Conversion of agricultural lands to wetlands and native prairie is widely viewed as beneficial because it can restore natural ecological and hydrologic functions. Some of these functions, such as reduced peak flows and improved water quality, are often attributed to restoration; however, such benefits have not been quantified at a small scale. To inform future restoration efforts, especially in northern prairie settings, the U.S. Geological Survey, in cooperation with the Minnesota Environment and Natural Resources Trust Fund, the U.S. Fish and Wildlife Service, and the Red Lake Watershed District, compared the hydrology of the Nation’s largest wetland and prairie restoration, Glacial Ridge National Wildlife Refuge, before and after restoration.
Wetland and prairie restorations resulted in substantial changes in flows through the hydrologic cycle, in reduction of overland runoff and ditch flow during storms, and in improvements in water quality. Wetland and prairie restorations within the six basins characterized in this study resulted in a 14-percent decrease of cropland, a 6-percent increase of wetlands, and a 19-percent increase of native prairie between 2002 and 2015. During the same period, runoff rate decreased 33 percent (as a proportion of precipitation) and ditch flow rate decreased by 23 percent. Areal groundwater recharge rate increased from 30 to 35 percent (16 percent relative change in flow rate). Base flow as a proportion of total ditch flow increased from 25 to 35 percent (a 40-percent relative change). Peak ditch flow from storms decreased, ditch-flow recessions lengthened, and base flow from groundwater discharge increased, though only a small amount in some basins. These changes reduce the amount of ditch water leaving the study area, reducing flows that contribute to downstream flooding. Median surficial groundwater and ditch-water nitrate concentrations decreased by 79 and 53 percent, respectively. Median ditch-water suspended-sediment concentration decreased by 64 percent.
Neither the density of restorations nor the beneficial changes in hydrology were evenly distributed in the study area. The amount of hydrologic benefits within an individual ditch basin did not relate directly with the amount of restoration in that basin; however, the landscape characteristics that related most closely with hydrologic benefits were the area of a basin underlain by a surficial aquifer and the area of drained wetlands (indicating the potential for wetland restoration). In western Minnesota, the basins underlain by surficial aquifers that contain large areas of drained wetlands are the uplands of the Alexandria Moraine Complex and the beaches of glacial Lake Agassiz on the eastern side of the western one-third of Minnesota, north of Wilmar, Minnesota. These findings provide resource managers with information that can help focus restoration resources in areas where the greatest hydrologic benefits can be realized.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195041","collaboration":"Prepared in cooperation with the Minnesota Environment and Natural Resources Trust Fund, the U.S. Fish and Wildlife Service, and the Red Lake Watershed District","usgsCitation":"Cowdery, T.K., Christenson, C.A., and Ziegeweid, J.R., 2019, The hydrologic benefits of wetland and prairie restoration in western Minnesota—Lessons learned at the Glacial Ridge National Wildlife Refuge, 2002–15: U.S. Geological Survey Scientific Investigations Report 2019–5041, 81 p., https://doi.org/10.3133/sir20195041.","productDescription":"Report: ix, 81 p.; Data Release","numberOfPages":"96","onlineOnly":"Y","ipdsId":"IP-093837","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":366811,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5041/sir20195041.pdf","text":"Report","size":"7.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5041"},{"id":366812,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QRD7A3","text":"USGS data release ","linkHelpText":"A Soil-Water-Balance model and precipitation data used for HEC/HMS modelling at the Glacial Ridge National Wildlife Refuge area, northwestern Minnesota, 2002–15"},{"id":366810,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5041/coverthb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Glacial Ridge National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.52107238769531,\n 47.584399766577576\n ],\n [\n -96.12007141113281,\n 47.584399766577576\n ],\n [\n -96.12007141113281,\n 47.823298103444806\n ],\n [\n -96.52107238769531,\n 47.823298103444806\n ],\n [\n -96.52107238769531,\n 47.584399766577576\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN
Director, Earth System Processes Division
U.S. Geological Survey
Mail Stop 411
12201 Sunrise Valley Drive
Reston, VA 20192
Changing Arctic climate may alter freshwater ecosystems as a result of warmer surface waters, longer open-water periods, reduced wintertime lake ice growth, and altered hydrologic connectivity. This study aims to characterize zooplankton community composition and size structure in the context of hydrologic connectivity and ice regimes in Arctic lakes. Between 2011 and 2016, we sampled the phytoplankton, zooplankton, and fish communities from a set of representative lakes on the Arctic Coastal Plain (ACP) of northern Alaska to determine potential food web responses to changing Arctic ecosystems. Multivariate analyses showed that time from ice-out had a strong influence on zooplankton community structure and that seasonal succession of zooplankton differed between lakes with varying hydrologic connectivity. Trends were observed suggesting that large-bodied zooplankton (Daphnia, calanoid copepods) may be more prevalent in poorly connected lakes with low fish diversity. Large-bodied zooplankton displayed higher biomass in lakes with high occurrences of bedfast ice, while small-bodied zooplankton (Bosmina, rotifers) displayed highest biomass in deeper lakes with low occurrences of bedfast ice. Our results contribute to limited knowledge of zooplankton in remote lakes of the ACP and suggest that the anticipated changes to aquatic ecosystems in the Arctic may include energetically less efficient plankton food webs.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15230430.2019.1643210","usgsCitation":"Beaver, J.R., Arp, C.D., Tausz, C.E., Jones, B.M., Whitman, M.S., Renicker, T.R., Samples, E.E., Ordosch, D.M., and Scotese, K.C., 2019, Potential shifts in zooplankton community structure in response to changing ice regimes and hydrologic connectivity: Arctic, Antarctic, and Alpine Research, v. 51, no. 1, p. 327-345, https://doi.org/10.1080/15230430.2019.1643210.","productDescription":"19 p.","startPage":"327","endPage":"345","ipdsId":"IP-086427","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":467357,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15230430.2019.1643210","text":"Publisher Index Page"},{"id":408649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150.4555084446034,\n 70.42307829371518\n ],\n [\n -154.7694812572369,\n 70.42307829371518\n ],\n [\n -154.7694812572369,\n 68.72452581295417\n ],\n [\n -150.4555084446034,\n 68.72452581295417\n ],\n [\n -150.4555084446034,\n 70.42307829371518\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-08-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Beaver, John R. 0000-0003-0091-2387","orcid":"https://orcid.org/0000-0003-0091-2387","contributorId":202089,"corporation":false,"usgs":false,"family":"Beaver","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":36339,"text":"BSA Environmental Services, Inc.","active":true,"usgs":false}],"preferred":false,"id":855597,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855598,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tausz, Claudia E.","contributorId":202091,"corporation":false,"usgs":false,"family":"Tausz","given":"Claudia","email":"","middleInitial":"E.","affiliations":[{"id":36339,"text":"BSA Environmental Services, Inc.","active":true,"usgs":false}],"preferred":false,"id":855715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":855599,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitman, Matthew S.","contributorId":67961,"corporation":false,"usgs":false,"family":"Whitman","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":855600,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Renicker, Thomas R.","contributorId":202090,"corporation":false,"usgs":false,"family":"Renicker","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":36339,"text":"BSA Environmental Services, Inc.","active":true,"usgs":false}],"preferred":false,"id":855601,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Samples, Erin E","contributorId":298429,"corporation":false,"usgs":false,"family":"Samples","given":"Erin","email":"","middleInitial":"E","affiliations":[{"id":64577,"text":"BSA Environmental Services","active":true,"usgs":false}],"preferred":false,"id":855602,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ordosch, David M","contributorId":298430,"corporation":false,"usgs":false,"family":"Ordosch","given":"David","email":"","middleInitial":"M","affiliations":[{"id":64577,"text":"BSA Environmental Services","active":true,"usgs":false}],"preferred":false,"id":855603,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scotese, Kyle C.","contributorId":201592,"corporation":false,"usgs":false,"family":"Scotese","given":"Kyle","email":"","middleInitial":"C.","affiliations":[{"id":36339,"text":"BSA Environmental Services, Inc.","active":true,"usgs":false}],"preferred":true,"id":855604,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70217322,"text":"70217322 - 2019 - Development and implementation of an empirical habitat change model and decision support tool for estuarine ecosystems","interactions":[],"lastModifiedDate":"2021-01-19T12:55:34.568699","indexId":"70217322","displayToPublicDate":"2019-08-19T07:07:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Development and implementation of an empirical habitat change model and decision support tool for estuarine ecosystems","docAbstract":"Widespread land use change in coastal ecosystems has led to a decline in the amount of habitat available for fish and wildlife, lower production of ecosystem goods and services, and loss of recreational and aesthetic value. This has prompted global efforts to restore the natural hydrologic regimes of developed shorelines, especially resource-rich estuaries, but the resilience of these restored ecosystems in the face of accelerated sea-level rise (SLR) remains uncertain. We implemented a Monitoring-based Simulation of Accretion in Coastal Estuaries (MOSAICS) in R statistical software to address uncertainty in the resilience of modified estuarine habitats, using the Nisqually River Delta in the Pacific Northwest USA as a case study. MOSAICS is a spatially explicit model with a numerical foundation that uses empirical monitoring datasets to forecast habitat change in response to rising tidal levels. Because it accounts for the crucial ecomorphodynamic feedbacks between tidal inundation, vegetative growth, and sediment accretion, MOSAICS can be used to determine whether alternative management scenarios, such as enhanced sediment inputs, will bolster estuarine resilience to SLR. Under moderate SLR (0.62 m), the model predicted that a two-fold increase in mean daily suspended sediment during the rainy season was sufficient to maintain Nisqually’s emergent marshes through 2100, but under high SLR (1.35 m) MOSAICS indicated that greater sediment additions would be necessary to prevent submergence. A comparison between a restored marsh with subsided and high-elevation areas and a relict marsh demonstrated that the subsided restoration area was highly susceptible to SLR. Findings from the MOSAICS model highlight the importance of a site’s initial elevation, capacity for producing above and belowground biomass, and suspended sediment availability when considering management actions in estuaries and other coastal ecosystems.
Hennig Brandt's discovery of phosphorus (P) occurred during the early European colonization of the Chesapeake Bay region. Today, P, an essential nutrient on land and water alike, is one of the principal threats to the health of the bay. Despite widespread implementation of best management practices across the Chesapeake Bay watershed following the implementation in 2010 of a total maximum daily load (TMDL) to improve the health of the bay, P load reductions across the bay's 166,000‐km2 watershed have been uneven, and dissolved P loads have increased in a number of the bay's tributaries. As the midpoint of the 15‐yr TMDL process has now passed, some of the more stubborn sources of P must now be tackled. For nonpoint agricultural sources, strategies that not only address particulate P but also mitigate dissolved P losses are essential. Lingering concerns include legacy P stored in soils and reservoir sediments, mitigation of P in artificial drainage and stormwater from hotspots and converted farmland, manure management and animal heavy use areas, and critical source areas of P in agricultural landscapes. While opportunities exist to curtail transport of all forms of P, greater attention is required toward adapting P management to new hydrologic regimes and transport pathways imposed by climate change.
