The U.S. Army Fort Irwin National Training Center (NTC), in the Mojave Desert, obtains all of its potable water supply from three groundwater basins (Irwin, Langford, and Bicycle) within the NTC boundaries (fig. 1; California Department of Water Resources, 2003). Because of increasing water demands at the NTC, the U.S. Geological Survey (USGS), in cooperation with the U.S. Army, completed several studies to evaluate water resources in the developed and undeveloped groundwater basins underlying the NTC. In all of the developed basins, groundwater withdrawals exceed natural recharge, resulting in water-level declines. However, artificial recharge of treated wastewater has had some success in offsetting water-level declines in Irwin Basin. Additionally, localized water-quality changes have occurred in some parts of Irwin Basin as a result of human activities (i.e., wastewater disposal practices, landscape irrigation, and/or leaking pipes). As part of the multi-faceted NTC-wide studies, traditional datacollection methods were used and include lithological and geophysical logging at newly drilled boreholes, hydrologic data collection (i.e. water-level, water-quality, aquifer tests, wellbore flow). Because these data cover a small portion of the 1,177 square-mile (mi2 ) NTC, regional mapping, including geologic, gravity, aeromagnetic, and InSAR, also were done. In addition, ground and airborne electromagnetic surveys were completed and analyzed to provide more detailed subsurface information on a regional, base-wide scale. The traditional and regional ground and airborne data are being analyzed and will be used to help develop preliminary hydrogeologic framework and groundwater-flow models in all basins. This report is intended to provide an overview of recent water-resources and land-surface deformation studies at the NTC.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2017 Desert Symposium Field Guide and Proceedings - ECSZ does it: Revisiting the eastern California Shear Zone","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"California State University Desert Studies Center","usgsCitation":"Densmore, J.N., Dishart, J.E., Miller, D., Buesch, D.C., Ball, L.B., Bedrosian, P.A., Woolfenden, L.R., Cromwell, G., Burgess, M.K., Nawikas, J., O’Leary, D., Kjos, A., Sneed, M., and Brandt, J.T., 2017, Water-resources and land-surface deformation evaluation studies at Fort Irwin National Training Center, Mojave Desert, California, in 2017 Desert Symposium Field Guide and Proceedings - ECSZ does it: Revisiting the eastern California Shear Zone, p. 290-298.","productDescription":"9 p.","startPage":"290","endPage":"298","ipdsId":"IP-083966","costCenters":[{"id":154,"text":"California Water Science 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LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes","interactions":[],"lastModifiedDate":"2018-04-10T10:56:16","indexId":"70196469","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5091,"text":"GigaScience","active":true,"publicationSubtype":{"id":10}},"title":"LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes","docAbstract":"Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states.
LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600–12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gigascience/gix101","usgsCitation":"Soranno, P.A., Bacon, L.C., Beauchene, M., Bednar, K.E., Bissell, E.G., Boudreau, C.K., Boyer, M.G., Bremigan, M.T., Carpenter, S.R., Carr, J.W., Cheruvelil, K.S., Christel, S.T., Claucherty, M., Collins, S.M., Conroy, J.D., Downing, J.A., Dukett, J., Fergus, C.E., Filstrup, C.T., Funk, C., Gonzalez, M.J., Green, L.T., Gries, C., Halfman, J.D., Hamilton, S.K., Hanson, P.C., Henry, E.N., Herron, E.M., Hockings, C., Jackson, J.R., Jacobson-Hedin, K., Janus, L.L., Jones, W.W., Jones, J., Keson, C.M., King, K.B., Kishbaugh, S.A., Lapierre, J., Lathrop, B., Latimore, J.A., Lee, Y., Lottig, N.R., Lynch, J.A., Matthews, L.J., McDowell, W.H., Moore, K.E., Neff, B., Nelson, S.J., Oliver, S., Pace, M.L., Pierson, D.C., Poisson, A.C., Pollard, A.I., Post, D.M., Reyes, P.O., Rosenberry, D., Roy, K.M., Rudstam, L.G., Sarnelle, O., Schuldt, N.J., Scott, C.E., Skaff, N.K., Smith, N.J., Spinelli, N.R., Stachelek, J.J., Stanley, E.H., Stoddard, J.L., Stopyak, S.B., Stow, C.A., Tallant, J.M., Tan, P., Thorpe, A.P., Vanni, M.J., Wagner, T., Watkins, G., Weathers, K.C., Webster, K.E., White, J., Wilmes, M.K., and Yuan, S., 2017, LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes: GigaScience, v. 6, no. 12, p. 1-22, https://doi.org/10.1093/gigascience/gix101.","productDescription":"22 p.","startPage":"1","endPage":"22","ipdsId":"IP-088165","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gigascience/gix101","text":"Publisher Index Page"},{"id":353287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Iowa, Illinois, Indiana, Massachusetts, 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Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States","docAbstract":"Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for ~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000–2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination R2 of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints.
