            [\n              -86.95,\n              40.3833\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_in@usgs.gov\" data-mce-href=\"mailto:dc_in@usgs.gov\">Director</a>, Ohio-Kentucky-<a href=\"https://in.water.usgs.gov/\" data-mce-href=\"https://in.water.usgs.gov/\">Indiana Water Science Center</a><br> U.S. Geological Survey <br> 5957 Lakeside Boulevard <br> Indianapolis, IN 46278</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Creation of Flood-Inundation-Map Library</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2018-05-10","noUsgsAuthors":false,"publicationDate":"2018-05-10","publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdba","contributors":{"authors":[{"text":"Kim, Moon H. 0000-0002-4328-8409 mkim@usgs.gov","orcid":"https://orcid.org/0000-0002-4328-8409","contributorId":204039,"corporation":false,"usgs":true,"family":"Kim","given":"Moon H.","email":"mkim@usgs.gov","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":732985,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196155,"text":"sir20185046 - 2018 - Methods for peak-flow frequency analysis and reporting for streamgages in or near Montana based on data through water year 2015","interactions":[],"lastModifiedDate":"2018-09-25T05:33:19","indexId":"sir20185046","displayToPublicDate":"2018-05-10T00:00:00","publicationYear":"2018","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":"2018-5046","title":"Methods for peak-flow frequency analysis and reporting for streamgages in or near Montana based on data through water year 2015","docAbstract":"<p>This report documents the methods for peak-flow frequency (hereinafter “frequency”) analysis and reporting for streamgages in and near Montana following implementation of the Bulletin 17C guidelines. The methods are used to provide estimates of peak-flow quantiles for 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for selected streamgages operated by the U.S. Geological Survey Wyoming-Montana Water Science Center (WY–MT WSC). These annual exceedance probabilities correspond to 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.</p><p>Standard procedures specific to the WY–MT WSC for implementing the Bulletin 17C guidelines include (1) the use of the Expected Moments Algorithm analysis for fitting the log-Pearson Type III distribution, incorporating historical information where applicable; (2) the use of weighted skew coefficients (based on weighting at-site station skew coefficients with generalized skew coefficients from the Bulletin 17B national skew map); and (3) the use of the Multiple Grubbs-Beck Test for identifying potentially influential low flows. For some streamgages, the peak-flow records are not well represented by the standard procedures and require user-specified adjustments informed by hydrologic judgement. The specific characteristics of peak-flow records addressed by the informed-user adjustments include (1) regulated peak-flow records, (2) atypical upper-tail peak-flow records, and (3) atypical lower-tail peak-flow records. In all cases, the informed-user adjustments use the Expected Moments Algorithm fit of the log-Pearson Type III distribution using the at-site station skew coefficient, a manual potentially influential low flow threshold, or both.</p><p>Appropriate methods can be applied to at-site frequency estimates to provide improved representation of long-term hydroclimatic conditions. The methods for improving at-site frequency estimates by weighting with regional regression equations and by Maintenance of Variance Extension Type III record extension are described.</p><p>Frequency analyses were conducted for 99 example streamgages to indicate various aspects of the frequency-<br>analysis methods described in this report. The frequency analyses and results for the example streamgages are presented in a separate data release associated with this report consisting of tables and graphical plots that are structured to include information concerning the interpretive decisions involved in the frequency analyses. Further, the separate data release includes the input files to the PeakFQ program, version 7.1, including the peak-flow data file and the analysis specification file that were used in the peak-flow frequency analyses. Peak-flow frequencies are also reported in separate data releases for selected streamgages in the Beaverhead River and Clark Fork Basins and also for selected streamgages in the Ruby, Jefferson, and Madison River Basins.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185046","collaboration":"Prepared in cooperation with the Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., and McCarthy, P.M., 2018, Methods for peak-flow frequency analysis and reporting for streamgages in or near Montana based on data through water year 2015: U.S. Geological Survey Scientific Investigations Report 2018–5046, 39 p., https://doi.org/10.3133/sir20185046.","productDescription":"Report: vi, 39 p.; Data Releases","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082119","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":437916,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J1U1GB","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in the Upper Yellowstone River Basin, based on data through water year 2022"},{"id":437915,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92U1D63","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in Dawson and Richland Counties, and the Powder River Basin, Montana, based on data through water year 2022"},{"id":437914,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L8UM2P","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages on tributaries of the Bighorn, Tongue, and Lower Yellowstone Rivers, based on data through water year 2021"},{"id":437913,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C4K7OS","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages on the Bighorn, Tongue, and Lower Yellowstone Rivers and tributaries and Home Creek, Montana, based on data through water year 2021"},{"id":437912,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NAJFPL","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in and near the Milk River Basin, Montana, based on data through water year 2018, part 2"},{"id":437911,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95IFBAH","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in and near Teton County, Montana, based on data through water year 2019"},{"id":437910,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91HB8GI","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in Carbon County, Montana, based on data through water year 2018"},{"id":437909,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y53FX3","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in and near the Milk River Basin, Montana, based on data through water year 2018, Part 1"},{"id":437908,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JNKYKH","text":"USGS data release","linkHelpText":"Peak-Flow Frequency Analyses for Selected Streamgages in Missoula and Granite Counties, Montana, Based on Data through Water Year 2018"},{"id":437907,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RC008L","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for Elk Creek at Augusta, Montana, based on data through water year 2018"},{"id":437906,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TK3KFE","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for 11 selected streamgages in Jefferson County, Montana, based on data through water year 2017 (ver. 1.1, September 2019)"},{"id":354044,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JW8C21","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Peak-flow frequency analyses for 14 selected streamgages in the Beaverhead River and Clark Fork Basins Montana, based on data through water year 2016"},{"id":354045,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75Q4V99","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Peak-flow frequency analyses for 14 selected streamgages in the Ruby, Jefferson, and Madison River Basins, Montana, based on data through water year 2016"},{"id":354042,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5046/sir20185046.pdf","text":"Report","size":"2.