","language":"English","publisher":"Wiley","doi":"10.2134/jeq2019.03.0112","usgsCitation":"Kleinman, P., Fanelli, R., Hirsch, R.M., Buda, A.R., Easton, Z.M., Wainger, L.A., Brosch, C., Lowenfish, M., Collick, A.S., Shirmohammadi, A., Boomer, K., Hubbart, J.A., Bryant, R.B., and Shenk, G., 2019, Phosphorus and the Chesapeake Bay: Lingering issues and emerging concerns for agriculture: Journal of Environmental Quality, v. 48, no. 5, p. 1191-1203, https://doi.org/10.2134/jeq2019.03.0112.","productDescription":"13 p.","startPage":"1191","endPage":"1203","ipdsId":"IP-106511","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":467365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2019.03.0112","text":"Publisher Index Page"},{"id":379941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.11328125,\n 36.92793899776678\n ],\n [\n -75.948486328125,\n 37.23470197166817\n ],\n [\n -75.673828125,\n 37.896530447543\n ],\n [\n -75.816650390625,\n 38.28993659801203\n ],\n [\n -75.8221435546875,\n 38.436379603\n ],\n [\n -76.0858154296875,\n 38.44498466889473\n ],\n [\n -76.0308837890625,\n 38.71980474264237\n ],\n [\n -75.7781982421875,\n 39.614152077002664\n ],\n [\n -76.1956787109375,\n 39.592990390285024\n ],\n [\n -76.7230224609375,\n 39.21948715423953\n ],\n [\n -76.629638671875,\n 38.565347844885466\n ],\n [\n -76.629638671875,\n 38.40194908237822\n ],\n [\n -77.0635986328125,\n 38.487994609214795\n ],\n [\n -77.05810546875,\n 38.21660403859855\n ],\n [\n -76.4373779296875,\n 37.92686760148135\n ],\n [\n -77.04711914062499,\n 38.190704293996504\n ],\n [\n -77.156982421875,\n 38.043765107439675\n ],\n [\n -76.497802734375,\n 37.501010429493284\n ],\n [\n -76.4813232421875,\n 37.322120359451766\n ],\n [\n -76.4813232421875,\n 37.14718209972376\n ],\n [\n -76.234130859375,\n 36.85764758564407\n ],\n [\n -76.11328125,\n 36.92793899776678\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kleinman, Peter","contributorId":244141,"corporation":false,"usgs":false,"family":"Kleinman","given":"Peter","email":"","affiliations":[{"id":48855,"text":"USDA-ARS, Pasture Syst. and Watershed Mgmt. Res. Unit, University Park, PA 16877","active":true,"usgs":false}],"preferred":false,"id":803404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":206608,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":803478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buda, Anthony R 0000-0002-5194-4998","orcid":"https://orcid.org/0000-0002-5194-4998","contributorId":243977,"corporation":false,"usgs":false,"family":"Buda","given":"Anthony","email":"","middleInitial":"R","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":803479,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Easton, Zachary M.","contributorId":244188,"corporation":false,"usgs":false,"family":"Easton","given":"Zachary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":803480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wainger, Lisa A.","contributorId":127628,"corporation":false,"usgs":false,"family":"Wainger","given":"Lisa","email":"","middleInitial":"A.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":803481,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brosch, Chris","contributorId":244189,"corporation":false,"usgs":false,"family":"Brosch","given":"Chris","email":"","affiliations":[],"preferred":false,"id":803482,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lowenfish, Mark","contributorId":244191,"corporation":false,"usgs":false,"family":"Lowenfish","given":"Mark","email":"","affiliations":[],"preferred":false,"id":803483,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Collick, Amy S.","contributorId":244192,"corporation":false,"usgs":false,"family":"Collick","given":"Amy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":803484,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shirmohammadi, Adel","contributorId":244193,"corporation":false,"usgs":false,"family":"Shirmohammadi","given":"Adel","email":"","affiliations":[],"preferred":false,"id":803485,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Boomer, Kathy","contributorId":218733,"corporation":false,"usgs":false,"family":"Boomer","given":"Kathy","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":803486,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hubbart, Jason A.","contributorId":194439,"corporation":false,"usgs":false,"family":"Hubbart","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":803487,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bryant, R. B.","contributorId":191824,"corporation":false,"usgs":false,"family":"Bryant","given":"R.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":803488,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Shenk, Gary","contributorId":244194,"corporation":false,"usgs":false,"family":"Shenk","given":"Gary","affiliations":[],"preferred":false,"id":803489,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70204253,"text":"sir20195068 - 2019 - Flood-inundation maps for Joachim Creek, De Soto, Missouri, 2018","interactions":[],"lastModifiedDate":"2019-08-16T06:55:10","indexId":"sir20195068","displayToPublicDate":"2019-08-15T13:46:58","publicationYear":"2019","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":"2019-5068","displayTitle":"Flood-Inundation Maps for Joachim Creek, De Soto, Missouri, 2018","title":" Flood-inundation maps for Joachim Creek, De Soto, Missouri, 2018","docAbstract":"Digital flood-inundation maps for a 6.7-mile reach of Joachim Creek, De Soto, Missouri, were created by the U.S. Geological Survey (USGS) in cooperation with the city of De Soto and Jefferson County, Missouri. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage Joachim Creek at De Soto, Missouri (station number 07019500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps2/hydrograph.php?wfo=lsx&gage=desm7, which also forecasts flood hydrographs at this site (site DESM7).
Flood profiles were computed for the stream reach using a one-dimensional model for simulation of water-surface profiles with steady-state (gradually varied) or unsteady-state flow computation options. The model was calibrated by using the theoretical stage-discharge relation at the USGS streamgage Joachim Creek at De Soto, Missouri (station number 07019500), and documented high-water marks from the flood of April 18, 2013.
The hydraulic model was then used to compute 10 water surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum. The profiles ranged from 8.0 ft, or near bankfull, to 17.0 ft, which exceeds the stage that corresponds to the estimated 0.2-percent annual exceedance probability flood (500-year recurrence interval flood). The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.60-ft vertical accuracy and 1.97-ft horizontal resolution) 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 and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures and for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195068","collaboration":"Prepared in cooperation with the city of De Soto, Missouri, and Jefferson County, Missouri","usgsCitation":"Heimann, D.C., Voss, J.D., and Rydlund, P.H., Jr., 2019, Flood-inundation maps for Joachim Creek, De Soto, Missouri, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5068, 10 p., https://doi.org/10.3133/sir20195068.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-105218","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":366556,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5068/sir20195068.pdf","text":"Report","size":"2.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5068"},{"id":366557,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MD7KUL","text":"USGS data release","linkHelpText":"Geospatial datasets for the flood-inundation study of Joachim Creek, De Soto, Missouri, 2018"},{"id":366555,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5068/coverthb.jpg"}],"country":"United States","state":"Missouri","county":"Jefferson County","city":"De Soto","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-94.1091,39.1434],[-94.1183,38.9171],[-94.1223,38.8323],[-94.4007,38.837],[-94.5528,38.844],[-94.5705,38.8447],[-94.6082,38.8463],[-94.6075,39.0399],[-94.6075,39.0437],[-94.6082,39.1147],[-94.5966,39.1144],[-94.5889,39.115],[-94.5801,39.1188],[-94.566,39.1231],[-94.5637,39.124],[-94.5531,39.1287],[-94.5455,39.1343],[-94.5393,39.1426],[-94.5358,39.1449],[-94.5334,39.1463],[-94.5293,39.1464],[-94.5228,39.1487],[-94.5204,39.1492],[-94.5163,39.1502],[-94.5122,39.1503],[-94.508,39.1508],[-94.5039,39.1504],[-94.5015,39.1495],[-94.4985,39.1482],[-94.4931,39.1465],[-94.4883,39.1439],[-94.4834,39.1394],[-94.4797,39.1349],[-94.467,39.1242],[-94.4651,39.1229],[-94.461,39.1221],[-94.4592,39.1226],[-94.4563,39.124],[-94.4522,39.1276],[-94.4452,39.1314],[-94.4446,39.1314],[-94.4353,39.1379],[-94.4277,39.1425],[-94.4271,39.143],[-94.4266,39.1439],[-94.426,39.1448],[-94.4254,39.1453],[-94.4248,39.1453],[-94.4178,39.1517],[-94.4098,39.1609],[-94.4092,39.1614],[-94.4063,39.1655],[-94.4058,39.1678],[-94.4052,39.1687],[-94.4036,39.1755],[-94.4068,39.1823],[-94.413,39.1931],[-94.413,39.1944],[-94.4107,39.1963],[-94.406,39.1982],[-94.4054,39.1982],[-94.3989,39.1969],[-94.394,39.1943],[-94.3934,39.1938],[-94.3885,39.188],[-94.3847,39.1763],[-94.3816,39.1713],[-94.3798,39.17],[-94.3791,39.1687],[-94.3779,39.1655],[-94.376,39.1633],[-94.3748,39.1624],[-94.3718,39.1611],[-94.3695,39.162],[-94.3631,39.168],[-94.3602,39.1703],[-94.3561,39.1735],[-94.3549,39.174],[-94.3538,39.1745],[-94.3479,39.1777],[-94.3473,39.1791],[-94.3386,39.1856],[-94.3369,39.1879],[-94.3357,39.1893],[-94.3323,39.1929],[-94.3311,39.1948],[-94.3282,39.1975],[-94.3265,39.1994],[-94.3253,39.2007],[-94.3248,39.2021],[-94.3236,39.2035],[-94.3236,39.2044],[-94.3231,39.2062],[-94.3226,39.2085],[-94.318,39.2176],[-94.3134,39.2213],[-94.3128,39.2222],[-94.3122,39.2227],[-94.3111,39.2236],[-94.3099,39.2254],[-94.307,39.2291],[-94.3064,39.2296],[-94.3053,39.2305],[-94.3047,39.231],[-94.3024,39.2324],[-94.3006,39.2333],[-94.2982,39.2342],[-94.2959,39.2352],[-94.2947,39.2356],[-94.2929,39.2361],[-94.2912,39.2366],[-94.2906,39.2371],[-94.2894,39.2371],[-94.2876,39.2367],[-94.2858,39.2367],[-94.2847,39.2367],[-94.284,39.2363],[-94.2811,39.2363],[-94.2787,39.2363],[-94.2769,39.2364],[-94.2739,39.2359],[-94.2703,39.2351],[-94.2674,39.2351],[-94.2656,39.2356],[-94.2644,39.2356],[-94.2638,39.2356],[-94.2614,39.2357],[-94.2603,39.2361],[-94.2585,39.2362],[-94.2561,39.2362],[-94.2537,39.2358],[-94.2525,39.2353],[-94.2519,39.2354],[-94.2507,39.2349],[-94.2489,39.2345],[-94.2471,39.2341],[-94.2459,39.2336],[-94.2441,39.2327],[-94.2436,39.2323],[-94.2417,39.2314],[-94.2411,39.231],[-94.2405,39.2305],[-94.2399,39.2296],[-94.2393,39.2283],[-94.2387,39.2274],[-94.2368,39.2233],[-94.2349,39.2202],[-94.2331,39.2179],[-94.2313,39.2166],[-94.2295,39.2157],[-94.2283,39.2148],[-94.2277,39.2144],[-94.2265,39.2135],[-94.2252,39.2122],[-94.224,39.2117],[-94.2222,39.2099],[-94.2186,39.2091],[-94.218,39.2086],[-94.2174,39.2082],[-94.2168,39.2077],[-94.2144,39.2073],[-94.2132,39.2073],[-94.2127,39.2073],[-94.2085,39.2074],[-94.2067,39.2079],[-94.2056,39.2083],[-94.2044,39.2093],[-94.2009,39.2111],[-94.1997,39.212],[-94.1973,39.2125],[-94.1962,39.213],[-94.195,39.2135],[-94.1926,39.2144],[-94.1908,39.2144],[-94.1897,39.2145],[-94.1879,39.2145],[-94.1867,39.2145],[-94.1849,39.2145],[-94.1843,39.2145],[-94.1825,39.2146],[-94.1796,39.2141],[-94.1784,39.2137],[-94.1778,39.2132],[-94.1766,39.2124],[-94.1759,39.2119],[-94.1753,39.211],[-94.1753,39.2097],[-94.1764,39.2065],[-94.1764,39.2051],[-94.1764,39.2042],[-94.1769,39.2033],[-94.1769,39.2024],[-94.1781,39.2015],[-94.1792,39.1996],[-94.1804,39.1973],[-94.1815,39.196],[-94.1827,39.195],[-94.1844,39.1941],[-94.1862,39.1927],[-94.188,39.1918],[-94.1891,39.1904],[-94.1897,39.19],[-94.1903,39.1895],[-94.1914,39.1881],[-94.1902,39.1859],[-94.1871,39.1828],[-94.1865,39.1819],[-94.1859,39.181],[-94.1847,39.1801],[-94.1829,39.1796],[-94.1811,39.1792],[-94.1799,39.1788],[-94.1787,39.1788],[-94.1769,39.1784],[-94.1746,39.1775],[-94.1698,39.1766],[-94.1644,39.1749],[-94.159,39.1741],[-94.1501,39.1733],[-94.1489,39.1728],[-94.1466,39.1724],[-94.146,39.1724],[-94.1448,39.172],[-94.143,39.1716],[-94.1412,39.1711],[-94.1394,39.1702],[-94.1382,39.1693],[-94.1364,39.168],[-94.1351,39.1667],[-94.1345,39.1667],[-94.1327,39.1644],[-94.1315,39.1636],[-94.1303,39.1622],[-94.1296,39.1604],[-94.1284,39.1581],[-94.1187,39.1488],[-94.1091,39.1434]]]},\"properties\":{\"name\":\"Jackson\",\"state\":\"MO\"}}]}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The costs of invasive species in the United States alone are estimated to exceed US$100 billion per year so a critical tactic in minimizing the costs of invasive species is the development of effective, early-detection systems. To this end, we evaluated the efficacy of adding environmental (e)DNA surveillance to the U.S. Geological Survey (USGS) streamgage network, which consists of > 8,200 streamgages nationwide systemically visited by USGS hydrologic technicians. Incorporating strategic eDNA sample collection during routine streamgage visits could provide early detection surveillance of aquatic invasive species with minimal additional cost. For this evaluation, USGS hydrologic technicians collected monthly eDNA water samples, May – September 2018, from streamgages downstream of reservoirs in the Columbia River Basin thought to be vulnerable to invasive dreissenid mussel (Dreissenidae spp.) establishment. We tested water samples for dreissenid mussel DNA and also for kokanee (Oncorhynchus nerka) and yellow perch (Perca flavescens) DNA; the two fishes were used to assess if streamgages are adequately located to provide early-detection eDNA surveillance of taxa known to be present in upstream reservoirs. No Columbia River Basin streamgage samples met our criteria for being scored as positive for dreissenid DNA. We did detect kokanee and yellow perch DNA at all streamgages downstream of reservoirs where these species are known to occur. Field collection, laboratory analyses, and personnel time required for collection of four eDNA samples at a streamgage site cost US$500 -US$600 (net). Given these results, incorporating eDNA biosurveillance into routine streamgage visits might decrease costs associated with an invasion since early detection maximizes the potential for eradication, containment, and mitigation.