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\"}}]}","volume":"9","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-29","publicationStatus":"PW","scienceBaseUri":"5a60fafbe4b06e28e9c22a82","contributors":{"authors":[{"text":"Reitz, Meredith 0000-0001-9519-6103 mreitz@usgs.gov","orcid":"https://orcid.org/0000-0001-9519-6103","contributorId":196694,"corporation":false,"usgs":true,"family":"Reitz","given":"Meredith","email":"mreitz@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":724058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":724059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"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":724060,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194472,"text":"70194472 - 2017 - Progress and lessons learned from water-quality monitoring networks","interactions":[],"lastModifiedDate":"2017-11-30T10:00:52","indexId":"70194472","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5570,"text":"Chemistry and Water","active":true,"publicationSubtype":{"id":24}},"title":"Progress and lessons learned from water-quality monitoring networks","docAbstract":"Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The science behind sustaining the world's most crucial resource","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-809330-6.00002-7","usgsCitation":"Myers, D.N., and Ludtke, A.S., 2017, Progress and lessons learned from water-quality monitoring networks, chap. of The science behind sustaining the world's most crucial resource: Chemistry and Water, p. 23-120, https://doi.org/10.1016/B978-0-12-809330-6.00002-7.","productDescription":"98 p.","startPage":"23","endPage":"120","ipdsId":"IP-079349","costCenters":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"links":[{"id":349508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a92","contributors":{"authors":[{"text":"Myers, Donna N. 0000-0001-6359-2865 dnmyers@usgs.gov","orcid":"https://orcid.org/0000-0001-6359-2865","contributorId":512,"corporation":false,"usgs":true,"family":"Myers","given":"Donna","email":"dnmyers@usgs.gov","middleInitial":"N.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":723988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ludtke, Amy S. asludtke@usgs.gov","contributorId":4735,"corporation":false,"usgs":true,"family":"Ludtke","given":"Amy","email":"asludtke@usgs.gov","middleInitial":"S.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":723989,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199762,"text":"70199762 - 2017 - Estimating discharge and nonpoint source nitrate loading to streams from three end‐member pathways using high‐frequency water quality data","interactions":[],"lastModifiedDate":"2018-09-27T14:15:17","indexId":"70199762","displayToPublicDate":"2017-11-21T13:34:20","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating discharge and nonpoint source nitrate loading to streams from three end‐member pathways using high‐frequency water quality data","docAbstract":"The myriad hydrologic and biogeochemical processes taking place in watersheds occurring across space and time are integrated and reflected in the quantity and quality of water in streams and rivers. Collection of high‐frequency water quality data with sensors in surface waters provides new opportunities to disentangle these processes and quantify sources and transport of water and solutes in the coupled groundwater‐surface water system. A new approach for separating the streamflow hydrograph into three components was developed and coupled with high‐frequency nitrate data to estimate time‐variable nitrate loads from chemically dilute quick flow, chemically concentrated quick flow, and slowflow groundwater end‐member pathways for periods of up to 2 years in a groundwater‐dominated and a quick‐flow‐dominated stream in central Wisconsin, using only streamflow and in‐stream water quality data. The dilute and concentrated quick flow end‐members were distinguished using high‐frequency specific conductance data. Results indicate that dilute quick flow contributed less than 5% of the nitrate load at both sites, whereas 89 ± 8% of the nitrate load at the groundwater‐dominated stream was from slowflow groundwater, and 84 ± 25% of the nitrate load at the quick‐flow‐dominated stream was from concentrated quick flow. Concentrated quick flow nitrate concentrations varied seasonally at both sites, with peak concentrations in the winter that were 2–3 times greater than minimum concentrations during the growing season. Application of this approach provides an opportunity to assess stream vulnerability to nonpoint source nitrate loading and expected stream responses to current or changing conditions and practices in watersheds.
","language":"English ","publisher":"American Geophysical Union","doi":"10.1002/2017WR021654","usgsCitation":"Miller, M.P., Tesoriero, A.J., Hood, K., Terziotti, S., and Wolock, D.M., 2017, Estimating discharge and nonpoint source nitrate loading to streams from three end‐member pathways using high‐frequency water quality data: Water Resources Research, v. 53, no. 12, p. 10201-10216, https://doi.org/10.1002/2017WR021654.","productDescription":"16 p.","startPage":"10201","endPage":"10216","ipdsId":"IP-091844","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":469303,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr021654","text":"Publisher Index Page"},{"id":357845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"12","noUsgsAuthors":false,"publicationDate":"2017-12-07","publicationStatus":"PW","scienceBaseUri":"5bc030a6e4b0fc368eb53a0a","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hood, Krista","contributorId":208243,"corporation":false,"usgs":false,"family":"Hood","given":"Krista","email":"","affiliations":[],"preferred":false,"id":746521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":746523,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190505,"text":"sim3386 - 2017 - Bedrock geology and hydrostratigraphy of the Edwards and Trinity aquifers within the Driftwood and Wimberley 7.5-minute quadrangles, Hays and Comal Counties, Texas","interactions":[],"lastModifiedDate":"2017-11-16T17:10:15","indexId":"sim3386","displayToPublicDate":"2017-11-16T17:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3386","title":"Bedrock geology and hydrostratigraphy of the Edwards and Trinity aquifers within the Driftwood and Wimberley 7.5-minute quadrangles, Hays and Comal Counties, Texas","docAbstract":"The Edwards and Trinity aquifers are major sources of water in south-central Texas and are both classified as major aquifers by the State of Texas. The population in Hays and Comal Counties is rapidly growing, increasing demands on the area’s water resources. To help effectively manage the water resources in the area, refined maps and descriptions of the geologic structures and hydrostratigraphic units of the aquifers are needed. This report presents the detailed 1:24,000-scale bedrock hydrostratigraphic map as well as names and descriptions of the geologic and hydrostratigraphic units of the Driftwood and Wimberley 7.5-minute quadrangles in Hays and Comal Counties, Tex.
Hydrostratigraphically, the rocks exposed in the study area represent a section of the upper confining unit to the Edwards aquifer, the Edwards aquifer, the upper zone of the Trinity aquifer, and the middle zone of the Trinity aquifer. In the study area, the Edwards aquifer is composed of the Georgetown Formation and the rocks forming the Edwards Group. The Trinity aquifer is composed of the rocks forming the Trinity Group. The Edwards and Trinity aquifers are karstic with high secondary porosity along bedding and fractures. The Del Rio Clay is a confining unit above the Edwards aquifer and does not supply appreciable amounts of water to wells in the study area.