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5046"},{"id":354041,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5046/coverthb2.jpg"},{"id":354043,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7C827GQ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Peak-flow frequency analyses for 99 selected streamgages in or near Montana, based on data through water year 2015"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto: dc_MT@usgs.gov\" data-mce-href=\"mailto: dc_MT@usgs.gov\">Director</a>, <a href=\"https://wy-mt.water.usgs.gov\" data-mce-href=\"https://wy-mt.water.usgs.gov\">Wyoming-Montana Water Science Center</a><br>U.S. Geological Survey<br>3162 Bozeman Avenue <br>Helena, MT 59601&nbsp;</p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Overview of Bulletin 17B and Bulletin 17C Guidelines for Peak-Flow Frequency Analysis<br></li><li>The Expected Moments Algorithm Procedures in Relation to Montana Peak-Flow Datasets<br></li><li>Selected Considerations for Peak-Flow Frequency Analysis<br></li><li>Methods for Peak-Flow Frequency Analysis<br></li><li>Methods for Peak-Flow Frequency Reporting<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-05-10","noUsgsAuthors":false,"publicationDate":"2018-05-10","publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdc6","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":203451,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"","middleInitial":"K.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":731529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Peter M. 0000-0003-3194-041X pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-041X","contributorId":203452,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","middleInitial":"M.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731530,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70201480,"text":"70201480 - 2018 - Rethinking the use of seabed sediment temperature profiles to trace submarine groundwater flow","interactions":[],"lastModifiedDate":"2018-12-14T14:24:18","indexId":"70201480","displayToPublicDate":"2018-05-08T14:24:08","publicationYear":"2018","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":"Rethinking the use of seabed sediment temperature profiles to trace submarine groundwater flow","docAbstract":"<p><span>Submarine groundwater fluxes across the seafloor facilitate important hydrological and biogeochemical exchanges between oceans and seabed sediment, yet few studies have investigated spatially distributed groundwater fluxes in deep‐ocean environments such as continental slopes. Heat has been previously applied as a submarine groundwater tracer using an analytical solution to a heat flow equation assuming steady state conditions and homogeneous thermal conductivity. These assumptions are often violated in shallow seabeds due to ocean bottom temperature changes or sediment property variations. Here heat tracing analysis techniques recently developed for terrestrial settings are applied in concert to examine the influences of groundwater flow, ocean temperature changes, and seabed thermal conductivity variations on deep‐ocean sediment temperature profiles. Temperature observations from the sediment and bottom ocean water on the Scotian Slope off eastern Canada are used to demonstrate how simple thermal methods for tracing groundwater can be employed if more comprehensive techniques indicate that the simplifying assumptions are valid. The spatial distribution of the inferred groundwater fluxes on the slope suggests a downward groundwater flow system with recharge occurring over the upper‐middle slope and discharge on the lower slope. We speculate that the downward groundwater flow inferred on the Scotian Slope is due to density‐driven processes arising from underlying salt domes, in contrast with upward slope systems driven by geothermal convection. Improvements in the design of future submarine hydrogeological studies are proposed for thermal data collection and groundwater flow analysis, including new equations that quantify the minimum detectable flux magnitude for a given sensor accuracy and profile length.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2017WR022353","usgsCitation":"Kurylyk, B.L., Irvine, D.J., Mohammed, A., Bense, V.F., Briggs, M.A., Loder, J., and Geshelin, Y., 2018, Rethinking the use of seabed sediment temperature profiles to trace submarine groundwater flow: Water Resources Research, v. 54, no. 7, p. 4595-4614, https://doi.org/10.1029/2017WR022353.","productDescription":"20 p.","startPage":"4595","endPage":"4614","ipdsId":"IP-095613","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr022353","text":"Publisher Index Page"},{"id":360328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Scotian Slope","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -63,\n              41\n            ],\n            [\n              -60,\n              41\n            ],\n            [\n              -60,\n              43\n            ],\n            [\n              -63,\n              43\n            ],\n            [\n              -63,\n              41\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-07","publicationStatus":"PW","scienceBaseUri":"5c14cfb8e4b006c4f8545d3f","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":754277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Dylan J.","contributorId":190404,"corporation":false,"usgs":false,"family":"Irvine","given":"Dylan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":754278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mohammed, A.A.","contributorId":211492,"corporation":false,"usgs":false,"family":"Mohammed","given":"A.A.","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":754279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bense, V. F.","contributorId":211493,"corporation":false,"usgs":false,"family":"Bense","given":"V.","email":"","middleInitial":"F.","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":754280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":754276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loder, J.W.","contributorId":211494,"corporation":false,"usgs":false,"family":"Loder","given":"J.W.","email":"","affiliations":[{"id":38259,"text":"Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":754281,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Geshelin, Y.","contributorId":211495,"corporation":false,"usgs":false,"family":"Geshelin","given":"Y.","email":"","affiliations":[{"id":38259,"text":"Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":754282,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70195030,"text":"sir20185018 - 2018 - Hydrologic and water-quality characteristics of Caño Boquerón, Cabo Rojo, and Puerto Mosquito, Isla de Vieques, Puerto Rico, July 2015–July 2016","interactions":[],"lastModifiedDate":"2018-09-25T06:00:30","indexId":"sir20185018","displayToPublicDate":"2018-05-07T00:00:00","publicationYear":"2018","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":"2018-5018","title":"Hydrologic and water-quality characteristics of Caño Boquerón, Cabo Rojo, and Puerto Mosquito, Isla de Vieques, Puerto Rico, July 2015–July 2016","docAbstract":"<p>Coastal lagoons are common features of the Puerto Rico shoreline that provide habitat for commercial and recreational species and serve important roles in the nutrient cycle of the ecosystems. The U.S. Geological Survey, in cooperation with the Puerto Rico Environmental Quality Board, conducted a limnological study at Caño Boquerón in Cabo Rojo and at Puerto Mosquito on Isla de Vieques, Puerto Rico, to assess the principal mechanisms affecting the hydrology and water-quality characteristics of these coastal lagoons and provide baseline information to the regulatory agencies responsible for the management and conservation of these coastal waters and the preservation of their aquatic life.</p><p>Field measurements and water samples were collected and processed during July 2015–July 2016 for analysis of physical, chemical, biological, and bacteriological characteristics. In addition, bathymetric surveys were made and sediment cores were collected in each lagoon to determine water volume and sediment deposition rate. Physicochemical properties assessed at Caño Boquerón indicated values were generally in compliance with Puerto Rico Environmental Quality Board standards; turbidity was occasionally slightly greater than the established standards, and dissolved oxygen concentration at bottom depths was lower than standards limits. Water transparency was evaluated through the Secchi disk method, and the average depth of disappearance was 1.0 meter (m) for Caño Boquerón and 1.9 m for Puerto Mosquito.