","language":"English","publisher":"ESA","doi":"10.1002/ecs2.2843","usgsCitation":"Sepulveda, A.J., Schmidt, C., Amberg, J., Hutchins, P.R., Stratton, C., Mebane, C.A., Laramie, M., and Pilliod, D.S., 2019, Adding invasive species bio-surveillance to the U.S. Geological Survey streamgage network: Ecosphere, v. 10, no. 8, e02843, 17 p., https://doi.org/10.1002/ecs2.2843.","productDescription":"e02843, 17 p.","ipdsId":"IP-106819","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":460309,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2843","text":"Publisher Index Page"},{"id":366852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.33203125,\n 48.980216985374994\n ],\n [\n -115.927734375,\n 33.063924198120645\n ],\n [\n -105.64453124999999,\n 31.353636941500987\n ],\n [\n -93.42773437499999,\n 45.02695045318546\n ],\n [\n -93.42773437499999,\n 48.69096039092549\n ],\n [\n -125.33203125,\n 48.980216985374994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":768956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Christian 0000-0001-6842-0392","orcid":"https://orcid.org/0000-0001-6842-0392","contributorId":217710,"corporation":false,"usgs":true,"family":"Schmidt","given":"Christian","email":"","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":768958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hutchins, Patrick R. 0000-0001-5232-0821 phutchins@usgs.gov","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":198337,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick","email":"phutchins@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":768959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stratton, Christian","contributorId":217711,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":768960,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768961,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Laramie, Matthew 0000-0001-7820-2583 mlaramie@usgs.gov","orcid":"https://orcid.org/0000-0001-7820-2583","contributorId":152532,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768962,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":216342,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768963,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70207556,"text":"70207556 - 2019 - Geophysical mapping of plume discharge to surface water at a crude oil spill site: Inversion versus machine learning","interactions":[],"lastModifiedDate":"2019-12-24T12:27:15","indexId":"70207556","displayToPublicDate":"2019-08-12T12:15:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical mapping of plume discharge to surface water at a crude oil spill site: Inversion versus machine learning","docAbstract":"The interpretation of geophysical survey results to answer hydrologic, engineering, and geologic questions is critical to diverse problems for management of water, energy, and mineral resources. Although geophysical images provide valuable qualitative insight into subsurface architecture and conditions, translating geophysical images into quantitative information (e.g., saturation, concentration, and hydraulic properties) often involves substantial nonuniqueness and uncertainty owing to the limited resolution of geophysical imaging and uncertainty in petrophysical relations. We have developed a machine-learning approach to address these challenges in the context of a field-based investigation to map zones where a hydrocarbon plume was discharging to surface water at the National Crude Oil Spill Fate and Natural Attenuation Research Site in Bemidji, Minnesota, USA. The two-step approach combines multiple types of geophysical and direct information and effectively bypasses inversion and its associated assumptions. Integrating multifrequency electromagnetic induction, ground-penetrating radar, and fluid-sampling data, we first identify discharge zones and second estimate specific conductance versus depth. Compared with conventional inversion results, the machine-learning results (1) directly address the study objectives (delineating the discharge zones); (2) better extract depth-dependent information from the data, for which sensitivity diminishes rapidly with depth; and (3) quantify the uncertainty of the predictions (i.e., discharge versus nondischarge zones), rather than the uncertainty of the geophysical estimates (i.e., the standard error of estimation for the logarithm of electrical conductivity).
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/geo2018-0690.1","usgsCitation":"Terry, N., Day-Lewis, F.D., Lane, J., Trost, J.J., and Bekins, B.A., 2019, Geophysical mapping of plume discharge to surface water at a crude oil spill site: Inversion versus machine learning: Geophysics, v. 84, no. 5, p. EN67-EN80, https://doi.org/10.1190/geo2018-0690.1.","productDescription":"14 p.","startPage":"EN67","endPage":"EN80","ipdsId":"IP-105187","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":370676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Bemidji","otherGeospatial":"National Crude Oil Spill Fate and Natural Attenuation Research Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.0820,\n 47.5775\n ],\n [\n -95.0920,\n 47.5775\n ],\n [\n -95.0920,\n 47.5715\n ],\n [\n -95.0820,\n 47.5715\n ],\n [\n -95.0820,\n 47.5775\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":778454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":778455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":778456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":778457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":778458,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70205112,"text":"70205112 - 2019 - The effects of restored hydrologic connectivity on floodplain trapping vs. release of phosphorus, nitrogen, and sediment along the Pocomoke River, Maryland USA","interactions":[],"lastModifiedDate":"2019-09-03T17:34:57","indexId":"70205112","displayToPublicDate":"2019-08-09T17:24:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"The effects of restored hydrologic connectivity on floodplain trapping vs. release of phosphorus, nitrogen, and sediment along the Pocomoke River, Maryland USA","docAbstract":"River channelization and artificial levees have decreased the hydrologic connectivity of river-floodplain systems around the world. In response, restoration through enhancing connectivity has been advocated to improve the functions of floodplains, but uncertain benefits and the possibility of phosphate release from re-flooded soils has limited implementation. In this study, we measured change in floodplain P, N, and sediment mass balances after restoration along channelized reaches in the lowland Pocomoke River, Maryland USA. Two floodplains (one headwater, one mainstem) restored through partial levee breaches were compared to two additional mainstem floodplains (one natural unchannelized, one unrestored channelized). Potential soluble reactive P (SRP) release from soil cores during experimental laboratory floods; soil P, Fe, and Al fractionation; and deposition and P and N content of sediment were measured before and after the restoration period, as well as in situ inputs and release of SRP and dissolved inorganic N from soils after restorations. Potential SRP release, during both the before and after restoration period, was greatest at the channelized mainstem and restored mainstem sites, lower at the restored headwater site, and small at the natural mainstem site. Both restored sites had smaller potential SRP release after restoration compared to before restoration. In situ SRP release slightly exceeded inputs to soils at connected sites during the post-restoration period, with less net release at the restored sites compared to the natural mainstem site. The magnitude of gross and net SRP release from soils in the field was smaller than, and uncorrelated with, potential SRP release estimated from laboratory experimental floods. Gross soil SRP release rates in the field were predictable using the ratio of soil oxalate-extractable P/Al. Sedimentation inputs of P and N increased at all sites during the post-restoration period, with rates at restored sites intermediate compared to the much higher rates at the natural mainstem site and somewhat lower rates at the channelized mainstem site. These sediment inputs of nutrients were much larger than rates of inorganic P and N release from soils, indicating net trapping of P and N after restoration. Restoring floodplain hydrologic connectivity showed moderate success at increasing the trapping of P, N, and sediment, with relatively little phosphate release, and therefore improving water quality.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2019.08.002","usgsCitation":"Noe, G.E., Boomer, K., Gillespie, J., Hupp, C.R., Martin-Alciati, M., Floro, K., Schenk, E.R., Jacobs, A.K., and Strano, S., 2019, The effects of restored hydrologic connectivity on floodplain trapping vs. release of phosphorus, nitrogen, and sediment along the Pocomoke River, Maryland USA: Ecological Engineering, v. 138, p. 334-352, https://doi.org/10.1016/j.ecoleng.2019.08.002.","productDescription":"19 p.","startPage":"334","endPage":"352","ipdsId":"IP-106687","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2019.08.002","text":"Publisher Index Page"},{"id":367160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Pocomoke River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.5859375,\n 38.0091482264894\n ],\n [\n -75.3717041015625,\n 38.08268954483802\n ],\n [\n -75.29891967773438,\n 38.13887716726548\n ],\n [\n -75.19454956054688,\n 38.28885871419223\n ],\n [\n -75.2838134765625,\n 38.43960662292255\n ],\n [\n -75.35110473632812,\n 38.4514377951069\n ],\n [\n -75.4046630859375,\n 38.4514377951069\n ],\n [\n -75.43899536132812,\n 38.429925130409366\n ],\n [\n -75.53237915039062,\n 38.24680876017446\n ],\n [\n -75.61203002929688,\n 38.212288054388175\n ],\n [\n -75.68206787109375,\n 38.04052046968823\n ],\n [\n -75.66696166992186,\n 37.96152331396614\n ],\n [\n -75.5859375,\n 38.0091482264894\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"138","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":770071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boomer, Kathy","contributorId":218733,"corporation":false,"usgs":false,"family":"Boomer","given":"Kathy","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":770072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gillespie, Jaimie 0000-0002-6483-0359","orcid":"https://orcid.org/0000-0002-6483-0359","contributorId":202016,"corporation":false,"usgs":true,"family":"Gillespie","given":"Jaimie","email":"","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":770073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":770074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin-Alciati, Mario 0000-0003-3094-2843","orcid":"https://orcid.org/0000-0003-3094-2843","contributorId":218734,"corporation":false,"usgs":true,"family":"Martin-Alciati","given":"Mario","email":"","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":770075,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Floro, Kelly","contributorId":218735,"corporation":false,"usgs":false,"family":"Floro","given":"Kelly","email":"","affiliations":[],"preferred":false,"id":770076,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schenk, Edward R.","contributorId":202018,"corporation":false,"usgs":false,"family":"Schenk","given":"Edward","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":770077,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jacobs, Amy K.","contributorId":174754,"corporation":false,"usgs":false,"family":"Jacobs","given":"Amy","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":770078,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Strano, Steve","contributorId":218736,"corporation":false,"usgs":false,"family":"Strano","given":"Steve","email":"","affiliations":[{"id":13501,"text":"USDA NRCS","active":true,"usgs":false}],"preferred":false,"id":770079,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70204693,"text":"70204693 - 2019 - Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models","interactions":[],"lastModifiedDate":"2019-08-09T12:01:26","indexId":"70204693","displayToPublicDate":"2019-08-07T11:53:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models","docAbstract":"Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribution of base flow inputs and the utility of this method to build a hydrologic model calibration dataset. OHS models with acceptable goodness-of-fit criteria were insensitive to drainage area, stream density, watershed slope, elevation, agricultural or perennial snow/ice land cover, average annual precipitation, runoff, or evapotranspiration, implying that OHS results are a viable calibration dataset applicable in diverse watersheds. OHS-estimated base flow contribution was compared to base flow-like model components from the USGS National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS). The NHM-PRMS variable gwres_flow is most conceptually like a base flow component of streamflow but the gwres_flow contribution to total streamflow is generally smaller than the OHS-estimated base flow contribution. The NHM-PRMS variable slow_flow, added to gwres_flow, produced similar or greater estimates of base flow contributions to total streamflow than the OHS-estimated base flow contribution but was dependent on the total flow magnitude.