The hydrologic connection between the Edwards and Trinity aquifers and the various hydrostratigraphic units is complex because the aquifer system is a combination of the original Cretaceous depositional environment, bioturbation, primary and secondary porosity, diagenesis, and fracturing of the area from Miocene faulting. All of these factors have resulted in development of modified porosity, permeability, and transmissivity within and between the aquifers. Faulting produced highly fractured areas which allowed for rapid infiltration of water and subsequently formed solutionally enhanced fractures, bedding planes, channels, and caves that are highly permeable and transmissive. Because of faulting the juxtaposition of the aquifers and hydrostratigraphic units has resulted in areas of interconnectedness between the Edwards and Trinity aquifers and the various hydrostratigraphic units that form the aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3386","usgsCitation":"Clark, A.K., and Morris, R.R., 2017, Bedrock geology and hydrostratigraphy of the Edwards and Trinity aquifers within the Driftwood and Wimberley 7.5-minute quadrangles, Hays and Comal Counties, Texas: U.S. Geological Survey Scientific Investigations Map 3386, 12 p., 1 sheet, scale 1:24,000, https://doi.org/10.3133/sim3386.","productDescription":"Report: iv, 12 p.; Plates: 34.78 x 53.96 inches; Table; Data Release; Read Me","onlineOnly":"Y","ipdsId":"IP-078819","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":348918,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_ReadMe.txt","text":"Read Me","size":"8.00 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3386 Read Me"},{"id":348916,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_map.pdf","text":"Map","size":"63.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3386 Map"},{"id":348917,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_geomap.pdf","text":"Georeferenced map","size":"70.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3386 Georeferenced Map"},{"id":348913,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_pamphlet.pdf","text":"Report","size":"46.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3386 Report"},{"id":348933,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3386/sim3386_Table_1.pdf","text":"Table 1—","size":"264 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3386 Table 1","linkHelpText":"Summary of bedrock geology and hydrostratigraphy of the Edwards and Trinity aquifers within the Driftwood and Wimberley 7.5-minute quadrangles, Hays and Comal Counties, Texas"},{"id":348912,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3386/coverthb.jpg"},{"id":348921,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3363","text":"Scientific Investigations Map 3363—","linkHelpText":"Geologic framework, hydrostratigraphy, and ichnology of the Blanco, Payton, and Rough Hollow 7.5-minute quadrangles, Blanco, Comal, Hays, and Kendall Counties, Texas"},{"id":348919,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76D5RXQ","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data release for bedrock geology and hydrostratigraphy of the Edwards and Trinity Aquifers within the Driftwood and Wimberley 7.5-Minute Quadrangles, Hays and Comal Counties, Texas at 1:24,000 scale"}],"country":"United States","state":"Texas","county":"Comal County, Hays County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.125,\n 30.125\n ],\n [\n -98,\n 30.125\n ],\n [\n -98,\n 29.875\n ],\n [\n -98.125,\n 29.875\n ],\n [\n -98.125,\n 30.125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754-4501
The U.S. Geological Survey (USGS), in cooperation with the Virginia Department of Environmental Quality (DEQ), reviewed a previously compiled set of linear regression models to assess their utility in defining the response of the aquatic biological community to streamflow depletion.
As part of the 2012 Virginia Healthy Watersheds Initiative (HWI) study conducted by Tetra Tech, Inc., for the U.S. Environmental Protection Agency (EPA) and Virginia DEQ, a database with computed values of 72 hydrologic metrics, or indicators of hydrologic alteration (IHA), 37 fish metrics, and 64 benthic invertebrate metrics was compiled and quality assured. Hydrologic alteration was represented by simulation of streamflow record for a pre-water-withdrawal condition (baseline) without dams or developed land, compared to the simulated recent-flow condition (2008 withdrawal simulation) including dams and altered landscape to calculate a percent alteration of flow. Biological samples representing the existing populations represent a range of alteration in the biological community today.
For this study, all 72 IHA metrics, which included more than 7,272 linear regression models, were considered. This extensive dataset provided the opportunity for hypothesis testing and prioritization of flow-ecology relations that have the potential to explain the effect(s) of hydrologic alteration on biological metrics in Virginia streams.
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\"}}]}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond VA 23228
Digital flood-inundation maps for a 3.2-mile reach of North Fork Salt Creek at Nashville, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding that correspond to selected water levels (stages) at the North Fork Salt Creek at Nashville, Ind., streamgage (USGS station number 03371650). Real-time stages at this streamgage may be obtained from the USGS National Water Information System at http://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also shows observed USGS stages at the same site as the USGS streamgage (NWS site NFSI3).
Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current (2015) stage-discharge rating at the USGS streamgage 03371650, North Fork Salt Creek at Nashville, Ind. The hydraulic model was then used to compute 12 water-surface profiles for flood stages at 1-foot (ft) intervals, except for the highest profile of 22.9 ft, referenced to the streamgage datum ranging from 12.0 ft (the NWS “action stage”) to 22.9 ft, which is the highest stage of the current (2015) USGS stage-discharge rating curve and 1.9 ft higher than the NWS “major flood stage.” 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 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each stage.