</p><p>Assessment of biological characteristics at both sites included primary productivity calculations as well as carbon production equivalents and monthly water sampling for bacteriological and nutrient analyses. For Caño Boquerón, gross plankton primary productivity averaged 3.38 grams of oxygen per cubic meter per day (gO<sub>2</sub>/m<sup>3</sup>-d); this value was computed as the sum of net phytoplankton primary productivity (0.74 gO<sub>2</sub>/m<sup>3</sup>-d) and plankton respiration (2.64 gO<sub>2</sub>/m<sup>3</sup>-d). Net community primary productivity averaged 1.44 gO<sub>2</sub>/m<sup>3</sup>-d, and the community respiration rate&nbsp;averaged 8.10 gO<sub>2</sub>/m<sup>3</sup>-d, which indicates that the biological community, aside from phytoplankton, acts as a net consumer rather than a net producer of biomass. In Puerto Mosquito, gross plankton primary productivity averaged 2.07 gO<sub>2</sub>/m<sup>3</sup>-d, of which 0.39 gO<sub>2</sub>/m<sup>3</sup>-d could be ascribed to net phytoplankton primary productivity, and 1.68 gO<sub>2</sub>/m<sup>3</sup>-d could be ascribed to plankton respiration. Diel studies conducted at Puerto Mosquito reflected an average net community primary productivity of 2.43 gO<sub>2</sub>/m<sup>3</sup>-d, and the average respiration rate was 6.72 gO<sub>2</sub>/m<sup>3</sup>-d.</p><p>In a bathymetric survey conducted in August 2015, the water volume for the Caño Boquerón lagoon was calculated as 967,000 cubic meters (m<sup>3</sup>), and the water volume at Puerto Mosquito was calculated as 1,182,200 m<sup>3</sup>, with an average depth of 1.5 m for Caño Boquerón and 1.8 m for Puerto Mosquito. The daily seawater exchange for Caño Boquerón and Puerto Mosquito was 13 and 5 percent of their water volumes referenced to mean sea level, respectively. A total of 20 sediment samples were processed and analyzed for cesium-137 (<sup>137</sup>Cs) and lead-210 (<sup>210</sup>Pb) radioisotopes. Analyses indicated that the sediment deposition rate at Caño Boquerón ranged from 0.32 to 0.36 centimeter per year, based on age dating analysis of <sup>137</sup>Cs and <sup>210</sup>Pb data; in Puerto Mosquito, the sediment deposition rate ranged from 0.26 to 0.27 centimeter per year, based on <sup>137</sup>Cs and <sup>210</sup>Pb data.</p><p>Bacteriological analyses at Caño Boquerón and Puerto Mosquito indicated that fecal coliform and enterococci concentrations were below Puerto Rico Environmental Quality Board standards during the study. The highest concentrations of fecal coliform (22 colonies per 100 milliliters) and enterococci (9 colonies per 100 milliliters) at Caño Boquerón occurred in July, which coincided with the busiest season of vacation rentals near the lagoon. Bacteria concentrations were generally lower in Puerto Mosquito than in Caño Boquerón; maximum concentrations of fecal coliform and enterococci bacteria were measured in November 2015. The potential sources of contamination for Puerto Mosquito are limited, because it is within a conservation area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185018","collaboration":"Prepared in cooperation with the Puerto Rico Environmental Quality Board","usgsCitation":"Gómez-Fragoso, J.M., and Santiago-Sáez, J.A., 2018, Hydrologic and water-quality characteristics of Caño Boquerón, Cabo Rojo, and Puerto Mosquito, Isla de Vieques, Puerto Rico, July 2015–July 2016: U.S. Geological Survey Scientific Investigations Report 2018–5018, 34 p., https://doi.org/10.3133/sir20185018.","productDescription":"Report: ix, 34 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-078162","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":437920,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WH2P6K","text":"USGS data release","linkHelpText":"Gomez-Fragoso, Julieta, 2017, Data for the Hydrologic and Water-Quality Characterization of Cano Boqueron, Cabo Rojo, and Puerto Mosquito, Isla de Vieques, Puerto Rico, July 2015-July 2016: U.S. Geological Survey data release"},{"id":353903,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7WH2P6K","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for the Hydrologic and Water-Quality Characterization of Puerto Mosquito, Vieques and Caño Boquerón, Cabo Rojo, Puerto Rico, July 2015–July 2016"},{"id":353901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5018/coverthb2.jpg"},{"id":353902,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5018/sir20185018.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5018"}],"country":"United States","otherGeospatial":"Caño Boquerón, Cabo Rojo, Puerto Mosquito, Isla de Vieques, Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -67.2167,\n              17.9833\n            ],\n            [\n              -67.1333,\n              17.9833\n            ],\n            [\n              -67.1333,\n              18.04\n            ],\n            [\n              -67.2167,\n              18.04\n            ],\n            [\n              -67.2167,\n              17.9833\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -65.4833,\n              18.0833\n            ],\n            [\n              -65.4,\n              18.0833\n            ],\n            [\n              -65.4,\n              18.1333\n            ],\n            [\n              -65.4833,\n              18.1333\n            ],\n            [\n              -65.4833,\n              18.0833\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director,&nbsp;<a href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\" data-mce-href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\">Caribbean-Florida Water Science Center</a> <br>U.S. Geological Survey <br>4446 Pet Lane, Suite 108 <br>Lutz, FL 33559&nbsp;</p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Methods of Investigation<br></li><li>Results and Discussion<br></li><li>Summary and Conclusions<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2018-05-07","noUsgsAuthors":false,"publicationDate":"2018-05-07","publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbdde","contributors":{"authors":[{"text":"Gómez-Fragoso, Julieta M. 0000-0002-1080-2950","orcid":"https://orcid.org/0000-0002-1080-2950","contributorId":201641,"corporation":false,"usgs":true,"family":"Gómez-Fragoso","given":"Julieta M.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":726651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Santiago-Saez, Jose A. 0000-0002-6162-5720","orcid":"https://orcid.org/0000-0002-6162-5720","contributorId":204602,"corporation":false,"usgs":true,"family":"Santiago-Saez","given":"Jose","email":"","middleInitial":"A.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":false,"id":734480,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70195537,"text":"sir20185030 - 2018 - Hydrogeologic setting, conceptual groundwater flow system, and hydrologic conditions 1995–2010 in Florida and parts of Georgia, Alabama, and South Carolina","interactions":[],"lastModifiedDate":"2018-09-25T06:19:59","indexId":"sir20185030","displayToPublicDate":"2018-05-04T14:00:00","publicationYear":"2018","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":"2018-5030","title":"Hydrogeologic setting, conceptual groundwater flow system, and hydrologic conditions 1995–2010 in Florida and parts of Georgia, Alabama, and South Carolina","docAbstract":"<p>The hydrogeologic setting and groundwater flow system in Florida and parts of Georgia, Alabama, and South Carolina is dominated by the highly transmissive Floridan aquifer system. This principal aquifer is a vital source of freshwater for public and domestic supply, as well as for industrial and agricultural uses throughout the southeastern United States. Population growth, increased tourism, and increased agricultural production have led to increased demand on groundwater from the Floridan aquifer system, particularly since 1950. The response of the Floridan aquifer system to these stresses often poses regional challenges for water-resource management that commonly transcend political or jurisdictional boundaries. To help water-resource managers address these regional challenges, the U.S. Geological Survey (USGS) Water Availability and Use Science Program began assessing groundwater availability of the Floridan aquifer system in 2009.</p><p>The current conceptual groundwater flow system was developed for the Floridan aquifer system and adjacent systems partly on the basis of previously published USGS Regional Aquifer-System Analysis (RASA) studies, specifically many of the potentiometric maps and the modeling efforts in these studies. The Floridan aquifer system extent was divided into eight hydrogeologically distinct subregional groundwater basins delineated on the basis of the estimated predevelopment (circa 1880s) potentiometric surface: (1) Panhandle, (2) Dougherty Plain-Apalachicola, (3)&nbsp;Thomasville-Tallahassee, (4) Southeast Georgia-Northeast Florida-South South Carolina, (5) Suwannee, (6) West-central Florida, (7) East-central Florida, and (8) South Florida. The use of these subregions allows for a more detailed analysis of the individual basins and the groundwater flow system as a whole.