","language":"English","publisher":"MDPI","doi":"10.3390/w11081629","usgsCitation":"Foks, S., Raffensperger, J.P., Penn, C.A., and Driscoll, J.M., 2019, Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models: Water, v. 11, no. 8, 1629, 25 p., https://doi.org/10.3390/w11081629.","productDescription":"1629, 25 p.","ipdsId":"IP-104087","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467387,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11081629","text":"Publisher Index Page"},{"id":437370,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XF3C11","text":"USGS data release","linkHelpText":"Base flow estimation via optimal hydrograph separation at CONUS watersheds and comparison to the National Hydrologic Model - Precipitation-Runoff Modeling System by HRU calibrated version"},{"id":366442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"11","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Foks, Sydney 0000-0002-7668-9735","orcid":"https://orcid.org/0000-0002-7668-9735","contributorId":218029,"corporation":false,"usgs":true,"family":"Foks","given":"Sydney","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":768086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raffensperger, Jeff P. 0000-0001-9275-6646 jpraffen@usgs.gov","orcid":"https://orcid.org/0000-0001-9275-6646","contributorId":199119,"corporation":false,"usgs":true,"family":"Raffensperger","given":"Jeff","email":"jpraffen@usgs.gov","middleInitial":"P.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Penn, Colin A. 0000-0002-5195-2744","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":203851,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":768089,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203464,"text":"sir20195044 - 2019 - Using the precipitation-runoff modeling system to predict seasonal water availability in the upper Klamath River basin, Oregon and California","interactions":[],"lastModifiedDate":"2019-08-07T08:45:48","indexId":"sir20195044","displayToPublicDate":"2019-08-06T12:45:52","publicationYear":"2019","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":"2019-5044","displayTitle":"Using the Precipitation-Runoff Modeling System to Predict Seasonal Water Availability in the Upper Klamath River Basin, Oregon and California","title":"Using the precipitation-runoff modeling system to predict seasonal water availability in the upper Klamath River basin, Oregon and California","docAbstract":"Accurate forecasts of the streamflow expected during late spring and summer in the Upper Klamath River Basin in southern-central Oregon and northern California are used by water management agencies to balance water allocations for agriculture, aquatic habitat, and hydropower-production needs. Streamflow forecasts are also used by irrigation farmers for planning. The forecasts are typically made twice a month starting as early in the water year as December. Multiple regression equations relating real-time snowpack and precipitation conditions to seasonal streamflow volumes have been used for many years in forecasting. However, with warming temperature trends and lower snowpack, such forecasts based on historical data could become less reliable in the future. If the timing and relation of snowpack and precipitation are outside of the range of the historical data used to create the equations, the forecasts become extrapolations. Statistical forecast equations are also limited in their ability to forecast streamflow in groundwater-dominated basins having inter-annual lag. As an additional method for seasonal streamflow forecasting, a physical-process-based hydrologic model employing the Precipitation-Runoff Modeling System (PRMS) was developed in cooperation with the U.S. Bureau of Reclamation for the Upper Klamath Basin in this study. The model was calibrated for the portion of the basin draining into Upper Klamath Lake. PRMS is a deterministic, distributed-parameter, physical-process-based modeling system developed by the U.S. Geological Survey. It simulates daily streamflow, snow, solar radiation, evapotranspiration, surface-water, and groundwater processes within the basin. A model calibration and validation period for water years 2000–15 and water years 1984–99, respectively, was used. The model was calibrated and validated using measured streamflow, snowpack, evapotranspiration, and solar radiation data sets. Interpolated daily precipitation and air temperature data from 32 meteorological stations within and surrounding the Upper Klamath Basin were used as model input. Performance statistics, used to evaluate how well simulated daily streamflow matched with measured streamflow included percent bias, percent relative error, and root-mean-square error. The statistics were computed annually, monthly, for October–March, and for April–September. With the exception of the October–March period, percent bias statistics were all within plus or minus 5-percent for both the calibration and validation periods. Limitations to using the model are error in the precipitation and air temperature input time series data, which include measurement error and error in the spatial interpolation method. Other errors include measured daily streamflow data, which were adjusted for consumptive use losses to make them more closely resemble natural streamflow for calibration.
The model developed for the Upper Klamath Basin can be used to forecast streamflow from the Sprague and Williamson River Basins and inflow to Upper Klamath Lake. Reliable forecasts at these locations are needed for managing water for irrigation, ecosystem health, and power production. Using the models in a forecast application requires assembling model input data sets of anticipated daily precipitation and minimum and maximum air temperature for the period after the date the forecast is made and the end of the forecasted period. These climate data sets can be based on historical or synthetic records, at the discretion of the forecaster. With the Ensemble Streamflow Prediction method, a suite of streamflow scenarios is simulated using multiple years of climate data as model input. The forecasted streamflow is determined from knowing the exceedance probabilities of the simulated streamflows. In this study, the model and the Ensemble Streamflow Prediction method were used to forecast the volume of inflow to Upper Klamath Lake for a 6-month period from April 1, 2015, to September 30, 2015, using a range of climate data sets based on El Niño Southern Oscillation (ENSO) criteria. Because 2015 was a warm phase ENSO period, climate data for 10 warm phase ENSO years from 1980 to 2010 were used as input to the model. The simulated April–September 2015 UKL inflow volume based on measured 2015 climate data was 482,000 acre-feet, which was very close to the 50th percent exceedance probability computed from 10 simulated scenarios that used warm phase ENSO climate input data from 1980–2010.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195044","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Risley, J.C., 2019, Using the precipitation-runoff modeling system to predict seasonal water availability in the upper Klamath River basin, Oregon and California: U.S. Geological Survey Scientific Investigations Report 2019–5044, 37 p., https://doi.org/10.3133/sir20195044.","productDescription":"vi, 37 p.","onlineOnly":"Y","ipdsId":"IP-098864","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":366315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5044/coverthb.jpg"},{"id":366316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5044/sir20195044.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5044"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.42041015624999,\n 40.76806170936614\n ],\n [\n -119.94323730468749,\n 40.76806170936614\n ],\n [\n -119.94323730468749,\n 43.205175817237304\n ],\n [\n -123.42041015624999,\n 43.205175817237304\n ],\n [\n -123.42041015624999,\n 40.76806170936614\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
De facto reuse is increasingly being studied among the variety of stressors that are relevant to drinking water systems that obtain their source water from surface waters. De facto reuse may influence the levels and types of precursors relevant to formation of disinfection by-products (DBPs) in surface water systems. DBPs such as trihalomethanes (THMs) and haloacetic acids (HAAs) have been associated with bladder cancer and other health concerns in people who use drinking water provided by public water systems (PWSs). In this study, we used compliance monitoring data from conventional surface water PWSs in the Shenandoah River watershed to evaluate the relationship between de facto reuse in the watershed with DBP formation in those systems. The Shenandoah River watershed was selected for this study because it has a relatively small group of PWSs that draw their source water from surface waters in the watershed, the majority of whom treat their water using chlorine, and are less likely to have confounding factors (such as complex distribution systems or lengthy residence times) than other watersheds. We found that concentrations of THM4 and HAA5 increase in drinking water systems as de facto reuse increases in their source waters and that the relation is observed at both annual average and low streamflow conditions (annual average and low streamflow increases were statistically significant for THM4 with p values of 0.027 and 0,021, respectively). In addition, using a t-test, we found that a 1% level of de facto reuse was associated with significantly higher levels of THM4 and HAA5 (p < 0.05) under annual average streamflow conditions. While the concentrations of HAA5 were also higher under annual average and low streamflow conditions, we did not find that they achieved a level of a significant difference. Results from this research will be helpful to operators of PWSs and other researchers and stakeholders with an interest in water reuse and DBPs.