The availability of these maps, along with information regarding current stage from the USGS streamgage, will provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175127","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for North Fork Salt Creek at Nashville, Indiana: U.S. Geological Survey Scientific Investigations Report 2017–5127, 10 p., https://doi.org/10.3133/sir20175127.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087895","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":348732,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5127/sir20175127.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5127"},{"id":348733,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ316V","text":"USGS data release","description":"USGS Data Release","linkHelpText":"North Fork Salt Creek at Nashville, Indiana, flood-inundation model and GIS data"},{"id":348731,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5127/coverthb.jpg"}],"country":"United States","state":"Indiana","city":"Nashville","otherGeospatial":"North Fork Salt Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.26336097717285,\n 39.190954761524445\n ],\n [\n -86.22027397155762,\n 39.190954761524445\n ],\n [\n -86.22027397155762,\n 39.213036788153914\n ],\n [\n -86.26336097717285,\n 39.213036788153914\n ],\n [\n -86.26336097717285,\n 39.190954761524445\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard,
Indianapolis, IN 46278–1996
Local governmental agencies are increasingly undertaking potentially costly “status-and-trends” monitoring to evaluate the effectiveness of stormwater control measures and land-use planning strategies, or to satisfy regulatory requirements. Little guidance is presently available for such efforts, and so we have explored the application, interpretation, and temporal limitations of well-established hydrologic metrics of runoff changes from urbanization, making use of an unusually long-duration, high-quality data set from the Pacific Northwest (USA) with direct applicability to urban and urbanizing watersheds. Three metrics previously identified for their utility in identifying hydrologic conditions with biological importance that respond to watershed urbanization—TQmean (the fraction of time that flows exceed the mean annual discharge), the Richards-Baker Index (characterizing flashiness relative to the mean discharge), and the annual tally of wet-season day-to-day flow reversals (the total number of days that reverse the prior days’ increasing or decreasing trend)—are all successful in stratifying watersheds across a range of urbanization, as measured by total contributing area of urban development. All metrics respond with statistical significance to multi-decadal trends in urbanization, but none detect trends in watershed-scale urbanization over the course of a single decade. This suggests a minimum period over which dependable trends in hydrologic alteration (or improvement) can be detected with confidence. The metrics also prove less well suited to urbanizing watersheds in a semi-arid climate, with only flow reversals showing a response consistent with prior findings from more humid regions. We also explore the use of stage as a surrogate for discharge in calculating these metrics, recognizing potentially significant agency cost savings in data collection with minimal loss of information. This approach is feasible but cannot be implemented under current data-reporting practices, requiring measurement of water-depth values and preservation of the full precision of the original recorded data. With these caveats, however, hydrologic metrics based on stage should prove as or more useful, at least in the context of status-and-trends monitoring, as those based on subsequent calculations of discharge.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11369","usgsCitation":"Booth, D.B., and Konrad, C.P., 2017, Hydrologic metrics for status-and-trends monitoring in urban and urbanizing watersheds: Hydrological Processes, v. 31, no. 25, p. 4507-4519, https://doi.org/10.1002/hyp.11369.","productDescription":"13 p.","startPage":"4507","endPage":"4519","ipdsId":"IP-090190","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":348629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"25","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-23","publicationStatus":"PW","scienceBaseUri":"5a096bb0e4b09af898c9413d","contributors":{"authors":[{"text":"Booth, Derek B.","contributorId":100873,"corporation":false,"usgs":false,"family":"Booth","given":"Derek","email":"","middleInitial":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":717492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717491,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193809,"text":"70193809 - 2017 - Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection","interactions":[],"lastModifiedDate":"2017-11-09T11:57:32","indexId":"70193809","displayToPublicDate":"2017-11-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection","docAbstract":"Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-21-5443-2017","usgsCitation":"Poole, S., Vis, M., Knight, R., and Seibert, J., 2017, Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection: Hydrology and Earth System Sciences, v. 21, p. 5443-5457, https://doi.org/10.5194/hess-21-5443-2017.","productDescription":"15 p.","startPage":"5443","endPage":"5457","ipdsId":"IP-078840","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":469334,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-21-5443-2017","text":"Publisher Index Page"},{"id":348538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Tennessee River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.549560546875,\n 36.474306755095206\n ],\n [\n -89.40673828124999,\n 36.1290016556965\n ],\n [\n -88.450927734375,\n 34.49750272138159\n ],\n [\n -88.04443359375,\n 34.125447565116126\n ],\n [\n -87.29736328125,\n 34.125447565116126\n ],\n [\n -86.63818359374999,\n 34.11635246997272\n ],\n [\n -85.924072265625,\n 34.30714385628802\n ],\n [\n -85.71533203124999,\n 34.56990638085633\n ],\n [\n -85.60546875,\n 34.93998515156041\n ],\n [\n -84.99023437499999,\n 34.99400375757575\n ],\n [\n -84.57275390624999,\n 34.858890491257796\n ],\n [\n -84.12231445312499,\n 34.867904962568744\n ],\n [\n -83.60595703124999,\n 35.54116627999815\n ],\n [\n -83.03466796874999,\n 35.71975793933433\n ],\n [\n -82.86987304687499,\n 35.90684930677118\n ],\n [\n -82.46337890625,\n 36.01356058518151\n ],\n [\n -81.91406249999999,\n 36.1822249804225\n ],\n [\n -81.94702148437499,\n 36.70365959719453\n ],\n [\n -81.73828125,\n 37.21283151445594\n ],\n [\n -81.771240234375,\n 37.39634613318923\n ],\n [\n -81.990966796875,\n 37.47485808497102\n ],\n [\n -82.24365234375,\n 37.33522435930639\n ],\n [\n -83.34228515624999,\n 36.84446074079561\n ],\n [\n -84.08935546874999,\n 36.76529191711621\n ],\n [\n -84.86938476562499,\n 36.756490329505155\n ],\n [\n -85.62744140624999,\n 36.633162095586556\n ],\n [\n -85.81420898437499,\n 36.27970720524017\n ],\n [\n -86.91284179687499,\n 36.11125252076156\n ],\n [\n -87.50610351562499,\n 36.32397712011264\n ],\n [\n -87.80273437499999,\n 36.712467243386264\n ],\n [\n -88.01147460937499,\n 37.020098201368086\n ],\n [\n -88.2861328125,\n 37.142803443716836\n ],\n [\n -88.51684570312499,\n 37.05517710666079\n ],\n [\n -88.72558593749999,\n 37.10776507118514\n ],\n [\n -89.03320312499999,\n 37.17782559332976\n ],\n [\n -89.18701171874999,\n 37.02886944696474\n ],\n [\n -89.12109375,\n 36.976226784640936\n ],\n [\n -89.28588867187499,\n 36.5449494414832\n ],\n [\n -89.43969726562499,\n 36.55377524336086\n ],\n [\n -89.549560546875,\n 36.474306755095206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-06","publicationStatus":"PW","scienceBaseUri":"5a05771de4b09af898c70868","contributors":{"authors":[{"text":"Poole, Sandra","contributorId":174147,"corporation":false,"usgs":false,"family":"Poole","given":"Sandra","email":"","affiliations":[{"id":27368,"text":"University of Zurich","active":true,"usgs":false}],"preferred":false,"id":720577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vis, Marc","contributorId":174146,"corporation":false,"usgs":false,"family":"Vis","given":"Marc","email":"","affiliations":[{"id":27368,"text":"University of Zurich","active":true,"usgs":false}],"preferred":false,"id":720578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Rodney 0000-0001-9588-0167 rrknight@usgs.gov","orcid":"https://orcid.org/0000-0001-9588-0167","contributorId":152422,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney","email":"rrknight@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":720576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seibert, Jan","contributorId":176322,"corporation":false,"usgs":false,"family":"Seibert","given":"Jan","email":"","affiliations":[],"preferred":false,"id":720579,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190965,"text":"ofr20171118 - 2017 - Evaluation of the Eureka Manta2 Water-Quality Multiprobe Sonde ","interactions":[],"lastModifiedDate":"2017-11-10T09:59:07","indexId":"ofr20171118","displayToPublicDate":"2017-11-08T10:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1118","title":"Evaluation of the Eureka Manta2 Water-Quality Multiprobe Sonde ","docAbstract":"Two Eureka Manta2 3.5 water-quality multiprobe sondes by Eureka Water Probes were tested at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) against known standards over the sonde operating temperatures to verify the manufacturer’s stated accuracy specifications for pH, specific conductance (SC) at 25 degrees Celsius (°C), dissolved oxygen (DO), and turbidity. The Manta2 sondes were evaluated for compliance with the USGS National Field Manual for the Collection of Water-Quality Data (NFM) criteria for continuous water-quality monitors, and for compliance with the manufacturer’s technical specifications. The Manta2 was also evaluated for its compliance to Serial Digital Interface at 1200 baud (SDI-12) version 1.3.