</p><p>The hydrologic conditions and associated groundwater budget were updated relative to previous RASA studies to include additional data collected since the 1980s and to reflect the entire groundwater flow system, including the surficial, intermediate, and Floridan aquifer systems for a contemporary period (1995–2010). Inflow to the groundwater flow system of 33,700 million gallons per day (Mgal/d) was assumed to be exclusively from net recharge (precipitation minus evapotranspiration and surface runoff). Outflow from the groundwater flow system included spring discharge (7,700 Mgal/d) and groundwater withdrawals (5,200 Mgal/d). Estimates for all components of the groundwater system were not possible because of large uncertainties associated with internal leakage, coastal discharge, and discharge to streams and lakes. A numerical modeling analysis is required to improve this hydrologic budget calculation and to forecast future changes in groundwater levels and aquifer storage caused by groundwater withdrawals, land-use change, and the effects of climate variability and change.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185030","collaboration":"Water Availability and Use Science Program","usgsCitation":"Bellino, J.C., Kuniansky, E.L., O’Reilly, A.M., and Dixon, J.F., 2018, Hydrogeologic setting, conceptual groundwater flow system, and hydrologic conditions 1995–2010 in Florida and parts of Georgia, Alabama, and South Carolina: U.S. Geological Survey Scientific Investigations Report 2018–5030, 103 p., https://doi.org/10.3133/sir20185030.","productDescription":"Report: viii, 103 p.; Plate: 36.0 x 49.0 inches; Data Releases","numberOfPages":"115","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056534","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":353934,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2018/5030/sir20185030_plate.pdf","text":"Plate 1","size":"3.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5030 Plate 1"},{"id":353936,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CJ8BMS","text":"USGS data release","description":"USGS Data Release","linkHelpText":" Soil-Water-Balance model datasets used to estimate mean groundwater recharge in Florida and parts of Georgia, Alabama, and South Carolina, 1995–2010"},{"id":353933,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5030/sir20185030.pdf","text":"Report","size":"46.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5030"},{"id":353932,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5030/coverthb2.jpg"},{"id":353937,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75Q4TZD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Potentiometric Surface Contours, Wells, and Groundwater Basin Divides for the Upper Floridan Aquifer in Florida and Parts of Georgia, South Carolina, and Alabama, May–June 2010—Updated"},{"id":353935,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78K7749","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Groundwater Withdrawals in Florida and parts of Georgia, Alabama, and South Carolina, 1995–2010"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.17626953125,\n              24.467150664739002\n            ],\n            [\n              -79.6728515625,\n              24.467150664739002\n            ],\n            [\n              -79.6728515625,\n              32.85190345738802\n            ],\n            [\n              -88.17626953125,\n              32.85190345738802\n            ],\n            [\n              -88.17626953125,\n              24.467150664739002\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www2.usgs.gov/water/caribbeanflorida/\" data-mce-href=\"https://www2.usgs.gov/water/caribbeanflorida/\">Caribbean-Florida Water Science Center</a><br>U.S. Geological Survey<br>4446 Pet Lane <br>Lutz, FL 33559</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Hydrogeologic Setting<br></li><li>Conceptual Groundwater Flow System<br></li><li>Hydrologic Conditions<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendixes<br></li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2018-05-04","noUsgsAuthors":false,"publicationDate":"2018-05-04","publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbde0","contributors":{"authors":[{"text":"Bellino, Jason C. 0000-0001-9046-9344 jbellino@usgs.gov","orcid":"https://orcid.org/0000-0001-9046-9344","contributorId":3724,"corporation":false,"usgs":true,"family":"Bellino","given":"Jason","email":"jbellino@usgs.gov","middleInitial":"C.","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":true,"id":729182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuniansky, Eve L. 0000-0002-5581-0225 elkunian@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":932,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"elkunian@usgs.gov","middleInitial":"L.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":729183,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Reilly, Andrew M. 0000-0003-3220-1248","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":202638,"corporation":false,"usgs":false,"family":"O'Reilly","given":"Andrew M.","affiliations":[{"id":36508,"text":"University of Mississippi","active":true,"usgs":false}],"preferred":false,"id":729181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dixon, Joann F. 0000-0001-9200-6407 jdixon@usgs.gov","orcid":"https://orcid.org/0000-0001-9200-6407","contributorId":1756,"corporation":false,"usgs":true,"family":"Dixon","given":"Joann","email":"jdixon@usgs.gov","middleInitial":"F.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true},{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729184,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236152,"text":"70236152 - 2018 - Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States","interactions":[],"lastModifiedDate":"2022-08-30T14:26:41.124038","indexId":"70236152","displayToPublicDate":"2018-05-01T09:19:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States","docAbstract":"<p>Winter snowfall and accumulation is an important component of the surface water supply in the western United States. In these areas, increasing winter temperatures<span>&nbsp;</span><i>T</i><span>&nbsp;</span>associated with global warming can influence the amount of winter precipitation<span>&nbsp;</span><i>P</i><span>&nbsp;</span>that falls as snow<span>&nbsp;</span><i>S</i>. In this study we examine long-term trends in the fraction of winter<span>&nbsp;</span><i>P</i><span>&nbsp;</span>that falls as<span>&nbsp;</span><i>S</i><span>&nbsp;</span>(Sfrac) for 175 hydrologic units (HUs) in snow-covered areas of the western United States for the period 1951–2014. Because<span>&nbsp;</span><i>S</i><span>&nbsp;</span>is a substantial contributor to runoff<span>&nbsp;</span><i>R</i><span>&nbsp;</span>across most of the western United States, we also examine long-term trends in water-year runoff efficiency [computed as water-year<span>&nbsp;</span><i>R</i>/water-year<span>&nbsp;</span><i>P</i><span>&nbsp;</span>(Reff)] for the same 175 HUs. In that most<span>&nbsp;</span><i>S</i><span>&nbsp;</span>records are short in length, we use model-simulated<span>&nbsp;</span><i>S</i><span>&nbsp;</span>and<span>&nbsp;</span><i>R</i><span>&nbsp;</span>from a monthly water balance model. Results for Sfrac indicate long-term negative trends for most of the 175 HUs, with negative trends for 139 (~79%) of the HUs being statistically significant at a 95% confidence level (<i>p</i><span>&nbsp;</span>= 0.05). Additionally, results indicate that the long-term negative trends in Sfrac have been largely driven by increases in<span>&nbsp;</span><i>T</i>. In contrast, time series of Reff for the 175 HUs indicate a mix of positive and negative long-term trends, with few trends being statistically significant (at<span>&nbsp;</span><i>p</i><span>&nbsp;</span>= 0.05). Although there has been a notable shift in the timing of<span>&nbsp;</span><i>R</i><span>&nbsp;</span>to earlier in the year for most HUs, there have not been substantial decreases in water-year<span>&nbsp;</span><i>R</i><span>&nbsp;</span>for the 175 HUs.