","language":"English","publisher":"The Royal Society of Chemistry","doi":"10.1039/C9EW00326F","usgsCitation":"Weisman, R.J., Barber, L., Rapp, J., and Ferreira, C.M., 2019, De facto reuse and disinfection by-products in drinking water systems in the Shenandoah River watershed: Environmental Science: Water Research & Technology, v. 5, no. 10, p. 1699-1708, https://doi.org/10.1039/C9EW00326F.","productDescription":"10 p.","startPage":"1699","endPage":"1708","ipdsId":"IP-106374","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":367385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.189697265625,\n 39.67337039176558\n ],\n [\n -80.474853515625,\n 37.47485808497102\n ],\n [\n -79.9365234375,\n 37.23032838760387\n ],\n [\n -78.673095703125,\n 37.47485808497102\n ],\n [\n -77.47558593749999,\n 38.91668153637508\n ],\n [\n -77.266845703125,\n 39.639537564366684\n ],\n [\n -78.189697265625,\n 39.67337039176558\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"10","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weisman, Richard J","contributorId":218952,"corporation":false,"usgs":false,"family":"Weisman","given":"Richard","email":"","middleInitial":"J","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":770757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barber, Larry B. 0000-0002-0561-0831","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":218953,"corporation":false,"usgs":true,"family":"Barber","given":"Larry B.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"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":770758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rapp, Jennifer 0000-0003-2253-9886","orcid":"https://orcid.org/0000-0003-2253-9886","contributorId":218954,"corporation":false,"usgs":true,"family":"Rapp","given":"Jennifer","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferreira, Celso M","contributorId":218955,"corporation":false,"usgs":false,"family":"Ferreira","given":"Celso","email":"","middleInitial":"M","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":770760,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236154,"text":"70236154 - 2019 - Hydroclimatology of the Mississippi River Basin","interactions":[],"lastModifiedDate":"2022-08-30T14:18:05.915762","indexId":"70236154","displayToPublicDate":"2019-08-01T09:11:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Hydroclimatology of the Mississippi River Basin","docAbstract":"Model estimated monthly water balance (WB) components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff [R]) for 848 United States (U.S.) Geological Survey 8-digit hydrologic units located in the Mississippi River Basin (MRB) are used to examine the temporal and spatial variability of the MRB WB for water years 1901 through 2014. Results indicate the MRB can be divided into nine subregions with similar temporal variability in R. The WB analyses indicated ~79% of total water-year MRB runoff is generated by four of the nine subregions and most of the R in the basin is derived from surplus (S) water during the months of December through May. Furthermore, the analyses showed temporal variability in S is largely controlled by the occurrence of negative atmospheric pressure anomalies over the western U.S. and positive atmospheric pressure anomalies over the eastern U.S. coast. This combination of atmospheric pressure anomalies results in an anomalous flow of moist air from the Gulf of Mexico into the MRB. In the context of paleo-climate reconstructions of the Palmer Drought Severity Index, since about 1900 the MRB has experienced wetter conditions than were experienced during the previous 500 years.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12749","usgsCitation":"McCabe, G.J., and Wolock, D.M., 2019, Hydroclimatology of the Mississippi River Basin: Journal of the American Water Resources Association, v. 55, no. 4, p. 1053-1064, https://doi.org/10.1111/1752-1688.12749.","productDescription":"12 p.","startPage":"1053","endPage":"1064","ipdsId":"IP-101403","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467399,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/1752-1688.12749","text":"External Repository"},{"id":405907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.5986328125,\n 48.8936153614802\n ],\n [\n -112.939453125,\n 47.96050238891509\n ],\n [\n -112.67578124999999,\n 47.30903424774781\n ],\n [\n -111.357421875,\n 46.195042108660154\n ],\n [\n -112.3681640625,\n 45.61403741135093\n ],\n [\n -111.357421875,\n 44.715513732021336\n ],\n [\n -109.5556640625,\n 44.809121700077355\n ],\n [\n -109.423828125,\n 44.02442151965934\n ],\n [\n -109.0283203125,\n 43.61221676817573\n ],\n [\n -107.7978515625,\n 42.779275360241904\n ],\n [\n -106.2158203125,\n 41.57436130598913\n ],\n [\n -105.4248046875,\n 40.3130432088809\n ],\n [\n -105.29296874999999,\n 38.89103282648846\n ],\n [\n -105.5126953125,\n 37.82280243352756\n ],\n [\n -105.29296874999999,\n 36.06686213257888\n ],\n [\n -104.80957031249999,\n 34.84987503195418\n ],\n [\n -102.7001953125,\n 34.34343606848294\n ],\n [\n -99.404296875,\n 34.08906131584994\n ],\n [\n -97.1630859375,\n 33.43144133557529\n ],\n [\n -94.7021484375,\n 32.21280106801518\n ],\n [\n -94.04296874999999,\n 29.49698759653577\n ],\n [\n -89.82421875,\n 28.76765910569123\n ],\n [\n -89.6484375,\n 31.015278981711266\n ],\n [\n -90.615234375,\n 32.62087018318113\n ],\n [\n -90.263671875,\n 34.379712580462204\n ],\n [\n -88.06640625,\n 34.92197103616377\n ],\n [\n -84.7705078125,\n 34.994003757575776\n ],\n [\n -82.44140625,\n 36.24427318493909\n ],\n [\n -80.9912109375,\n 37.37015718405753\n ],\n [\n -79.0576171875,\n 38.993572058209466\n ],\n [\n -78.79394531249999,\n 42.84375132629021\n ],\n [\n -82.0458984375,\n 41.57436130598913\n ],\n [\n -84.90234375,\n 40.78054143186033\n ],\n [\n -87.099609375,\n 41.86956082699455\n ],\n [\n -87.890625,\n 42.779275360241904\n ],\n [\n -89.8681640625,\n 43.866218006556394\n ],\n [\n -90.087890625,\n 45.089035564831036\n ],\n [\n -89.82421875,\n 46.34692761055676\n ],\n [\n -90.791015625,\n 47.100044694025215\n ],\n [\n -94.6142578125,\n 47.69497434186282\n ],\n [\n -96.767578125,\n 46.255846818480315\n ],\n [\n -99.6240234375,\n 47.517200697839414\n ],\n [\n -100.37109375,\n 49.009050809382046\n ],\n [\n -113.5986328125,\n 48.8936153614802\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-04-22","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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850265,"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":850266,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238061,"text":"70238061 - 2019 - Simulations of hydrology and water quality for irrigated fields near Yakima, Washington","interactions":[],"lastModifiedDate":"2022-11-09T14:53:52.300317","indexId":"70238061","displayToPublicDate":"2019-08-01T08:47:40","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Simulations of hydrology and water quality for irrigated fields near Yakima, Washington","docAbstract":"Reliable tools are needed by farmers and managers to estimate and mitigate impacts of altered hydrology and degraded water quality downstream of agricultural areas. The Water, Energy, and Biogeochemical Model (WEBMOD) (Webb and Parkhurst 2017) was used to simulate daily variations of hydrology and water quality for 5 square kilometers of irrigated fields draining to the DR2 Drain, southeast of Yakima, WA.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Working watersheds and coastal systems: Research and management for a changing future — Proceedings of the Sixth Interagency Conference on Research in the Watersheds","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Sixth Interagency Conference on Research in the Watersheds","conferenceDate":"July 23-26, 2018","conferenceLocation":"Shepherdstown, WV","language":"English","publisher":"U.S. Department of Agriculture Forest Service, Southern Research Station","collaboration":"EPA, USFS","usgsCitation":"Webb, R.M., 2019, Simulations of hydrology and water quality for irrigated fields near Yakima, Washington, in Working watersheds and coastal systems: Research and management for a changing future — Proceedings of the Sixth Interagency Conference on Research in the Watersheds, Shepherdstown, WV, July 23-26, 2018, p. 202-205.","productDescription":"4 p.","startPage":"202","endPage":"205","ipdsId":"IP-100453","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":409260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409218,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.usda.gov/treesearch/pubs/59031"}],"country":"United States","state":"Washington","city":"Yakima","otherGeospatial":"Yakima River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.56886577450334,\n 46.633070609190895\n ],\n [\n -120.56886577450334,\n 46.12956834060162\n ],\n [\n -119.41838691883319,\n 46.12956834060162\n ],\n [\n -119.41838691883319,\n 46.633070609190895\n ],\n [\n -120.56886577450334,\n 46.633070609190895\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":856734,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70205670,"text":"70205670 - 2019 - Timescales of water-quality change in a karst aquifer, south-central Texas","interactions":[],"lastModifiedDate":"2021-04-02T14:41:48.358402","indexId":"70205670","displayToPublicDate":"2019-07-31T14:34:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5836,"text":"Journal of Hydrology X","onlineIssn":"2589-9155","active":true,"publicationSubtype":{"id":10}},"title":"Timescales of water-quality change in a karst aquifer, south-central Texas","docAbstract":"Understanding the drivers and timescales over which groundwater quality changes informs groundwater management, use, and protection. To better understand timescales of water-quality change over short (daily to monthly) and long (seasonal to decadal) timescales, the U.S. Geological Survey’s National Water-Quality Assessment (NAWQA) Enhanced Trends Network (ETN) program instrumented and sampled three wells in the Edwards aquifer in south-central Texas. The wells were instrumented to provide high-frequency continuous (subhourly) water-quality data (temperature, pH, specific conductance, and dissolved oxygen), which were augmented by the collection of discrete samples (about 6 per year) for a range of geochemical constituents (including selected isotopes and age tracers). ETN data (2013–2017) are considered with data from additional sites for the same time period, and also historical records (over more than 80 years) of climatic and hydrologic conditions. During the four-year study, hydrologic conditions transitioned from very dry to very wet. Sites in the updip/unconfined part of the aquifer showed notable changes in water level and geochemistry (1) in response to rainfall/recharge events, and (2) over the multiyear dry/wet cycle. Sites in the downdip/confined part of the aquifer showed changes in water level/spring discharge over similar timescales, although the response is more muted. Geochemistry at the downdip/confined sites, however, varied slowly and minimally, indicating that the geochemical response of the deeper aquifer is decoupled from recent hydrologic responses. Changes at the updip/unconfined sites reflect mixing with recent recharge, whereas the downdip/confined sites were dominated by mineral-solution reactions resulting from longer (decadal) residence times. Mean groundwater ages interpreted from measured age tracers and lumped parameter models range from 7 to >700 years (where mixed with premodern downdip water) but were mostly modern. The aquifer is characterized by updip-to-downdip trends in geochemistry with respect to water-rock interaction and groundwater age. Fourier spectral analysis of historical records indicate hydrologic variability has occurred at dominant periods of 30 and 15 years; in conjunction with age tracers, these results provide insight into timescales at which the aquifer’s public supply is vulnerable to changes in the water quality of recharge.