The Manta2 met the NFM recommendations and manufacturer’s accuracy specifications for DO and turbidity at all values tested. The Manta2 pH sensors met the NFM recommendations and manufacturer’s accuracy specification for nominal pH values of 10 and lower. One of the two sensors was out of compliance by 1.2 units for pH 11.16 at 15 °C and by 0.25 unit for pH 10.78 at 40 °C. The Manta2 sensors were within the NFM recommendations for SC, except at 100 microsiemens (μS/cm) at 40 °C, where the SC sensor exceeded the test standard value by as much as 25 percent. One of two sensors was within manufacturer’s accuracy specifications at 25 °C for all the tested SC values, while the other SC sensor was outside the manufacturer’s accuracy specifications at 100 μS/cm, exceeding the test standard value by 9 percent. One of two sensors was outside the manufacturer’s accuracy specifications at 10,000 μS/cm at 15°C, exceeding the test standard value by 3 percent. One Manta2 passed SDI-12 compliance testing with a NR Systems SDI-12 Verifier. One Manta2 was field tested for 6 weeks at USGS station 02492620, National Space Technology Laboratories (NSTL) Station, Mississippi, on the Pearl River and showed overall good agreement with a well-maintained Hydrolab Datasonde 5X site sonde for water temperature, pH, and DO. Differences in SC values between the Manta2 and the site sonde were most likely due to differences in the deployment depth of the sondes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171118","usgsCitation":"Tillman, E.F., 2017, Evaluation of the Eureka Manta2 Water-Quality Multiprobe Sonde: U.S. Geological Survey Open-File Report 2017–1118, 37 p., https://doi.org/10.3133/ofr20171118. ","productDescription":"vi, 37 p.","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076099","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":347738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1118/coverthb.jpg"},{"id":347739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1118/ofr20171118.pdf","text":"Report","size":"1.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1118"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
Large Mississippi River (MR) diversions (peak water flow >1416 m3/s and sediment loads >165 kg/s) have been proposed as part of a suite of coastal restoration projects and are expected to rehabilitate and rebuild wetlands to alleviate the significant historic wetland loss in coastal Louisiana. These coastal wetlands are undergoing increasing eustatic sea‐level rise, land subsidence, climate change, and anthropogenic disturbances. However, the effect of MR diversions on wetland soil organic carbon (SOC) sequestration in receiving basins remains unknown. The rate of SOC sequestration or carbon burial in wetlands is one of the variables used to assess the role of wetland soils in carbon cycling and also to construct wetland carbon budgets. In this study, we examined the effects of MR water and sediment diversions on landscape‐scale SOC sequestration rates that were estimated from vertical accretion for the next 50 yr (2010–2060) under two environmental (moderate and less optimistic) scenarios. Our analyses were based on model simulations taken from the Wetland Morphology model developed for Louisiana's 2012 Coastal Master Plan. The master plan modeled a “future‐without‐action” scenario as well as eight individual MR diversion projects in two of the hydrologic basins (Barataria and Breton Sound). We examined the effects that discharge rates (peak flow) and locations of these individual diversion projects had on SOC sequestration rates. Modeling results indicate that large river diversions are capable of improving basin‐wide SOC sequestration capacity (162–222 g C·m−2·yr−1) by up to 14% (30 g C·m−2·yr−1) in Louisiana deltaic wetlands compared to the future‐without‐action scenario, especially under the less optimistic scenario. When large river diversions are placed in the upper receiving basin, SOC sequestration rates are 3.7–10.5% higher (6–24 g C·m−2·yr−1) than when these structures are placed in the lower receiving basin. Modeling results also indicate that both diversion discharge and location have large effects on SOC sequestration in low‐salinity (freshwater and intermediate marshes) as compared to high‐salinity marshes (brackish and saline marshes).