</p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-17-0227.1","usgsCitation":"McCabe, G.J., Wolock, D.M., and Valentin, M., 2018, Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States: Journal of Hydrometeorology, v. 19, p. 803-814, https://doi.org/10.1175/JHM-D-17-0227.1.","productDescription":"12 p.","startPage":"803","endPage":"814","ipdsId":"IP-080058","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":468787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-17-0227.1","text":"Publisher Index Page"},{"id":405909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.7734375,\n              32.39851580247402\n            ],\n            [\n              -107.70996093749999,\n              31.840232667909365\n            ],\n            [\n              -106.69921875,\n              33.394759218577995\n            ],\n            [\n              -106.4794921875,\n              35.209721645221386\n            ],\n            [\n              -104.67773437499999,\n              35.92464453144099\n            ],\n            [\n              -104.7216796875,\n              37.64903402157866\n            ],\n            [\n              -104.5458984375,\n              38.89103282648846\n            ],\n            [\n              -104.94140625,\n              39.80853604144591\n            ],\n            [\n              -104.80957031249999,\n              40.48038142908172\n            ],\n            [\n              -105.64453124999999,\n              41.343824581185686\n            ],\n            [\n              -104.94140625,\n              42.19596877629178\n            ],\n            [\n              -106.787109375,\n              43.35713822211053\n            ],\n            [\n              -106.6552734375,\n              44.308126684886126\n            ],\n            [\n              -107.9296875,\n              45.36758436884978\n            ],\n            [\n              -110.25878906249999,\n              45.85941212790755\n            ],\n            [\n              -111.09374999999999,\n              46.76996843356982\n            ],\n            [\n              -112.67578124999999,\n              47.66538735632654\n            ],\n            [\n              -113.51074218749999,\n              49.06666839558117\n            ],\n            [\n              -123.53027343749999,\n              49.06666839558117\n            ],\n            [\n              -123.26660156249999,\n              48.37084770238366\n            ],\n            [\n              -125.3759765625,\n              48.60385760823255\n            ],\n            [\n              -124.4091796875,\n              45.336701909968134\n            ],\n            [\n              -124.93652343749999,\n              43.004647127794435\n            ],\n            [\n              -124.76074218749999,\n              40.38002840251183\n            ],\n            [\n              -124.18945312500001,\n              38.75408327579141\n            ],\n            [\n              -122.3876953125,\n              36.35052700542763\n            ],\n            [\n              -120.9375,\n              34.19817309627726\n            ],\n            [\n              -117.7734375,\n              32.39851580247402\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"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},{"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":850262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valentin, Melissa","contributorId":202218,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":850264,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196206,"text":"sir20185044 - 2018 - Estimation of unregulated monthly, annual, and peak streamflows in Forest City Stream and lake levels in East Grand Lake, United States-Canada border between Maine and New Brunswick","interactions":[],"lastModifiedDate":"2018-05-01T16:07:09","indexId":"sir20185044","displayToPublicDate":"2018-04-30T11:45:00","publicationYear":"2018","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":"2018-5044","title":"Estimation of unregulated monthly, annual, and peak streamflows in Forest City Stream and lake levels in East Grand Lake, United States-Canada border between Maine and New Brunswick","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the International Joint Commission, compiled historical data on regulated streamflows and lake levels and estimated unregulated streamflows and lake levels on Forest City Stream at Forest City, Maine, and East Grand Lake on the United States-Canada border between Maine and New Brunswick to study the effects on streamflows and lake levels if two or all three dam gates are left open. Historical regulated monthly mean streamflows in Forest City Stream at the outlet of East Grand Lake (referred to as Grand Lake by Environment Canada) fluctuated between 114 cubic feet per second (ft3 /s) (3.23 cubic meters per second [m3 /s]) in November and 318 ft3 /s (9.01 m3 /s) in September from 1975 to 2015 according to Environment Canada streamgaging data. Unregulated monthly mean streamflows at this location estimated from regression equations for unregulated sites range from 59.2 ft3 /s (1.68 m3 /s) in September to 653 ft3 /s (18.5 m3 /s) in April. Historical lake levels in East Grand Lake fluctuated between 431.3 feet (ft) (131.5 meters [m]) in October and 434.0 ft (132.3 m) in May from 1969 to 2016 according to Environment Canada lake level data for East Grand Lake. Average monthly lake levels modeled by using the estimated hydrology for unregulated flows, and an outflow rating built from a hydraulic model with all gates at the dam open, range from 427.7 ft (130.4 m) in September to 431.1 ft (131.4 m) in April. Average monthly lake levels would likely be from 1.8 to 5.4 ft (0.55 to 1.6 m) lower with the gates at the dam opened than they have been historically. The greatest lake level changes would be from June through September. </p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185044","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Lombard, P.J., 2018, Estimation of unregulated monthly, annual, and peak streamflows in Forest City Stream and lake levels in East Grand Lake, United States-Canada border between Maine and New Brunswick: U.S. Geological Survey Scientific Investigations Report 2018–5044, 8 p., https://doi.org/10.3133/sir20185044.","productDescription":"Report: iv, 8 p.; Data release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092951","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":353763,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PN94VN","text":"USGS data release","description":"USGS data release","linkHelpText":"Bathymetric data for St. Croix River at outlet to East Grand Lake and Forest City Dam Survey, United States-Canadian border between Maine and New Brunswick"},{"id":353745,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5044/sir20185044.pdf","text":"Report","size":"873 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5044"},{"id":353744,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5044/coverthb.jpg"}],"country":"Canada, United States","state":"Maine, New Brunswick","otherGeospatial":"East Grand Lake, Forest City Stream","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -67.884521484375,\n              45.60587170876381\n            ],\n            [\n              -67.68951416015625,\n              45.60587170876381\n            ],\n            [\n              -67.68951416015625,\n              45.82066487514085\n            ],\n            [\n              -67.884521484375,\n              45.82066487514085\n            ],\n            [\n              -67.884521484375,\n              45.60587170876381\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://newengland.water.usgs.gov\" data-mce-href=\"https://newengland.water.usgs.gov\">New England Water Science Center</a><br> U.S. Geological Survey<br> 196 Whitten Road<br> Augusta, ME 04330</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Data Collection and Analysis</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2018-04-30","noUsgsAuthors":false,"publicationDate":"2018-04-30","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe22","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":203509,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731678,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70203196,"text":"70203196 - 2018 - Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability","interactions":[],"lastModifiedDate":"2019-04-26T16:44:27","indexId":"70203196","displayToPublicDate":"2018-04-26T16:33:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability","docAbstract":"<ol><li>Streamflow is essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Changes in climate, land use and water use practices may alter water availability. Understanding the potential effect of these changes on aquatic ecosystems is critical for long-term water management to maintain a balance between water for human consumption and ecosystem needs.</li><li>Fish species data and streamflow estimates from a rainfall-runoff and flow routing model were used to develop boosted regression tree models to predict the relationship between streamflow and fish species richness (FSR) under plausible scenarios of (1) water withdrawal, (2) climate change and (3) increases in impervious surfaces in the Piedmont ecoregion of North Carolina, U.S.A. Maximum monthly flow, the fraction of total flow originating from impervious surface runoff, coefficient of monthly streamflow variability, and the specific river basin accounted for 50% of the variability in FSR. This model was used to predict FSR values for all twelve-digit Hydrological Unit Code catchments (HUC-12s) in the North Carolina Piedmont under current flow conditions and under water withdrawal, climate change and impervious surface scenarios.