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hydroa.2019.100041","usgsCitation":"Musgrove, M., Solder, J.E., Opsahl, S.P., and Wilson, J.T., 2019, Timescales of water-quality change in a karst aquifer, south-central Texas: Journal of Hydrology X, v. 4, 100041, 16 p., https://doi.org/10.1016/j.hydroa.2019.100041.","productDescription":"100041, 16 p.","ipdsId":"IP-105452 ","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":467403,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hydroa.2019.100041","text":"Publisher Index Page"},{"id":437377,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9247J56","text":"USGS data release","linkHelpText":"Data for timescales of water-quality change in a karst aquifer, south-central Texas"},{"id":367845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367872,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5c9ba747e4b0b8a7f62c2edd","text":"USGS data release","linkHelpText":"Data for timescales of water-quality change in a karst aquifer, south-central Texas"}],"country":"United States","state":"Texas","otherGeospatial":"Edwards Aquifer","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-97.240849,26.411504],[-97.276425,26.521729],[-97.31073,26.556558],[-97.345822,26.700589],[-97.370438,26.723896],[-97.368343,26.795649],[-97.387459,26.820789],[-97.390078,27.156512],[-97.359963,27.304732],[-97.361796,27.359988],[-97.317277,27.46369],[-97.236882,27.598293],[-97.231383,27.632336],[-97.214099,27.631551],[-97.200743,27.650144],[-97.203474,27.684533],[-97.103326,27.789068],[-97.098874,27.82285],[-97.134489,27.825206],[-97.056713,27.842294],[-96.985745,27.954048],[-96.967807,28.020041],[-96.952618,28.01644],[-96.906004,28.076147],[-96.886233,28.084396],[-96.879424,28.131402],[-96.84538,28.108881],[-96.83003,28.111842],[-96.81042,28.126034],[-96.816443,28.174808],[-96.791958,28.188687],[-96.703838,28.198246],[-96.702659,28.211208],[-96.662462,28.227314],[-96.651856,28.251275],[-96.592934,28.296972],[-96.450998,28.337039],[-96.403206,28.371475],[-96.397846,28.343513],[-96.4137,28.327343],[-96.547774,28.270798],[-96.694666,28.18212],[-96.849624,28.064939],[-96.966996,27.950531],[-97.166682,27.676583],[-97.30447,27.407734],[-97.350398,27.268105],[-97.370941,27.161166],[-97.37913,27.047996],[-97.370731,26.909706],[-97.333028,26.736479],[-97.194644,26.306513],[-97.154271,26.066841],[-97.169842,26.077853],[-97.194458,26.27164],[-97.240849,26.411504]]],[[[-94.886539,29.510724],[-94.894747,29.52697],[-94.87675,29.507922],[-94.886539,29.510724]]],[[[-97.868235,26.056656],[-97.88653,26.066339],[-97.967358,26.051718],[-97.981335,26.067182],[-98.028759,26.06647],[-98.039239,26.041275],[-98.070021,26.047992],[-98.084755,26.070808],[-98.091038,26.059169],[-98.105505,26.067537],[-98.146622,26.049412],[-98.177897,26.074672],[-98.197046,26.056153],[-98.220673,26.076467],[-98.248806,26.073101],[-98.264514,26.085507],[-98.277218,26.098802],[-98.265698,26.12037],[-98.296195,26.120321],[-98.302979,26.11005],[-98.323828,26.121249],[-98.336837,26.166432],[-98.354645,26.15304],[-98.386694,26.157872],[-98.404433,26.182564],[-98.442536,26.199151],[-98.450976,26.219904],[-98.496684,26.212853],[-98.543852,26.234492],[-98.576188,26.235221],[-98.599154,26.257612],[-98.669397,26.23632],[-98.681167,26.26271],[-98.745272,26.303096],[-98.755242,26.3251],[-98.789822,26.331575],[-98.807348,26.369421],[-98.890965,26.357569],[-98.921277,26.381426],[-98.950186,26.380303],[-98.967587,26.398266],[-99.008003,26.395459],[-99.032316,26.412082],[-99.082002,26.39651],[-99.110855,26.426278],[-99.091635,26.476977],[-99.127782,26.525199],[-99.166742,26.536079],[-99.178064,26.620547],[-99.209948,26.693938],[-99.208907,26.724761],[-99.240023,26.745851],[-99.242444,26.788262],[-99.268613,26.843213],[-99.295146,26.86544],[-99.316753,26.865831],[-99.3289,26.879761],[-99.324684,26.915973],[-99.379149,26.93449],[-99.393748,26.96073],[-99.377312,26.973819],[-99.415476,27.01724],[-99.42938,27.010833],[-99.446524,27.023008],[-99.452316,27.062669],[-99.429209,27.090982],[-99.442123,27.106839],[-99.426348,27.176262],[-99.441549,27.24992],[-99.463309,27.268437],[-99.492407,27.264118],[-99.494604,27.303542],[-99.536443,27.312538],[-99.504837,27.338289],[-99.487521,27.412396],[-99.495104,27.451518],[-99.480419,27.481596],[-99.497519,27.500496],[-99.52582,27.496696],[-99.515978,27.572131],[-99.55495,27.614454],[-99.580006,27.602251],[-99.578099,27.619196],[-99.594038,27.638573],[-99.638929,27.626758],[-99.665948,27.635968],[-99.668942,27.659974],[-99.711511,27.658365],[-99.77074,27.732134],[-99.796342,27.735586],[-99.813086,27.773952],[-99.835127,27.762881],[-99.850877,27.793974],[-99.877677,27.799427],[-99.876003,27.837968],[-99.904385,27.875284],[-99.895828,27.904178],[-99.937142,27.940537],[-99.931812,27.980967],[-99.991447,27.99456],[-100.017914,28.064787],[-100.053123,28.08473],[-100.083393,28.144035],[-100.208059,28.190383],[-100.22363,28.235224],[-100.2462,28.234092],[-100.289384,28.273491],[-100.286471,28.312296],[-100.341869,28.384953],[-100.349586,28.402604],[-100.337797,28.44296],[-100.368288,28.477196],[-100.333814,28.499252],[-100.38886,28.515748],[-100.411414,28.551899],[-100.398385,28.584884],[-100.44732,28.609325],[-100.445529,28.637144],[-100.495863,28.658569],[-100.510055,28.690723],[-100.507613,28.740599],[-100.533017,28.76328],[-100.53583,28.805888],[-100.547324,28.825817],[-100.57051,28.826317],[-100.602054,28.901944],[-100.640568,28.914212],[-100.651512,28.943432],[-100.645894,28.986421],[-100.674656,29.099777],[-100.772649,29.168492],[-100.767059,29.195287],[-100.785521,29.228137],[-100.795681,29.22773],[-100.797671,29.246943],[-100.876049,29.279585],[-100.886842,29.307848],[-100.948972,29.347246],[-101.004207,29.364772],[-101.060151,29.458661],[-101.151877,29.477005],[-101.173821,29.514566],[-101.254895,29.520342],[-101.242023,29.592512],[-101.259127,29.607284],[-101.307332,29.587847],[-101.311219,29.648491],[-101.361756,29.657821],[-101.415402,29.756561],[-101.441059,29.753451],[-101.475269,29.780663],[-101.522695,29.759671],[-101.546797,29.796991],[-101.582562,29.771334],[-101.625958,29.771063],[-101.646418,29.754304],[-101.662453,29.77128],[-101.706636,29.762737],[-101.852604,29.801895],[-101.922585,29.790161],[-101.974548,29.810276],[-101.987539,29.801057],[-102.034759,29.804028],[-102.050044,29.78507],[-102.115682,29.79239],[-102.159601,29.814356],[-102.181894,29.846034],[-102.227553,29.843534],[-102.315389,29.87992],[-102.364542,29.845387],[-102.386678,29.76688],[-102.508313,29.783219],[-102.513381,29.76576],[-102.539417,29.751629],[-102.559343,29.760377],[-102.630151,29.734315],[-102.670971,29.741954],[-102.698347,29.695591],[-102.693466,29.676507],[-102.742031,29.632142],[-102.739991,29.599041],[-102.768341,29.594734],[-102.771429,29.548546],[-102.808692,29.522319],[-102.807327,29.494009],[-102.832539,29.433109],[-102.824564,29.399558],[-102.843021,29.357988],[-102.879534,29.353327],[-102.888328,29.291947],[-102.906296,29.260011],[-102.871347,29.241625],[-102.866846,29.225015],[-102.890064,29.208814],[-102.915866,29.215878],[-102.917805,29.190697],[-102.944911,29.18882],[-102.953475,29.176308],[-102.989432,29.183174],[-103.015028,29.12577],[-103.035683,29.103029],[-103.074407,29.088534],[-103.100266,29.0577],[-103.113922,28.988547],[-103.156646,28.972831],[-103.227801,28.991532],[-103.239109,28.981651],[-103.260308,28.989731],[-103.28119,28.982138],[-103.341463,29.041224],[-103.355428,29.021529],[-103.427754,29.042334],[-103.471265,29.073115],[-103.503236,29.11911],[-103.524613,29.120998],[-103.523384,29.133389],[-103.558679,29.154962],[-103.645635,29.159286],[-103.71377,29.185008],[-103.816642,29.270927],[-103.975235,29.296017],[-104.038282,29.320156],[-104.106467,29.373127],[-104.166563,29.399352],[-104.233487,29.492734],[-104.318074,29.527938],[-104.334811,29.519463],[-104.381041,29.543406],[-104.399591,29.572319],[-104.507568,29.639624],[-104.539761,29.676074],[-104.565688,29.770462],[-104.679772,29.924659],[-104.679661,29.975272],[-104.706874,30.050685],[-104.685003,30.085643],[-104.695366,30.13213],[-104.687296,30.179464],[-104.713166,30.237957],[-104.733822,30.261221],[-104.749664,30.26126],[-104.761634,30.301148],[-104.809794,30.334926],[-104.824314,30.370466],[-104.859521,30.390413],[-104.85242,30.418792],[-104.876787,30.511004],[-104.924796,30.604832],[-104.967167,30.608107],[-105.002057,30.680972],[-105.062334,30.686303],[-105.113816,30.746001],[-105.152362,30.751452],[-105.195144,30.792138],[-105.255416,30.797029],[-105.287238,30.822206],[-105.314863,30.816961],[-105.360672,30.847384],[-105.394242,30.852979],[-105.399609,30.888941],[-105.533088,30.984859],[-105.55743,30.990229],[-105.60333,31.082625],[-105.64189,31.098322],[-105.646731,31.113908],[-105.709491,31.136375],[-105.742678,31.164897],[-105.773257,31.166897],[-105.779725,31.191283],[-105.869353,31.288634],[-105.938452,31.318735],[-105.953943,31.364749],[-106.004926,31.392458],[-106.080258,31.398702],[-106.203969,31.465378],[-106.246203,31.541153],[-106.280811,31.562062],[-106.303536,31.620413],[-106.378039,31.72831],[-106.451541,31.764808],[-106.484642,31.747809],[-106.542097,31.802146],[-106.602727,31.825024],[-106.605845,31.846305],[-106.635926,31.866235],[-106.629197,31.883717],[-106.645296,31.894859],[-106.614346,31.918003],[-106.623933,31.925335],[-106.614702,31.956],[-106.622819,31.952891],[-106.618745,31.966955],[-106.638186,31.97682],[-106.618486,32.000495],[-103.064423,32.000518],[-103.064625,32.999899],[-103.043531,34.018014],[-103.041924,36.500439],[-100.003762,36.499699],[-100.000381,34.560509],[-99.929334,34.576714],[-99.825325,34.497596],[-99.754248,34.421289],[-99.696462,34.381036],[-99.665992,34.374185],[-99.600026,34.374688],[-99.569696,34.418418],[-99.499875,34.409608],[-99.430995,34.373414],[-99.399603,34.375079],[-99.394956,34.442099],[-99.381011,34.456936],[-99.358795,34.455863],[-99.318363,34.408296],[-99.289922,34.414731],[-99.264167,34.405149],[-99.25898,34.391243],[-99.273958,34.38756],[-99.242945,34.372668],[-99.233274,34.344101],[-99.210716,34.336304],[-99.211648,34.292232],[-99.19457,34.272424],[-99.189511,34.214312],[-99.159016,34.20888],[-99.130609,34.219408],[-99.126567,34.203004],[-99.079535,34.211518],[-99.048792,34.198209],[-99.013075,34.203222],[-98.990852,34.221633],[-98.974132,34.203566],[-98.952513,34.21265],[-98.909349,34.177499],[-98.872922,34.166584],[-98.868116,34.149635],[-98.8579,34.159627],[-98.812954,34.158444],[-98.749291,34.124238],[-98.735471,34.135208],[-98.696518,34.133521],[-98.648073,34.164441],[-98.603978,34.160249],[-98.577136,34.148962],[-98.486328,34.062598],[-98.414426,34.085074],[-98.384381,34.146317],[-98.367494,34.156191],[-98.16912,34.114171],[-98.114506,34.154727],[-98.09066,34.12198],[-98.120208,34.072127],[-98.099096,34.048639],[-98.104022,34.036233],[-98.088203,34.005481],[-98.027672,33.993357],[-97.978243,34.005387],[-97.947572,33.991053],[-97.974173,33.942832],[-97.955511,33.938186],[-97.957155,33.914454],[-97.983552,33.904002],[-97.967777,33.88243],[-97.877387,33.850236],[-97.834333,33.857671],[-97.784657,33.890632],[-97.783717,33.91056],[-97.76377,33.914241],[-97.762768,33.934396],[-97.725289,33.941045],[-97.69311,33.983699],[-97.671772,33.99137],[-97.589598,33.953554],[-97.589254,33.903922],[-97.551541,33.897947],[-97.50096,33.919643],[-97.460376,33.903948],[-97.451469,33.87093],[-97.462857,33.841772],[-97.426493,33.819398],[-97.365507,33.823763],[-97.33294,33.87444],[-97.315913,33.865838],[-97.299245,33.880175],[-97.256625,33.863286],[-97.24618,33.900344],[-97.210921,33.916064],[-97.179609,33.89225],[-97.166629,33.847311],[-97.203514,33.821825],[-97.205431,33.801488],[-97.172192,33.737545],[-97.126102,33.716941],[-97.086195,33.743933],[-97.087999,33.808747],[-97.058623,33.818752],[-97.052209,33.841737],[-97.023899,33.844213],[-96.985567,33.886522],[-96.996183,33.941728],[-96.979415,33.956178],[-96.973807,33.935697],[-96.9163,33.957798],[-96.875281,33.860505],[-96.85609,33.84749],[-96.837413,33.871349],[-96.794276,33.868886],[-96.761588,33.824406],[-96.704457,33.835021],[-96.667187,33.91694],[-96.630117,33.895422],[-96.592948,33.895616],[-96.590112,33.880665],[-96.625399,33.856542],[-96.623155,33.841483],[-96.572937,33.819098],[-96.523863,33.818114],[-96.502286,33.77346],[-96.422643,33.776041],[-96.348306,33.686379],[-96.309964,33.710489],[-96.294867,33.764771],[-96.277269,33.769735],[-96.220521,33.74739],[-96.178059,33.760518],[-96.162757,33.788769],[-96.178964,33.810553],[-96.150765,33.816987],[-96.15163,33.831946],[-96.138905,33.839159],[-96.09936,33.83047],[-96.101349,33.845721],[-96.005296,33.845505],[-95.991487,33.866869],[-95.951609,33.857017],[-95.936132,33.886826],[-95.831948,33.835161],[-95.821666,33.856633],[-95.805149,33.861304],[-95.776255,33.845145],[-95.75431,33.853992],[-95.761916,33.883402],[-95.747335,33.895756],[-95.696962,33.885218],[-95.669978,33.905844],[-95.636978,33.906613],[-95.599678,33.934247],[-95.556915,33.92702],[-95.545197,33.880294],[-95