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.1984","usgsCitation":"Wang, H., Steyer, G.D., Couvillion, B., Beck, H.J., Rybczyk, J.M., Rivera-Monroy, V.H., Krauss, K.W., and Visser, J.M., 2017, Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration: Ecosphere, v. 8, no. 11, e01984, 15 p., https://doi.org/10.1002/ecs2.1984.","productDescription":"e01984, 15 p.","ipdsId":"IP-070521","costCenters":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469345,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1984","text":"Publisher Index Page"},{"id":438156,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72R3PWW","text":"USGS data release","linkHelpText":"Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration"},{"id":385545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Barataria Basin, Breton Sound Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.3128662109375,\n 29.480252193344267\n ],\n [\n -89.00,\n 29.480252193344267\n ],\n [\n -89.00,\n 30.285159872426014\n ],\n [\n -91.3128662109375,\n 30.285159872426014\n ],\n [\n -91.3128662109375,\n 29.480252193344267\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"11","noUsgsAuthors":false,"publicationDate":"2017-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":815331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":815332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Couvillion, Brady 0000-0001-5323-1687 couvillionb@usgs.gov","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":146832,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","email":"couvillionb@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":815333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Holly J. 0000-0002-0567-9329 hbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-0567-9329","contributorId":257931,"corporation":false,"usgs":true,"family":"Beck","given":"Holly","email":"hbeck@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research 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kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":815337,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Visser, Jenneke M.","contributorId":178417,"corporation":false,"usgs":false,"family":"Visser","given":"Jenneke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":815338,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70193669,"text":"70193669 - 2017 - Inequity in ecosystem service delivery: Socioeconomic gaps in the public-private conservation network","interactions":[],"lastModifiedDate":"2017-11-29T13:48:07","indexId":"70193669","displayToPublicDate":"2017-11-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Inequity in ecosystem service delivery: Socioeconomic gaps in the public-private conservation network","docAbstract":"Conservation areas, both public and private, are critical tools to protect biodiversity and deliver important ecosystem services (ES) to society. Although societal benefits from such ES are increasingly used to promote public support of conservation, the number of beneficiaries, their identity, and the magnitude of benefits are largely unknown for the vast majority of conservation areas in the United States public-private conservation network. The location of conservation areas in relation to people strongly influences the direction and magnitude of ES flows as well as the identity of beneficiaries. We analyzed benefit zones, the areas to which selected ES could be conveyed to beneficiaries, to assess who benefits from a typical conservation network. Better knowledge of ES flows and beneficiaries will help land conservationists make a stronger case for the broad collateral benefits of conservation and help to address issues of social-environmental justice. To evaluate who benefits the most from the current public-private conservation network, we delineated the benefit zones for local ES (within 16 km) that are conveyed along hydrological paths from public (federal and state) and private (easements) conservation lands in the states of North Carolina and Virginia, USA. We also discuss the challenges and demonstrate an approach for delineating nonhydrological benefits that are passively conveyed to beneficiaries. We mapped and compared the geographic distribution of benefit zones within and among conservation area types. We further compared beneficiary demographics across benefit zones of the conservation area types and found that hydrological benefit zones of federal protected areas encompass disproportionately fewer minority beneficiaries compared to statewide demographic patterns. In contrast, benefit zones of state protected areas and private easements encompassed a much greater proportion of minority beneficiaries (~22–25%). Benefit zones associated with private conservation lands included beneficiaries of significantly greater household income than benefit zones of other types of conservation areas. Our analysis of ES flows revealed significant socioeconomic gaps in how the current public-private conservation network benefits the public. These gaps warrant consideration in regional conservation plans and suggest that private conservation initiatives may be best suited for responding to the equity challenge. Enhancing the ecosystem benefits and the equity of benefit delivery from private conservation networks could build public and political support for long-term conservation strategies and ultimately enhance conservation efficacy.
","language":"English","doi":"10.5751/ES-09021-220136","usgsCitation":"Villamagna, A., Mogollon, B., and Angermeier, P.L., 2017, Inequity in ecosystem service delivery: Socioeconomic gaps in the public-private conservation network: Ecology and Society, v. 22, no. 1, Article 36; 16 p., https://doi.org/10.5751/ES-09021-220136.","productDescription":"Article 36; 16 p.","ipdsId":"IP-071190","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469349,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-09021-220136","text":"Publisher Index Page"},{"id":348206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, 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biota@usgs.gov","contributorId":1432,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":613,"text":"Virginia Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":719843,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193710,"text":"70193710 - 2017 - Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana","interactions":[],"lastModifiedDate":"2017-11-03T10:56:17","indexId":"70193710","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1198,"text":"Catena","active":true,"publicationSubtype":{"id":10}},"title":"Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana","docAbstract":"Floodplain lakes are important wetlands on many lowland floodplains of the world but depressional floodplain lakes are rare in the Mississippi River Alluvial Valley. One of the largest is Catahoula Lake, which has existed with seasonally fluctuating water levels for several thousand years but is now in an increasingly hydrologically altered floodplain. Woody vegetation has been encroaching into the lake bed and the rate of this expansion has increased since major human hydrologic modifications, such as channelization, levee construction, and dredging for improvement of navigation, but it remains unknown what role those modifications may have played in altering lake sedimentation processes. Profiles of thirteen 137Cs sediment cores indicate sedimentation has been about 0.26 cm y− 1 over the past 60 years and has been near this rate since land use changes began about 200 years ago (210Pb, and 14C in Tedford, 2009). Carbon sequestration was low (10.4 g m− 2 y− 1), likely because annual drying promotes mineralization and export. Elemental composition (high Zr and Ti and low Ca and K) and low pH of recent (<~60 y) or surface sediments suggest Gulf Coastal Plain origin, but below the recent sediment deposits, 51% of sediment profiles showed influence of Mississippi River alluvium, rich in base cations such as K+, Ca2 +, and Mg2 +. The recent shift to dominance of Coastal Plain sediments on the lake-bed surface suggests hydrologic modification has disconnected the lake from sediment-bearing flows from the Mississippi River. Compared to its condition prior to hydrologic alterations that intensified in the 1930s, Catahoula Lake is about 15 cm shallower and surficial sediments are more acidic. Although these results are not sufficient to attribute ecological changes directly to sedimentological changes, it is likely the altered sedimentary and hydrologic environment is contributing to the increased dominance of woody vegetation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2017.04.020","usgsCitation":"Latuso, K.D., Keim, R.F., King, S.L., Weindorf, D.C., and DeLaune, R.D., 