</li><li>Flow–ecology modeling results indicate that predicted FSR declined significantly with increased water withdrawals. However, the magnitude of decline varied geographically. A “hot-spot” analysis was conducted based on predicted changes in FSR under each scenario to understand which HUC-12s were most likely to be affected by changes in water withdrawals, climate and impervious surfaces. Under the 20% withdrawal increase scenario, 413 of 886 (47%) HUC-12s in the study area were predicted to lose one or more species. HUC-12s in the Broad, Catawba, Yadkin and Cape Fear river basins were most susceptible to species loss.</li><li>These findings may help decision making efforts by identifying catchments most vulnerable to changing water availability. Additionally, FSR-discharge modeling results can assist resource agencies, water managers and stakeholders in assessing the effect of water withdrawals in catchments to better support the protection and long-term conservation of species.</li></ol>","language":"English","doi":"10.1111/fwb.13048","usgsCitation":"Hain;, E.F., Kennen, J., Caldwell, P.V., Nelson, S.A., Ge Sun, and McNulty, S.G., 2018, Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability: Freshwater Biology, v. 63, p. 928-945, https://doi.org/10.1111/fwb.13048.","productDescription":"17 p.","startPage":"928","endPage":"945","ipdsId":"IP-084804","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":363277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.936279296875,\n              33.797408767572485\n            ],\n            [\n              -76.893310546875,\n              33.797408767572485\n            ],\n            [\n              -76.893310546875,\n              36.53612263184686\n            ],\n            [\n              -80.936279296875,\n              36.53612263184686\n            ],\n            [\n              -80.936279296875,\n              33.797408767572485\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"63","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Hain;, Ernie F.","contributorId":215083,"corporation":false,"usgs":false,"family":"Hain;","given":"Ernie","email":"","middleInitial":"F.","affiliations":[{"id":39171,"text":"Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, 27695, USA","active":true,"usgs":false}],"preferred":false,"id":761593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761592,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Peter V.","contributorId":215084,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V.","affiliations":[{"id":39172,"text":"USDA Forest Service, Center for Forest Watershed Science, Coweeta Hydrologic Laboratory, Otto, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Stacy A.C.","contributorId":215085,"corporation":false,"usgs":false,"family":"Nelson","given":"Stacy","email":"","middleInitial":"A.C.","affiliations":[{"id":39171,"text":"Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, 27695, USA","active":true,"usgs":false}],"preferred":false,"id":761595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ge Sun","contributorId":215086,"corporation":false,"usgs":false,"family":"Ge Sun","affiliations":[{"id":39173,"text":"USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNulty, Steven G.","contributorId":215087,"corporation":false,"usgs":false,"family":"McNulty","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":39173,"text":"USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761597,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196707,"text":"70196707 - 2018 - Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal","interactions":[],"lastModifiedDate":"2018-04-26T11:32:22","indexId":"70196707","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5679,"text":"Open Water Journal","active":true,"publicationSubtype":{"id":10}},"title":"Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal","docAbstract":"<p><span>The U.S. Geological Survey (USGS) is the primary U.S. Government agency for water data collection and dissemination. In this role, the USGS has recently created and deployed a National Water Census Data Portal (NWC-DP) which provides access to streamflow, evapotransporation, precipitation, aquatic biology and other data at the national level. Recognizing the value of these data sets for hydrologic science education, this paper presents an effort to bridge the gap between pencil–and-paper-based hydrology curriculum and the USGS NWC-DP resource. Specifically, we have developed an R package, National Water Census Education (NWCEd), and five associated laboratory exercises that integrate R- and web-services-based access to the NWC-DP data sets. Using custom functions built into the NWCEd, students are able to access unprecedented amounts of hydrologic data from the NWC-DP, which can be applied to current hydrology curriculum and analyzed using NWCEd and a number of other open-source R tools.</span></p>","language":"English","publisher":"BYU","usgsCitation":"Nelson, J., Ames, D.P., and Blodgett, D.L., 2018, Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal: Open Water Journal, v. 5, no. 1, p. 1-14.","productDescription":"Article 1; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-086854","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":353730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353724,"type":{"id":15,"text":"Index Page"},"url":"https://scholarsarchive.byu.edu/openwater/vol5/iss1/1/"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cfe4b0da30c1bfbe42","contributors":{"authors":[{"text":"Nelson, Jake","contributorId":204467,"corporation":false,"usgs":false,"family":"Nelson","given":"Jake","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":734059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ames, Daniel P.","contributorId":204468,"corporation":false,"usgs":false,"family":"Ames","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":734060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":734058,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196561,"text":"70196561 - 2018 - Cyclic heliothermal behaviour of the shallow, hypersaline Lake Hayward, Western Australia","interactions":[],"lastModifiedDate":"2018-04-17T10:34:23","indexId":"70196561","displayToPublicDate":"2018-04-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Cyclic heliothermal behaviour of the shallow, hypersaline Lake Hayward, Western Australia","docAbstract":"<div class=\"Abstracts\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">Lake Hayward is one of only about 30 hypersaline lakes worldwide that is meromictic and heliothermal and as such behaves as a natural salt gradient solar pond. Lake Hayward acts as a local groundwater sink, resulting in seasonally variable hypersaline lake water with total dissolved solids (TDS) in the upper layer (mixolimnion) ranging between 56 kg m<sup>−3</sup><span>&nbsp;</span>and 207 kg m<sup>−3</sup><span>&nbsp;</span>and the deeper layer (monimolimnion) from 153 kg m<sup>−3</sup><span>&nbsp;</span>to 211 kg m<sup>−3</sup>. This is up to six times the salinity of seawater and thus has the highest salinity of all eleven lakes in the Yalgorup National Park lake system. A program of continuously recorded water temperature profiles has shown that salinity stratification initiated by direct rainfall onto the lake’s surface and local runoff into the lake results in the onset of heliothermal conditions within hours of rainfall onset.</p><p id=\"sp0015\">The lake alternates between being fully mixed and becoming thermally and chemically stratified several times during the annual cycle, with the longest extended periods of heliothermal behaviour lasting 23 and 22 weeks in the winters of 1992 and 1993 respectively. The objective was to quantify the heat budgets of the cyclical heliothermal behaviour of Lake Hayward.</p><p id=\"sp0020\">During the period of temperature profile logging, the maximum recorded temperature of the monimolimnion was 42.6 °C at which time the temperature of the mixolimnion was 29.4 °C.</p><p id=\"sp0025\">The heat budget of two closed heliothermal cycles initiated by two rainfall events of 50 mm and 52 mm in 1993 were analysed. The cycles prevailed for 11 and 20 days respectively and the heat budget showed net heat accumulations of 34.2 MJ m<sup>−3</sup><span>&nbsp;</span>and 15.4 MJ m<sup>−3</sup>, respectively. The corresponding efficiencies of lake heat gain to incident solar energy were 0.17 and 0.18 respectively. Typically, artificial salinity gradient solar ponds (SGSP) have a solar radiation capture efficiencies ranging from 0.10 up to 0.30. Results from Lake Hayward have implications for comparative biogeochemistry and its characteristics should aid in identification of other hitherto unknown heliothermal lakes.