.515302,33.891142],[-95.492028,33.874822],[-95.461499,33.883686],[-95.464211,33.873372],[-95.44737,33.86885],[-95.339122,33.868873],[-95.334523,33.885788],[-95.283445,33.877746],[-95.280351,33.896751],[-95.255747,33.902939],[-95.252906,33.933648],[-95.219358,33.961567],[-95.121184,33.931307],[-95.093929,33.895963],[-95.061065,33.895292],[-95.049025,33.86409],[-95.008376,33.866089],[-94.983303,33.851354],[-94.976208,33.859847],[-94.948716,33.818023],[-94.91945,33.810176],[-94.919614,33.786305],[-94.879218,33.764912],[-94.8693,33.745871],[-94.830804,33.740068],[-94.817427,33.752172],[-94.798634,33.744527],[-94.775064,33.755038],[-94.762961,33.731787],[-94.742576,33.727009],[-94.732384,33.700254],[-94.714865,33.707261],[-94.710725,33.691654],[-94.684792,33.684353],[-94.659167,33.692138],[-94.646113,33.6693],[-94.57962,33.677623],[-94.520725,33.616567],[-94.491503,33.625115],[-94.485875,33.637867],[-94.448637,33.642766],[-94.468086,33.599436],[-94.430039,33.591124],[-94.413155,33.569368],[-94.378076,33.577019],[-94.397398,33.562314],[-94.389515,33.546778],[-94.355945,33.54318],[-94.345513,33.567313],[-94.309582,33.551673],[-94.289129,33.582144],[-94.280849,33.577187],[-94.290901,33.558872],[-94.27909,33.557026],[-94.245932,33.589114],[-94.237975,33.577757],[-94.250197,33.556765],[-94.226392,33.552912],[-94.205634,33.567229],[-94.193248,33.556154],[-94.192483,33.570425],[-94.217408,33.57926],[-94.183913,33.594682],[-94.152626,33.575923],[-94.146048,33.581975],[-94.14852,33.565678],[-94.136864,33.571],[-94.128658,33.550952],[-94.088943,33.575322],[-94.061283,33.568805],[-94.055663,33.561887],[-94.073744,33.558285],[-94.06548,33.550909],[-94.04604,33.551321],[-94.04272,31.999265],[-94.018664,31.990843],[-93.971712,31.920384],[-93.923929,31.88985],[-93.904766,31.890599],[-93.874761,31.821661],[-93.827451,31.777741],[-93.830647,31.745811],[-93.802694,31.697783],[-93.826462,31.666919],[-93.816838,31.622509],[-93.838057,31.606795],[-93.834924,31.586211],[-93.798087,31.534044],[-93.743376,31.525196],[-93.725925,31.504092],[-93.74987,31.475276],[-93.70093,31.437784],[-93.704879,31.410881],[-93.674117,31.397681],[-93.665052,31.363886],[-93.687851,31.309835],[-93.642516,31.269508],[-93.620343,31.271025],[-93.598828,31.174679],[-93.588503,31.165581],[-93.535097,31.185614],[-93.551693,31.097258],[-93.52301,31.065241],[-93.516943,31.032584],[-93.539526,31.008498],[-93.566017,31.004567],[-93.571906,30.987614],[-93.526245,30.939411],[-93.567788,30.888302],[-93.554057,30.824941],[-93.561666,30.807739],[-93.584265,30.796663],[-93.592828,30.763986],[-93.619129,30.742002],[-93.611192,30.718053],[-93.629904,30.67994],[-93.6831,30.640763],[-93.684329,30.592586],[-93.727844,30.57407],[-93.729195,30.544842],[-93.740253,30.539569],[-93.714322,30.518562],[-93.697828,30.443838],[-93.757654,30.390423],[-93.765822,30.333318],[-93.708645,30.288317],[-93.705083,30.242752],[-93.720946,30.209852],[-93.688212,30.141376],[-93.701252,30.137376],[-93.702436,30.112721],[-93.732485,30.088914],[-93.70082,30.056274],[-93.720805,30.053043],[-93.739734,30.023987],[-93.786935,29.99058],[-93.838374,29.882855],[-93.927992,29.80964],[-93.926504,29.78956],[-93.89847,29.771577],[-93.891637,29.744618],[-93.873941,29.73777],[-93.837971,29.690619],[-93.866981,29.673085],[-94.001406,29.681486],[-94.132577,29.646217],[-94.594853,29.467903],[-94.694158,29.415632],[-94.731047,29.369141],[-94.778691,29.361483],[-94.783131,29.375642],[-94.766848,29.393489],[-94.6724,29.476843],[-94.608557,29.483345],[-94.566674,29.531988],[-94.532348,29.5178],[-94.495025,29.525031],[-94.503429,29.54325],[-94.522421,29.545672],[-94.553988,29.573882],[-94.740699,29.525858],[-94.783296,29.535314],[-94.78954,29.546494],[-94.755237,29.562782],[-94.708741,29.625226],[-94.693154,29.694453],[-94.695317,29.723052],[-94.735271,29.785433],[-94.816085,29.75671],[-94.851108,29.721373],[-94.872551,29.67125],[-94.893107,29.661336],[-94.915413,29.656614],[-94.936089,29.692704],[-94.965963,29.70033],[-95.015636,29.639457],[-94.982936,29.60167],[-95.016889,29.548303],[-94.981916,29.511141],[-94.909898,29.49691],[-94.930861,29.450504],[-94.8908,29.433432],[-94.893994,29.30817],[-94.921593,29.281556],[-94.952526,29.290122],[-95.099101,29.173529],[-95.151925,29.151162],[-95.16525,29.113566],[-95.136221,29.084537],[-94.879239,29.285839],[-94.824953,29.306005],[-94.822307,29.344254],[-94.810696,29.353435],[-94.784895,29.335535],[-94.72253,29.331446],[-95.081773,29.111222],[-95.38239,28.866348],[-95.439594,28.859022],[-95.812504,28.664942],[-96.220376,28.491966],[-96.378616,28.383909],[-96.37596,28.401682],[-96.335119,28.437795],[-96.223825,28.495067],[-96.21505,28.509679],[-95.98616,28.606319],[-95.978526,28.650594],[-95.996338,28.658736],[-96.006516,28.648049],[-96.047737,28.649067],[-96.221784,28.580364],[-96.233998,28.596649],[-96.212624,28.622604],[-96.230944,28.641433],[-96.192267,28.687744],[-96.19583,28.69894],[-96.222802,28.698431],[-96.287942,28.683164],[-96.304227,28.671459],[-96.303718,28.644996],[-96.373439,28.626675],[-96.487943,28.569677],[-96.485907,28.607845],[-96.510844,28.61497],[-96.499648,28.635835],[-96.563262,28.644487],[-96.572931,28.667897],[-96.561226,28.696395],[-96.584091,28.722798],[-96.664534,28.696904],[-96.61059,28.638889],[-96.61975,28.627693],[-96.611099,28.585962],[-96.565297,28.5824],[-96.561226,28.570695],[-96.526111,28.557972],[-96.505755,28.525911],[-96.402446,28.449066],[-96.59176,28.357462],[-96.672677,28.335579],[-96.705247,28.348811],[-96.710336,28.406827],[-96.772209,28.408074],[-96.794554,28.365688],[-96.791761,28.31217],[-96.809573,28.290287],[-96.787181,28.255681],[-96.800413,28.224128],[-96.934765,28.123873],[-96.962755,28.123365],[-97.027014,28.148408],[-97.021303,28.1841],[-97.037008,28.185528],[-97.153601,28.13318],[-97.214039,28.087494],[-97.21535,28.076575],[-97.176444,28.059892],[-97.137421,28.057037],[-97.025693,28.11216],[-97.035528,28.084688],[-97.025859,28.041939],[-97.129168,27.919801],[-97.186709,27.825453],[-97.219738,27.823939],[-97.250797,27.876035],[-97.272253,27.881427],[-97.379042,27.837867],[-97.393291,27.782905],[-97.368355,27.741683],[-97.316446,27.712676],[-97.253955,27.696696],[-97.296598,27.613947],[-97.294054,27.5941],[-97.321535,27.571199],[-97.401942,27.335574],[-97.508304,27.275014],[-97.532223,27.278577],[-97.544437,27.284175],[-97.498126,27.308602],[-97.502706,27.322343],[-97.483877,27.338628],[-97.48693,27.358984],[-97.501688,27.366618],[-97.609068,27.285193],[-97.63146,27.28621],[-97.640111,27.270943],[-97.628916,27.242953],[-97.54291,27.229213],[-97.42408,27.264073],[-97.443673,27.116235],[-97.45665,27.099695],[-97.495836,27.094098],[-97.477515,27.066108],[-97.48693,27.057711],[-97.486676,27.03481],[-97.473444,27.02285],[-97.478533,26.999186],[-97.555378,26.99028],[-97.555378,26.93888],[-97.540874,26.90631],[-97.563266,26.842188],[-97.509831,26.803511],[-97.468609,26.740915],[-97.445708,26.609362],[-97.416955,26.553637],[-97.441383,26.455418],[-97.41721,26.44982],[-97.42179,26.417249],[-97.382485,26.411326],[-97.369627,26.394603],[-97.388965,26.36585],[-97.387947,26.330481],[-97.358176,26.356435],[-97.335275,26.355672],[-97.336802,26.331753],[-97.352833,26.318521],[-97.343927,26.267376],[-97.311866,26.273737],[-97.307031,26.253126],[-97.32128,26.236078],[-97.296598,26.200709],[-97.306776,26.159487],[-97.282094,26.120301],[-97.294054,26.11394],[-97.270898,26.086459],[-97.199651,26.077044],[-97.195071,26.04193],[-97.224842,26.027426],[-97.219244,25.996128],[-97.208557,25.991802],[-97.167208,26.007069],[-97.162628,26.023482],[-97.18273,26.053126],[-97.152009,26.062108],[-97.146294,25.955606],[-97.276707,25.952147],[-97.277163,25.935438],[-97.350398,25.925241],[-97.37443,25.907444],[-97.360082,25.868874],[-97.372864,25.840117],[-97.422636,25.840378],[-97.445113,25.850026],[-97.454727,25.879337],[-97.521762,25.886458],[-97.546421,25.934077],[-97.582565,25.937857],[-97.583044,25.955443],[-97.598043,25.957556],[-97.643708,26.016943],[-97.758838,26.032131],[-97.789823,26.04246],[-97.801344,26.060017],[-97.868235,26.056656]]]]},\"properties\":{\"name\":\"Texas\",\"nation\":\"USA \"}}]}","volume":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":197013,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":772054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solder, John E. 0000-0002-0660-3326 jsolder@usgs.gov","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":171916,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"jsolder@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Opsahl, Stephen P. 0000-0002-4774-0415 sopsahl@usgs.gov","orcid":"https://orcid.org/0000-0002-4774-0415","contributorId":4713,"corporation":false,"usgs":true,"family":"Opsahl","given":"Stephen","email":"sopsahl@usgs.gov","middleInitial":"P.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Jennifer T. 0000-0003-4481-6354 jenwilso@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-6354","contributorId":1782,"corporation":false,"usgs":true,"family":"Wilson","given":"Jennifer","email":"jenwilso@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772057,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203750,"text":"sir20195052 - 2019 - Hydrogeologic framework and delineation of transient areas contributing recharge and zones of contribution to selected wells in the upper Santa Fe Group aquifer, southeastern Albuquerque, New Mexico, 1900–2050","interactions":[],"lastModifiedDate":"2019-08-01T07:18:46","indexId":"sir20195052","displayToPublicDate":"2019-07-31T11:28:41","publicationYear":"2019","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":"2019-5052","displayTitle":"Hydrogeologic Framework and Delineation of Transient Areas Contributing Recharge and Zones of Contribution to Selected Wells in the Upper Santa Fe Group Aquifer, Southeastern Albuquerque, New Mexico, 1900–2050","title":"Hydrogeologic framework and delineation of transient areas contributing recharge and zones of contribution to selected wells in the upper Santa Fe Group aquifer, southeastern Albuquerque, New Mexico, 1900–2050","docAbstract":"The Santa Fe Group aquifer is an important source of water to communities within the Middle Rio Grande Basin, including the Albuquerque-Rio Rancho metropolitan area and Kirtland Air Force Base, New Mexico. In November 1999, Kirtland Air Force Base personnel observed fuel-stained soils at the Bulk Fuels Facility on the base. Subsequent pressure tests identified pipeline leaks. Fuels stored at the Bulk Fuels Facility have included aviation gasoline, jet propellant 4, and jet propellant 8. The fuels migrated about 480 feet down to the water table. Ethylene dibromide, the constituent making up the most extensive part of the plume and a component of leaded aviation gasoline, has formed a plume that, in December 2016, was 400 to 1,300 feet wide, extended about 5,800 feet northeast from the Bulk Fuels Facility, and was about 3,700 feet from the nearest downgradient water-supply well.
Prior to widespread development of groundwater resources in southeastern Albuquerque, groundwater near the present-day location of the Bulk Fuels Facility flowed to the southwest. Groundwater began flowing northeast in about 1980 towards a large area of lowered water levels caused by groundwater pumping.
In 2013 and 2014 the Albuquerque Bernalillo County Water Utility Authority, the U.S. Air Force, and the U.S. Geological Survey began a cooperative study to characterize the geology and hydrology of the Santa Fe Group aquifer in the vicinity of the ethylene dibromide plume and to develop a local-scale groundwater flow model to delineate areas contributing recharge and zones of contribution to selected water-supply wells.