2017, Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana: Catena, v. 156, p. 290-297, https://doi.org/10.1016/j.catena.2017.04.020.","productDescription":"8 p.","startPage":"290","endPage":"297","ipdsId":"IP-061448","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Catahoula Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.1697998046875,\n 31.42749129448044\n ],\n [\n -92.04277038574219,\n 31.502458420817206\n ],\n [\n -91.99607849121094,\n 31.552793227677334\n ],\n [\n -91.99745178222656,\n 31.613626970322684\n ],\n [\n -92.06748962402344,\n 31.610703179979982\n ],\n [\n -92.12448120117188,\n 31.577950455417472\n ],\n [\n -92.17666625976562,\n 31.52411741833466\n ],\n [\n -92.22198486328125,\n 31.48313670206181\n ],\n [\n -92.23915100097656,\n 31.454439514853256\n ],\n [\n -92.22335815429688,\n 31.433350262414404\n ],\n [\n -92.19863891601562,\n 31.42749129448044\n ],\n [\n -92.1697998046875,\n 31.42749129448044\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"156","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fd8027e4b0531197b5013b","contributors":{"authors":[{"text":"Latuso, Karen D.","contributorId":113984,"corporation":false,"usgs":false,"family":"Latuso","given":"Karen","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keim, Richard F.","contributorId":117125,"corporation":false,"usgs":false,"family":"Keim","given":"Richard","email":"","middleInitial":"F.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weindorf, David C.","contributorId":140924,"corporation":false,"usgs":false,"family":"Weindorf","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":27688,"text":"Texas Tech University, Lubbock, TX 79409","active":true,"usgs":false}],"preferred":false,"id":720025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeLaune, Ronald D.","contributorId":61581,"corporation":false,"usgs":false,"family":"DeLaune","given":"Ronald","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720026,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191750,"text":"sir20175123 - 2017 - Flood-inundation maps for the White River at Noblesville, Indiana","interactions":[],"lastModifiedDate":"2017-11-06T09:55:58","indexId":"sir20175123","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5123","title":"Flood-inundation maps for the White River at Noblesville, Indiana","docAbstract":"Digital flood-inundation maps for a 7.5-mile reach of the White River at Noblesville, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the White River at Noblesville, Ind., streamgage (USGS station number 03349000). Real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at the same site as the USGS streamgage (NWS site NBLI3).
Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current (2016) stage-discharge rating at the USGS streamgage 03349000, White River at Noblesville, Ind., and documented high-water marks from the floods of September 4, 2003, and May 6, 2017. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 10.0 ft (the NWS “action stage”) to 24.0 ft, which is the highest stage interval of the current (2016) USGS stage-discharge rating curve and 2 ft higher than the NWS “major flood stage.” 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 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each stage.
The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175123","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for the White River at Noblesville, Indiana: U.S. Geological Survey Scientific Investigations Report 2017–5123, 11 p., https://doi.org/10.3133/sir20175123.","productDescription":"Report: vi, 11 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-086871","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":347858,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5123/sir20175123.pdf","text":"Report","size":"1.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5123"},{"id":347859,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MG7N0J","text":"USGS data release","description":"USGS Data Release","linkHelpText":"White River at Noblesville, Indiana, flood-inundation model and GIS data"},{"id":347857,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5123/coverthb.jpg"}],"country":"United States","state":"Indiana","city":"Noblesville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.03616714477539,\n 40.033792168980135\n ],\n [\n -85.95720291137695,\n 40.033792168980135\n ],\n [\n -85.95720291137695,\n 40.10919420673381\n ],\n [\n -86.03616714477539,\n 40.10919420673381\n ],\n [\n -86.03616714477539,\n 40.033792168980135\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278–1996
Arsenic concentrations from 20 450 domestic wells in the U.S. were used to develop a logistic regression model of the probability of having arsenic >10 μg/L (“high arsenic”), which is presented at the county, state, and national scales. Variables representing geologic sources, geochemical, hydrologic, and physical features were among the significant predictors of high arsenic. For U.S. Census blocks, the mean probability of arsenic >10 μg/L was multiplied by the population using domestic wells to estimate the potential high-arsenic domestic-well population. Approximately 44.1 M people in the U.S. use water from domestic wells. The population in the conterminous U.S. using water from domestic wells with predicted arsenic concentration >10 μg/L is 2.1 M people (95% CI is 1.5 to 2.9 M). Although areas of the U.S. were underrepresented with arsenic data, predictive variables available in national data sets were used to estimate high arsenic in unsampled areas. Additionally, by predicting to all of the conterminous U.S., we identify areas of high and low potential exposure in areas of limited arsenic data. These areas may be viewed as potential areas to investigate further or to compare to more detailed local information. Linking predictive modeling to private well use information nationally, despite the uncertainty, is beneficial for broad screening of the population at risk from elevated arsenic in drinking water from private wells.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.7b02881","usgsCitation":"Ayotte, J.D., Medalie, L., Qi, S.L., Backer, L.C., and Nolan, B.T., 2017, Estimating the high-arsenic domestic-well population in the conterminous United States: Environmental Science & Technology, v. 51, no. 21, p. 12443-12454, https://doi.org/10.1021/acs.est.7b02881.","productDescription":"12 p.","startPage":"12443","endPage":"12454","ipdsId":"IP-085175","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":469369,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8842838","text":"Publisher Index Page"},{"id":349554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n","volume":"51","issue":"21","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-18","publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d29","contributors":{"authors":[{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medalie, Laura 0000-0002-2440-2149 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C.","contributorId":198459,"corporation":false,"usgs":false,"family":"Backer","given":"Lorraine","email":"","middleInitial":"C.","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":true,"id":716077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":716078,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194664,"text":"70194664 - 2017 - The magnitude and origin of groundwater discharge to eastern U.S. and Gulf of Mexico coastal waters","interactions":[],"lastModifiedDate":"2025-05-13T16:31:44.664965","indexId":"70194664","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The magnitude and origin of groundwater discharge to eastern U.S. and Gulf of Mexico coastal waters","docAbstract":"Fresh groundwater discharge to coastal environments contributes to the physical and chemical conditions of coastal waters, but the role of coastal groundwater at regional to continental scales remains poorly defined due to diverse hydrologic conditions and the difficulty of tracking coastal groundwater flow paths through heterogeneous subsurface materials. We use three-dimensional groundwater flow models for the first time to calculate the magnitude and source areas of groundwater discharge from unconfined aquifers to coastal waterbodies along the entire eastern U.S. We find that 27.1 km3/yr (22.8–30.5 km3/yr) of groundwater directly enters eastern U.S. and Gulf of Mexico coastal waters. The contributing recharge areas comprised ~175,000 km2 of U.S. land area, extending several kilometers inland. This result provides new information on the land area that can supply natural and anthropogenic constituents to coastal waters via groundwater discharge, thereby defining the subterranean domain potentially affecting coastal chemical budgets and ecosystem processes.