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.03.056","usgsCitation":"Turner, J.V., Rosen, M.R., Coshell, L., and Woodbury, R.J., 2018, Cyclic heliothermal behaviour of the shallow, hypersaline Lake Hayward, Western Australia: Journal of Hydrology, v. 560, p. 495-511, https://doi.org/10.1016/j.jhydrol.2018.03.056.","productDescription":"17 p.","startPage":"495","endPage":"511","ipdsId":"IP-081223","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":488766,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2018.03.056","text":"Publisher Index Page"},{"id":353480,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              115.587158203125,\n              -33.121450558365964\n            ],\n            [\n              115.76156616210938,\n              -33.121450558365964\n            ],\n            [\n              115.76156616210938,\n              -32.69717735929062\n            ],\n            [\n              115.587158203125,\n              -32.69717735929062\n            ],\n            [\n              115.587158203125,\n              -33.121450558365964\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"560","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6dae4b0da30c1bfbea2","contributors":{"authors":[{"text":"Turner, Jeffrey V.","contributorId":204299,"corporation":false,"usgs":false,"family":"Turner","given":"Jeffrey","email":"","middleInitial":"V.","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":733587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coshell, Lee","contributorId":204300,"corporation":false,"usgs":false,"family":"Coshell","given":"Lee","email":"","affiliations":[{"id":36910,"text":"University of New England, Australia","active":true,"usgs":false}],"preferred":false,"id":733588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodbury, Robert J.","contributorId":204301,"corporation":false,"usgs":false,"family":"Woodbury","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":733589,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198066,"text":"70198066 - 2018 - Relative contributions of microbial and infrastructure heat at a crude oil-contaminated site","interactions":[],"lastModifiedDate":"2018-07-12T22:33:48","indexId":"70198066","displayToPublicDate":"2018-04-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Relative contributions of microbial and infrastructure heat at a crude oil-contaminated site","docAbstract":"<p>Biodegradation of contaminants can increase the temperature in the subsurface due to heat generated from exothermic reactions, making temperature observations a potentially low-cost approach for determining microbial activity. For this technique to gain more widespread acceptance, it is necessary to better understand all the factors affecting the measured temperatures. Biodegradation has been occurring at a crude oil-contaminated site near Bemidji, Minnesota for 39 years, creating a quasi-steady-state plume of contaminants and degradation products. A model of subsurface heat generation and transport helps elucidate the contribution of microbial and infrastructure heating to observed temperature increases at this site. We created a steady-state, two-dimensional, heat transport model using previous-published parameter values for physical, chemical and biodegradation properties. Simulated temperature distributions closely match the observed average annual temperatures measured in the contaminated area at the site within less than 0.2 °C in the unsaturated zone and 0.4 °C in the saturated zone. The model results confirm that the observed subsurface heat from microbial activity is due primarily to methane oxidation in the unsaturated zone resulting in a 3.6 °C increase in average annual temperature. Another important source of subsurface heat is from the active, crude-oil pipelines crossing the site. The pipelines impact temperatures for a distance of 200 m and contribute half the heat. Model results show that not accounting for the heat from the pipelines leads to overestimating the degradation rates by a factor of 1.7, demonstrating the importance of identifying and quantifying all heat sources. The model results also highlighted a zone where previously unknown microbial activity is occurring at the site.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2018.03.011","usgsCitation":"Warren, E., and Bekins, B.A., 2018, Relative contributions of microbial and infrastructure heat at a crude oil-contaminated site: Journal of Contaminant Hydrology, v. 211, p. 94-103, https://doi.org/10.1016/j.jconhyd.2018.03.011.","productDescription":"10 p.","startPage":"94","endPage":"103","ipdsId":"IP-091056","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":355636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","county":"Beltrami County","city":"Bemidji","volume":"211","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e598e4b060350a15d1e2","contributors":{"authors":[{"text":"Warren, Ean 0000-0002-2634-8289 ewarren@usgs.gov","orcid":"https://orcid.org/0000-0002-2634-8289","contributorId":206234,"corporation":false,"usgs":true,"family":"Warren","given":"Ean","email":"ewarren@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":739851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":739852,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196498,"text":"70196498 - 2018 - Effects of climate change on forest vegetation in the Northern Rockies Region","interactions":[],"lastModifiedDate":"2020-08-20T16:39:00.804433","indexId":"70196498","displayToPublicDate":"2018-04-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"RMRS-GTR-374","chapter":"6","title":"Effects of climate change on forest vegetation in the Northern Rockies Region","docAbstract":"<p><span>The projected rapid changes in climate will affect the unique vegetation assemblages of the Northern Rockies region in myriad ways, both directly through shifts in vegetation growth, mortality, and regeneration, and indirectly through changes in disturbance regimes and interactions with changes in other ecosystem processes, such as hydrology, snow dynamics, and exotic invasions (Bonan 2008; Hansen and Phillips 2015; Hansen et al. 2001; Notaro et al. 2007). These impacts, taken collectively, could change the way vegetation is managed by public land agencies in this area. Some species may be in danger of rapid decreases in abundance, while others may undergo range expansion (Landhäusser et al. 2010). New vegetation communities may form, while historical vegetation complexes may simply shift to other areas of the landscape or become rare. Juxtaposed with climate change concerns are the consequences of other land management policies and past activities, such as fire exclusion, fuels treatments, and grazing. A thorough assessment of the responses of vegetation to projected climate change is needed, along with an evaluation of the vulnerability of important species, communities, and vegetation-related resources that may be influenced by the effects, both direct and indirect, of climate change. This assessment must also account for past management actions and current vegetation conditions and their interactions with future climates.</span></p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Climate change vulnerability and adaptation in the Northern Rocky Mountains - Part 1","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Forest Service","usgsCitation":"Keane, R.E., Mahalovich, M.F., Bollenbacher, B.L., Manning, M., Loehman, R.A., Jain, T.B., Holsinger, L.M., Larson, A.J., and Webster, M.M., 2018, Effects of climate change on forest vegetation in the Northern Rockies Region: General Technical Report RMRS-GTR-374, 46 p.","productDescription":"46 p.","startPage":"128","endPage":"173","ipdsId":"IP-072292","costCenters":[{"id":118,"text":"Alaska Science Center 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J.","contributorId":197832,"corporation":false,"usgs":false,"family":"Larson","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":7089,"text":"University of Montana, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":733260,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Webster, Meredith M.","contributorId":204163,"corporation":false,"usgs":false,"family":"Webster","given":"Meredith","email":"","middleInitial":"M.