For this study, a previously developed Middle Rio Grande Basin regional groundwater-flow model was updated, and a smaller local-scale model was developed. Advective groundwater-flow paths were delineated and visualized with the MODPATH particle-tracking program.
Of 11 wells included in the historical pumping analysis of areas contributing recharge, only wells K-3, K-7, and RC-4 derived a portion of their water from simulated recharge sources within the local-scale model. None of the areas contributing recharge overlap the Bulk Fuels Facility area or the ethylene dibromide plume footprint as delineated using December 2016 ethylene dibromide data.
For the historical pumping analysis of zones of contribution, particles for the 11 selected wells generally moved southwest from the north and east boundaries of the local-scale model, moved past their target well, but reversed direction and moved back towards their target well after 1980 when groundwater flow changed to the northeast. Of the 11 wells, only BR-5, RC-5, and VH-2 had 1980–2013 particle pathlines that overlap the December 2016 ethylene dibromide plume footprint, and wells BR-5 and VH-2 have 1980–2013 particle pathlines that overlap the Bulk Fuels Facility area. Particles that were north of the Bulk Fuels Facility when groundwater flow reversed direction would not have the opportunity to interact with the ethylene dibromide plume. Wells BR-5, K-15, and VH-2 did have particles southwest of the Bulk Fuels Facility in 1980. Particles traveling to BR-5 and K-15 passed under or very near the Bulk Fuels Facility area in the 1980–2013 period, but none of the pathlines were shallow enough to interact with ethylene dibromide at the Bulk Fuels Facility. A few particles traveling to VH-2 passed through the Bulk Fuels Facility area at shallow enough depths to interact with ethylene dibromide at the Bulk Fuels Facility in the 1980–2013 period. Ethylene dibromide has not been detected in water samples collected in 2012 through 2015 from the VH-2 well.
Of 10 water-supply wells near the ethylene dibromide plume included in the future pumping analysis of areas contributing recharge, only wells K-3, RC-3, and RC-4 had areas contributing recharge within the local-scale model. The areas contributing recharge for wells RC-3 and RC-4 do not overlap the Bulk Fuels Facility area or the December 2016 ethylene dibromide plume footprint, but K-3 derives part of its recharge prior to 1980 and during 1980–2015 from within the area of the December 2016 plume footprint.
The analysis of the future pumping scenarios indicated that wells BR-5, K-3, K-16, RC-5, and VH-2 have pathlines for 1980–2015 and wells K-16 and VH-2 have pathlines for 2015–50 that when projected in plan view pass through the December 2016 plume footprint. Of these five wells, only K-3 and RC-5 have pathlines for 1980–2015 that are above an elevation of 4,800 feet and could interact with the ethylene dibromide plume if ethylene dibromide was present when the particles were present.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195052","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority and the U.S. Air Force","usgsCitation":"Myers, N.C., and Friesz, P.J., 2019, Hydrogeologic framework and delineation of transient areas contributing recharge and zones of contribution to selected wells in the upper Santa Fe Group aquifer, southeastern Albuquerque, New Mexico, 1900–2050: U.S. Geological Survey Scientific Investigations Report 2019–5052, 73 p., https://doi.org/10.3133/sir20195052.","productDescription":"Report: viii, 73 p.; Data Release","numberOfPages":"86","onlineOnly":"Y","ipdsId":"IP-080008","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":365539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5052/sir20195052.pdf","text":"Report","size":"38.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5052"},{"id":365538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5052/coverthb.jpg"},{"id":365540,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79P303S","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"MODFLOW–LGR2 groundwater-flow model used to delineate transient areas contributing recharge and zones of contribution to selected wells in the upper Santa Fe Group aquifer, southeastern Albuquerque, New Mexico"}],"country":"United States","state":"New Mexico","county":"Bernalillo County","city":"Albuquerque","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-106.242,35.2147],[-106.2387,35.0549],[-106.2386,35.0408],[-106.2373,34.9568],[-106.1453,34.9547],[-106.1446,34.872],[-106.3328,34.8712],[-106.3569,34.8702],[-106.409,34.8687],[-106.4097,34.8914],[-106.417,34.8945],[-106.4221,34.9013],[-106.6755,34.9065],[-106.6838,34.9006],[-106.6917,34.901],[-106.6922,34.896],[-106.7139,34.8772],[-106.7127,34.8713],[-107.0181,34.8727],[-107.0227,34.8817],[-107.0641,34.9618],[-107.104,35.0395],[-107.1068,35.0454],[-107.1769,35.1809],[-107.1972,35.2197],[-107.1628,35.2192],[-107.1623,35.2192],[-107.1578,35.2192],[-107.1262,35.2186],[-107.1105,35.2188],[-107.0936,35.2189],[-107.0801,35.2186],[-107.0761,35.2186],[-107.0345,35.2185],[-106.9416,35.217],[-106.9337,35.2171],[-106.8808,35.2171],[-106.8622,35.2172],[-106.5955,35.2184],[-106.5645,35.2186],[-106.4964,35.2184],[-106.479,35.2176],[-106.4531,35.2172],[-106.3822,35.2175],[-106.3765,35.2175],[-106.242,35.2147]]]},\"properties\":{\"name\":\"Bernalillo\",\"state\":\"NM\"}}]}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE, Suite B
Albuquerque, NM 87113
Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
801-908-5000
The South Atlantic Water Science Center Strategic Science Planning Team has developed a unified strategic science plan to guide the science vision of the South Atlantic Water Science Center (SAWSC) in response to the merging of the Georgia, North Carolina, and South Carolina Water Science Centers. This plan proposes a path forward to keep SAWSC science activities relevant to the many diverse needs of stakeholders in the South Atlantic region (Georgia, North Carolina, and South Carolina) and considers the hydrologic setting and issues of the region. This plan advises the creation of five working groups to address five priority science topics for the period 2019–23 and beyond. The five priority science topics are (1) Foundational Data, (2) Effects of Land-Use Change, (3) Coastal Plain Science, (4) Water Availability, and (5) Hazards. From the goals laid forth in this plan for each priority science topic, the working groups plan to devise a set of strategic actions and milestones to be achieved by the SAWSC to provide valuable and relevant data, research, and assessments in the South Atlantic region. In this report, the “South Atlantic region” is used to describe the area encompassed by the States of North Carolina, South Carolina, and Georgia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191068","usgsCitation":"Cuffney, T.F., Garcia, A.M., Horowitz, A.J., LaFontaine, J.H., Landmeyer, J.E., McKee, A.M., McSwain, K.B., Painter, J.A., Shelton, J.M., and Smith, C.A., 2019, South Atlantic Water Science Center strategic science plan—2019–23: U.S. Geological Survey Open-File Report 2019–1068, 31 p., https://doi.org/10.3133/ofr20191068.","productDescription":"v, 31 p.","onlineOnly":"Y","ipdsId":"IP-090584","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":365956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1068/ofr20191068.pdf","text":"Report","size":"6.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1068"},{"id":365955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1068/coverthb.jpg"}],"contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 resulted in an increased demand for water in areas within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project.
An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. As of 2018, the network consisted of 120 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the ABCWUA, the New Mexico Office of the State Engineer, and Bernalillo County, measures water levels from the 120 wells and piezometers in the network; this report, prepared in cooperation with the ABCWUA, presents water-level data collected by USGS personnel at those 120 sites through water year 2018 (October 1, 2017, through September 30, 2018). Water levels that were collected from wells in previous water years were published in previous USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1116","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Ritchie, A.B., and Galanter, A.E., 2019, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2018 (ver. 1.1, August 2021): U.S. Geological Survey Data Series 1116, 40 p., https://doi.org/10.3133/ds1116.","productDescription":"iii, 40 p.","numberOfPages":"49","onlineOnly":"Y","ipdsId":"IP-108049","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":365903,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1116/coverthb2.jpg"},{"id":388360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1116/ds1116.pdf","text":"Report","size":"5.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1116"},{"id":388361,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/1116/versionHist.txt","text":"Version History","size":"554 B","linkFileType":{"id":2,"text":"txt"},"description":"DS 1116 Verson History"}],"country":"United States","state":"New Mexico","otherGeospatial":"Albuquerque Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107,\n 34.85\n ],\n [\n -106.375,\n 34.85\n ],\n [\n -106.375,\n 35.4\n ],\n [\n -107,\n 35.4\n ],\n [\n -107,\n 34.85\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: August 2021","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
For many years, marshes in the coastal areas from Texas to Louisiana have served as critical habitat for Anas fulvigula, the mottled duck. Mottled ducks are a priority species in the Texas/Louisiana Gulf Coast area and have been affected by critical habitat reduction. In recent years, mottled duck habitats have been threatened by natural and anthropogenic changes including urbanization, flooding, saltwater intrusion, and hydrologic alterations. These impacts are affecting the quality of habitat that is essential for the mottled duck nesting, feeding, and livelihood. Cumulative and synergistic effects of contamination and invasive species encroachment have also caused mottled duck habitat to be considered as some of the most critically endangered habitats in the United States. To help understand the environmental conditions that characterize the coastal landscape, U.S. Geological Survey researchers used an unmanned aerial system (UAS) to acquire high-resolution imagery to document current land and water spatial configuration and wetland health at McFaddin National Wildlife Refuge, Texas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191045","usgsCitation":"Jones, W.R., Hartley, S.B., Stagg, C.L., and Osland, M.J., 2019, Using UAS capabilities to help identify hummock-hollow formation and fragmentation in critical marsh habitat (Spartina patens) for mottled ducks in southeast Texas: U.S. Geological Survey Open-File Report 2019–1045, 6 p., https://doi.org/10.3133/ofr20191045.","productDescription":"6 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-105924","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365530,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1045/coverthb.jpg"},{"id":365531,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1045/ofr20191045.pdf","text":"Report","size":"4.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1045"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.66796875,\n 25.760319754713887\n ],\n [\n -93.6474609375,\n 25.760319754713887\n ],\n [\n -93.6474609375,\n 32.24997445586331\n ],\n [\n -99.66796875,\n 32.24997445586331\n ],\n [\n -99.66796875,\n 25.760319754713887\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
The hydrothermal systems associated with the restless high-threat volcanoes at Lassen and Long Valley, California, each release large amounts of arsenic (As) to surface waters – ~6 and ~8 metric tons/yr, respectively. The hydrothermal As output can increase during volcanic unrest, as illustrated by a two-fold increase during unrest at Lassen in 2014–15. During that period of unrest, increased As concentrations and fluxes were measured up to 75 km downstream from the Lassen source, in Mill Creek near the confluence with the Sacramento River. In eastern California, the Long Valley hydrothermal system feeds into the Los Angeles Aqueduct (LAA), and the Los Angeles Department of Water and Power (LADWP) actively manages the LAA system to remove hydrothermal As. In 1980, during a series of ~Mw6 earthquakes, the discharge of a particular group of hydrothermal vents in Long Valley increased approximately 7-fold, though the total increase in As flux to the LAA system at that time is unknown. The likely mechanism for increased hydrothermal discharge in each case is permeability enhancement due to strong ground motion. A review of the global literature on earthquake hydrology suggests a worst-case scenario of a roughly 10-fold increase in permeability, with commensurate increase in the hydrothermal As flux persisting for days to months. Here we evaluate the potential impact of such increases in hydrothermal As flux on the California water-supply system.
Runoff in steep channels is capable of transitioning into debris flows with hazardous implications for downstream communities and infrastructure, particularly in alpine landscapes with minimal vegetation and areas recently disturbed by wildfire. Here, we derive thresholds for the initiation of runoff‐generated debris flows based on critical values of dimensionless discharge and Shields stress. These thresholds are derived by using a numerical model to estimate the hydrodynamic conditions coinciding with the timing of debris flow activity in a recently burned basin. A benefit of hydrodynamic thresholds is that they can be used to assess debris flow likelihood based on measurable hydrologic and geomorphic parameters and therefore provide more universal criteria for quantifying the runoff‐to‐debris flow transition in landscape evolution studies and hazard assessments. We then demonstrate how hydrodynamic thresholds can be used to estimate rainfall intensity‐duration thresholds for runoff‐generated debris flows without the need for historic debris flow observations.