","language":"English","publisher":"AGU","doi":"10.1002/2017GL075238","usgsCitation":"Befus, K., Kroeger, K.D., Smith, C.G., and Swarzenski, P.W., 2017, The magnitude and origin of groundwater discharge to eastern U.S. and Gulf of Mexico coastal waters: Geophysical Research Letters, v. 44, no. 20, p. 10396-10406, https://doi.org/10.1002/2017GL075238.","productDescription":"11 p.","startPage":"10396","endPage":"10406","ipdsId":"IP-088608","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469383,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl075238","text":"Publisher Index Page"},{"id":349917,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","volume":"44","issue":"20","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-28","publicationStatus":"PW","scienceBaseUri":"5a60fb23e4b06e28e9c22d2e","contributors":{"authors":[{"text":"Befus, Kevin 0000-0001-7553-4195 kbefus@usgs.gov","orcid":"https://orcid.org/0000-0001-7553-4195","contributorId":190617,"corporation":false,"usgs":true,"family":"Befus","given":"Kevin","email":"kbefus@usgs.gov","affiliations":[],"preferred":true,"id":724822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":724821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":724824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724823,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193176,"text":"70193176 - 2017 - Hydrological responses to channelization and the formation of valley plugs and shoals","interactions":[],"lastModifiedDate":"2017-10-31T09:46:24","indexId":"70193176","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Hydrological responses to channelization and the formation of valley plugs and shoals","docAbstract":"Rehabilitation of floodplain systems focuses on restoring interactions between the fluvial system and floodplain, however, there is a paucity of information on the effects of valley plugs and shoals on floodplain hydrological processes. We investigated hydrologic regimes in floodplains at three valley plug sites, two shoal sites, and three unchannelized sites. Valley plug sites had altered surface and sub-surface hydrology relative to unchannelized sites, while only sub-surface hydrology was affected at shoal sites. Some of the changes were unexpected, such as reduced flood duration and flood depth in floodplains associated with valley plugs. Our results emphasize the variability associated with hydrologic processes around valley plugs and our rudimentary understanding of the effects associated with these geomorphic features. Water table levels were lower at valley plug sites compared to unchannelized sites, however, valley plug sites had a greater proportion of days when water table inundation was above mean root collar depth than both shoal and unchannelized sites as a result of lower root collar depths and higher deposition rates. This study has provided evidence that valley plugs can affect both surface and sub-surface hydrology in different ways than previously thought and illustrates the variability in hydrological responses to valley plug formation.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-017-0886-4","usgsCitation":"Pierce, A.R., and King, S.L., 2017, Hydrological responses to channelization and the formation of valley plugs and shoals: Wetlands, v. 37, no. 3, p. 513-523, https://doi.org/10.1007/s13157-017-0886-4.","productDescription":"11 p.","startPage":" 513","endPage":"523","ipdsId":"IP-075866","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":347797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-22","publicationStatus":"PW","scienceBaseUri":"59f98bace4b0531197af9fb3","contributors":{"authors":[{"text":"Pierce, Aaron R.","contributorId":94421,"corporation":false,"usgs":false,"family":"Pierce","given":"Aaron","email":"","middleInitial":"R.","affiliations":[{"id":33463,"text":"Nicholls State University, Thibodaux, LA","active":true,"usgs":false}],"preferred":false,"id":718178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718125,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195397,"text":"70195397 - 2017 - Flow and residence times of dynamic river bank storage and sinuosity-driven hyporheic exchange","interactions":[],"lastModifiedDate":"2018-02-14T10:11:16","indexId":"70195397","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Flow and residence times of dynamic river bank storage and sinuosity-driven hyporheic exchange","docAbstract":"Hydrologic exchange fluxes (HEFs) vary significantly along river corridors due to spatiotemporal changes in discharge and geomorphology. This variability results in the emergence of biogeochemical hot-spots and hot-moments that ultimately control solute and energy transport and ecosystem services from the local to the watershed scales. In this work, we use a reduced-order model to gain mechanistic understanding of river bank storage and sinuosity-driven hyporheic exchange induced by transient river discharge. This is the first time that a systematic analysis of both processes is presented and serves as an initial step to propose parsimonious, physics-based models for better predictions of water quality at the large watershed scale. The effects of channel sinuosity, alluvial valley slope, hydraulic conductivity, and river stage forcing intensity and duration are encapsulated in dimensionless variables that can be easily estimated or constrained. We find that the importance of perturbations in the hyporheic zone's flux, residence times, and geometry is mainly explained by two-dimensionless variables representing the ratio of the hydraulic time constant of the aquifer and the duration of the event (Γd) and the importance of the ambient groundwater flow ( ![\"math](\"http://binarystore.wiley.com/store/10.1002/2017WR021362/asset/equation/wrcr22904-math-0001.png?v=1&s=be103418b21131f03172a44a3017f7dbb804f190\")
). Our model additionally shows that even systems with small sensitivity, resulting in small changes in the hyporheic zone extent, are characterized by highly variable exchange fluxes and residence times. These findings highlight the importance of including dynamic changes in hyporheic zones for typical HEF models such as the transient storage model.