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":733261,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70196464,"text":"70196464 - 2018 - Methane in groundwater from a leaking gas well, Piceance Basin, Colorado, USA","interactions":[],"lastModifiedDate":"2018-04-10T11:07:39","indexId":"70196464","displayToPublicDate":"2018-04-10T00:00:00","publicationYear":"2018","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":"Methane in groundwater from a leaking gas well, Piceance Basin, Colorado, USA","docAbstract":"<p><span>Site-specific and regional analysis of time-series hydrologic and geochemical data collected from 15 monitoring wells in the Piceance Basin indicated that a leaking gas well contaminated shallow groundwater with thermogenic methane. The gas well was drilled in 1956 and plugged and abandoned in 1990. Chemical and isotopic data showed the thermogenic methane was not from mixing of gas-rich formation water with shallow groundwater or natural migration of a free-gas phase. Water-level and methane-isotopic data, and video logs from a deep monitoring well, indicated that a shale confining layer ~125&nbsp;m below the zone of contamination was an effective barrier to upward migration of water and gas. The gas well, located 27&nbsp;m from the contaminated monitoring well, had ~1000&nbsp;m of uncemented annular space behind production casing that was the likely pathway through which deep gas migrated into the shallow aquifer. Measurements of soil gas near the gas well showed no evidence of methane emissions from the soil to the atmosphere even though methane concentrations in shallow groundwater (16 to 20&nbsp;mg/L) were above air-saturation levels. Methane degassing from the water table was likely oxidized in the relatively thick unsaturated zone (~18&nbsp;m), thus rendering the leak undetectable at land surface. Drilling and plugging records for oil and gas wells in Colorado and proxies for depth to groundwater indicated thousands of oil and gas wells were drilled and plugged in the same timeframe as the implicated gas well, and the majority of those wells were in areas with relatively large depths to groundwater. This study represents one of the few detailed subsurface investigations of methane leakage from a plugged and abandoned gas well. As such, it could provide a useful template for prioritizing and assessing potentially leaking wells, particularly in cases where the leakage does not manifest itself at land surface.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.03.371","usgsCitation":"McMahon, P.B., Thomas, J.C., Crawford, J.T., Dornblaser, M.M., and Hunt, A.G., 2018, Methane in groundwater from a leaking gas well, Piceance Basin, Colorado, USA: Science of the Total Environment, v. 634, p. 791-801, https://doi.org/10.1016/j.scitotenv.2018.03.371.","productDescription":"11 p.","startPage":"791","endPage":"801","ipdsId":"IP-093525","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":353286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","volume":"634","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e5e4b0da30c1bfbef0","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Judith C. 0000-0001-7883-1419 juthomas@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":1468,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"juthomas@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":733020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dornblaser, Mark M. 0000-0002-6298-3757 mmdornbl@usgs.gov","orcid":"https://orcid.org/0000-0002-6298-3757","contributorId":1636,"corporation":false,"usgs":true,"family":"Dornblaser","given":"Mark","email":"mmdornbl@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":733021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":733022,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196479,"text":"70196479 - 2018 - Simulating selenium and nitrogen fate and transport in coupled stream-aquifer systems of irrigated regions","interactions":[],"lastModifiedDate":"2018-04-10T16:44:08","indexId":"70196479","displayToPublicDate":"2018-04-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Simulating selenium and nitrogen fate and transport in coupled stream-aquifer systems of irrigated regions","docAbstract":"<div class=\"Abstracts\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">Elevated levels of selenium (Se) in aqueous environments can harm aquatic life and endanger livestock and human health. Although Se occurs naturally in the rocks and soils of many alluvial aquifers, mining and agricultural activities can increase its rate of mobilization and transport to surface waters. Attention is given here to regions where nonpoint source return flows from irrigated lands carry pollutant loads to aquifers and streams, contributing to concentrations that violate regulatory and performance standards. Of particular concern is the heightened level and mobilization of Se influenced by nitrate (NO<sub>3</sub>), a harmful pollutant in its own right. We present a numerical model that simulates the reactive transport of Se and nitrogen (N) species in a coupled groundwater-surface water system. Building upon a conceptual model that incorporates the major processes affecting Se and NO<sub>3</sub><span>&nbsp;</span>transport in an irrigated watershed, the model links the finite-difference models MODFLOW, UZF-RT3D, and OTIS, to simulate flow and reactive transport of multiple chemical species in both the aquifer and a stream network, with mass exchange between the two. The capability of the new model is showcased by calibration, testing, and application to a 500 km<sup>2</sup><span>&nbsp;</span>region in Colorado’s Lower Arkansas River Valley using a rich data set gathered over a 10-yr period. Simulation of spatial and temporal distributions of Se concentration reveals conditions that exceed standards in groundwater for approximately 20% of the area. For the Arkansas River, standards are exceeded by 290%–450%. Simulation indicates that river concentrations of NO<sub>3</sub><span>&nbsp;</span>alone are near the current interim standard for the total of all dissolved N species. These results indicate the need for future use of the developed model to investigate the prospects for land and water best management practices to decrease pollutant levels.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.02.027","usgsCitation":"Shultz, C.D., Bailey, R.T., Gates, T.K., Heesemann, B.E., and Morway, E.D., 2018, Simulating selenium and nitrogen fate and transport in coupled stream-aquifer systems of irrigated regions: Journal of Hydrology, v. 560, p. 512-529, https://doi.org/10.1016/j.jhydrol.2018.02.027.","productDescription":"18 p.","startPage":"512","endPage":"529","ipdsId":"IP-091403","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":468837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2018.02.027","text":"Publisher Index Page"},{"id":353309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Arkansas River Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.9251708984375,\n              37.900865092570065\n            ],\n            [\n              -103.18359375,\n              37.900865092570065\n            ],\n            [\n              -103.18359375,\n              38.16047628099622\n            ],\n            [\n              -103.9251708984375,\n              38.16047628099622\n            ],\n            [\n              -103.9251708984375,\n              37.900865092570065\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"560","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e5e4b0da30c1bfbeee","contributors":{"authors":[{"text":"Shultz, Christopher D.","contributorId":204128,"corporation":false,"usgs":false,"family":"Shultz","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":36859,"text":"Colorado State University, Department of Civil and Environmental Engineerring","active":true,"usgs":false}],"preferred":false,"id":733150,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Ryan T. 0000-0002-6539-1474","orcid":"https://orcid.org/0000-0002-6539-1474","contributorId":204129,"corporation":false,"usgs":false,"family":"Bailey","given":"Ryan","email":"","middleInitial":"T.","affiliations":[{"id":36859,"text":"Colorado State University, Department of Civil and Environmental Engineerring","active":true,"usgs":false}],"preferred":false,"id":733151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gates, Timothy K.","contributorId":204130,"corporation":false,"usgs":false,"family":"Gates","given":"Timothy","email":"","middleInitial":"K.","affiliations":[{"id":36860,"text":"Colorado State University, Department of Civil and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":733152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heesemann, Brent E.","contributorId":204131,"corporation":false,"usgs":false,"family":"Heesemann","given":"Brent","email":"","middleInitial":"E.","affiliations":[{"id":36861,"text":"Parsons Corporation, Denver","active":true,"usgs":false}],"preferred":false,"id":733153,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733149,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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